Unintentional Prescription Opioid-Related Overdose Deaths: Description of Decedents by Next of Kin or Best Contact, Utah, 2008-2009
BACKGROUND: Little is known about the characteristics that may predispose an individual to being at risk for fatal overdose from prescription opioids. OBJECTIVE: To identify characteristics related to unintentional prescription opioid overdose deaths in Utah. DESIGN: Interviews were conducted (October 2008-October 2009) with a relative or friend most knowledgeable about the decedent's life. SUBJECTS: Analyses involved 254 decedents aged 18 or older, where cause of death included overdose on at least one prescription opioid. KEY RESULTS: Decedents were more likely to be middle-aged, Caucasian, non-Hispanic/Latino, less educated, not married, or reside in rural areas than the general adult population in Utah. In the year prior to death, 87.4 % were prescribed prescription pain medication. Reported potential misuse prescription pain medication in the year prior to their death was high (e.g., taken more often than prescribed [52.9 %], obtained from more than one doctor during the previous year [31.6 %], and used for reasons other than treating pain [29.8 %, almost half of which "to get high"]). Compared with the general population, decedents were more likely to experience financial problems, unemployment, physical disability, mental illness (primarily depression), and to smoke cigarettes, drink alcohol, and use illicit drugs. The primary source of prescription pain medication was from a healthcare provider (91.8 %), but other sources (not mutually exclusive) included: for free from a friend or relative (24 %); from someone without their knowledge (18.2 %); purchase from a friend, relative, or acquaintance (16.4 %); and purchase from a dealer (not a pharmacy) (11.6 %). CONCLUSIONS: The large majority of decedents were prescribed opioids for management of chronic pain and many exhibited behaviors indicative of prescribed medication misuse. Financial problems, unemployment, physical disability, depression, and substance use (including illegal drugs) were also common.
Unintentional Prescription Opioid-Related Overdose Deaths:
Description of Decedents by Next of Kin or Best Contact, Utah,
Erin M. Johnson, MPH
, William A. Lanier, DVM, MPH
, Ray M. Merrill, PhD, MPH,
MS, FACE, FAAHB
, Jacob Crook, MS
, Christina A. Porucznik, PhD, MSPH
Robert T. Rolfs, MD, MPH
, and Brian Sauer, PhD
Utah Department of Health, Prescription Pain Medication Program, Salt Lake City, UT, USA;
Epidemic Intelligence Service, Centers for
Disease Control and Prevention, Atlanta, GA, USA;
Department of Health Science, Brigham Young University, Provo, UT, USA;
Department of Health, Communicable Disease Epidemiology Program, Salt Lake City, UT, USA;
Department of Family and Preventive
Medicine, Division of Public Health, University of Utah School of Medicine, Salt Lake City, UT, USA;
IDEAS Center, George E. Wahlen
Department of Veterans Affairs Medical Center, Salt Lake City, UT, USA.
BACKGROUND: Little is known about the character-
istics that may predispose an individual to being at risk
for fatal overdose from prescription opioids.
OBJECTIVE: To identify characteristics related to un-
intentional prescription opioid overdose deaths in Utah.
DESIGN: Interviews were conducted (October 2008–
October 2009) with a relative or friend most knowledge-
able about the decedent’s life.
SUBJECTS: Analyses involved 254 decedents aged 18
or older, where cause of death included overdose on at
least one prescription opioid.
KEY RESULTS: Decedents were more likely to be
middle-aged, Caucasian, non-Hispanic/Latino, less ed-
ucated, not married, or reside in rural areas than the
general adult population in Utah. In the year prior to
death, 87.4 % were prescribed prescription pain med-
ication. Reported potential misuse prescription pain
medication in the year prior to their death was high
(e.g., taken more often than prescribed [52.9 %],
obtained from more than one doctor during the previous
year [31.6 %], and used for reasons other than treating
pain [29.8 %, almost half of which “to get high”]).
Compared with the general population, decedents were
more likely to experience financial problems, unemploy-
ment, physical disability, mental illness (primarily de-
pression), and to smoke cigarettes, drink alcohol, and
use illicit drugs. The primary source of prescription pain
medication was from a healthcare provider (91.8 %), but
other sources (not mutually exclusive) included: for free
from a friend or relative (24 %); from someone without
their knowledge (18. 2 %); purchase from a fri end,
relative, or acquaintance (16.4 %); and purchase from a
dealer (not a pharmacy) (11.6 %).
CONCLUSIONS: The large majority of decedents were
prescribed opioids for management of chronic pain and
many exhibited behaviors indicative of prescribed med-
ication misuse. Financial problems, unemployment,
physical disability, depression, and substance use
(including illegal drugs) were also common.
KEY WORDS: chronic pain; illicit drug use; mental illness; opioids;
overdose; overprescribed; prescription pain medication.
J Gen Intern Med
© Society of General Internal Medicine 2012
Overdose deaths involving prescription painkillers (opioid
analgesics) have reached epidemic levels in the United
In 2008, the age-adjusted rate of death from opioids
was 4.8 per 100,000, nearly four times the rate in 1999.
2009, over 15,000 people died from overdoses involving
This number is more than three times greater than
the 4,000 people who died from opioid-related drug
overdoses in 1999.
Nonmedical use of opioids is a common and growing
problem. In 2010, one in 20 people in the United States, age
12 or older, used these drugs without a prescription or with
the intent of getting “high.”
Prior studies indicate that
groups at greatest risk to abuse or overdose on prescription
pain relievers are men, middle- aged adults, people in rural
counties, whites and American Indian or Alaska Natives,
those suffering from mental disorders, and those with a
history of alcohol abuse or illicit substance use.
However, more can be learned about the characteristics of
and circumstances surrounding those most likely to abuse
and overdose on prescription pain relievers.
Because of the challenges of collecting information about
the history of decedents, limited research is available
Electronic supplementary material The online version of this article
(doi:10.1007/s11606-012- 2225-z) contains s upplementary material,
which is available to authorized users.
Received May 18, 2012
Revised August 3, 2012
Accepted September 5, 2012
regarding characteristics that might predispose someone to a
fatal prescription opioid overdose. The purpose of this study
was to provide more in-depth information about persons
who died from an opioid-related drug overdose, as provided
by next-of-kin or best contact interviews. Characteristics
examined included demographics, chronic pain, financial
problems, mental stability, substance use, and patterns of
pain medication use. Identifying these characteristics may
help design intervention strategies to reverse the escalating
trends in opioid abuse and overdose.
Setting and Participants
Decedents were identified from records of the Utah Office of
the Medical Examiner (OME) in Utah during October 26,
2008–October 25, 2009. Manner and causes of death (COD)
were determined by OME on the basis of scene-of-death
investigation, autopsy, and toxicology findings. The OME is
authorized under Title 26 of the Utah Code, Chapter 4,
Section 7 to investigate several types of death, including
deaths resulting from poisoning or overdose of drugs and
deaths under suspicious or unusual circumstances.
suspected or possible drug overdose cases during this time
period were included as candidates for interviewing the next
of kin. Inclusion criteria were the presence of specific drugs
(from a list of 66) or types of drugs (including methadone,
oxycodone, hydrocodone, fentanyl, and others), or key words
(intoxication, drug [multi-, poly-, mixed], overdose, prescrip-
tion, medication, toxicity, substance abuse), in any death
certificate field listing COD or contributing factor. Individ-
uals were excluded if they were less than 12 years of age, not
a resident of Utah, a suicide or homicide, cases were
undetermined in the first four COD fields, or if the cause
of death was solely caused by carbon monoxide, household
cleaners, or alcohol. International Classification of Disease
(ICD) codes were not used in this study because they lacked
the necessary specification. OME personnel updated and
maintained a list of potential interview candidates. The list
was provided to the interviewers.
This study received approval from the Utah Department
of Health (UDOH) institutional review board and was
approved by a Human Research Protection Coordinator at
the Centers for Disease Control and Prevention (CDC).
Funding for this study was provided by Utah Department of
Human Services, Division of Substance Abuse and Mental
Health and grant 1R21CE001612-01 from CDC.
A data collection instrument was designed to document
information regarding decedents from their next of kin or
best contact. Questions were included on the basis of
existing substance use, health-related questionnaires and
feedback from health professionals. The questionnaire is
available online. The instrument was pretested to establish
validity among seven volunteers who had experienced the
death of a family member from drug overdose.
Interviews were conducted by trained interviewers by
telephone, with persons who were identified by OME
death-scene investigators as either next of kin or best
person to contact.
Those identified as potential interviewees for the
study were contacted no sooner than a month following
the death of the person being investigated, in order to
allow the person to grieve and also so they could learn
more about the circumstances surrounding the death. Each
time an interviewer attempted to contact an interviewee
but was unsuccessful, a note was made of the date and
time of the attempted contact, along with a brief
explanation of the nature of the call (i.e. no answer, not
home, left a message to call back, answering machine,
wrong number, busy, disconnected, etc.). A few cases that
involved nonworking telephone numbers wer e referred
back to OME personnel , who followed-up with law
enforcement agencies or funeral service organizations to
seek contact information. Almost all interviews were
conducted within 1–6 months of the decedent s opioid-
related drug overdose. A few interviews were conducted
7–12 months after the person’s death, because of sched-
uling problems or difficulty locating the individual. Inter-
views typically lasted 30–40 min. Interviewers followed
scripts for introducing the questionnaire, leaving telephone
messages, and responding to participa nts’ study-related
questions. Interviewers referred all participants’ case-
specific questions to OME.
In 33 instances, two people were identified as being
appropriate to contact. Merging was completed following
a p redetermined logic to decide which response was to be
assigned for data entry when conflic ting answers were
received. Logic was design ed to accept an answer th at
provided a greater amo unt o f informatio n. Decedents
with multiple interviews were tracked, and the number of
questions with conflicting answers among multiple inter-
views was recorded and ente red into the survey database .
The average number of conflicting response s per case
was 13, with a range of 4 to 24 conflicting responses
among all cases with multiple interviews. Almost all of
these conflicting responses were resolve d using the
predetermined logic. In a couple situations where the
differences were not resolved, the responses were treated
Epi Info™ Version 3.5.1 (Centers for Disease Control
and Prevention, Atlanta, Georgia) was used for data entry of
completed questionnaires and to facilitate creation of the
survey database in Microsoft® Access® 2007 (Microsoft
Johnson et al.: Opioid-Related Deaths JGIM
Corporation, Redmond , Washing ton). Double entr y wa s
performed for all questionnaires. The two data bases
were compared and all discrepancies were r eviewed for
accuracy. Changes were made manually to the master
database. Interview data were lin ked to dec edent COD,
body mass index (BMI), sex, and age data from the
OME database, and to education level, race/ethnicity,
county of residence, and marital status data from death
Because heroin is metabolized to morphine in the
body, only decedents for whom source of morphine
identified during toxicology testing was determined to
have been prescription morphine were identified as
prescription opioid-related deaths. Among reports where
morphine was identified during toxicology testing but
where source of the morphine was not stated by OME (n=
69), morphine source was determined by further review of
OME records as follows: (1) from prescription morphine
(n =34) if evidence existed of recent prescription mor-
phine use (prescription morphine at scene of death,
evidence of current morphine prescription, or report by
witness to OME invest igat or that mo rphine ha d recently
been used); (2) from heroin ( n=14) if evidence existed of
recent heroin use (illicit drug paraphernalia at scene of
death, rece nt needle pun ctur es iden tified on autop sy, or
report by witness to OME investigator that heroin had
recently been used); or (3) undetermined (n =21), if
neither or both of (1) and (2) prescription morphine or
heroin criteria were met.
Additional Data Sources
The demographic profile of decedents was compared with
population survey data available from the U.S. Census
Bureau and the Centers for Disease Control and Preven-
Prevalence of financial problems, chronic con-
ditions, substance use or abuse, and psychiatric disorders
among decedents was compared with the distribution of
these problems, conditions, uses, and disorders in the
general population. Comparison data were obtained from
national surveys conducted by the Centers for Disease
Control and Prevention, the U.S. Census Bureau, the
National Center for Health Statistics, the World Health
Cases seen by Utah Medical Examiner
Oct 26, 2008-Oct 25, 2009
Excluded based on Manner of Death
Pending (on 2/2/2010): 13
Included based on
Manner of Death (989)
Excluded as not drug
<12 years old:1
Non-Utah resident: 6
Drugs not primary
Included in study
(involving at least one
Opioid-related with completed
Figure 1. Flowchart of cases seen by the Office of Medical Examiner in Utah, October 2008 through October 2009.
Johnson et al.: Opioid-Related DeathsJGIM
Organization, and the U.S. Substance Abuse and Mental
Health Data Archive.
Descriptive statistics were used to summarize the data.
Bivariate analyses were conducted and assessed by using
the chi-square test for independence. Ninety-five percent
confidence intervals were calculated for the percentages.
Statistical significance was based on the two-sided hypoth-
esis and the 0.05 level. Analyses were performed by using
SAS® version 9.3 (SAS Institute Incorporated, Cary, North
During the study period, 432 unintentional drug overdose
deaths were investigated by OME. A total of 278 had at
least one prescription opioid as a COD (Fig. 1). Opioid-
related unintentional deaths involving only prescription
opioid pain medications did not differ significantly from
deaths where both prescri ption and illicit drugs were
involved with respect to sex, age, race/ethnicity, marital
status, and urban/rural setting of residence. Therefore, we
combined these categories and report on all deaths in which
a prescription opioid was included as a COD. Interviews
were completed for 254 (91.4 %) of prescription opioid-
related decedents and were included in our analysis.
Demographic characteristics of those involved in an
opioid-related death are presented in Table 1. Compared
with the Utah population aged 18 years and older in 2009,
decedents were more likely to be middle-aged, Caucasian,
non-Hispanic/Latino, less educated, not currently married,
or reside in rural areas.
Overall, 225 (88.6 %) decedents were reported to have
suffered from pain. Back pain was most common (n=113,
50.2 %), followed by leg, knee, foot, or hip pain (76,
33.8 %), and head, jaw, neck, or face pain (66, 29.3 %). Less
common causes of pain included fibromyalgia (17, 7.6 %),
shoulder or arm pain (16, 7.1 %), and arthritis (13, 5.8 %).
Of the 254 decedents, 222 (87.4 %) were identified by
the interviewees as having taken prescription pain medica-
tion within a year of their death. The primary source for the
prescription pain medications was directly from a healthcare
provider (91.8 %), although other sources were identified
(Table 2). Other non-mutually exclusive sources included
for free from a friend or relative, theft, purchase from a
friend, relative, or acquaintance, purchase from a dealer (not
a pharmacy), and purchase off the internet.
Among 76.0 % of decedents, there was reportedly concern
among parents, siblings, spouses, children, friends, or relatives
about the decedent’s misuse of prescription pain medication.
A healthcare provider had expressed concern about the misuse
of prescription pain medication for 33.0 % of the decedents.
Regarding the pain medication prescribed by a healthcare
provider in the year prior to their death, interviewees reported
that 52.9 % took more than prescribed, 42.4 % had visited
more than one doctor to get more prescription pain medica-
tion, and 29.8 % used pain medications for reasons other than
to treat pain. Among those reported to have used prescription
pain medication for reasons other than to treat pain in the year
prior to their death, these reasons included recreational use
(48.4 %), self-medication for depression (25.0 %), self-
Table 1. Unintentional Opioid-Related Drug Deaths in Utah
According to Selected Demographic Variables, October 2008–
No. % No. % P Value
Men 135 53.2 953,770 49.9 0.302
Women 119 46.8 957,137 50.1
18–24 20 7.9 337,085 17.6 < 0.001
25–34 67 26.4 441,598 23.1
35–44 59 23.2 333,883 17.5
45–54 75 29.5 313,140 16.4
55+ 33 13.0 485,201 25.4
Caucasian 251 98.8 1,801,756 94.3 0.002
Other 3 1.2 109,151 5.7
Hispanic or Latino
Yes 10 3.9 248,418 13.0 < 0.001
No 244 96.1 1,662,489 87.0
Less than High
47 18.5 112,744 5.9 < 0.001
High School or GED 94 37.0 531,232 27.8
91 35.8 687,927 36.0
College degree or
22 8.7 579,005 30.3
Currently married 87 34.3 1,314,70 68.8 < 0.001
Divorced/separated 88 34.6 135,674 7.1
79 31.1 460,529 24.1
Urban 198 77.9 1,662,489 87.0 < 0.001
Rural 56 22.1 248,418 13.0
Data sources for the Utah Population, aged 18 years and older:
Table 2. Nonprescription Sources of Pain Medication Among
Unintentional Opioid-Related Drug Deaths
Did (name of decedent) ever get
prescription pain medications …
No. % 95 % CI
For free from a friend or relative 54 24.0 18.7–30.0
From someone without person’s
41 18.2 13.4–23.6
By purchasing from friend,
relative, acquaintance (non-dealer)
36 16.4 11.4–21.1
Purchasing from a dealer
(not a pharmacy)
25 11.6 7.1–15.4
Purchasing on-line 7 3.1 0.9–5.5
Any other source 9 4.0 1.5–6.6
Multiple responses could be given
This table applies to 222 decedents who were reported to have been
prescribed at least one pain medication by a physician the year prior
to their death
Johnson et al.: Opioid-Related Deaths JGIM
medication for anxiety (15.6 %), and self-medication for sleep
disorder (4.6 %).
Decedents were described further in Table 3. In compar-
ison with other Utah and U.S. statistics, decedents were
reported to have previously experienced greater financial
problems, unemployment, physical disability, mental ill-
ness, alcohol drinking, tobacco use, and illicit drug use.
Fifty-three (21 %) of decedents had used illicit drugs during
the 30 days prior to their death.
Frequency of diagnosed mental illness reported for the
decedents is presented in Table 4. The most common
disorder was depression, followed by bipolar di sorder,
anxiety, Attention deficit hyperactivity disorder (ADHD),
and schizophrenia. Decedents experienced significantly
greater levels of depression, bipolar disorder, anxiety, and
schizophrenia than the general population.
This study provided an in-depth assessment of persons who
died from an opioid-related drug overdose, based on next-of-
kin or best contact interv iews. Compared with the Utah adult
population, decedents were more likely to be men, middle
aged, non-Hispanic Caucasians, less educated, single, and
residing in a rural area. Previous research has identified that
Table 3. Frequency of Unintentional Opioid-Related Drug Deaths According to Selected Financial Problems, Chronic Conditions, and
History of Substance Abuse
Decedents, Utah Comparisons
% (Year) Description
Financial problems in 2 months prior to death 149 59.8 53.7–65.9 14.3 (09) U.S. Poverty
Employed in 2 months prior to death 92 36.8 30.7–42.8 61.4 (09) Utah
82.0 (09) Male, U.S.
73.0 (09) Female, U.S.
Had health insurance at the time of death 172 70.8 65.1 –76.5 83.3 (09) U.S.
Physical disability 120 47.8 41.6 –54.0 32.0 (09) U.S. 1+ difficulty
or complex activity
Mental illness 138 55.9 49.7 –62.1 47.4 (07) U.S. (ever)
Hospitalized for a psychiatric reason (in lifetime)
—Excluding treatment for substance abuse
62 44.6 38.4–52.9
History of substance use/abuse
Tobacco (ever) 195 78.3 73.1 –83.4 24.9 (09) Utah
44.7 (09) U.S.
Tobacco use in the past 30 days 156 57.4 51.3 –63.6 18.4 (08–09) Utah Ages 12+
28.0 (08–09) U.S. Ages 12+
Alcohol (ever used) 221 88.4 84.4 –92.4 82.9 (09) U.S. Ages 12+
Alcohol (at least one drink in past 30 days) 150 59.1 52.9 –65.1 28.1 (08–09) Utah Ages 12+
51.8 (08–09) U.S. Ages 12+
Any illicit drug use (ever) 154 61.4 55.2 –67.4
Marijuana (ever) 127 54.7 48.5 –61.1 41.7 (09) U.S. Ages 12+
Cocaine (ever) 77 34.7 28.7–40.9 14.7 (09) U.S. Ages 12+
Heroin (ever) 52 22.8 17.5–28.3 1.5 (09) U.S. Ages 12+
Methamphetamine (ever) 67 29.9 24.2–35.9 8.0 (09) U.S. Ages 12+
Hallucinogens (ever) 36 16.5 11.8–21.4 14.8 (09) U.S. Ages 12+
Hospitalized for substance abuse (in lifetime)
203 79.9 75.0 –84.8
Visited emergency room for substance abuse
196 77.2 72.0 –82.3
The denominator was not always 254 because of “don’t know” responses, which were not included in the percent calculation
Ages 18 years and older, unless otherwise specified
Including tobacco, alcohol, prescribed or over the counter medications, of illicit drugs
Table 4. Reported Types of Diagnosed Psychiatric Disorders Among Unintentional Opioid-Related Drug Deaths
Decedents, Utah Comparisons
No. % 95 % CI % (Year) Description
Depression 76 29.9 24.3–35.6 16.1 (08) U.S. (ever)
Biopolar 45 17.7 13.0–22.4 1.7 (07) U.S. (ever)
Anxiety 34 13.4 9.2–17.6 12.3 (08) U.S. (ever)
Attention deficit hyperactivity disorder 11 4.3 1.8–6.8 4.1 U.S. Ages 18–44
Schizophrenia 9 3.5 1.3–5.8 0.6 (07) U.S. (ever)
Multiple responses could be given
Other disorders mentioned included sleep (3, 1.2 %), eating (1, 0.4 %), and learning (1, 0.4 %)
Ages 18 years and older, unless otherwise specified
Johnson et al.: Opioid-Related DeathsJGIM
men have a higher risk of opioid-related death than
Moreover , one study showed that in a group of
individuals prescribed opioids for chronic pain, men had a
higher incidence of physician-reported aberrant drug behaviors
Findings that opioid-related drug deaths more
likely involved people of middle age, Caucasians, and of rural
residency is also consistent with previous studies.
assessing characteristics of veterans with chronic use of
opioids found that the risk of abuse/dependence was greater
among middle-aged, male, white, and divorced, single, or
Finally, another study showed that
lower education was associated with higher opioid misuse
among chronic opioid therapy recipients.
An excess of prescribed pain medication is implied, given
the large number of decedents who were able to obtain
prescription pain medication for free from a friend or relative,
from someone without the person’s knowledge, or by
purchasing it from a friend, relative, or other sources. This
may be partly due to a tendency of health-care providers to
prescribe more pain medication than is used by the recipient.
For example, previous studies have shown that opioids were
prescribed more than needed after minor surgeries,
veterans with mental health diagnoses,
and in urological
Over half of decedents with prescribed pain medication
in the year prior to their death took more than prescribed,
over 40 % had visited more than one doctor to get more
prescription pain medication, and about 30 % used pain
medications for reasons other than to treat pain. This
emphasizes a need for closer monitoring at the health
care–practitioner level. Prescription drug monitoring pro-
grams can help identify individuals who are obtaining
controlled substances from multiple providers, but have not
been shown to reduce overdose deaths.
Many of the decedents had concurrent indications of
financial problems, unemployment, physical disability, de-
pression, and substance use (including illegal drugs). The
prevalence of these factors were greater among decedents
than in the Utah adult population. The complexity of these
associations cannot be fully understood from the current
study design. Yet, previous research has identified mental
and illicit drug use
as primary risk factors for opioid-related abuse and death. It
may be that financial problems, unemployment, and physical
disability contribute to opioid-related deaths, because of their
association with depression and substance use. It may also be
that tobacco smoking is associated with opioid abuse because
of its addictive tendencies, and because tobacco smoking is
associated with other substance use disorders and mental
illness, probably because of shared risk factors.
Nearly half of all decedents had experienced physical
disability. Patients with chronic pain often have psycholog-
ical and chronic disease comorbidities, inadequate coping
skills, sedentary lifestyles, and complex treatment history.
Pain, particularly chronic pain, is often linked to an inability
This is consistent with only 36.8 % of
decedents being employed during the 2 months prior to
their death. About 56 % of decedents had experienced
mental illness, with depression the most commonly diag-
nosed disorder. Depressive symptoms have been associated
with self-reported opioid abuse and adverse events.
The majority (61.4 %) of decedents had previously used
illicit substances. Previous researchers have demonstrated
high rates of illicit substance abuse among prescription drug
Having a non-opioid substance abuse problem
was revealed to be among the most pertinent predictors of
misuse or abuse of prescription opioids.
prevalence of tobacco smoking and illicit drug use among
decedents (e.g., 21 % were reported to have used illicit
drugs in the 30 days prior to their death) indicates that the
population group of chronic pain patients who have a
substance use disorder is an appropriate target for
interventions. Research also indicates that substance use
disorders might go unrecognized among patients treated
with prescription opioids.
Closer monitoring with urine
drug testing m ay help identify some individuals at risk for
A limitation of this study was the lack of a direct compari son
group. We used sample and census data from Utah and the
U.S. to provide rough comparisons with our results, but did
not have data on the population of individuals who are
prescribed opioids; it is likely that many of the observed
differences are present for this entire group and may not help
to identify the subset who are at risk for overdose. In addition,
potential for recall bias, social desirability bias, and knowledge
bias existed among those interviewed because awareness of
the details of the decedent’s life varied among contacts. Some
questions were more prone to bias, such as illicit drug use and
nonprescription sources of pain medication. Bias may have
also occurred if knowledge that a person died from an
opioid-related drug overdose caused the interviewee to
overestimate or underestimate the presence of selected risk
factors (e.g., depression). Finally, the time after the
decedent’s death until the interview varied from 1 to
12 months. Although almost all interviews occurred within
5 months, recall bias may inc rease w ith longer time
between the death and the interview.
Deaths from an unintentional opioid-related overdose in
Utah primaril y occurred among ind ividuals who were
prescribed opioids for chronic pain. Many were reported
to have exhibited behaviors indicative of misuse, and to
have abused illicit drugs in the year prior to their death.
Most had a history of a substance use disorder and suffered
from a concurrent mental illness. Our findings reinforce the
Johnson et al.: Opioid-Related Deaths JGIM
need for more judicious prescribing of opioids, and closer
monitoring of those who are prescribed these drugs.
Acknowledgements: This study was funded by the Centers for
Disease Control and Prevention and the Utah Department of Health.
The findings and conclusions in this report are those of the authors
and do not necessarily represent the official position of the Centers
for Disease Control and Prevention. We express our appreciation to
the next of kin of best contacts that consented to be interviewed
after the death of a relative or friend as a result of a drug overdose.
Conflict of Interest: The authors declare that they do not have a
conflict of interest.
Corresponding Author: Ray M. Merrill, PhD, MPH, MS, FACE,
FAAHB; Department of Health Science, Brigham Young University,
Provo, UT 84602, USA (e-mail: Ray_Merrill@byu.edu).
1. Kuehn BM. Opioid prescriptions soar: increase in legitimate use as well
as abuse. JAMA. 2007;297(3):249–51.
2. Centers for Disease Control and Prevention. Vital signs: overdoses of
prescription opioid pain relievers—United States, 1999–2008. MMWR.
3. Centers for Disease Control and Prevention. CDC taking steps to combat
opioid deaths. Available at: http://asam-365.ascendeventmedia. com/
Highlight.aspx?id=4452&p=368. Accessed July 23, 2012.
4. Centers for Disease Control and Prevention. Prescription painkiller
overdoses in the U.S. Available at: http://www.cdc.gov/Features/Vital
signs/PainkillerOverdoses/. Accessed July 23, 2012.
5. Schonfeld L, King-Kallimanis BL, Duchene DM, et al. Screening and
brief intervention for substance misuse among older adults: the Florida
BRITE project. Am J Public Health. 2010;100(1):108–14.
6. Gourlay DL, Heit HA, Almahrezi A. Universal precautions in pain
medicine: a rational approach to the treatment of chronic pain. Pain
7. White AG, Birnbaum HG, Schiller M, Tang J, Katz NP. Analytic models
to identify patients at risk for prescription opioid abuse. Am J Manag
8. Braden JB, Russo J, Fan MY, et al. Emergency department visits
among recipients of chronic opioid therapy. Arch Intern Med. 2010;170
9. Centers for Disease Control and Prevention. Increase in poisoning
deaths c aused by non-illi cit drug s—Utah, 1991– 2003. MMWR.
10. Hall AJ, Logan JE, Toblin RL, Kaplan JA, Kraner JC, Bixler D, et al.
Patterns of abuse among unintentional pharmaceutical overdose fatal-
ities. JAMA. 2008;300(22):2613–20.
11. Jamison RN, Butler SF, Budman SH, Edwards RR, Wasan AD. Gender
differences in risk factors for aberrant prescription opioid use. J Pain.
12. Utah Health Code. Available at: http://le.utah.gov/code/TITLE26/htm/
26_04_000700.htm. Accessed July 28, 2012.
13. U.S. Census Bureau. Available at: http://factfinder2.census.gov/faces/
nav/jsf/pages/searchresults.xhtml?refresh=t. Accessed July 30, 2012.
14. Centers for Disease Control and Prevention. Prevalence and Trends
Data: All States 2009. Available at: http://apps.nccd.cdc.gov/BRFSS/
page.asp?cat=OB&yr=2009&state=All#OB. Accessed July 30, 2012.
15. U.S. Census Bureau. Current Population Survey, 1960 to 2010 Annual
Social and Economic Supplements. Available at: http://www.census.gov/
hhes/www/poverty/data/incpovhlth/2009/pov09fig04.pdf. Accessed Ju-
ly 30, 2012.
16. DeNavas-Walt C, Proctor BD, Smith JC. U.S. Census Bureau, Current
Population Reports, P60-238. Income, Poverty, and Health Insurance
Coverage in the United States: 2009. Washington, DC: U.S. Government
Printing Office; 2010.
17. National Center for Health Statistics. Health, United States, 2011: With
Special Feature on Socioeconomic Status and Health. Hyattsville, MD.
2012. Table 54. Available a t: http://www.cdc.gov/nchs/data/hus/
hus11.pdf. Accessed July 24, 2012.
18. Kessler RC, Angermeyer M, Anthony JC, et al. Lifetime prevalence
and age-of-onset distributions of mental disorders in the World Health
Organization’s World Mental Health Survey Initiative. World Psychiatry.
19. Substance Abuse and Mental Health Services Administration. State
Estimates of Substance Use and Mental Disorders from the 2008–2009
National Surveys on Drug Use and Health, NSDUH Series H-40, HHS
Publication No. (SMA) 11-4641. Rockville, MD: Substance Abuse and
Mental Health Services Administration, 2011.
20. Substance Abuse & Mental Health Data Archive. For the National Survey
on Drug Use and Health, 2009. A vailable at: http://www .icpsr .umich.edu/
quicktables/quickconfig.do?29621-0001_du. Accessed July 24, 2012.
21. Reeves WC, Strine TW, Pratt LA, et al. Mental illness surveillance
among adults in the United States. Available at: http://www.cdc.gov/
Accessed July 24, 2012.
22. Kessler RC, Chiu WT, Demler O, Walters EE. Prevalence, severity, and
comorbidity of twelve-month DSM-IV disorders in the National Comor-
bidity Survey Replication (NCS-R). Arch Gen Psychiatry. 2005;62(6):617–
23. Ives TJ, Chelminski PR, Hammett-Stabler CA, et al. Predictors of
opioid misuse in patients with chronic pain: a prospective cohort study.
BMC Health Serv Res. 2006;6:46.
24. Edlund MJ, Steffick D, Hudson T, Harris KM, Sullivan M. Risk
factors for clinically recognized opioid abuse and dependence among
veterans using opioids for chro nic non-c ancer pai n. Pain. 2 007;129
25. Grattan A, Sullivan MD, Saunders KW, Campbell CI, Von Korff MR.
Depression and prescri ption opio id misuse amon g chronic opioid
therapy recipients with no history of substance abuse. Ann Fam Med.
26. Alam A, Gomes T, Zheng H, Mamdani MM, Juurlink DN, Bell CM.
Long-term analgesic use after low-risk surgery: a retrospective cohort
study. Arch Intern Med. 2012;172(5):425–30.
27. Seal KH, Shi Y, Cohen G, et al. Association of mental health disorders
with prescription opioids and high-risk opioid use in US veterans of Iraq
and Afghanistan. JAMA. 2012;307(9):940–7.
28. Bates C, Laciak R, Southwick A, Bishoff J. Ove rprescription of
postoperative narcotics: a look at postoperative pain medication delivery,
consumption and disposal in urological practice. J Urol. 2011;185
29. Paulozzi LJ, Kilbourne EM, Desai HA. Prescription drug monitoring
program and death rates from drug overdose. Pain Med. 2011;12(5):747–
30. Bohnert AS, Valenstein M, Bair MJ, et al. Association between opioid
prescribing patterns and opioid overdose-related deaths. JAMA.
31. Edlund MJ, Martin BC, Fan MY, Devries A, Braden JB, Sullivan MD.
Risks for opioid abuse and dependence among recipients of chronic
opioid therapy: results from the TROUP study. Drug Alcohol Depend.
32. McLellan AT, Turner BJ. Chronic noncancer pain management and
opioid overdose: time to change prescribing practices. Ann Intern Med.
33. Dunn KM, Saunders KW, Rutter CM, Banta-Green CJ, Merrill JO,
Sullivan MD, et al.
Opioid prescriptions for chronic pain and overdose: a
cohort study. Ann Intern Med. 2010;152(2):85–92.
34. Toblin RL, Paulozzi LJ, Logan JE, Hall AJ, Kaplan JA. Mental illness
and psychotropic drug use among prescription drug overdose deaths: a
medical examiner chart review. J Clin Psychiatry. 2010;71(4):491–6.
35. Michna E, Ross EL, Hynes WL, et al. Predicting aberrant drug behavior
in patients treated for chronic pain: importance of abuse history. J Pain
Symptom Manage. 2004;28(3):250–8.
36. Utah Department of Health, Center for Health Data Indicator-Based
Information System for Public Health. Percentage of adults who reported
current cigarette smoking by education, Utah adults aged 25 and older,
2009; 2011. Available at: http://ibis.health.utah.gov/indicator/view/
CigSmokAdlt.Edu.html. Accessed 5 January, 2012.
37. Centers for Disease Control and Prevention. State-specific prevalance of
cigarette smoking and smokeless tobacco use among adults—United
States, 2009. MMWR. 2010;59(43):1400–6.
38. Wiesbeck GA, Kuhl HC, Yaldizli O, Wurst FM, WHO/ISBRA Study
Group on Biological State and Trait Markers of Alcohol Use and
Johnson et al.: Opioid-Related DeathsJGIM
Dependence. Tobacco smoking and depression—results from the WHO/
ISBRA study. Neuropsychobiology. 2008;57(1–2):26–31.
39. Von Korff M, Deyo RA. Potent opioids for chronic musculoskeletal pain:
flying blind? Pain. 2004;109(3):207–9.
40. Kidner CL, Mayer TG, Gatchel RJ. Higher opioid doses predict
poorer functional outcome in patients with chronic disabling occupa-
tional musculoskeletal disorders. J Bone Joint Surg Am. 2009;91
41. Volinn E, Fargo JD, Fine PG. Opioid therapy for nonspecific low back
pain and the outcome of chronic work loss. Pain. 2009;142(3):194–201.
42. Blyth FM, March LM, Brnabic AJ, Jorm LR, Williamson M, Cousins MJ.
Chronic pain in Australia: a prevalence stud y. Pain. 2001;89(2–3):127–34.
Johnson et al.: Opioid-Related Deaths JGIM