This document summarizes a study conducted in Utah that interviewed friends and family of individuals aged 13 and older who died from a drug overdose between October 2008 and October 2009. The study found that overdoses involving prescription opioids were most common among those aged 25-54, with oxycodone, methadone, hydrocodone, and alprazolam most frequently implicated. Characteristics strongly correlated with overdose death included financial problems, past substance abuse, and mental illness. Unemployment, past substance abuse history, and mental illness diagnosis merit further investigation to better understand their relationship to unintentional prescription opioid overdoses.
The document discusses the growing problem of prescription drug abuse and overdose deaths in the United States. Some key points made include:
- In 2010, there were over 38,000 drug overdose deaths in the US, with prescription drugs accounting for over 22,000 of those deaths.
- Prescription drug abuse is the fastest growing drug problem in the country.
- Deaths from drug overdoses now outnumber deaths from motor vehicle accidents.
- The number of forensic drug cases tested has increased over 240% from 2001 to 2011.
- States in the Southwest and Appalachia have the highest rates of drug overdose mortality.
This study examined health insurance claims data from over 10 million patients who were prescribed opioids to evaluate how opioid receipt differed based on preexisting psychiatric conditions and medications. The study found that patients with a variety of psychiatric conditions and those prescribed various psychoactive medications were more likely to receive opioids, particularly long-term opioid therapy. The increased risk for long-term opioid therapy ranged from 1.5 times higher for those previously prescribed ADHD medications, to over 8 times higher for those with prior opioid use disorder diagnoses. The results provide evidence that commercially insured patients with psychiatric conditions receive opioids more than those without such conditions.
Higher prescribed opioid doses are associated with elevated suicide risk among veterans with chronic pain. The study analyzed medical records of over 123,000 veterans with chronic pain receiving opioids from 2004 to 2005. It found that compared to those receiving less than 20 mg/day of opioids, the hazard ratio for suicide was 1.48 for 20 to less than 50 mg/day, 1.69 for 50 to less than 100 mg/day, and 2.15 for 100 mg/day or more, after controlling for other factors. Similarly, rates of suicide by intentional overdose increased from 8.2 per 100,000 person-years at less than 20 mg/day to 27.8 per 100,000 person-years at 100 mg
This document summarizes New Jersey's response to the rise in prescription drug and heroin abuse. It discusses several key aspects of New Jersey's approach, including the prescription drug monitoring program (NJPMP), drug take-back programs like Project Medicine Drop, educational campaigns, a Good Samaritan law providing legal protection for those reporting overdoses, expansion of drug treatment programs, and a Medicaid lock-in program. The strategies aim to curb prescription drug diversion and abuse, expand access to treatment, prevent overdoses, and reduce related harms like the spread of HIV/AIDS and hepatitis C.
This study examined factors affecting adherence to Suboxone treatment among 50 African American patients through a retrospective chart review. The results showed significantly negative correlations between adherence and concurrent use of opioids, cocaine, and alcohol. Surprisingly, PTSD showed a positive correlation with adherence, contradicting other studies. No correlation was found between adherence and unemployment. The study concluded that while mental health issues and unemployment may impact adherence, the small sample size likely influenced the results. Larger studies are still needed to fully understand factors affecting Suboxone adherence in minority groups.
Patterns of opioid use and risk of opioid overdose.Paul Coelho, MD
This study examined patterns of opioid use and risk of opioid overdose death among 150,821 noncancer pain patients in the Washington Medicaid program between 2006 and 2010. The results showed that risk of overdose death significantly increased with higher average daily opioid doses, with a 4.9 times higher risk at doses of 200 mg or more per day compared to doses of 1-19 mg. Patients using both long-acting and short-acting Schedule II opioids had a 4.7 times higher risk than those using non-Schedule II opioids alone. Concurrent use of sedative-hypnotics was associated with a significantly increased risk of overdose death compared to nonuse, with benzodiazepines and skeletal muscle relaxants posing the
The document discusses the growing problem of prescription drug abuse and overdose deaths in the United States. Some key points made include:
- In 2010, there were over 38,000 drug overdose deaths in the US, with prescription drugs accounting for over 22,000 of those deaths.
- Prescription drug abuse is the fastest growing drug problem in the country.
- Deaths from drug overdoses now outnumber deaths from motor vehicle accidents.
- The number of forensic drug cases tested has increased over 240% from 2001 to 2011.
- States in the Southwest and Appalachia have the highest rates of drug overdose mortality.
This study examined health insurance claims data from over 10 million patients who were prescribed opioids to evaluate how opioid receipt differed based on preexisting psychiatric conditions and medications. The study found that patients with a variety of psychiatric conditions and those prescribed various psychoactive medications were more likely to receive opioids, particularly long-term opioid therapy. The increased risk for long-term opioid therapy ranged from 1.5 times higher for those previously prescribed ADHD medications, to over 8 times higher for those with prior opioid use disorder diagnoses. The results provide evidence that commercially insured patients with psychiatric conditions receive opioids more than those without such conditions.
Higher prescribed opioid doses are associated with elevated suicide risk among veterans with chronic pain. The study analyzed medical records of over 123,000 veterans with chronic pain receiving opioids from 2004 to 2005. It found that compared to those receiving less than 20 mg/day of opioids, the hazard ratio for suicide was 1.48 for 20 to less than 50 mg/day, 1.69 for 50 to less than 100 mg/day, and 2.15 for 100 mg/day or more, after controlling for other factors. Similarly, rates of suicide by intentional overdose increased from 8.2 per 100,000 person-years at less than 20 mg/day to 27.8 per 100,000 person-years at 100 mg
This document summarizes New Jersey's response to the rise in prescription drug and heroin abuse. It discusses several key aspects of New Jersey's approach, including the prescription drug monitoring program (NJPMP), drug take-back programs like Project Medicine Drop, educational campaigns, a Good Samaritan law providing legal protection for those reporting overdoses, expansion of drug treatment programs, and a Medicaid lock-in program. The strategies aim to curb prescription drug diversion and abuse, expand access to treatment, prevent overdoses, and reduce related harms like the spread of HIV/AIDS and hepatitis C.
This study examined factors affecting adherence to Suboxone treatment among 50 African American patients through a retrospective chart review. The results showed significantly negative correlations between adherence and concurrent use of opioids, cocaine, and alcohol. Surprisingly, PTSD showed a positive correlation with adherence, contradicting other studies. No correlation was found between adherence and unemployment. The study concluded that while mental health issues and unemployment may impact adherence, the small sample size likely influenced the results. Larger studies are still needed to fully understand factors affecting Suboxone adherence in minority groups.
Patterns of opioid use and risk of opioid overdose.Paul Coelho, MD
This study examined patterns of opioid use and risk of opioid overdose death among 150,821 noncancer pain patients in the Washington Medicaid program between 2006 and 2010. The results showed that risk of overdose death significantly increased with higher average daily opioid doses, with a 4.9 times higher risk at doses of 200 mg or more per day compared to doses of 1-19 mg. Patients using both long-acting and short-acting Schedule II opioids had a 4.7 times higher risk than those using non-Schedule II opioids alone. Concurrent use of sedative-hypnotics was associated with a significantly increased risk of overdose death compared to nonuse, with benzodiazepines and skeletal muscle relaxants posing the
Socio demographic variables and personality profiles of patients with substan...Alexander Decker
This study examined the relationship between sociodemographic variables, personality types, and substance abuse among 65 patients at a drug abuse treatment facility in Nigeria. The study found that most patients were male, single, unemployed or students, and had secondary education or higher. The most commonly abused substances were cannabis, alcohol, and multiple substances. Personality assessments found that antisocial, passive-dependent, and passive-aggressive personality types were most common among patients. The study aimed to investigate relationships between personality profiles, substance use disorders, and sociodemographic factors like age, gender, education level, and employment among patients seeking treatment for substance abuse.
The opioid epidemic in the U.S. continues, with drug overdose deaths nearly tripling from 1999-2014. From 2014-2015, opioid overdose death rates increased by 15.6%, driven by increases in deaths involving heroin and synthetic opioids other than methadone. Specifically, death rates from synthetic opioids increased by 72.2% and heroin by 20.6%. These increases occurred across age groups, sexes, races/ethnicities, and regions. While methadone death rates declined by 9.1%, natural/semisynthetic opioid death rates rose by 2.6%. A multifaceted public health and law enforcement approach is urgently needed to address the crisis, including expanding access to treatment and
April 3, 2017
The current opiate epidemic has spurred long-overdue scrutiny on the pharmaceutical production and distribution of opiate medication, but it also raises questions of public policy and law regarding the regulation of medical access to and use of opiate medications with high potential for addiction. Expert panelists will address the challenges that arise from efforts to balance restrictions on access to opiates to limit addiction while also preserving sufficient access for legitimate medical management of pain.
Learn more on our website: http://petrieflom.law.harvard.edu/events/details/opiate-regulation-policies
This document summarizes opioid prescribing trends, policies, and their impacts in Canada and at the US-Canada border. It finds that while Canada and the US have high opioid consumption, Canadian policies like introducing tamper-deterrent OxyContin and a prescription monitoring program reduced potentially inappropriate prescribing by 1%. However, over 1 million such prescriptions remain, and inconsistencies in provincial policies and lack of prescriber access to prescription data limit the policies. The approval of generic long-acting oxycodone in Canada did not increase trafficking into the US, though losses cannot be tracked. Ongoing evaluation is needed to improve policies around opioid availability and curb misuse across the border.
Rx16 federal tues_200_1_gladden_2halpin_3greenOPUNITE
This document provides information about the emerging fentanyl overdose epidemic in the United States from the national and state perspectives. It discusses the rise in fentanyl-related overdoses and seizures from 2013-2014 according to data from various sources. The learning objectives are to explain the epidemiology of the rise in fentanyl overdoses, identify lessons from an Ohio investigation, and describe one state's experience. Recommendations include improving detection of fentanyl through testing and surveillance, expanding naloxone access, and long-term efforts to reduce opioid overdoses through prescribing guidelines and treatment expansion.
Correlation of opioid mortality with prescriptions and social determinants -a...Paul Coelho, MD
This study analyzed Medicare Part D data from 2013-2014 to examine the relationship between opioid prescription rates, socioeconomic factors, and opioid-related mortality rates at the county level in the United States. The results showed that higher county-level opioid prescription rates, especially those from emergency medicine, family medicine, internal medicine, and physician assistants, were associated with higher opioid-related mortality rates. Higher poverty levels and proportions of white populations in counties also correlated with increased mortality. Additionally, prescribers in the highest quartile of opioid prescription rates had a disproportionate impact on mortality compared to the remaining 75% of prescribers.
A Cross Sectional Study of Ethnic Differences in Occurrence and Severity of A...iosrphr_editor
Non-steroidal anti-inflammatory drugs are the most widely used "over the counter" medication all over the world despite their complications in different major organs. Present studies envisaged for knowing the occurrence and severity of adverse drug reactions from NSAIDs in different ethnic communities of Sikkim. A cross sectional study was undertaken in the medicine outpatients department of a secondary and tertiary care hospital. The patients belonging to Nepalese, Bhutias, Lepchas ethnic communities and others community (settlers from other parts of India) were included to analyzed the data based on the age and gender, ethnicity and ADRs, drugs and ADRs. Severity assessment was done using Hartwing and Siegel scale and causality assessment by Naranjo scale. Total 109 cases of ADRs, predominating in female were detected. Nepalese were the most affected and Gastrointestinal tract (GIT) being the most affected organ in them. Diclofenac showed maximum number of ADRs in all the communities. Maximum number of cases occurred on single day use (40.36%) of drugs. All the cases were belonging to the "possible category" and the maximum being the mild (72.48%) in nature. It is advisable to consider the ethnic/racial differences equally with other factors, to improve the safety and efficacy of a drug.
The document discusses addressing the opioid epidemic through a public health lens. It provides data on the rise in opioid-related deaths in Massachusetts from 2000-2016. It also discusses prevention, intervention, treatment and recovery efforts through Governor Baker's Opioid Working Group. This includes adopting core medical competencies focused on substance use, expanding treatment beds and recovery programs, and the Chapter 55 data initiative to better understand the epidemic through linking multiple health datasets.
This document discusses strategies to curb prescription drug abuse, specifically opioid abuse, in West Virginia. It notes that West Virginia has the highest drug overdose mortality rate in the US and clinicians there write a high number of opioid prescriptions. It explores reasons for high prescribing rates and discusses solutions like improving education for patients and doctors, changing financial incentives, using prescription drug monitoring programs, and following CDC guidelines for safer opioid prescribing. Alternative therapies for pain management and the role of EDIE in monitoring patients and interfacing with PDMPs are also covered. The document advocates for internal referrals to pain specialists and multidisciplinary approaches to pain care.
Injury is the leading cause of death among children and adults up to age 44 and is the leading cause of potential life lost before age 65 (Healthy States, 2007, p. 3). In 200, more than 120,000 Americans of all ages died from injuries from motor vehicle crashes, suicide, falls, poisoning, drug overdoses, drowning, fires and other causes (Centers for Disease Control and Prevention [CDC], 2006) while more than 20,000 persons in the United States die from drug overdose.
Because of its impact on the health of all Americans--young and old--preventing injury is a serious public health challenge. As recent tragedies shine the spotlight on accidental drug overdoses, it’s becoming increasingly clear that prescription drugs are playing an increasing role in accidental deaths (Kelley, 2009, p. 24).
This document provides guidelines from the CDC for prescribing opioids for chronic pain outside of active cancer treatment, palliative care, and end-of-life care. It summarizes that while opioids can provide short-term pain relief, there is little evidence for their long-term effectiveness and they present serious risks including overdose and opioid use disorder. It then outlines recommendations for clinicians on when to initiate or continue opioids, opioid selection and dosing, assessing risks, and addressing harms to improve safety and reduce risks of long-term opioid therapy.
TRENDS AND PATTERNS OF GEOGRAPHIC VARIATIONS IN OPIOID PRESCRIBINGwith Wind
The document analyzes trends in opioid prescribing practices across US states from 2006 to 2017. It finds that while the total amount of opioids prescribed decreased over this period, the duration of prescriptions increased. Specifically:
- The total amount of opioids prescribed per person decreased 12.8% on average nationally, though there was significant variation between states.
- The mean duration of opioid prescriptions increased 37.6% nationally, with increases in every state.
- Prescriptions for durations of 30 days or longer, which are more likely to treat chronic pain, increased 37.7% nationally, with increases in 39 states.
- However, prescribing rates decreased for high dosages, short durations,
This document summarizes a presentation on drugs to watch including tramadol, hydrocodone, and naloxone. It includes:
- Disclosures from presenters declaring no conflicts of interest.
- Learning objectives focused on analyzing the impact of schedule changes for tramadol and hydrocodone, educating on tramadol dangers, and evaluating pharmacist perspectives on naloxone.
- Information presented on the drugs including their classifications, potencies, risks of abuse and addiction, and impacts of rescheduling hydrocodone and tramadol in California. Data showed decreased hydrocodone prescriptions but increased tramadol and overall opioid prescriptions, as well as increased over
This document discusses drugged driving and the unique legal issues it presents. It notes that 1 in 8 weekend, nighttime drivers test positive for illicit drugs and 33% of fatally injured drivers tested positive for drugs in 2009. Marijuana, cocaine, and prescription drugs are commonly found. Studies show drugs like marijuana negatively impact driving ability. Per se drugged driving laws are complicated by the lack of impairment thresholds like the .08 BAC standard for alcohol. Prosecutors may need drug recognition experts as witnesses. Initial stops, admissibility of tests, the right to confrontation, and jury attitudes also present unique issues in drugged driving cases compared to DWI.
Fear of withdrawal perpetuates opioid use in CNP.Paul Coelho, MD
This document discusses a study that examined reasons for prescription opioid use among patients seeking treatment for opioid dependence. The study found that participants with chronic pain were more likely to report using opioids initially for pain relief, while avoiding withdrawal was the most common reason for current use among all participants. Participants with chronic pain rated coping with physical pain as a more important reason for use, and social or craving reasons as less important, compared to those without chronic pain. The results highlight the role of physical pain as a key reason for opioid use among patients with dependence who have chronic pain conditions.
How Do Opioid Prices and the Evolving Opioid Crisis Relate to the North Ameri...with Wind
The Role of Opioid Prices in the Evolving Opioid Crisis is a publication by order of the Commander in Chief; Our 45th President, Mr. Donald J Trump.
This is an objective purview of the role pharmaceutical marketing and advertising and the one true law that is Supply and Demand have had on the current crisis North America finds itself in.
I aim to be objective - no subjective - or opinionated argument - merely share the presentation as it was originally published by < whitehouse.gov. >
I will state this - however - the opioid crisis - is real - it is not some propaganda cooked up by CDC - DEA - or the Free Masons (wholly misunderstood by today's youth - Illuminati).
It has - in some, shape, form or fashion - affected every single North American at some point over the entirety of this - ridiculous attempt at going to war - against substances.
For my opinions, feel free to connect on
< https://www.linkedin.com/in/oudcollective >
FOLLOW @oudcollective
< https://www.twitter.com/oudcollective >
or help out in pinning beginnings at
< https://www.pinterest.com/THEWINDLLC >
Best,
< linktr.ee/C.Brennan.Poole >
< https://allmylinks.com/chasing-the-wind >
Chasing the Wind, LLC DBA THE WIND LLC is licensed under a creative commons attribution share-alike (CC BY-SA) International 4.0 license. Link to license at < www.creativecommons.org/licenses/by-sa/4.0 >
This document summarizes drug trends in Miami-Dade and Broward Counties in Florida based on data from 2012-2013. Key findings include: 1) Prescription drug diversion declined across Florida while deaths from opioids like hydromorphone increased. 2) Synthetic cathinones like methylone replaced MDMA and other emerging drugs were identified. 3) Cocaine deaths declined in both counties but treatment admissions also declined. Heroin indicators were rising. Marijuana treatment admissions declined significantly.
This research paper focuses on prescription opioids and its effects on the African American community. The author discusses the background, best treatment intervention, and ethical considerations associated with prescription opioids and their use within the African American population.
Daniel Blaney-Koen, American Medical Association, presented on The Nation's Opioid Epidemic: Are we Asking the Right Questions? at the State Legislative Conference on November 6, 2015.
This paper examines the relationship between socioeconomic factors and prescription drug abuse. It reviews 7 studies that found higher rates of opioid misuse among low-income populations, including Medicaid patients and those with mental health or substance abuse disorders. While doctors often perceive younger and non-white patients to be at higher risk of abuse, studies have found no evidence to support these assumptions. The paper calls for reducing reliance on opioids for chronic pain and improving clinician training on cultural competence and implicit biases.
Socio demographic variables and personality profiles of patients with substan...Alexander Decker
This study examined the relationship between sociodemographic variables, personality types, and substance abuse among 65 patients at a drug abuse treatment facility in Nigeria. The study found that most patients were male, single, unemployed or students, and had secondary education or higher. The most commonly abused substances were cannabis, alcohol, and multiple substances. Personality assessments found that antisocial, passive-dependent, and passive-aggressive personality types were most common among patients. The study aimed to investigate relationships between personality profiles, substance use disorders, and sociodemographic factors like age, gender, education level, and employment among patients seeking treatment for substance abuse.
The opioid epidemic in the U.S. continues, with drug overdose deaths nearly tripling from 1999-2014. From 2014-2015, opioid overdose death rates increased by 15.6%, driven by increases in deaths involving heroin and synthetic opioids other than methadone. Specifically, death rates from synthetic opioids increased by 72.2% and heroin by 20.6%. These increases occurred across age groups, sexes, races/ethnicities, and regions. While methadone death rates declined by 9.1%, natural/semisynthetic opioid death rates rose by 2.6%. A multifaceted public health and law enforcement approach is urgently needed to address the crisis, including expanding access to treatment and
April 3, 2017
The current opiate epidemic has spurred long-overdue scrutiny on the pharmaceutical production and distribution of opiate medication, but it also raises questions of public policy and law regarding the regulation of medical access to and use of opiate medications with high potential for addiction. Expert panelists will address the challenges that arise from efforts to balance restrictions on access to opiates to limit addiction while also preserving sufficient access for legitimate medical management of pain.
Learn more on our website: http://petrieflom.law.harvard.edu/events/details/opiate-regulation-policies
This document summarizes opioid prescribing trends, policies, and their impacts in Canada and at the US-Canada border. It finds that while Canada and the US have high opioid consumption, Canadian policies like introducing tamper-deterrent OxyContin and a prescription monitoring program reduced potentially inappropriate prescribing by 1%. However, over 1 million such prescriptions remain, and inconsistencies in provincial policies and lack of prescriber access to prescription data limit the policies. The approval of generic long-acting oxycodone in Canada did not increase trafficking into the US, though losses cannot be tracked. Ongoing evaluation is needed to improve policies around opioid availability and curb misuse across the border.
Rx16 federal tues_200_1_gladden_2halpin_3greenOPUNITE
This document provides information about the emerging fentanyl overdose epidemic in the United States from the national and state perspectives. It discusses the rise in fentanyl-related overdoses and seizures from 2013-2014 according to data from various sources. The learning objectives are to explain the epidemiology of the rise in fentanyl overdoses, identify lessons from an Ohio investigation, and describe one state's experience. Recommendations include improving detection of fentanyl through testing and surveillance, expanding naloxone access, and long-term efforts to reduce opioid overdoses through prescribing guidelines and treatment expansion.
Correlation of opioid mortality with prescriptions and social determinants -a...Paul Coelho, MD
This study analyzed Medicare Part D data from 2013-2014 to examine the relationship between opioid prescription rates, socioeconomic factors, and opioid-related mortality rates at the county level in the United States. The results showed that higher county-level opioid prescription rates, especially those from emergency medicine, family medicine, internal medicine, and physician assistants, were associated with higher opioid-related mortality rates. Higher poverty levels and proportions of white populations in counties also correlated with increased mortality. Additionally, prescribers in the highest quartile of opioid prescription rates had a disproportionate impact on mortality compared to the remaining 75% of prescribers.
A Cross Sectional Study of Ethnic Differences in Occurrence and Severity of A...iosrphr_editor
Non-steroidal anti-inflammatory drugs are the most widely used "over the counter" medication all over the world despite their complications in different major organs. Present studies envisaged for knowing the occurrence and severity of adverse drug reactions from NSAIDs in different ethnic communities of Sikkim. A cross sectional study was undertaken in the medicine outpatients department of a secondary and tertiary care hospital. The patients belonging to Nepalese, Bhutias, Lepchas ethnic communities and others community (settlers from other parts of India) were included to analyzed the data based on the age and gender, ethnicity and ADRs, drugs and ADRs. Severity assessment was done using Hartwing and Siegel scale and causality assessment by Naranjo scale. Total 109 cases of ADRs, predominating in female were detected. Nepalese were the most affected and Gastrointestinal tract (GIT) being the most affected organ in them. Diclofenac showed maximum number of ADRs in all the communities. Maximum number of cases occurred on single day use (40.36%) of drugs. All the cases were belonging to the "possible category" and the maximum being the mild (72.48%) in nature. It is advisable to consider the ethnic/racial differences equally with other factors, to improve the safety and efficacy of a drug.
The document discusses addressing the opioid epidemic through a public health lens. It provides data on the rise in opioid-related deaths in Massachusetts from 2000-2016. It also discusses prevention, intervention, treatment and recovery efforts through Governor Baker's Opioid Working Group. This includes adopting core medical competencies focused on substance use, expanding treatment beds and recovery programs, and the Chapter 55 data initiative to better understand the epidemic through linking multiple health datasets.
This document discusses strategies to curb prescription drug abuse, specifically opioid abuse, in West Virginia. It notes that West Virginia has the highest drug overdose mortality rate in the US and clinicians there write a high number of opioid prescriptions. It explores reasons for high prescribing rates and discusses solutions like improving education for patients and doctors, changing financial incentives, using prescription drug monitoring programs, and following CDC guidelines for safer opioid prescribing. Alternative therapies for pain management and the role of EDIE in monitoring patients and interfacing with PDMPs are also covered. The document advocates for internal referrals to pain specialists and multidisciplinary approaches to pain care.
Injury is the leading cause of death among children and adults up to age 44 and is the leading cause of potential life lost before age 65 (Healthy States, 2007, p. 3). In 200, more than 120,000 Americans of all ages died from injuries from motor vehicle crashes, suicide, falls, poisoning, drug overdoses, drowning, fires and other causes (Centers for Disease Control and Prevention [CDC], 2006) while more than 20,000 persons in the United States die from drug overdose.
Because of its impact on the health of all Americans--young and old--preventing injury is a serious public health challenge. As recent tragedies shine the spotlight on accidental drug overdoses, it’s becoming increasingly clear that prescription drugs are playing an increasing role in accidental deaths (Kelley, 2009, p. 24).
This document provides guidelines from the CDC for prescribing opioids for chronic pain outside of active cancer treatment, palliative care, and end-of-life care. It summarizes that while opioids can provide short-term pain relief, there is little evidence for their long-term effectiveness and they present serious risks including overdose and opioid use disorder. It then outlines recommendations for clinicians on when to initiate or continue opioids, opioid selection and dosing, assessing risks, and addressing harms to improve safety and reduce risks of long-term opioid therapy.
TRENDS AND PATTERNS OF GEOGRAPHIC VARIATIONS IN OPIOID PRESCRIBINGwith Wind
The document analyzes trends in opioid prescribing practices across US states from 2006 to 2017. It finds that while the total amount of opioids prescribed decreased over this period, the duration of prescriptions increased. Specifically:
- The total amount of opioids prescribed per person decreased 12.8% on average nationally, though there was significant variation between states.
- The mean duration of opioid prescriptions increased 37.6% nationally, with increases in every state.
- Prescriptions for durations of 30 days or longer, which are more likely to treat chronic pain, increased 37.7% nationally, with increases in 39 states.
- However, prescribing rates decreased for high dosages, short durations,
This document summarizes a presentation on drugs to watch including tramadol, hydrocodone, and naloxone. It includes:
- Disclosures from presenters declaring no conflicts of interest.
- Learning objectives focused on analyzing the impact of schedule changes for tramadol and hydrocodone, educating on tramadol dangers, and evaluating pharmacist perspectives on naloxone.
- Information presented on the drugs including their classifications, potencies, risks of abuse and addiction, and impacts of rescheduling hydrocodone and tramadol in California. Data showed decreased hydrocodone prescriptions but increased tramadol and overall opioid prescriptions, as well as increased over
This document discusses drugged driving and the unique legal issues it presents. It notes that 1 in 8 weekend, nighttime drivers test positive for illicit drugs and 33% of fatally injured drivers tested positive for drugs in 2009. Marijuana, cocaine, and prescription drugs are commonly found. Studies show drugs like marijuana negatively impact driving ability. Per se drugged driving laws are complicated by the lack of impairment thresholds like the .08 BAC standard for alcohol. Prosecutors may need drug recognition experts as witnesses. Initial stops, admissibility of tests, the right to confrontation, and jury attitudes also present unique issues in drugged driving cases compared to DWI.
Fear of withdrawal perpetuates opioid use in CNP.Paul Coelho, MD
This document discusses a study that examined reasons for prescription opioid use among patients seeking treatment for opioid dependence. The study found that participants with chronic pain were more likely to report using opioids initially for pain relief, while avoiding withdrawal was the most common reason for current use among all participants. Participants with chronic pain rated coping with physical pain as a more important reason for use, and social or craving reasons as less important, compared to those without chronic pain. The results highlight the role of physical pain as a key reason for opioid use among patients with dependence who have chronic pain conditions.
How Do Opioid Prices and the Evolving Opioid Crisis Relate to the North Ameri...with Wind
The Role of Opioid Prices in the Evolving Opioid Crisis is a publication by order of the Commander in Chief; Our 45th President, Mr. Donald J Trump.
This is an objective purview of the role pharmaceutical marketing and advertising and the one true law that is Supply and Demand have had on the current crisis North America finds itself in.
I aim to be objective - no subjective - or opinionated argument - merely share the presentation as it was originally published by < whitehouse.gov. >
I will state this - however - the opioid crisis - is real - it is not some propaganda cooked up by CDC - DEA - or the Free Masons (wholly misunderstood by today's youth - Illuminati).
It has - in some, shape, form or fashion - affected every single North American at some point over the entirety of this - ridiculous attempt at going to war - against substances.
For my opinions, feel free to connect on
< https://www.linkedin.com/in/oudcollective >
FOLLOW @oudcollective
< https://www.twitter.com/oudcollective >
or help out in pinning beginnings at
< https://www.pinterest.com/THEWINDLLC >
Best,
< linktr.ee/C.Brennan.Poole >
< https://allmylinks.com/chasing-the-wind >
Chasing the Wind, LLC DBA THE WIND LLC is licensed under a creative commons attribution share-alike (CC BY-SA) International 4.0 license. Link to license at < www.creativecommons.org/licenses/by-sa/4.0 >
This document summarizes drug trends in Miami-Dade and Broward Counties in Florida based on data from 2012-2013. Key findings include: 1) Prescription drug diversion declined across Florida while deaths from opioids like hydromorphone increased. 2) Synthetic cathinones like methylone replaced MDMA and other emerging drugs were identified. 3) Cocaine deaths declined in both counties but treatment admissions also declined. Heroin indicators were rising. Marijuana treatment admissions declined significantly.
This research paper focuses on prescription opioids and its effects on the African American community. The author discusses the background, best treatment intervention, and ethical considerations associated with prescription opioids and their use within the African American population.
Daniel Blaney-Koen, American Medical Association, presented on The Nation's Opioid Epidemic: Are we Asking the Right Questions? at the State Legislative Conference on November 6, 2015.
This paper examines the relationship between socioeconomic factors and prescription drug abuse. It reviews 7 studies that found higher rates of opioid misuse among low-income populations, including Medicaid patients and those with mental health or substance abuse disorders. While doctors often perceive younger and non-white patients to be at higher risk of abuse, studies have found no evidence to support these assumptions. The paper calls for reducing reliance on opioids for chronic pain and improving clinician training on cultural competence and implicit biases.
The economic burden of prescription opioid overdose... 2013.Paul Coelho, MD
The document summarizes a study that estimates the total economic burden of prescription opioid overdose, abuse, and dependence in the United States in 2013 was $78.5 billion. Over one third of this cost ($28.9 billion) was due to increased healthcare and substance abuse treatment costs. Approximately one quarter of the total cost was borne by the public sector through healthcare, substance abuse treatment, and criminal justice costs. The study utilized national data on opioid overdose deaths and abuse/dependence prevalence to estimate costs across multiple sectors including healthcare, substance abuse treatment, criminal justice, and lost productivity.
Dr Sabet Power Point Final Sept 23, 2013Heidi Denton
This document summarizes current drug use trends in the United States, with a focus on prescription drug abuse. It finds that prescription drug abuse is a major problem, with opioids like oxycodone and hydrocodone involved in most drug overdose deaths. It also discusses trends in other drugs like cocaine, heroin, methamphetamine, and marijuana. Prevention efforts discussed include education, prescription drug monitoring programs, proper medication disposal, and enforcement against "pill mills."
Examination of Over-the-Counter Drug Misuse Among Youth1 Erin J. F.docxgitagrimston
Examination of Over-the-Counter Drug Misuse Among Youth1 Erin J. Farley and Daniel J. O’Connell
Top of Form
Bottom of Form
Examination of Over-the-Counter Drug Misuse Among Youth by Erin J. Farley and Daniel J. O’Connell
Prepared by: Mary H. Maguire, California State University, Sacramento Article Kim Schnurbush, California State University,Sacramento
Examination of Over-the-Counter Drug Misuse Among Youth1 Erin J. Farley and Daniel J. O’Connell
Learning Outcomes
After reading this article, you will be able to:
• Discuss the factors that contribute to the prevalence of over- the-counter drug misuse by teens.
• Analyse the contribution of gender to over-the-counter drug misuse by teens.
• Discuss possible policy or practice efforts to decrease over- the-counter drug misuse by teens.
Introduction
Potential harm from the intentional misuse of over-the-counter (OTC) medicines among youth has become an area of increased concern among medical practitioners and researchers (Bryner et al. 2006; Lessenger et al. 2008; Substance Abuse and Mental Health Services Administration (SAMHSA) 2006). Although the likelihood of death from overdose is rare, research has revealed an increase in dextromethorphan (a key ingredient in numerous cough and cold medicines) abuse cases reported to poison control centers (Bryner et al. 2006). Equally important is the suspicion that OTC use may be a stepping stone to other forms of drug misuse and abuse.
While OTC misuse has garnered increased media coverage, it has not yet attracted an equivalent interest among research- ers. Further, it is possible that research to date has inappropri- ately specified the relationship between OTC and other drug misuse. Extant research has examined the relationship between OTC misuse and illicit drug use by utilizing a single construct, limiting the ability to completely flesh out the dimensions of this relationship between drug use. One area that needs further attention is if and how OTC misuse among youth is associated with other types of drug use. By combining all categories of
drugs under a single construct, the nuances of how particular drugs relate to OTC use is diminished. This paper examines the current state of knowledge on OTC misuse by examining the prevalence of OTC misuse and its relationship with other types of drug use among a specific cohort to expand the current understanding of the problem.
Prevalence of OTC Misuse
OTC cough and cold medicines (e.g., Coricidin and Nyquil) can be easily purchased from pharmacies and drug stores. Adolescents typically ingest OTC medicines for the ingredi- ent dextromethorphan (DXM). DXM is a synthetic drug related to opiates, which has the ability to produce effects similar to psychotropic drugs (Bobo et al. 2004; SAMHSA 2006). These effects include sensory enhancement, perceptual distortion, and hallucinations. DXM can be found in as many as 140 differ- ent cold and cough medications (Bobo et al. 2004; SAMHSA 2008). Misuse o ...
This study analyzed results from over 900,000 urine drug tests conducted between 2006-2009 on patients prescribed chronic opioids. The results showed:
- 11% tested positive for illicit drugs
- 29% tested positive for non-prescribed medications
- 38% did not detect the prescribed medication
- 15% had lower than expected levels of the prescribed medication
- 27% had higher than expected levels of the prescribed medication
These high rates of potential issues like non-compliance, abuse or diversion demonstrate the importance of periodic urine drug screening for patients on long-term opioid therapy to identify problems and ensure appropriate use of medications.
Patterns of Opioid Use and Risk of Opioid Overdose Death Among Medicaid PatientsPaul Coelho, MD
This study examined patterns of opioid use and risk of opioid overdose death among 150,821 noncancer pain patients in the Washington Medicaid program between 2006 and 2010. The results showed that compared to patients taking 1-19 mg per day of opioids, the risk of overdose death significantly increased at higher daily doses of 50 mg or more. Patients using both long-acting and short-acting Schedule II opioids had nearly 5 times the risk of overdose death compared to those using non-Schedule II opioids alone. Concurrent use of sedative-hypnotics, even at low opioid doses, was associated with a substantially greater risk of overdose death.
The Socioeconomic Consequences and Costs of Mental IllnessMika Truly
The document summarizes several socioeconomic consequences and costs of mental illness. It discusses how approximately half of adults with severe mental illnesses also have a substance abuse disorder, but only a small percentage receive treatment for both. It also examines how substance abuse and lack of medication adherence in the mentally ill have been associated with increased violence. Additionally, the document outlines how treating the mentally ill with co-occurring substance abuse disorders results in significantly higher psychiatric care costs. Lastly, it explores the high rates of incarceration and homelessness among the mentally ill population and the financial costs these issues impose on society.
National epidemiologic survey on alcohol and related conditions.seminar coorectDr. Amit Chougule
The document summarizes key findings from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). NESARC was a large national survey conducted in 2001-2002 and 2004-2005 to assess alcohol use, abuse and dependence. It found that 12-month and lifetime prevalence of alcohol abuse and dependence was 8.5% and 30.3%, respectively. Rates of abuse increased over time while dependence declined slightly. Risk was higher in men, whites, younger adults, and those with lower income or education levels. The survey also identified subgroups of alcoholics and found family history and comorbid disorders increased risk of dependence.
This document summarizes information about prescription drug monitoring programs (PMPs) and their role in preventing prescription drug abuse. Some key points:
- PMPs track prescriptions for controlled substances to identify patterns of abuse and diversion. Most states now have PMPs operating.
- Studies have found that a small percentage of individuals (around 1-2%) exhibit questionable patterns like using many prescribers and pharmacies. Early PMP queries in Kansas identified some individuals receiving high amounts of controlled substances from multiple providers.
- One study found that states with PMPs in place did not see significant reductions in overdose death rates compared to states without PMPs. However, PMP characteristics like mandatory
This document provides an overview of state prescription drug monitoring programs (PMPs) and summarizes their status and operations. It finds that 44 states currently operate PMPs that collect prescription data, with most programs housed in health departments or related agencies. States fund PMPs through various means like grants, state appropriations, and licensing/registration fees. Fourteen states receive funding from licensing and registration fees specifically. The overview examines PMP laws and operations to assist policymakers in addressing prescription drug abuse, addiction, and diversion.
Mitochondrial Disease Community Registry: First look at the data, perspectiv...SophiaZilber
Patient-populated registries are an important component of rare disease communities for many
reasons, including their use as a tool for gathering opinions on specific topics. The Mitochondrial
Disease Community Registry (MDCR) was launched in 2014 for this purpose as well as to identify and
characterize mitochondrial disease patients from the patient perspective. Data collected over a four
year period and provided by adult mitochondrial disease patients and caregivers of pediatric
mitochondrial disease patients in response to a single survey are presented. Primary findings include
the importance of clinician-patient communication, need for treatment and cure, impact of the disease
on the entire life of a person, and quality of life as top issues as described by patients. Despite multiple
challenges, patients are hopeful about the future and thankful for the survey. Efforts should be made
to identify ways to better support patients, improve communication, and create more trusting and
healing relationships between patients and doctors. Additionally, data quality checks showed that more
clear and simple questions and shorter more-targeted surveys are needed in order to get accurate
and meaningful data that can be used for analysis and research in the future.
Smoking and Cessation Among Men Who Have Sex with Men in Baltimore (Prier 2014)Kyle Prier
This document summarizes a study on smoking and cessation among men who have sex with men (MSM) in Baltimore in 2011. Some key findings include:
- 60.4% of MSM in Baltimore were current smokers, while 24.6% had never smoked and 14.9% were former smokers.
- Current smoking was associated with factors like being African American, younger age, lower education, history of homelessness, and arrest.
- A multinomial logistic regression found significant effects of race, age, education, homelessness, arrest, and number of male sex partners on smoking status.
Vowles et al (2015) opioid misuse, abuse, and addictionPaul Coelho, MD
This systematic review analyzed 38 studies on rates of problematic opioid use among chronic pain patients. The review sought to provide precise prevalence estimates for misuse, abuse, and addiction by applying explicit definitions and weighting studies by sample size and quality. Rates of misuse averaged between 21-29%, while rates of addiction averaged between 8-12%. Only one study reported rates of abuse. Significant variability remained between studies. Higher quality studies and those where prevalence was a primary objective tended to report lower addiction rates. The review provides guidance on possible average rates but also indicates need for further clarification.
Running head DRUG TRAFFICKING 1DRUG TRAFFICKING 2.docxtodd271
Running head: DRUG TRAFFICKING 1
DRUG TRAFFICKING 2
Drug trafficking
Name
Institution
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Course
Date
Lancaster, K., Hughes, C., & Ritter, A. (2017). ‘Drug dogs unleashed’: An historical and political account of drug detection dogs for street-level policing of illicit drugs in New South Wales, Australia. Australian & New Zealand Journal of Criminology, 50(3), 360-378.
The article shows the historical account which is related to the development of drug detection using dogs. Dogs were used to detect illicit drugs, and it has become one of the strategies which are used to combat drug trafficking. In political and historical context policies have been developed in addressing the issue of drug trafficking. Use of dogs is one of the strategies which is used to detect drug trafficking, and they play important roles. Drug policies help in reducing the incidences of drug trafficking and other associated impacts.
Fukumi, S. (2016). Cocaine trafficking in Latin America: EU and US policy responses. Routledge.
The article explains the role of women in drug trafficking in the USA. Most of the illicit drugs are transported by women. Historically, drug trafficking was linked to men, but nowadays women have taken a big role n distributed of the illicit drugs. The domineering role of the males made them be linked to the drugs and those who provided. Little attention was given to the role of women in drug trafficking as they were viewed as powerlessness who cannot involve in such matters. Illicit drugs such as cocaine and Heroin are smuggled by women as they are less suspected to be carrying illicit drugs.
Bagley, B. M., & Rosen, J. D. (2015). Drug trafficking, organized crime, and violence in the Americas today. University Press of Florida.
The article explains how the United States has become a consumer of illicit drugs despite efforts which have been made to combat it. Drug trafficking has become a global problem with many countries consuming illicit drugs. Policies have been implemented to control drug trafficking and reduce crimes which are related to it. Some of these policies regulate on how the victims of drug trafficking should be charged. Violence and organized crime are also linked to drug trafficking.
Broséus, J., Rhumorbarbe, D., Mireault, C., Ouellette, V., Crispino, F., & Décary-Hétu, D. (2016). Studying illicit drug trafficking on Darknet markets: structure and organization from a Canadian perspective. Forensic science international, 264, 7-14.
The article investigates Darknet markets which are used as a center for illicit drug trafficking. Online platforms are used to provide a market for illicit drugs. Technological techniques are used to ensure that the drugs reach to the buyer. Most of the illicit drug trafficking are distributed through online market until they reach the destination countries. Vendors are diversified and continue to replicate marketplaces to provide a wide range of market and come across.
The document discusses trends in methamphetamine use and related harms across the United States based on data from national surveys and treatment centers. It finds that:
1) Methamphetamine use and overdose deaths more than doubled from 2010-2014, though rates remain lower than other drugs.
2) Treatment admissions for methamphetamine surpassed cocaine admissions from 2013-2015 and increased 17% from 2011-2015.
3) Over 70% of law enforcement agencies in the Pacific and West Central regions reported methamphetamine as the greatest drug threat in their areas.
Prescription opioid use among adults with mental health disorders in the US.Paul Coelho, MD
This study analyzed nationally representative health survey data to examine prescription opioid use among US adults with mental health disorders. The key findings were:
1) An estimated 18.7% of the 38.6 million American adults with mental health disorders use prescription opioids, accounting for 51.4% of the total opioid prescriptions distributed in the US each year.
2) Adults with mental health disorders were over 3 times more likely to use opioids compared to adults without mental health disorders.
3) Having a mental health disorder was associated with a more than 2 times greater odds of prescription opioid use after adjusting for other health factors.
Prescription Opioid Use Among Adults with Mental Health Disorders in the USPaul Coelho, MD
This study used nationally representative survey data to examine prescription opioid use among US adults with mental health disorders. The key findings were:
1) An estimated 18.7% of the 38.6 million American adults with mental health disorders use prescription opioids, accounting for 51.4% of the total opioid prescriptions distributed in the US each year.
2) Adults with mental health disorders were over 3 times more likely to use opioids compared to adults without mental health disorders.
3) Having a mental health disorder, such as depression or anxiety, was associated with a more than 2 times greater odds of prescription opioid use after adjusting for other factors.
The Utah Veterinary Diagnostic Laboratory is a cooperative effort between the Utah Department of Agriculture and Food and Utah State University that provides laboratory testing and expertise to protect animal health, promote Utah's agricultural economy, and protect public health. It serves various groups including animal owners, veterinarians, and regulatory agencies. While accredited nationally, it has been running deficits in recent years as public funding has remained flat while operating costs have increased, leading to consequences like higher user fees, outsourcing tests, eliminating positions, and inability to adopt new technologies.
This document presents a report on health disparities by Utah state legislative district published by the Utah Department of Health Office of Health Disparities in January 2019. It includes profiles for each of Utah's 29 state senate districts and 75 state house districts that provide information on health indicators and disparities. The report utilizes Utah Small Areas, which group similar communities within legislative districts, and the Utah Health Improvement Index to assess health equity across districts in a novel way. The goal is to empower elected officials to address health disparities and improve outcomes in their constituencies.
Localscapes is a program created to promote more water-efficient landscaping in Utah. It provides a 5-step process for designing a landscape using local plants with less watering needed. Cost comparisons showed that a Localscapes design for a 0.22 acre property would save over 130,000 gallons of water per year compared to a traditional design, while only costing $1,873 more on average. The program offers rebates and incentives for homeowners who work with approved landscape professionals to install a qualifying Localscapes design. It is partnering with various organizations and growing a network of landscape designers, contractors, and retailers to promote water-efficient landscaping.
This document summarizes the results of surveys conducted between 1987-2017 to determine the success of a translocation program that aimed to reestablish a desert tortoise population in Zone 4. Key findings include:
1) Tortoise density and abundance have increased over time, from undetected in 1987-91 to 13.4 tortoises/sq km in 2017, compared to 19.6 tortoises/sq km in the reserve.
2) Translocated adult tortoises exhibited higher growth rates than reserve tortoises.
3) Translocated tortoises displayed high site fidelity within Zone 4 despite some movement greater than tortoises in other zones.
4) Mortality risks like
The Logan River Observatory collects and stores water quality and flow data from the Logan River and its tributaries. This data is used to inform water resource decisions, support education programs, and further understanding of issues like stormwater and drinking water. The observatory works with local agencies, researchers, and communities to ensure the data is accessible and can support efforts to manage water resources, balance competing demands, and plan for a changing climate.
This document outlines several workforce development programs in Utah receiving funding from Talent Ready Utah. Weber State University is leading programs in building design and construction and cybersecurity with ongoing funding of $260,000 and $295,000 respectively. Utah State University is leading a core IT statewide stackable credential pathway with $370,000 in ongoing funding.
The Utah Division of Forestry, Fire and State Lands is requesting appropriations for FY20. In 2018, Utah saw its most expensive and active fire season on record, with over 486,000 acres burned at an estimated cost of $42 million to the state. The Division is requesting $19.8 million in supplemental funding for 2018 fire suppression and rehabilitation costs. The Division also manages over 1.5 million acres of sovereign lands and provides forestry assistance. The document outlines several ongoing and one-time funding requests to support phragmites control on Great Salt Lake, management plans for Bear Lake and Dalton Wells, a land lease database, and the Catastrophic Wildfire Reduction Strategy.
The Division of Wildlife Resources director Mike Fowlks presented on February 1, 2019. Their mission is to serve Utah as trustee and guardian of the state's wildlife with a hardworking staff. Funding comes from various sources including general funds, restricted funds, dedicated credits, and federal funds. The division has improved technology efficiencies and completed a nature center. Winter conditions so far have provided good snow and wildlife are doing well. Ongoing drought and wildfires threaten wildlife habitat while aquatic invasive species require ongoing monitoring. A request was made for $405,000 to address these species. A $35,000,000 budget request was made to acquire the Tabby Mountain property to conserve wildlife habitat through various funding sources including general funds
The Utah Department of Transportation presented on several infrastructure and transportation projects and funding requests to the Infrastructure & General Government Appropriations Committee. They discussed the I-15 Technology Corridor project, data and input for long-range planning, implementing Senate Bill 136 which reorganized UDOT, and funding requests for aircraft replacement and maintenance in the Aeronautics program. They also requested additional funds for local government land use and planning technical assistance.
The document provides an overview of the Utah System of Technical Colleges' (UTech) proposed FY 2020 budget. It outlines five funding priorities: 1) employee compensation increases, 2) $7 million for employer-driven program expansion and student support, 3) $3 million for equipment funds, 4) $650,000 for Custom Fit program, and 5) $250,000 for additional data analyst and software engineer positions for the system office. The budget request aims to increase program offerings, student support, and system analytics capabilities to further align technical education with employer needs and economic growth in Utah.
This document from the Division of Drinking Water outlines criteria for public water systems and provides guidance to water system owners and operators. It discusses the federal definition of a public water system, categories of water systems, population estimates, permitting processes, and responsibilities for infrastructure associated with master meters and bulk water connections. The document seeks input on regulatory approaches to existing and future bulk meters to clarify responsibilities and protect public health.
The document summarizes data from a Utah legislative report on suicide prevention. It finds that Utah's suicide rate in 2017 was 25.6 per 100,000 people, comparable to previous years. Suicide rates were highest among white and American Indian males in rural areas where firearm suicide rates were also higher. The report also details funding and effectiveness of Utah's suicide prevention programs, and concludes that 85% of gun deaths in Utah are suicides, with recommendations around limiting access to firearms.
The Utah Division of Aeronautics annual report outlines funding amounts and projects. It distributed $3.29 million in state grants across 28 projects and $47.4 million in federal FAA grants across 25 projects. Major pavement projects in the past 5 years included runways at Ogden, Richfield, SkyPark, Morgan, Provo, Spanish Fork, Dutch John, Manti, and Logan airports. The report also describes Morgan County Airport's runway refurbishment project and reconstruction of Hanksville Airport, as well as Utah's nationally recognized flight training program and new FAA regulations for commercial drone operators.
This quarterly report from the Utah Division of Child and Family Services provides statistics and outcomes measures for the fourth quarter of FY2018. It summarizes data on referrals, child protective services investigations, in-home services, foster care, and kinship care. Some key findings include that 51% of referrals were accepted for investigation, the most common supported allegations were neglect, domestic violence, and sexual abuse, and over 90% of children did not have a subsequent supported CPS case within 12 months of their initial case.
This presentation provides an overview and history of FirstNet, a nationwide public safety wireless broadband network:
- FirstNet was created in 2012 by Congress to provide emergency responders with a dedicated communications network. It has partnered with AT&T to build and operate the network.
- The network is being deployed in phases from 2018-2022, with $200 million already invested in Utah. It provides priority access and preemption capabilities to ensure first responders have connectivity during emergencies.
- Unique features include a separate core from commercial networks, 24/7 security monitoring, and a lab that tests devices and applications on the network.
This document summarizes a performance audit of state energy incentives in the state. It finds that energy-incentivizing tax credits total $74 million annually and are still growing. Several grant and loan programs not focused on energy provide more incentives than those that are focused on energy. Utilities' energy incentive programs cost $438.6 million. The audit recommends clearly identifying program intent to better measure success and establishing appropriate metrics to evaluate whether programs accomplish energy goals cost-effectively.
This document summarizes historical trends and emerging issues related to transportation policy and funding in Utah. It outlines how the state's transportation budget has historically relied on motor fuel taxes and vehicle registration fees, but these revenues are stabilizing or declining. To address a growing funding shortfall compared to transportation needs, the state is exploring options like public-private partnerships, bonding programs, and demand management strategies to supplement traditional funding sources.
- Video recording of this lecture in English language: https://youtu.be/Pt1nA32sdHQ
- Video recording of this lecture in Arabic language: https://youtu.be/uFdc9F0rlP0
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Promoting Wellbeing - Applied Social Psychology - Psychology SuperNotesPsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
share - Lions, tigers, AI and health misinformation, oh my!.pptxTina Purnat
• Pitfalls and pivots needed to use AI effectively in public health
• Evidence-based strategies to address health misinformation effectively
• Building trust with communities online and offline
• Equipping health professionals to address questions, concerns and health misinformation
• Assessing risk and mitigating harm from adverse health narratives in communities, health workforce and health system
Mercurius is named after the roman god mercurius, the god of trade and science. The planet mercurius is named after the same god. Mercurius is sometimes called hydrargyrum, means ‘watery silver’. Its shine and colour are very similar to silver, but mercury is a fluid at room temperatures. The name quick silver is a translation of hydrargyrum, where the word quick describes its tendency to scatter away in all directions.
The droplets have a tendency to conglomerate to one big mass, but on being shaken they fall apart into countless little droplets again. It is used to ignite explosives, like mercury fulminate, the explosive character is one of its general themes.
Cell Therapy Expansion and Challenges in Autoimmune DiseaseHealth Advances
There is increasing confidence that cell therapies will soon play a role in the treatment of autoimmune disorders, but the extent of this impact remains to be seen. Early readouts on autologous CAR-Ts in lupus are encouraging, but manufacturing and cost limitations are likely to restrict access to highly refractory patients. Allogeneic CAR-Ts have the potential to broaden access to earlier lines of treatment due to their inherent cost benefits, however they will need to demonstrate comparable or improved efficacy to established modalities.
In addition to infrastructure and capacity constraints, CAR-Ts face a very different risk-benefit dynamic in autoimmune compared to oncology, highlighting the need for tolerable therapies with low adverse event risk. CAR-NK and Treg-based therapies are also being developed in certain autoimmune disorders and may demonstrate favorable safety profiles. Several novel non-cell therapies such as bispecific antibodies, nanobodies, and RNAi drugs, may also offer future alternative competitive solutions with variable value propositions.
Widespread adoption of cell therapies will not only require strong efficacy and safety data, but also adapted pricing and access strategies. At oncology-based price points, CAR-Ts are unlikely to achieve broad market access in autoimmune disorders, with eligible patient populations that are potentially orders of magnitude greater than the number of currently addressable cancer patients. Developers have made strides towards reducing cell therapy COGS while improving manufacturing efficiency, but payors will inevitably restrict access until more sustainable pricing is achieved.
Despite these headwinds, industry leaders and investors remain confident that cell therapies are poised to address significant unmet need in patients suffering from autoimmune disorders. However, the extent of this impact on the treatment landscape remains to be seen, as the industry rapidly approaches an inflection point.
Travel vaccination in Manchester offers comprehensive immunization services for individuals planning international trips. Expert healthcare providers administer vaccines tailored to your destination, ensuring you stay protected against various diseases. Conveniently located clinics and flexible appointment options make it easy to get the necessary shots before your journey. Stay healthy and travel with confidence by getting vaccinated in Manchester. Visit us: www.nxhealthcare.co.uk
1. Utah Drug Overdose Mortality
F I N D I N G S F R O M I N T E R V I E W S W I T H FA M I LY A N D F R I E N D S
O F U TA H R E S I D E N T S A G E D 1 3 A N D O L D E R W H O
DIED OF A DRUG OVERDOSE BETWEEN
OCTOBER 26, 2008 AND OCTOBER 25, 2009
Prepared by Erin Johnson, Utah Department of Health
1
2. Contributing Agencies and Programs
Prescription Pain Medication Program, Utah Department
of Health
Office of Medical Examiner, Utah Department of Health
Utah Department of Human Services, Division of
Substance Abuse and Mental Health
Weber Human Services
Salt Lake County Division of Substance Abuse
Davis Behavioral Health
Utah County Division of Substance Abuse
Valley Mental Health- Tooele Office
2
3. Summary and Highlights
Prescription-related drug overdose death has been a growing problem in the United States and in Utah. Since this is a relatively new epidemic, little is
known about the factors that may predispose someone using a prescription opioid to have a fatal overdose. In order to identify characteristics related
to unintentional (including accidental and undetermined intent) drug overdose deaths in Utah, an investigation was conducted of all drug overdose
deaths under the jurisdiction of the Utah Medical Examiner by interviewing the relative or friend most knowledgeable about the decedent’s life.
Interviews were conducted for Utah residents ages 12 and older who died between October 26, 2008-October 25, 2009.
Of the 2086 cases seen by the Medical Examiner in this timeframe, 432 were drug overdose deaths. The majority (64- N=278) of these involved at
least one opioid (240 included an opioid with no illicit drugs and 38 included an opioid with at least one illicit). Of the 432 drug-related overdose
deaths in the study period, interviews were completed on 385 cases, resulting in a 90% response rate. Overdose deaths involving only illicit drugs
were most common from ages 18 to 44 . Overdose deaths involving nonillicit drugs were most common from ages 25 to 54.
Of the 240 opioid-related, nonillicit drug overdose deaths. We found that 51% of decedents were male and 78% were ages 25-54. Oxycodone was the
drug most frequently mentioned as a contributing cause of death, followed by methadone, hydrocodone and alprazolam. The respondents reported
that 83% of decedents suffered from chronic or ongoing pain.
The results illuminated three characteristics that appear to be strongly correlated to overdose deaths: financial problems, past history of substance
abuse, and mental illness.
Financial problems:
63% of decedents were unemployed during the last two months of life.
59% of respondents reported that the decedent had a financial problem during the two months prior to death.
27% of individuals were uninsured at the time of death. This is higher than the statewide rate of uninsured of 14% in 2008.
Past history of substance abuse:
When asked if the decedent experienced a substance abuse problem during the two months prior to death, 40% responded ‘yes’.
Specific drugs that the decedent had ever used during their lifetime included high rates of marijuana (48) cocaine (25), methamphetamine (23) and heroin (17).
Twelve percent of decedents were reported to have used prescription pain medication for reasons other than pain in the year prior to death. This is higher than the 5.2% who reported using pain
relievers nonmedically during 2006-2007, the most current year that the data are available (NSDUH).
49% of decedents had ever received treatment for substance abuse.
Mental stability:
49% were reported to have been diagnosed with a mental illness by a healthcare provider.
24% of decedents had been hospitalized for psychiatric reasons.
There are many characteristics that could be used by providers in order to screen for patients who have more of a propensity for having a fatal
overdose on prescription opioid medications. Unemployment, past history of substance abuse, and mental illness are characteristics that merit further
investigation in order to better understand how they may be related to unintentional, opioid-related overdose deaths.
3
*Cases were included in the analysis if at least one opioid was implicated as a contributing cause of death and no illicit drugs were implicated.
4. Methods
Questionnaire development
Interview questions were developed based on research team hypotheses to: 1) identify risk factors related to prescription opioid overdose death; 2) guide efforts aimed at
reducing unintentional deaths from prescription opioid overdose and suicide. The questionnaire was developed over the course of several months through meetings with
the research team. Where standard questions already existed in validated studies, these questions were used. Feedback was obtained from professionals in the fields of
medicine, pain management and public health. The data collection instrument (questionnaire) was developed for use as a phone-based survey to be administered by a
trained interviewer (Appendix A).
Prior to data collection, the research team met weekly for a period of one month to train interviewers, practice questionnaire administration, and refine questionnaire
format. The questionnaire was also pre-tested to establish face validity with a small sample (n=7) of volunteers who had experienced the death of a family member due to
drug overdose or suicide.
Changes were made to the questionnaire approximately 1.5 months after data collection began to help clarify questions that were difficult for respondents to understand
and to obtain more complete data on certain topics (Appendix B). Data gathered using the original version of the questionnaire were tracked and recorded.
Case selection
Cases were selected from deaths occurring in Utah between October 26, 2008 and October 25, 2009, which fell under the jurisdiction of the Office of the Medical Examiner
(OME)(Appendix C). All suspected or possible drug overdose OME cases during this time period, as determined by OME personnel, were initially selected for the study
(Appendix D). OME personnel updated and maintained a list of potential study candidates.
This resulted in an over-selection of cases; some cases with an initial/suspected cause of death of drug overdose did not meet the study criteria upon final determination of
the cause and manner of death. At the end of the year a complete audit was done of all cases seen by the Medical Examiner during the study period to determine which
cases fit the inclusion criteria (Appendix E). Once a final list of cases was created, we hand-coded the cases based on the substances listed by the medical examiner as
being involved in a case. The hand-coding allowed us to further distinguish cases by drug category: illicit, nonillicit, combination, as well as determine presence of opioids. A
list of substances included to create each category can be found in Appendix J. For cases that listed drugs that were not otherwise specified, independent case files were
examined at the Medical Examiner's Office for further information. This was also done for cases that listed morphine, but did not specify if it was prescription morphine or
heroin (which metabolizes to morphine over time).
Data Sources
Demographic information was extracted from the Medical Examiner’s System – Utah (MESU) database. MESU data were also used to determine BMI and to obtain manner
and cause of death. All other information in this report came from the completed questionnaires from next of kin responses.
4
5. Methods (Cont.)
Interview administration
Between 11/26/09 and 2/18/10, interviewers attempted telephone interviews with persons identified as either next-of-kin or “best person to contact” by
OME death-scene investigators. In many cases, contact information was either erroneous or not initially available. Members of the research team followed
up with law enforcement agencies and/or funeral service organizations involved in the case to seek additional contact information. Interviewers made
multiple attempts to contact each participant, if necessary, including after-hours and weekend calls. Each attempt was logged on the cover sheet of the
interview.
Interviews were conducted between 1-15 months from the date of death, and lasted between 10 minutes to two hours depending upon responses of the
interviewee. The average duration of each interview was approximately 30-40 minutes.
Interviewers followed scripts for introducing the questionnaire, leaving telephone messages, and responding to participants’ questions (Appendix F,G).
Interviewers provided participants with instructions on obtaining the Medical Examiner’s report, and provided scripted answers to study-related questions,
however, interviewers referred all participants’ case-specific questions to the assigned OME physician.
Data Management
Epi Info™ Version 3.5.1 (Epi Info) was used for data entry (Appendix H) and to facilitate creation of the survey database in Microsoft Access 2007 (Access).
In cases where more than one interview was completed for the same case, the answers from the multiple interviews were merged into one set of answers
for the case based on a pre-determined logic established for deciding, in the case of conflicting answers, which response was to be assigned to the case for
data entry (Appendix I) . The logic was designed to accept the answer that provided the greater amount of information. In cases where the two answers
contradicted each other, answers were counted as “conflicting” and neither answer was included in analysis. Cases with multiple interviews were tracked,
and the number of questions with conflicting answers among the multiple interviews was recorded and entered into the survey database.
Double-entry was done for all questionnaires. The two databases were compared and all discrepancies were reviewed for accuracy. Changes were made
manually into the master database.
Analysis
Survey data was linked to MESU data by the OME assigned case number, and were subsequently analyzed using SAS 9.2.
5
6. Breakdown of Cases Seen by Medical Examiner
During Study Period
Oct 26, 2008-Oct 25, 2009 Cases seen by Utah
Medical Examiner
(2086)
432 cases in study
Included based on Manner of Death
Excluded based on Manner of Death (989)
(1097) Interviews Completed: 385
Accident: 652
Homicide: 51
Refused: 10
Undetermined: 337
Unable to contact: 34
Natural: 593
Language barrier: 3
Suicide: 440
Pending (on 2/2/2010): 13
Excluded as not Drug related
drug related (451)
(538)
Excluded Included in study
(19) (432)
<12 years old:1 Undetermined: 227
*non-Utah resident: Accident: 205
6
Drugs not primary
COD: 12 Combination of
Nonillicit only 2 Illicit only1
Nonillicit and Illicit4
(267) (109)
Key: (45)
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances Combination Illicit
⁴at least one illicit substance and at least one nonillicit substance Opioid present3 and Opioid5
⁵at least one illicit substance and at least one opioid (240) (38)
6
7. Special Considerations: Tramadol
Tramadol is a narcotic that is used to treat pain. It is considered an “atypical opioid”
because it has been found to cause less problems with respiratory depression as other
opioids. It is not currently a controlled substance in Utah.
Tramadol was mentioned in 31 drug overdose death cases. It was grouped as an
opioid for the purposes of this study.
In most drug overdose deaths where Tramadol was found, there was at least one
other opioid that contributed to the cause of death. In 10 cases, Tramadol was the
only opioid.
Tramadol was the only opioid involved in 7 of the “nonillicit with opioid cases”
Tramadol was the only opioid involved in 3 of the “combination illicit with opioid”
cases
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid
7
Note: Proportion estimate and CI exclude missing values unless specified
8. Overall Findings for All Drug
Categories
D I V I D E D I N T O F I V E C AT E G O R I E S :
I L L I C I T, N O N I L L I C I T, N O N I L L I C I T W I T H O P I O I D ( A
S U B S E T O F T H E N O N I L L I C I T C AT E G O R Y ) , C O M B I N AT I O N
I L L I C I T A N D N O N I L L I C I T, A N D C O M B I N AT I O N I L L I C I T
A N D O P I O I D ( A S U B S E T O F T H E C O M B I N AT I O N
C AT E G O R Y )
8
9. Overdose Deaths by Sex and Age
Combination Illicit and Combination Illicit and
Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Nonillicit⁴ Opioid⁵
(n=109 ) (n=267 ) (n=240 ) (n=45) (n=38)
N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI)
Sex
Female 24 22.2%(14.4-30.1) 132 49.4%(43.4-55.4) 117 48.8%(42.4-55.1) 16 35.6%(21.6-49.5) 14 36.8%(21.5-52.2)
Male 84 77.8%(69.9-85.6) 135 50.6%(44.6-56.6) 123 51.3%(44.9-57.6) 29 64.4%(50.5-78.4) 24 63.2%(47.8-78.5)
Age
18-24 22 20.2%(12.7-27.7) 22 8.2%(4.9-11.5) 20 8.3%(4.8-11.8) 4 8.9%(0.6-17.2) 3 7.9%(0-16.5)
25-34 30 27.5%(19.1-35.9) 67 25.1%(19.9-30.3) 64 26.7%(21.1-32.3) 13 28.9%(15.7-42.1) 11 29%(14.5-43.4)
35-44 29 26.6%(18.3-34.9) 61 22.9%(17.8-27.9) 52 21.7%(16.5-26.9) 15 33.3%(19.6-47.1) 13 34.2%(19.1-49.3)
45 -54 16 14.7%(8-21.3) 81 30.3%(24.8-35.9) 72 30%(24.2-35.8) 10 22.2%(10.1-34.4) 9 23.7%(10.2-37.2)
55-64 9 8.3%(3.1-13.4) 30 11.2%(7.5-15) 27 11.3%(7.3-15.3) 3 6.7%(0-14) 2 5.3%(0-12.4)
65 & older 3 2.8%(0-5.8) 6 2.3%(0.5-4) 5 2.1%(0.3-3.9) 0 0 0 0
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
9
⁵at least one illicit substance and at least one opioid Note: Proportion estimate and CI exclude missing values unless specified
10. Number of Accidental and Undetermined Overdose
Decedents by Category: Utah Oct 2008-Oct 2009
90
80
70
60 Illicit
50
40 Nonillicit
30
20 Combination Illicit
10 and Nonillicit
0
18-24 25-34 35-44 45 - 55-64 65 &
54 older
10
11. Overdose Deaths by Race and Ethnicity
Combination Illicit and Combination Illicit and
Race Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Nonillicit⁴ Opioid⁵
(MESU data)
(n=109 ) (n=267 ) (n=240 )* (n=45) (n=38)**
N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI)
White (Caucasian) 103 95.4%(91.4-99.3) 264 98.9%(97.6-100) 238 99.2%(98-100) 43 95.6%(89.5-100) 36 94.7%(87.6-100)
Black 2 1.9%(0-4.4) 0 0 0 0 1 2.2%(0-6.5) 1 2.6%(0-7.7)
Pacific Islander 0 0 0 0 0 0 0 0 0 0
Native American 2 1.9%(0-4.4) 3 1.1%(0-2.4) 2 0.8%(0-2) 0 0 0 0
Unknown 0 0 0 0 0 0 1 2.2%(0-6.5) 1 2.6%(0-7.7)
Other 1 0.9%(0-2.7) 0 0 0 0 0 0 0 0
Ethnicity
7.4% (N=32) of the 432 drug overdose deaths were Hispanic.
4.7% (N=11) of “Nonillicit with Opioid” cases were Hispanic
In 2008, 12% of the population in Utah were Hispanic/Latino (Source: U.S. Census)
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid
Note: Proportion estimate and CI exclude missing values unless specified 11
12. Overdose Deaths by County
Combination Combination
County Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Illicit and Nonillicit⁴ Illicit and Opioid⁵
(where death occurred)
(n=109 ) (n=267 ) (n=240 ) (n=45) (n=38)
N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI)
Box Elder 0 0 <5 NA <5 NA 0 0 0 0
Cache <5 NA 7 2.6%(0.7-4.5) 6 2.5%(0.5-4.5) <5 NA <5 NA
Carbon 0 0 5 1.9%(0.3-3.5) <5 NA <5 NA <5 NA
Duchesne 0 0 <5 NA <5 NA 0 0 0 0
Davis 7 6.4%(1.8-11) 30 11.2%(7.5-15) 27 11.3%(7.3-15.3) <5 NA <5 NA
Emery 0 0 <5 NA <5 NA 0 0 0 0
Iron <5 NA <5 NA <5 NA 0 0 0 0
Juab <5 NA <5 NA <5 NA 0 0 0 0
Kane 0 0 6 2.3%(0.5-4) 6 2.5%(0.5-4.5) 0 0 0 0
NA
Millard <5 0 0 0 0 0 0 0 0
San Juan 0 0 <5 NA 0 0 0 0 0 0
Salt Lake 60 55.1%(45.7-64.4) 107 40.1%(34.2-46) 96 40%(33.8-46.2) 25 55.6%(41-70.1) 19 50%(34.1-65.9)
Sanpete 0 0 <5 NA <5 NA 0 0 0 0
Summit <5 NA <5 NA <5 NA 0 0 0 0
Sevier 0 0 <5 NA <5 NA 0 0 0 0
Tooele <5 NA 5 1.9%(0.3-3.5) 5 2.1%(0.3-3.9) 0 0 0 0
Uintah <5 NA <5 NA <5 NA 0 0 0 0
Utah 15 13.8%(7.3-20.2) 40 15%(10.7-19.3) 36 15%(10.5-19.5) 6 13.3%(3.4-23.3) 5 13.2%(2.4-23.9)
Weber 16 14.7%(8-21.3) 31 11.6%(7.8-15.5) 26 10.8%(6.9-14.8) 5 11.1%(1.9-20.3) 5 13.2%(2.4-23.9)
<5
<5 NA
Washington illicit substance with no nonillicit substances
¹at least one 11 4.1%(1.7-6.5) 11 4.6%(1.9-7.2) NA <5 NA
²at least one nonillicit substance with no illicit substances
Wasatch 0 0 5 1.9%(0.3-3.5) 5 2.1%(0.3-3.9) 0 0 0 0
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 12
Note: Proportion estimate and CI exclude missing values unless specified
13. Overdose Deaths by Religion
What religion
did (decedent) Combination Combination
Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
consider Illicit and Nonillicit⁴ Illicit and Opioid⁵
himself/herself?
N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI)
Protestant 3 3.3%(0-7) 8 3.4%(1.1-5.6) 8 3.7%(1.2-6.2) 0 0 0 0
Catholic 11 12.2%(5.5-19) 17 7.1%(3.9-10.4) 16 7.4%(3.9-10.9) 1 2.6%(0-7.7) 1 3%(0-8.9)
Jewish 0 0 0 0 0 0 1 2.6%(0-7.7) 1 3%(0-8.9)
LDS
(Latter-Day 35 38.9%(28.8-49) 128 53.6%(47.2-59.9) 113 52.1%(45.4-58.7) 20 52.6%(36.8-68.5) 18 54.6%(37.6-71.5)
Saint/Mormon)
Other 15 16.7%(9-24.4) 38 15.9%(11.3-20.5) 33 15.2%(10.4-20) 9 23.7%(10.2-37.2) 8 24.2%(9.6-38.9)
No religion 18 20%(11.7-28.3) 40 16.7%(12-21.5) 39 18%(12.9-23.1) 6 15.8%(4.2-27.4) 4 12.1%(1-23.3)
Don’t Know 8 8.9%(3-14.8) 6 2.5%(0.5-4.5) 6 2.8%(0.6-5) 1 2.6%(0-7.7) 1 3%(0-8.9)
Refused 0 0 2 0.8%(0-2) 2 0.9%(0-2.2) 0 0 0 0
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
13
⁵at least one illicit substance and at least one opioid Note: Proportion estimate and CI exclude missing values unless specified
14. Overdose Deaths by Religious Activity
Combination Combination
How frequently in the Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Illicit and Nonillicit⁴ Illicit and Opioid⁵
past year did (decedent)
attend religious services? N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Among decedents who
considered themselves
Catholic
Active* 0 0 1 5.9%(0-17.1) 1 6.3%(0-18.1) 0 0 0 0
Inactive** 10 90.9%(73.9-100) 16 94.1%(82.9-100) 15 93.8%(81.9-100) 1 100%(100-100) 1 100%(100-100)
Don't Know 1 9.1%(0-26.1) 0 0 0 0 0 0 0 0
Among decedents who
considered themselves LDS
(Latter-Day Saint/Mormon)
Active* 5 14.3%(2.7-25.9) 32 25.2%(17.7-32.8) 27 24.1%(16.2-32) 1 5%(0-14.6) 1 5.6%(0-16.1)
Inactive** 28 80%(66.8-93.3) 86 67.7%(59.6-75.9) 78 69.6%(61.1-78.2) 19 95%(85.5-100) 17 94.4%(83.9-100)
Don't Know 2 5.7%(0-13.4) 9 7.1%(2.6-11.6) 7 6.3%(1.8-10.7) 0 0 0 0
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances *Active: decedent was reported to have attended church services once a week
³at least one opioid with no illicit substances **Inactive: decedent was reported to have attended church services less often than once a week
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid
14
Note: Proportion estimate and CI exclude missing values unless specified
15. Problems during last two months of life
Regarding any time during the Nonillicit with Combination Combination
Illicit Only¹ Nonillicit Only²
last two months, did (name of Opioid³ Illicit and Nonillicit⁴ Illicit and Opioid⁵
decedent) experience any of
the following: N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI)
Romantic relationship
39 42.4%(32.3-52.5) 59 24.4%(19-29.8) 55 25.1%(19.4-30.9) 12 31.6%(16.8-46.4) 10 30.3%(14.6-46)
problem
Financial Problem 61 66.3%(56.7-76) 137 56.6%(50.4-62.9) 129 58.9%(52.4-65.4) 23 60.5%(45-76.1) 20 60.6%(43.9-77.3)
Work problem (if employed)* 14 26.4%(14.6-38.3) 28 32.6%(22.7-42.5) 26 33.3%(22.9-43.8) 5 31.3%(8.5-54) 4 30.8%(5.7-55.9)
School problem (if in school)* 0 0 1 8.3%(0-24) 1 11.1%(0-31.6) 1 25%(0-67.4) 1 33.3%(0-86.7)
Substance Abuse problem/
59 64.1%(54.3-73.9) 98 40.7%(34.5-46.9) 87 39.9%(33.4-46.4) 20 52.6%(36.8-68.5) 17 51.5%(34.5-68.6)
Relapse
Inadequate pain relief 18 19.8%(11.6-28) 90 37.3%(31.2-43.5) 81 37.2%(30.7-43.6) 9 23.7%(10.2-37.2) 9 27.3%(12.1-42.5)
Death of a friend or family
9 9.8%(3.7-15.9) 36 14.9%(10.4-19.4) 33 15.1%(10.4-19.9) 5 13.2%(2.4-23.9) 4 12.1%(1-23.3)
member
Attempted suicide of friend
1 1.1%(0-3.2) 4 1.7%(0.1-3.3) 3 1.4%(0-2.9) 0 0 0 0
or family member
*Not all individuals were asked this question based on skip patterns.
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 15
Note: Proportion estimate and CI exclude missing values unless specified
16. Use of Pain Medications for Other Reasons
In the year prior to
(decedent)’s
death, did he/she use
Combination Combination
prescription pain Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
medication for
Illicit and Nonillicit⁴ Illicit and Opioid⁵
reasons other than to
treat pain?
N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI)
All ages 21 22.8%(14.3-31.4) 63 25.9%(20.4-31.4) 57 25.9%(20.1-31.7) 7 18.4%(6.1-30.8) 7 21.2%(7.3-35.2)
18-24 6 28.6%(9.3-47.9) 11 17.5%(8.1-26.8) 10 17.5%(7.7-27.4) 1 14.3%(0-40.2) 1 14.3%(0-40.2)
25-34 9 42.9%(21.7-64) 20 31.8%(20.3-43.2) 20 35.1%(22.7-47.5) 3 42.9%(6.2-79.5) 3 42.9%(6.2-79.5)
35-44 5 23.8%(5.6-42) 10 15.9%(6.9-24.9) 8 14%(5-23.1) 1 14.3%(0-40.2) 1 14.3%(0-40.2)
45 -54 1 4.8%(0-13.9) 16 25.4%(14.7-36.2) 13 22.8%(11.9-33.7) 2 28.6%(0-62) 2 28.6%(0-62)
55-64 0 12.5%(2.3-22.8) 6 9.5%(2.3-16.8) 6 10.5%(2.6-18.5) 0 4%(0-11.7) 0 4%(0-11.7)
65 & older 0 7.5%(0-15.7) 0 1.9%(0.1-3.7) 0 2%(0.1-4) 0 0 0 0
Male 15 71.4%(52.1-90.8) 34 54%(41.7-66.3) 32 56.1%(43.3-69) 2 28.6%(0-62) 2 28.6%(0-62)
Female 6 28.6%(9.3-47.9) 29 46%(33.7-58.3) 25 43.9%(31-56.7) 5 71.4%(38-100) 5 71.4%(38-100)
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid
16
Note: Proportion estimate and CI exclude missing values unless specified
17. History of Substance Use
Did (decedent) ever use Nonillicit with Combination Illicit Combination Illicit
Illicit Only¹ Nonillicit Only²
any of the following? Opioid³ and Nonillicit⁴ and Opioid⁵
N % (95% CI) N % (95% CI) N % (95% CI) N % (95% CI) N % (95% CI)
Alcohol 88 95.7%(91.5-99.8) 208 86.7%(82.4-91) 189 86.7%(82.2-91.2) 37 97.4%(92.3-100) 32 97%(91.1-100)
Tobacco 73 80.2%(72-88.4) 181 75.7%(70.3-81.2) 165 76%(70.4-81.7) 35 92.1%(83.5-100) 30 90.9%(81.1-100)
Marijuana 67 73.6%(64.6-82.7) 116 48.3%(42-54.7) 105 48.2%(41.5-54.8) 25 65.8%(50.7-80.9) 22 66.7%(50.6-82.8)
Heroin 61 67%(57.4-76.7) 42 17.5%(12.7-22.3) 37 17%(12-22) 17 44.7%(28.9-60.6) 15 45.5%(28.5-62.4)
Cocaine 53 58.2%(48.1-68.4) 59 24.6%(19.1-30) 55 25.2%(19.5-31) 26 68.4%(53.6-83.2) 22 66.7%(50.6-82.8)
Hallucinogens 21 23.1%(14.4-31.7) 27 11.3%(7.3-15.3) 23 10.6%(6.5-14.6) 16 42.1%(26.4-57.8) 13 39.4%(22.7-56.1)
Methamphetamine 43 47.3%(37-57.5) 55 22.9%(17.6-28.2) 51 23.4%(17.8-29) 18 47.4%(31.5-63.2) 16 48.5%(31.4-65.5)
Prescription medication
(used for reasons other than to 21 22.8%(14.3-31.4) 63 25.9%(20.4-31.4) 57 25.9%(20.1-31.7) 7 18.4%(6.1-30.8) 7 21.2%(7.3-35.2)
treat pain)
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 17 Note: Proportion estimate and CI exclude missing values unless specified
18. Alcohol Consumption
Nonillicit with Combination Combination
Illicit Only¹ Nonillicit Only²
Opioid³ Illicit and Nonillicit⁴ Illicit and Opioid⁵
N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI)
Used in last 2 months of life 44 47.8%(37.6-58) 82 34.2%(28.2-40.2) 72 33%(26.8-39.3) 14 36.8%(21.5-52.2) 11 33.3%(17.3-49.4)
If in last 2 months, how often?*
Daily 11 25.6%(12.5-38.6) 28 34.2%(23.9-44.4) 25 34.7%(23.7-45.7) 5 35.7%(10.6-60.8) 3 27.3%(1-53.6)
Few times/week 15 34.9%(20.6-49.1) 11 13.4%(6-20.8) 10 13.9%(5.9-21.9) 3 21.4%(0-42.9) 3 27.3%(1-53.6)
Weekly 6 14%(3.6-24.3) 11 13.4%(6-20.8) 11 15.3%(7-23.6) 1 7.1%(0-20.6) 0 0
Monthly 2 4.7%(0-11) 4 4.9%(0.2-9.5) 4 5.6%(0.3-10.9) 2 14.3%(0-32.6) 2 18.2%(0-41)
Don't Know 5 11.6%(2.1-21.2) 8 9.8%(3.3-16.2) 8 11.1%(3.9-18.4) 1 7.1%(0-20.6) 1 9.1%(0-26.1)
Sporadic 2 4.7%(0-11) 13 15.9%(8-23.8) 10 13.9%(5.9-21.9) 1 7.1%(0-20.6) 1 9.1%(0-26.1)
Other 2 4.7%(0-11) 7 8.5%(2.5-14.6) 4 5.6%(0.3-10.9) 1 7.1%(0-20.6) 1 9.1%(0-26.1)
Did he/she drink enough to be
intoxicated?* 53 63.9%(53.5-74.2) 107 59.8%(52.6-67) 99 61.5%(54-69) 24 70.6%(55.3-85.9) 22 73.3%(57.5-89.2)
If in last 2 months, how often?*
Daily 4 9.3%(0.6-18) 14 19.7%(10.5-29) 14 21.5%(11.5-31.5) 3 20%(0-40.2) 2 15.4%(0-35)
Few times/week 6 14%(3.6-24.3) 7 9.9%(2.9-16.8) 6 9.2%(2.2-16.3) 2 13.3%(0-30.5) 1 7.7%(0-22.2)
Weekly 2 4.7%(0-11) 5 7%(1.1-13) 5 7.7%(1.2-14.2) 1 6.7%(0-19.3) 1 7.7%(0-22.2)
Monthly 6 14%(3.6-24.3) 3 4.2%(0-8.9) 3 4.6%(0-9.7) 0 0 0 0
Don't Know 13 30.2%(16.5-44) 17 23.9%(14-33.9) 15 23.1%(12.8-33.3) 4 26.7%(4.3-49.1) 4 30.8%(5.7-55.9)
Sporadic 8 18.6%(7-30.2) 14 19.7%(10.5-29) 12 18.5%(9-27.9) 2 13.3%(0-30.5) 2 15.4%(0-35)
Other 4 9.3%(0.6-18) 11 15.5%(7.1-23.9) 10 15.4%(6.6-24.2) 3 20%(0-40.2) 3 23.1%(0.2-46)
In the past two months, did
drinking interfere with his/her
daily ability to function?*
¹at least one illicit substance with no nonillicit substances
Yes least one nonillicit substance with no illicit substances
²at
14 20%(10.6-29.4)
³at least one opioid with no illicit substances
24 18.9%(12.1-25.7) 23 20%(12.7-27.3) 3 11.5%(0-23.8) 3 13.6%(0-28)
No⁴at least one illicit substance and at least one nonillicit substance
47 67.1%(56.1-78.2) 94 74%(66.4-81.6) 84 73%(64.9-81.2) 21 80.8%(65.6-95.9) 17 77.3%(59.8-94.8)
⁵at least one illicit substance and at least one opioid
Don't Know
9 12.9%(5-20.7) 18
9 7.1%(2.6-11.6) 8 7%(2.3-11.6) 2 7.7%(0-17.9) 2 9.1%(0-21.1)
Note: Proportion estimate and CI exclude missing values unless specified *Not all individuals were asked this question based on skip patterns.
19. Tobacco Use
Combination Combination
Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Ever used Tobacco? Illicit and Nonillicit⁴ Illicit and Opioid⁵
N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Yes
73 80.2%(72-88.4) 181 75.7%(70.3-81.2) 165 76%(70.4-81.7) 35 92.1%(83.5-100) 30 90.9%(81.1-100)
No 17 18.7%(10.7-26.7) 57 23.9%(18.5-29.3) 51 23.5%(17.9-29.1) 3 7.9%(0-16.5) 3 9.1%(0-18.9)
Don't Know 1 1.1%(0-3.2) 1 0.4%(0-1.2) 1 0.5%(0-1.4) 0 0 0 0
If YES, in the two months
prior to death did
(decedent) use tobacco
products of any kind?*
Yes 60 84.5%(76.1-92.9) 143 79.9%(74-85.8) 131 80.4%(74.3-86.5) 30 85.7%(74.1-97.3) 25 83.3%(70-96.7)
No 8 11.3%(3.9-18.6) 29 16.2%(10.8-21.6) 25 15.3%(9.8-20.9) 3 8.6%(0-17.9) 3 10%(0-20.7)
Don't know
3 4.2%(0-8.9) 6 3.4%(0.7-6) 6 3.7%(0.8-6.6) 2 5.7%(0-13.4) 2 6.7%(0-15.6)
If YES, How often?*
Daily 50 84.8%(75.6-93.9) 129 90.9%(86.1-95.6) 119 91.5%(86.8-96.3) 27 90%(79.3-100) 22 88%(75.3-100)
Few times/week 0 0 1 0.7%(0-2.1) 1 0.8%(0-2.3) 0 0 0 0
Weekly 0 0 1 0.7%(0-2.1) 1 0.8%(0-2.3) 0 0 0 0
Monthly 0 0 0 0 0 0 0 0 0 0
Don't Know 6 10.2%(2.5-17.9) 8 5.6%(1.8-9.4) 7 5.4%(1.5-9.3) 2 6.7%(0-15.6) 2 8%(0-18.6)
Sporadic 3 5.1%(0-10.7) 2 1.4%(0-3.4) 1 0.8%(0-2.3) 1 3.3%(0-9.8) 1 4%(0-11.7)
Other
0 0 1 0.7%(0-2.1) 1 0.8%(0-2.3) 0 0 0 0
*Not all individuals were asked this question based on skip patterns.
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 19
Note: Proportion estimate and CI exclude missing values unless specified
20. Marijuana Use
Combination Combination
Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Ever used Marijuana? Illicit and Nonillicit⁴ Illicit and Opioid⁵
N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Yes
67 73.6%(64.6-82.7) 116 48.3%(42-54.7) 105 48.2%(41.5-54.8) 25 65.8%(50.7-80.9) 22 66.7%(50.6-82.8)
No 9 9.9%(3.8-16) 108 45%(38.7-51.3) 99 45.4%(38.8-52) 8 21.1%(8.1-34) 6 18.2%(5-31.3)
Don't Know 15 16.5%(8.9-24.1) 16 6.7%(3.5-9.8) 14 6.4%(3.2-9.7) 5 13.2%(2.4-23.9) 5 15.2%(2.9-27.4)
Used in last 2 months of
life * 8 8.8%(3-14.6) 15 6.3%(3.2-9.3) 13 6%(2.8-9.1) 3 7.9%(0-16.5) 3 9.1%(0-18.9)
If in last 2 months, how
often?*
Daily 0 0 6 40%(15.2-64.8) 6 46.2%(19.1-73.3) 1 50%(0-100) 1 50%(0-100)
Few times/week 2 25%(0-55) 3 20%(0-40.2) 3 23.1%(0.2-46) 0 0 0 0
Weekly 0 0 0 0 0 0 0 0 0 0
Monthly 0 0 0 0 0 0 0 0 0 0
Don't Know 3 37.5%(4-71.1) 3 20%(0-40.2) 1 7.7%(0-22.2) 1 50%(0-100) 1 50%(0-100)
Sporadic 2 25%(0-55) 1 6.7%(0-19.3) 1 7.7%(0-22.2) 0 0 0 0
Other 1 12.5%(0-35.4) 2 13.3%(0-30.5) 2 15.4%(0-35) 0 0 0 0
*Not all individuals were asked this question based on skip patterns.
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 20
Note: Proportion estimate and CI exclude missing values unless specified
21. Heroin Use
Combination Combination
Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Ever used Heroin? Illicit and Nonillicit⁴ Illicit and Opioid⁵
N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Yes
61 67%(57.4-76.7) 42 17.5%(12.7-22.3) 37 17%(12-22) 17 44.7%(28.9-60.6) 15 45.5%(28.5-62.4)
No 15 16.5%(8.9-24.1) 178 74.2%(68.6-79.7) 162 74.3%(68.5-80.1) 17 44.7%(28.9-60.6) 14 42.4%(25.6-59.3)
Don't Know 15 16.5%(8.9-24.1) 20 8.3%(4.8-11.8) 19 8.7%(5-12.5) 4 10.5%(0.8-20.3) 4 12.1%(1-23.3)
Used in last 2 months of
life* 36 39.6%(29.5-49.6) 3 1.3%(0-2.7) 3 1.4%(0-2.9) 7 18.4%(6.1-30.8) 5 15.2%(2.9-27.4)
If in last 2 months, how
often?*
Daily 5 14.3%(2.7-25.9) 2 66.7%(13.3-100) 2 66.7%(13.3-100) 2 28.6%(0-62) 2 40%(0-82.9)
Few times/week 0 0 0 0 0 0 0 0 0 0
Weekly 1 2.9%(0-8.4) 0 0 0 0 0 0 0 0
Monthly 1 2.9%(0-8.4) 0 0 0 0 0 0 0 0
Don't Know 15 42.9%(26.5-59.3) 0 0 0 0 4 57.1%(20.5-93.8) 2 40%(0-82.9)
Sporadic 1 2.9%(0-8.4) 0 0 0 0 0 0 0 0
Other 12 34.3%(18.6-50) 1 33.3%(0-86.7) 1 33.3%(0-86.7) 1 14.3%(0-40.2) 1 20%(0-55.1)
*Not all individuals were asked this question based on skip patterns.
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 21
Note: Proportion estimate and CI exclude missing values unless specified
22. Cocaine Use
Combination Combination
Ever used Cocaine, Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Illicit and Nonillicit⁴ Illicit and Opioid⁵
Powder, Freebase, Crack?
N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Yes
53 58.2%(48.1-68.4) 59 24.6%(19.1-30) 55 25.2%(19.5-31) 26 68.4%(53.6-83.2) 22 66.7%(50.6-82.8)
No 17 18.7%(10.7-26.7) 154 64.2%(58.1-70.2) 138 63.3%(56.9-69.7) 8 21.1%(8.1-34) 7 21.2%(7.3-35.2)
Don't Know 21 23.1%(14.4-31.7) 27 11.3%(7.3-15.3) 25 11.5%(7.2-15.7) 4 10.5%(0.8-20.3) 4 12.1%(1-23.3)
Used in last 2 months of
life * 20 22%(13.5-30.5) 3 1.3%(0-2.7) 3 1.4%(0-2.9) 8 21.1%(8.1-34) 7 21.2%(7.3-35.2)
If in last 2 months, how
often? *
Daily 2 10.5%(0-24.3) 2 66.7%(13.3-100) 2 66.7%(13.3-100) 2 25%(0-55) 2 28.6%(0-62)
Few times/week 1 5.3%(0-15.3) 0 0 0 0 0 0 0 0
Weekly 0 0 0 0 0 0 0 0 0 0
Monthly 1 5.3%(0-15.3) 0 0 0 0 0 0 0 0
Don't Know 9 47.4%(24.9-69.8) 0 0 0 0 3 37.5%(4-71.1) 3 42.9%(6.2-79.5)
Sporadic 1 5.3%(0-15.3) 0 0 0 0 1 12.5%(0-35.4) 0 0
Other 5 26.3%(6.5-46.1) 1 33.3%(0-86.7) 1 33.3%(0-86.7) 2 25%(0-55) 2 28.6%(0-62)
*Not all individuals were asked this question based on skip patterns.
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 22
Note: Proportion estimate and CI exclude missing values unless specified
23. Hallucinogen Use
Ever used Hallucinogens Combination Combination
Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
(LSD, mushrooms, Illicit and Nonillicit⁴ Illicit and Opioid⁵
ecstasy) ? N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Yes
21 23.1%(14.4-31.7) 27 11.3%(7.3-15.3) 23 10.6%(6.5-14.6) 16 42.1%(26.4-57.8) 13 39.4%(22.7-56.1)
No 44 48.4%(38.1-58.6) 182 75.8%(70.4-81.3) 168 77.1%(71.5-82.7) 16 42.1%(26.4-57.8) 14 42.4%(25.6-59.3)
Don't Know 26 28.6%(19.3-37.9) 31 12.9%(8.7-17.2) 27 12.4%(8-16.8) 6 15.8%(4.2-27.4) 6 18.2%(5-31.3)
Used in last 2 months of
life* 1 1.1%(0-3.2) 0 0 0 0 1 2.6%(0-7.7) 1 3%(0-8.9)
If in last 2 months, how
often?*
Daily 0 0 0 0 0 0 0 0 0 0
Few times/week 0 0 0 0 0 0 0 0 0 0
Weekly 0 0 0 0 0 0 0 0 0 0
Monthly 0 0 0 0 0 0 1 100%(100-100) 1 100%(100-100)
Don't Know 0 0 0 0 0 0 0 0 0 0
Sporadic 0 0 0 0 0 0 0 0 0 0
Other 0 0 0 0 0 0 0 0 0 0
*Not all individuals were asked this question based on skip patterns.
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 23
Note: Proportion estimate and CI exclude missing values unless specified
24. Methamphetamine Use
Combination Combination
Ever used Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Illicit and Nonillicit⁴ Illicit and Opioid⁵
Methamphetamine?
N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Yes
43 47.3%(37-57.5) 55 22.9%(17.6-28.2) 51 23.4%(17.8-29) 18 47.4%(31.5-63.2) 16 48.5%(31.4-65.5)
No 27 29.7%(20.3-39.1) 162 67.5%(61.6-73.4) 146 67%(60.7-73.2) 14 36.8%(21.5-52.2) 11 33.3%(17.3-49.4)
Don't Know 21 23.1%(14.4-31.7) 23 9.6%(5.9-13.3) 21 9.6%(5.7-13.6) 6 15.8%(4.2-27.4) 6 18.2%(5-31.3)
Used in last 2 months of
life* 8 8.8%(3-14.6) 4 1.7%(0.1-3.3) 4 1.8%(0.1-3.6) 3 7.9%(0-16.5) 3 9.1%(0-18.9)
If in last 2 months, how
often?*
Daily 2 28.6%(0-62) 1 25%(0-67.4) 1 25%(0-67.4) 0 0 0 0
Few times/week 0 0 0 0 0 0 0 0 0 0
Weekly 0 0 0 0 0 0 0 0 0 0
Monthly 0 0 0 0 0 0 0 0 0 0
Don't Know 3 42.9%(6.2-79.5) 0 0 0 0 2 100%(100-100) 2 100%(100-100)
Sporadic 0 0 1 25%(0-67.4) 1 25%(0-67.4) 0 0 0 0
Other 2 28.6%(0-62) 2 50%(1-99) 2 50%(1-99) 0 0 0 0
*Not all individuals were asked this question based on skip patterns.
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 24
Note: Proportion estimate and CI exclude missing values unless specified
25. Pain
Combination Combination
Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Illicit and Nonillicit⁴ Illicit and Opioid⁵
N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Did (decedent) suffer
from pain?
Yes 44 47.8%(37.6-58) 219 89.8%(86-93.6) 198 89.6%(85.6-93.6) 29 76.3%(62.8-89.8) 26 78.8%(64.8-92.7)
Chronic/Ongoing* 32 72.7%(59.6-85.9) 200 91.3%(87.6-95.1) 182 91.9%(88.1-95.7) 25 86.2%(73.7-98.8) 22 84.6%(70.8-98.5)
Not chronic* 10 22.7%(10.3-35.1) 14 6.4%(3.2-9.6) 11 5.6%(2.4-8.8) 4 13.8%(1.2-26.3) 4 15.4%(1.5-29.3)
No 43 46.7%(36.5-56.9) 23 9.4%(5.8-13.1) 21 9.5%(5.6-13.4) 8 21.1%(8.1-34) 6 18.2%(5-31.3)
Don’t Know 5 5.4%(0.8-10.1) 2 0.8%(0-2) 2 0.9%(0-2.2) 1 2.6%(0-7.7) 1 3%(0-8.9)
Did (decedent) take
prescription medications
for pain during the year
before his/her death?
All ages 40 48.2%(37.4-58.9) 215 88.1%(84.1-92.2) 197 89.1%(85-93.2) 25 67.6%(52.5-82.7) 25 78.1%(63.8-92.5)
18-24 7 17.5%(5.7-29.3) 11 5.1%(2.2-8.1) 10 5.1%(2-8.1) 2 8%(0-18.6) 2 8%(0-18.6)
25-34 12 30%(15.8-44.2) 54 25.1%(19.3-30.9) 52 26.4%(20.2-32.6) 7 28%(10.4-45.6) 7 28%(10.4-45.6)
35-44 10 25%(11.6-38.4) 50 23.3%(17.6-28.9) 43 21.8%(16.1-27.6) 9 36%(17.2-54.8) 9 36%(17.2-54.8)
45 -54 3 7.5%(0-15.7) 72 33.5%(27.2-39.8) 65 33%(26.4-39.6) 6 24%(7.3-40.7) 6 24%(7.3-40.7)
55-64 5 12.5%(2.3-22.8) 24 11.2%(7-15.4) 23 11.7%(7.2-16.2) 1 4%(0-11.7) 1 4%(0-11.7)
65 & older 3 7.5%(0-15.7) 4 1.9%(0.1-3.7) 4 2%(0.1-4) 0 0 0 0
Male 33 82.5%(70.7-94.3) 104 48.4%(41.7-55.1) 96 48.7%(41.8-55.7) 15 60%(40.8-79.2) 15 60%(40.8-79.2)
Female 7 17.5%(5.7-29.3) 111 51.6%(45-58.3) 101 51.3%(44.3-58.3) 10 40%(20.8-59.2) 10 40%(20.8-59.2)
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances *Not all individuals were asked this question based on skip patterns.
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 25
Note: Proportion estimate and CI exclude missing values unless specified
26. Sleep Apnea
Combination Combination
Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Illicit and Nonillicit⁴ Illicit and Opioid⁵
N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI)
Number of sleep
apnea indicators
*reported
1 20 35.7%(23.2-48.3) 50 25.9%(19.7-32.1) 46 26.3%(19.8-32.8) 6 22.2%(6.5-37.9) 6 25%(7.7-42.3)
2 16 28.6%(16.7-40.4) 51 26.4%(20.2-32.7) 46 26.3%(19.8-32.8) 8 29.6%(12.4-46.9) 8 33.3%(14.5-52.2)
3 12 21.4%(10.7-32.2) 42 21.8%(15.9-27.6) 36 20.6%(14.6-26.6) 5 18.5%(3.9-33.2) 3 12.5%(0-25.7)
4 1 1.8%(0-5.3) 26 13.5%(8.7-18.3) 24 13.7%(8.6-18.8) 5 18.5%(3.9-33.2) 5 20.8%(4.6-37.1)
5 4 7.1%(0.4-13.9) 17 8.8%(4.8-12.8) 17 9.7%(5.3-14.1) 3 11.1%(0-23) 2 8.3%(0-19.4)
6 3 5.4%(0-11.3) 7 3.6%(1-6.3) 6 3.4%(0.7-6.1) 0 0 0 0
Did (decedent) suffer
from sleep apnea?
Yes 9 10%(3.8-16.2) 41 17.2%(12.4-22) 36 16.6%(11.6-21.5) 9 23.7%(10.2-37.2) 9 27.3%(12.1-42.5)
No 68 75.6%(66.7-84.4) 152 63.9%(57.8-70) 141 65%(58.6-71.3) 23 60.5%(45-76.1) 20 60.6%(43.9-77.3)
Don’t Know 13 14.4%(7.2-21.7) 45 18.9%(13.9-23.9) 40 18.4%(13.3-23.6) 6 15.8%(4.2-27.4) 4 12.1%(1-23.3)
If ‘Yes’, did they have
4 44.4%(12-76.9) 15 33.3%(19.6-47.1) 12 30%(15.8-44.2) 3 30%(1.6-58.4) 3 30%(1.6-58.4)
a CPAP machine?*
* Indicators include: excessive daytime sleepiness, awakening un-refreshed, snoring unusually loud, sounding like he/she was having
trouble breathing while he/she slept, stop breathing for a period while asleep
*Not all individuals were asked this question based on skip patterns.
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid
Note: Proportion estimate and CI exclude missing values unless specified 26
27. Lived with at Time of Death
Who did (decedent)
Combination Combination
live with at the time of Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
his/her death?
Illicit and Nonillicit⁴ Illicit and Opioid⁵
N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI) N %(95%CI)
Alone 15 16.3%(8.8-23.9) 57 23.4%(18.1-28.7) 53 24%(18.4-29.6) 10 26.3%(12.3-40.3) 9 27.3%(12.1-42.5)
Friend/Roommate 14 15.2%(7.9-22.6) 22 9%(5.4-12.6) 19 8.6%(4.9-12.3) 7 18.4%(6.1-30.8) 7 21.2%(7.3-35.2)
Parent/Sibling 32 34.8%(25.1-44.5) 54 22.1%(16.9-27.3) 48 21.7%(16.3-27.2) 9 23.7%(10.2-37.2) 6 18.2%(5-31.3)
Spouse 9 9.8%(3.7-15.9) 66 27.1%(21.5-32.6) 57 25.8%(20-31.6) 4 10.5%(0.8-20.3) 4 12.1%(1-23.3)
Significant Other 10 10.9%(4.5-17.2) 23 9.4%(5.8-13.1) 23 10.4%(6.4-14.4) 5 13.2%(2.4-23.9) 5 15.2%(2.9-27.4)
Children 11 12%(5.3-18.6) 66 27.1%(21.5-32.6) 57 25.8%(20-31.6) 5 13.2%(2.4-23.9) 5 15.2%(2.9-27.4)
Relative 3 3.3%(0-6.9) 8 3.3%(1-5.5) 8 3.6%(1.2-6.1) 1 2.6%(0-7.7) 1 3%(0-8.9)
Other 16 17.4%(9.7-25.1) 37 15.2%(10.7-19.7) 32 14.5%(9.8-19.1) 3 7.9%(0-16.5) 2 6.1%(0-14.2)
Of the Nonillicit with Opioid interviewed cases, 77 were married at time of death and 58 had never been married (Death Certificate Data).
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid
Note: Proportion estimate and CI exclude missing values unless specified 27
28. Drug Overdose by BMI
Nonillicit with Combination Combination
Calculated BMI (MESU Illicit Only¹ Nonillicit Only²
Opioid³ Illicit and Nonillicit⁴ Illicit and Opioid⁵
Data)
N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Ideal 38 45.2%(34.6-55.9) 70 29.9%(24.1-35.8) 65 30.5%(24.3-36.7) 8 22.9%(9-36.8) 7 22.6%(7.9-37.3)
Overweight 27 32.1%(22.2-42.1) 64 27.4%(21.6-33.1) 59 27.7%(21.7-33.7) 11 31.4%(16.1-46.8) 9 29%(13.1-45)
Obese 17 20.2%(11.7-28.8) 91 38.9%(32.6-45.1) 82 38.5%(32-45) 16 45.7%(29.2-62.2) 15 48.4%(30.8-66)
Underweight 2 2.4%(0-5.6) 9 3.9%(1.4-6.3) 7 3.3%(0.9-5.7) 0 0 0 0
In 2008, 24.2% (22.6, 25.5) of Utah adults 18+ were obese and 36.11% (34.46, 37.78) were overweight. (95% CI) (Source: BRFSS)
*Missing values are, in part, due to deaths where a designated representative signs off on behalf of the Office of the Medical Examiner and BMI is not entered into MESU.
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 28
Note: Proportion estimate and CI exclude missing values unless specified
29. Chronic Conditions and Sleep Medications
Nonillicit with Combination Combination
Illicit Only¹ Nonillicit Only²
Opioid³ Illicit and Nonillicit⁴ Illicit and Opioid⁵
N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Did (decedent) suffer from:
Seizures 7 7.7%(2.2-13.2) 37 15.2%(10.7-19.7) 33 14.9%(10.2-19.6) 8 21.1%(8.1-34) 7 21.2%(7.3-35.2)
Diabetes 6 6.5%(1.5-11.6) 24 9.8%(6.1-13.6) 23 10.4%(6.4-14.4) 6 15.8%(4.2-27.4) 6 18.2%(5-31.3)
Obesity 13 14.1%(7-21.3) 63 25.8%(20.3-31.3) 59 26.7%(20.9-32.5) 11 29%(14.5-43.4) 10 30.3%(14.6-46)
Cancer 2 2.2%(0-5.2) 23 9.4%(5.8-13.1) 21 9.5%(5.6-13.4) 4 10.5%(0.8-20.3) 4 12.1%(1-23.3)
Mental Illness 40 43.5%(33.4-53.6) 123 50.4%(44.1-56.7) 111 50.2%(43.6-56.8) 22 57.9%(42.2-73.6) 20 60.6%(43.9-77.3)
Physical Disability 17 18.5%(10.6-26.4) 116 47.7%(41.5-54) 108 49.1%(42.5-55.7) 13 34.2%(19.1-49.3) 12 36.4%(20-52.8)
Traumatic Brain Injury 3 3.3%(0-6.9) 32 13.1%(8.9-17.4) 28 12.7%(8.3-17.1) 5 13.2%(2.4-23.9) 3 9.1%(0-18.9)
Did (decedent) ever use
medications to help 32 34.8%(25.1-44.5) 179 74.9%(69.4-80.4) 160 73.7%(67.9-79.6) 27 71.1%(56.6-85.5) 24 72.7%(57.5-87.9)
him/her sleep?
¹at least one illicit substance with no nonillicit substances
²at least one nonillicit substance with no illicit substances
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid 29
Note: Proportion estimate and CI exclude missing values unless specified
30. Health Care Coverage at Time of Death
At the time of
death, did
Combination Combination
(decedent) have any Illicit Only¹ Nonillicit Only² Nonillicit with Opioid³
Illicit and Nonillicit⁴ Illicit and Opioid⁵
kind of health care
coverage*?
N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI) N % (95%CI)
Yes 43 47.3%(37-57.5) 167 69.9%(64.1-75.7) 150 69.1%(63-75.3) 23 60.5%(45-76.1) 22 66.7%(50.6-82.8)
No 39 42.9%(32.7-53) 65 27.2%(21.6-32.8) 60 27.7%(21.7-33.6) 14 36.8%(21.5-52.2) 11 33.3%(17.3-49.4)
Don’t Know/
9 9.9%(3.8-16) 7 2.9%(0.8-5.1) 7 3.2%(0.9-5.6) 1 2.6%(0-7.7) 0 0
Not Sure
In 2008, the percent of uninsured in Utah was 14.7%. (Source: BRFSS)
¹at least one illicit substance with no nonillicit substances *includes health insurance, prepaid plans such as HMOs, or
²at least one nonillicit substance with no illicit substances government plans such as Medicare
³at least one opioid with no illicit substances
⁴at least one illicit substance and at least one nonillicit substance
⁵at least one illicit substance and at least one opioid
Note: Proportion estimate and CI exclude missing values unless specified 30
32. Frequency of Drugs Listed by Medical Examiner as
Contributing to Cause of Death for Nonillicit Overdose
Deaths that Include at Least One Opioid (Accidental and
Undetermined Deaths): Utah Oct 2008-Oct 2009
100
93
90
80
70 66
63
60
50 45
40
30
20
10
0
32
33. Interview Responses by Next of Kin Regarding Nonillicit Overdose
Decedents with at Least One Opioid (Accidental and Undetermined
Manner of Death)
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
*At time of death
**During two months prior to death
***Ever
33
34. Mental Illness
Yes No I Don't Know Total Missing/Blank
Item N % N % N % N % N %
Was (decedent) ever diagnosed
with a mental illness by a 108 49.3% 95 43.4% 15 6.8% 219 100% 21 8.8%
healthcare provider?**
Excluding treatment for substance
abuse, was (name of decedent)
52 41.3% 66 52.4% 8 6.3% 126 100% 114 47.5%
ever hospitalized for a psychiatric
reason? *
Did (name of decedent) ever see a 90 69.2% 38 29.2% 2 1.5% 130 100% 110 45.8%
therapist for individual therapy?*
Did (name of decedent) ever
receive any psychiatric 131 60.4% 72 33.2% 14 6.5% 217 100% 23 9.6%
medication?
Did (name of decedent) ever
participate in self-harming 31 14.4% 183 84.7% 2 0.9% 216 100% 24 10%
behavior?
Did (name of decedent) ever 47 21.8% 159 73.6% 10 4.6% 216 100% 24 10%
attempt suicide?
*Not all individuals were asked this question based on skip patterns.
**The values in missing plus total may equal less than expected due to a N/A response option.
Cases are accidental and undetermined drug overdose deaths with at least one
opioid and no illicit substances
Note: Proportion estimate and CI exclude missing values unless specified
34
35. Diagnosed Mental Illness
49% of decedents were reported to have been
diagnosed with a mental illness by a healthcare
provider.
A follow-up question asked what the disorder was.
Multiple disorders could be listed.
32% were reported to have been diagnosed with depression
15% were reported to have been diagnosed with bipolar
14% were reported to have been diagnosed with an anxiety
disorder
Other disorders that were reported include schizophrenia (2)
and ADHD (3).
35
36. Insurance
Yes No I Don't Know Total Missing/Blank
Item N % N % N % N % N %
At the time of death, did
(decedent) have any kind of
health care coverage, including
150 69.1% 60 27.6% 7 3.2% 217 100% 23 9.6%
health insurance, prepaid plans
such as HMOs, or government
plans such as Medicare?
Cases are accidental and undetermined drug overdose deaths with at least one
opioid and no illicit substances
Note: Proportion estimate and CI exclude missing values unless specified
36
37. Marital Status
Never married: 58
Married: 77
Widowed: 7
Divorced: 68
Married/separated: 3
Unknown: 1
Cases are accidental and undetermined drug overdose deaths with at least one
opioid and no illicit substances Numbers represent marital status among interviewed decedents only.
Source: Death Certificate Data
Note: Proportion estimate and CI exclude missing values unless specified
37
38. History of Substance Use
Yes No I Don't Know Total Missing/Blank
Did decedent ever use any of the following? N % N % N % N % N %
Alcohol 189 86.7% 28 12.8% 1 0.5% 218 100% 22 9.2%
Did he/she drink enough to be intoxicated?* 99 61.5% 47 29.2% 15 9.3% 161 100% 79 32.9%
In the past two months, did drinking interfere 23 20% 84 73% 8 7% 115 100% 125 52.1%
with his/her daily ability to function?*
Tobacco 165 76% 51 23.5% 1 0.5% 217 100% 23 9.6%
If YES, In the two months prior to death did 131 79.9% 26 15.9% 6 3.7% 164 100% 76 31.7%
(decedent) use tobacco products of any kind?*
Marijuana 105 48.2% 99 45.4% 14 6.4% 218 100% 22 9.2%
Heroin 37 17% 162 74.3% 19 8.7% 218 100% 22 9.2%
Cocaine 55 25.2% 138 63.3% 25 11.5% 218 100% 22 9.2%
Hallucinogens 23 10.6% 168 77.1% 27 12.4% 218 100% 22 9.2%
Methamphetamine 51 23.4% 146 67% 21 9.6% 218 100% 22 9.2%
Other Substance (includes Prescription
medication ) 107 49.3% 91 41.9% 19 8.8% 217 100% 23 9.6%
Did (decedent) ever receive specific treatment
106 48.6% 105 48.2% 7 3.2% 218 100% 22 9.2%
for substance abuse?
Regarding any time in the past two months, did
(decedent) have a substance abuse problem or 87 39.9% 117 53.7% 14 6.4% 218 100% 22 9.2%
relapse?
Cases are accidental and undetermined drug overdose deaths with at least one
opioid and no illicit substances
Note: Proportion estimate and CI exclude missing values unless specified
*Not all individuals were asked this question based on skip patterns. 38
39. Sleep
Yes No I Don't Know Total Missing/Blank
Regarding sleep, in the past two
months did (name of decedent)
experience any of the following?
N % N % N % N % N %
109 50.2% 90 41.5% 18 8.3% 217 100% 23
Excessive daytime sleepiness 9.6%
105 48.4% 63 29% 49 22.6% 217 100% 23
Awakening un-refreshed 9.6%
69 31.8% 95 43.8% 53 24.4% 217 100% 23
Snoring unusually loud 9.6%
Stop breathing for a period of time 77 35.5% 97 44.7% 43 19.8% 217 100% 23
while asleep 9.6%
Any other issues related to sleep that 68 31.3% 142 65.4% 7 3.2% 217 100% 23
you observed? 9.6%
To your knowledge, did (name of 36 16.6% 141 65% 40 18.4% 217 100% 23
decedent) suffer from sleep apnea? 9.6%
Did he/she have a CPAP breathing 12 30% 27 67.5% 1 2.5% 40 100% 200
machine for sleep apnea? * 83.3%
Did he/she use it (CPAP machine) 2 13.3% 12 80% 1 6.7% 15 100% 225
regularly? * 93.8%
*Not all individuals were asked this question based on skip patterns.
Cases are accidental and undetermined drug overdose deaths with at least one
opioid and no illicit substances
Note: Proportion estimate and CI exclude missing values unless specified
39
40. Use of Medications
Yes No I Don't Know Total Missing/Blank
N % N % N % N % N %
Did (decedent) suffer from pain? 198 89.6% 21 9.5% 2 0.9% 221 100% 19 7.9%
Did (decedent) suffer from chronic (or ongoing) pain?* 182 91.5% 12 6% 5 2.5% 199 100% 41 17.1%
Did (decedent) take prescription medications for pain
197 89.1% 18 8.1% 6 2.7% 221 100% 19 7.9%
during the year before his/her death?
Did (decedent) take prescription medications for pain
179 90.4% 5 2.5% 14 7.1% 198 100% 42 17.5%
in the last month of life?*
In the year prior to (decedent)’s death, did he/she use
prescription pain medication for reasons other than to 57 25.9% 133 60.5% 30 13.6% 220 100% 20 8.3%
treat pain?
Did (decedent) suffer from any of the following
chronic medical conditions? (Seizures, diabetes,
199 90% 17 7.7% 5 2.3% 221 100% 19 7.9%
obesity, cancer, mental illness, physical disability,
traumatic brain injury, other**)
Did (decedent) ever use medications to help him/her
160 73.7% 37 17.1% 20 9.2% 217 100% 23 9.6%
to SLEEP?
Did (decedent) ever use medications to RELIEVE
158 77.5% 35 17.2% 11 5.4% 204 100% 36 15%
STRESS OR ANXIETY?
*Not all individuals were asked this question based on skip patterns.
Cases are accidental and undetermined drug overdose deaths with at least one
opioid and no illicit substances
40
Note: Proportion estimate and CI exclude missing values unless specified