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Research article
Francisco Alejandro Montiel Ishino
National Institutes of Health
Corresponding Author
ORCiD: https://orcid.org/0000-0002-2837-726X
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Few studies have comprehensively and contextually examined the relationship of variables associated with opioid use. Our purpose was to fill a critical gap in comprehensive risk models of opioid misuse and use disorder in the United States by identifying the most salient predictors.
Methods: A multivariate logistic regression was used on the 2017 and 2018 National Survey on Drug Use and Health, which included all 50 states and the District of Columbia of the United States. The sample included all noninstitutionalized civilian adults aged 18 and older (N=85,580; weighted N=248,008,986). The outcome of opioid misuse and/or use disorder was based on reported prescription pain reliever and/or heroin use dependence, abuse, or misuse. Biopsychosocial predictors of opioid misuse and use disorder in addition to sociodemographic characteristics and other substance dependence or abuse were examined in our comprehensive model. Biopsychosocial characteristics included socioecological and health indicators. Criminality was the socioecological indicator. Health indicators included self-reported health, private health insurance, psychological distress, and suicidality. Sociodemographic variables included age, sex/gender, race/ethnicity, sexual identity, education, residence, income, and employment status. Substance dependence or abuse included both licit and illicit substances (i.e., nicotine, alcohol, marijuana, cocaine, inhalants, methamphetamine, tranquilizers, stimulants, sedatives).
Results. The comprehensive model found that criminality (adjusted odds ratio [AOR]=2.58, 95% confidence interval [CI]=1.98-3.37, p<0.001), self-reported health (i.e., excellent compared to fair/poor [AOR=3.71, 95%CI=2.19-6.29, p<0.001], good [AOR=3.43, 95%CI=2.20-5.34, p<0.001], and very good [AOR=2.75, 95%CI=1.90-3.98, p<0.001]), no private health insurance (AOR=2.12, 95%CI=1.55-2.89, p<0.001), serious psychological distress (AOR=2.12, 95%CI=1.55-2.89, p<0.001), suicidality (AOR=1.58, 95%CI=1.17-2.14, p=0.004), and other substance dependence or abuse were significant predictors of opioid misuse and/or use disorder. Substances associated were nicotine (AOR=3.01, 95%CI=2.30-3.93, p<0.001), alcohol (AOR=1.40, 95%CI=1.02-1.92, p=0.038), marijuana (AOR=2.24, 95%CI=1.40-3.58, p=0.001), cocaine (AOR=3.92, 95%CI=2.14-7.17, p<0.001), methamphetamine (AOR=3.32, 95%CI=1.96-5.64, p<0.001), tranquilizers (AOR=16.72, 95%CI=9.75-28.65, p<0.001), and stimulants (AOR=2.45, 95%CI=1.03-5.87, p=0.044).
Conclusions. Biopsychosocial characteristics such as socioecological and health indicators, as well as other substance dependence or abuse were stronger predictors of opioid misuse and use disorder than sociodemographic characteristics.
Keywords
opioids; opioid misuse; opioid use disorder; biopsychosocial factors; comprehensive risk
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On 04 Sep, 2020
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On 03 Sep, 2020
Version 2
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Editorial decision: Major revision
On 29 Jul, 2020
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Received 23 Jul, 2020
Reviewer #2 agreed
On 13 Jul, 2020
Review #1 received
Received 01 Jul, 2020
Reviewers invited
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Reviewer #1 agreed
On 29 Jun, 2020
Editor assigned
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On 24 Jun, 2020
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On 24 Jun, 2020
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Editorial decision: Major revision
On 19 May, 2020
Review #1 received
Received 12 May, 2020
Review #2 received
Received 27 Apr, 2020
Reviewer #2 agreed
On 25 Apr, 2020
Reviewer #1 agreed
On 23 Apr, 2020
Reviewers invited
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Francisco Alejandro Montiel Ishino
National Institutes of Health
Corresponding Author
ORCiD: https://orcid.org/0000-0002-2837-726X
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Public Health.
No community comments so far
Editorial decision: Accept
On 05 Nov, 2020
Editor assigned
On 03 Nov, 2020
Submission checks complete
On 03 Nov, 2020
Editor invited
On 03 Nov, 2020
No comments provided
Editor assigned
On 27 Oct, 2020
Submission checks complete
On 27 Oct, 2020
Editor invited
On 27 Oct, 2020
No comments provided
Review #3 received
Received 19 Oct, 2020
Reviewer #3 agreed
On 30 Sep, 2020
Review #2 received
Received 19 Sep, 2020
Reviewers invited
Invitations sent on 15 Sep, 2020
Reviewer #1 agreed
On 15 Sep, 2020
Reviewer #2 agreed
On 15 Sep, 2020
Review #1 received
Received 15 Sep, 2020
Editor assigned
On 13 Sep, 2020
Submission checks complete
On 12 Sep, 2020
Editor invited
On 12 Sep, 2020
No comments provided
Editor assigned
On 04 Sep, 2020
Editorial decision: Major revision
On 04 Sep, 2020
Submission checks complete
On 03 Sep, 2020
Editor invited
On 03 Sep, 2020
Version 2
Posted 26 Jun, 2020
No comments provided
Editorial decision: Major revision
On 29 Jul, 2020
Review #2 received
Received 23 Jul, 2020
Reviewer #2 agreed
On 13 Jul, 2020
Review #1 received
Received 01 Jul, 2020
Reviewers invited
Invitations sent on 29 Jun, 2020
Reviewer #1 agreed
On 29 Jun, 2020
Editor assigned
On 25 Jun, 2020
Submission checks complete
On 24 Jun, 2020
Editor invited
On 24 Jun, 2020
No comments provided
Editorial decision: Major revision
On 19 May, 2020
Review #1 received
Received 12 May, 2020
Review #2 received
Received 27 Apr, 2020
Reviewer #2 agreed
On 25 Apr, 2020
Reviewer #1 agreed
On 23 Apr, 2020
Reviewers invited
Invitations sent on 23 Mar, 2020
Editor assigned
On 03 Mar, 2020
Submission checks complete
On 02 Mar, 2020
Editor invited
On 02 Mar, 2020
First submitted
On 27 Feb, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Public Health.
Background: Few studies have comprehensively and contextually examined the relationship of variables associated with opioid use. Our purpose was to fill a critical gap in comprehensive risk models of opioid misuse and use disorder in the United States by identifying the most salient predictors.
Methods: A multivariate logistic regression was used on the 2017 and 2018 National Survey on Drug Use and Health, which included all 50 states and the District of Columbia of the United States. The sample included all noninstitutionalized civilian adults aged 18 and older (N=85,580; weighted N=248,008,986). The outcome of opioid misuse and/or use disorder was based on reported prescription pain reliever and/or heroin use dependence, abuse, or misuse. Biopsychosocial predictors of opioid misuse and use disorder in addition to sociodemographic characteristics and other substance dependence or abuse were examined in our comprehensive model. Biopsychosocial characteristics included socioecological and health indicators. Criminality was the socioecological indicator. Health indicators included self-reported health, private health insurance, psychological distress, and suicidality. Sociodemographic variables included age, sex/gender, race/ethnicity, sexual identity, education, residence, income, and employment status. Substance dependence or abuse included both licit and illicit substances (i.e., nicotine, alcohol, marijuana, cocaine, inhalants, methamphetamine, tranquilizers, stimulants, sedatives).
Results. The comprehensive model found that criminality (adjusted odds ratio [AOR]=2.58, 95% confidence interval [CI]=1.98-3.37, p<0.001), self-reported health (i.e., excellent compared to fair/poor [AOR=3.71, 95%CI=2.19-6.29, p<0.001], good [AOR=3.43, 95%CI=2.20-5.34, p<0.001], and very good [AOR=2.75, 95%CI=1.90-3.98, p<0.001]), no private health insurance (AOR=2.12, 95%CI=1.55-2.89, p<0.001), serious psychological distress (AOR=2.12, 95%CI=1.55-2.89, p<0.001), suicidality (AOR=1.58, 95%CI=1.17-2.14, p=0.004), and other substance dependence or abuse were significant predictors of opioid misuse and/or use disorder. Substances associated were nicotine (AOR=3.01, 95%CI=2.30-3.93, p<0.001), alcohol (AOR=1.40, 95%CI=1.02-1.92, p=0.038), marijuana (AOR=2.24, 95%CI=1.40-3.58, p=0.001), cocaine (AOR=3.92, 95%CI=2.14-7.17, p<0.001), methamphetamine (AOR=3.32, 95%CI=1.96-5.64, p<0.001), tranquilizers (AOR=16.72, 95%CI=9.75-28.65, p<0.001), and stimulants (AOR=2.45, 95%CI=1.03-5.87, p=0.044).
Conclusions. Biopsychosocial characteristics such as socioecological and health indicators, as well as other substance dependence or abuse were stronger predictors of opioid misuse and use disorder than sociodemographic characteristics.
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