Association between tobacco smoking and opioid use: A meta-analysis

Rajabi, Abdolhalim; Dehghani, Mohsen; Shojaei, Azadeh; Farjam, Mojtaba; Motevalian, Seyed Abbas

doi:10.1016/j.addbeh.2018.11.043

Cited by 57 publications

(49 citation statements)

References 40 publications

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“…Other substance dependence or abuse has been associated with opioid misuse based on varying risk factors. [13,28,33,47,50] In this study, we speci cally found that nicotine, [28,29] alcohol, [28,30] cocaine, [50] methamphetamine, [32] tranquilizers, [34,35,51] other illicit stimulants [20], and marijuana [28] have a positive relationship with opioid misuse and use disorder. The stimulant effect from nicotine, cocaine, methamphetamine, and other illicit stimulants have been stipulated to mitigate the depressive effects of opioids and may increase the "high" effect.…”

Section: Discussionmentioning

confidence: 63%

“…The role of other substance dependence, abuse, and/or misuse, whether legal, illicit, or prescribed, has also been linked to opioid misuse and/or use disorder. Concurrent substance use such as nicotine and tobacco dependence [28,29], alcohol [30], sedatives [31], methamphetamines [32], tranquilizers [33][34][35], other analgesics [36], and marijuana [37] have been positively associated with opioid misuse and use disorder [37,38]. Marijuana may be context dependent as it has a mixed relationship with opioid use, misuse, and use disorder.…”

Section: Introductionmentioning

confidence: 99%

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A comprehensive multivariate model of biopsychosocial factors associated with opioid misuse and use disorder in a 2017-2018 United States national survey

Ishino

Gilreath

Salmeron

et al. 2020

Preprint

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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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Section: Discussionmentioning

confidence: 63%

Section: Introductionmentioning

confidence: 99%

A comprehensive multivariate model of biopsychosocial factors associated with opioid misuse and use disorder in a 2017-2018 United States national survey

Ishino

Gilreath

Salmeron

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Other substance dependence or abuse has been associated with opioid misuse based on varying risk factors. 19, 25−28 In this study, we specifically found that nicotine, 25,29 marijuana, 25 cocaine, 28 methamphetamine, 30 tranquilizers, 31−33 and stimulants 34 increase the probability toward opioid misuse. Although the present study revealed an increased association of opioid misuse with marijuana compared to non-marijuana users, the relationship in the literature has been mixed.…”

Section: Discussionmentioning

confidence: 74%

Biopsychosocial factors associated with opioid misuse in a 2017-2018 United States national survey: A comprehensive multivariate model

Ishino¹,

Gilreath²,

Salmeron³

et al. 2020

Preprint

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Background Few studies have comprehensively and contextually examined the relationship of variables associated with opioid misuse. Our purpose was to fill a critical gap in comprehensive risk models of opioid misuse in the United States by identifying the most salient predictors. MethodsA 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 was based on reported prescription pain reliever and/or heroin dependence or abuse. Biopsychosocial predictors of opioid misuse 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. 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).

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“…In 2003, Bashardost et al (23) estimated the prevalence of substance use at 5.0 % among 6400 randomly selected men in Isfahan.Yazd has a lower prevalence of substance use disorder than the northern regions of Iran (19,20,24).According to the results of these studies, Iran, in the vicinity of countries producing narcotics (poppy) and in some way its passage, is in the high-risk area in terms of the prevalence of substance use, its production and transportation (8). Based on a meta-analysis study, it has been con rmed that: smoking is considered a risk factor for substance use disorders, and signi cantly increases the risk of substance use disorders (25,26). As in the present study, this relationship between smoking and substance use disorders was signi cant.…”

Section: Discussionmentioning

confidence: 99%

Substance use in adults of Yazd Greater Area, 2014-2015: A population based study

Bagheri

Mehrara

Mirzaei

2020

Preprint

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Background: Substance use disorders (SUDs), including substance dependence or abuse, have a tremendous impact on individuals, families, communities, and governments. Objective: The purpose of this study was to investigate the prevalence of SUDs in Yazd Greater Area during 2014-2015.Method: This study uses data from the Yazd Health Study (YaHS) recruitment phase which was conducted from 2014 to 2015, to investigate the epidemiology of SUDs among 20-70 year-old adults. We studied 9965 participants 20-70 years old who lived in Yazd Greater Area. Data were collected using a validated questionnaire. Results: The age-adjusted prevalence of illicit substance use was 6.2% (95% CI: 5%-7.4%). for men and 2.5% (95% CI: 1.7%-3.6%) for women. The substance use was significantly correlated with age (r= -0.29, p=0.006), educational level (r= -0.24, p=0.021), tobacco smoking (r= 0.23, p= 0.001), and sex (r= -0.98, p=0.001), But with hookah smoking had no significant relationship (r= -0.01, p=0.891). 35.6% of those consuming drugs had a previous history of addiction treatment. Also, the prevalence of substance use was greater in elders. Conclusion: This study indicated that the prevalence of substance use in adults of Yazd Greater Area which was correlated to the factors including consumption of cigarettes, age, and sex. The prevalence of various addictions is slightly higher than the rest of Iran.

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Association between tobacco smoking and opioid use: A meta-analysis

Cited by 57 publications

References 40 publications

A comprehensive multivariate model of biopsychosocial factors associated with opioid misuse and use disorder in a 2017-2018 United States national survey

A comprehensive multivariate model of biopsychosocial factors associated with opioid misuse and use disorder in a 2017-2018 United States national survey

Biopsychosocial factors associated with opioid misuse in a 2017-2018 United States national survey: A comprehensive multivariate model

Substance use in adults of Yazd Greater Area, 2014-2015: A population based study

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