Table 3.
Effects of Job Loss/Unemployment on Substance-Use Disorders.
| Data Source, N, Age | Authors | Outcome Measures | Effects |
|---|---|---|---|
| U.K., MCS/ALSPAC/NS/BCS70/NCDS/USOC/ELSA/GS, 2020, 27,841, 16–66 | Green, M. et al., 2022 [45] | Current smoking, vaping, and drinking among furloughed, no longer employed and stable unemployed people | Only correlation between stable unemployment women and smoking (ARR * = 1.35) as well as no longer employed women and vaping (ARR = 2.74). |
| Netherlands, DLCS, 2006–2013, 45,967, 25–50 | Mangot-Sala, L. et al., 2021 [34] | Abstainers, moderate/heavy/binge drinking | Only correlation between long-term unemployment and heavy as well as binge drinking. Moreover, some short-term unemployed individuals are more likely to become abstinent. |
| USA, TEDS, 1993–2016, n.a., age ≥ 18 | Azagba, S. et al., 2021 [48] | Treatment admissions for primary substance abuse (opiates, cocaine, alcohol, marijuana, other drugs, stimulants) | For every unit of rising unemployment rate, opiate treatment admissions increase by 9%. Other substances are associated with similar results; only stimulants show negative correlation. |
| Sweden, SWIP, 2005–2017, 2,743,764, 18–61 | Jonsson, J. et al., 2021 [26] | Substance abuse | Unemployment is associated with higher risk of developing substance abuse (HR ** = 1.05–2.19). |
| England, GP, 2011–2017, 8736, n.a. | Vandoros, S. et al., 2020 [49] | Opioid prescribing | For every percentage point of rising unemployment rate, defined daily dose of opioid per capita increase by 0.017 (0.9% compared to the average). |
| USA, CARDIA, 2005–2010, 1307, n.a. | Swift, S. et al., 2020 [50] | Binge drinking, past 30-day drug use | Negative employment changes are associated with decreasing binge drinking, but increasing drug use in the past 30 days. |
| Italy, n.a., 2019, 314, n.a. | De Sio, S. et al., 2020 [41] | Alcohol-related biomarkers (carbohydrate-deficient transferrin, aspartate transaminase, alanine transaminase, γ-glutamyltransferase, mean corpuscular volume) | Office worker show lower rates in alcohol-related biomarkers then unemployed people. |
| USA, n.a., n.a., 553, ≥18 | Miguel, A. et al., 2019 [43] | History of cocaine use and substance abuse treatment, concomitant psychiatric (alcohol-use) disorders | Stable unemployment during treatment of cocaine use is associated with negative outcomes. In contrast, being employed during treatment is associated with better outcomes. |
| Spain, EDADES, 2013, 14,113, 25–64 | Teixidó-Compañó, E. et al., 2018 [32] | Hazardous drinking, heavy cannabis use, hypnosedative consumption | Unemployed people, no matter if male or female, show higher rates of cannabis and hypnosedative use, whereas unemployed women show less rates in alcohol drinking. |
| Netherlands, HIS, 2004–2013, 26,355, 30–64 | De Goeij, M. et al., 2017 [53] | Episodic drinking before and during 2008 economic crisis | Job loss during economic crisis is only associated with chronic (OR 1.43/OR 1.42), but not with episodic drinking. |
| USA, PSID, 1999–2011, 41,231, n.a. | Grafova, I. et al., 2017 [31] | Current and former smoker, smoking relapse, increased and decreased cigarette consumption, quit smoking | Unemployment initially decreases the risk of cigarette consumption and its relapse in men, but not in long term. |
| Spain, Flash EB 401, 2011/2014, n.a., 15–24 | Ayllón, S. et al., 2017 [29] | Consumption of cannabis and new substances | For 1% of rising unemployment rate, consumption of cannabis at any point in time among young people increases by 0.7%. |
| Germany, SUF, 2016, 8951, 15–64 | Hollederer, A. et al., 2016 [27] | Consumption of beer, wine, alcoholic mixed drinks, spirits, and nicotine | Twice as high rate of unemployed smokers as employed smokers; but alcohol consumption rates are higher in employed people. |
| AT/BE/CZ/DK/FR/ DE/IT/NL/ES/SE/CH ***, SHARE, 2006–2012, 7615, 50–64 |
Bosque-Prous, M. et al., 2015 [39] | Hazardous drinking | Increasing unemployment rate leads to increasing rates of hazardous drinking by 32%. |
| USA, SSDP, n.a., n.a., 22–33 | Lee, J. et al., 2015 [54] |
Heavy episodic drinking, daily cigarette smoking, and marijuana use |
Unemployment among young adults is associated with heavy episodic drinking. This does not apply to marijuana use and just possibly to daily cigarette smoking. |
| USA, NSDUH, 2002–2004/2005- 2007/2008/2009- 2010, ~405,000, ≥18 | Compton, W. et al., 2014 [28] | Heavy alcohol, illicit drug and tobacco use; alcohol and illicit drug abuse or dependence | Unemployed people tend to higher rates in all mentioned outcome measures; also during economic crisis. |
| USA, NAS12, 2009–2010, 5382, ≥18 | Mulia, N. et al., 2014 [33] | Alcohol-related health problems prior to recession | Job loss is associated with higher risk of alcohol-related health problems in men, especially drunkenness, its consequences and alcohol dependence. |
| USA, NESARC, 2001–2002/2004–2005, n.a., 19–60 | Baldwin, M. et al., 2013 [57] | Alcohol and drug disorder | Unemployed people with alcohol disorder in wave I have a 3.7 respectively 8.8 percentage point higher chance of finding part-time respectively full-time work in wave II. Part-time employed people with alcohol disorder in wave I have a 6.1 percentage point higher chance of continuing in their work in wave II while those with drug disorder have a 13.8 percentage point lower chance of this work in wave II. |
| Germany, SOEP, 1998–2009, 52,940, 17–65 |
Schunck, R. et al., 2012 [30] | Smoking and number of cigarettes per day | Unemployment increases the risk of smoking, but not its intensity. |
| USA, NESARC, 2001–2002/2004–2005, 34,120, ≥18 | Dávalos, M. et al., 2011 | Alcohol consumption (binge drinking and its number of days, driving after too much to drink, abuse/dependence) | Unemployment is associated with rising alcoholic (binge) drinking events as well as its abuse/dependence. |
MCS: Millennium Cohort Study, ALSPAC: Avon Longitudinal Study of Parents and Children (G0 = parents, G1 = children), NS: Next Steps, BCS70: 1970 British Cohort Study, NCDS: National Child Development Study, USOC: Understanding Society, ELSA: English Longitudinal Study of Aging, GS: Generation Scotland, DLCS: Dutch Lifelines Cohort Study, TEDS: Treatment Episode Data Set, SWIP: Swedish Work, Illness, and Labour-market Participation, GP: General Practice Data Dashbord, CARDIA: Coronary Artery Risk Development in Young Adults, EDADES: Spanish Household Survey on Alcohol and Drugs, HIS: Health Interview Survey, PSID: Panel Study of Income Dynamics, Flash EB 401: Flash Eurobarometer 401 “Young people and drugs”, Survey on Alcohol and Related Conditions, SUF: Scientific Use File, SHARE: Survey of Health, Ageing and Retirement in Europe, SSDP: Seattle Social Development Project, NSDUH: U.S. National Survey on Drug Use and Health, NAS12: U.S. National Alcohol Survey, NESARC: National Epidemiologic Survey on Alcohol and Related Conditions, SOEP: German Socio-Economic Panel, * ARR: Absolute Risk Reduction, ** HR: Hazard Ratio, *** AT/BE/CZ/DK/FR/DE/IT/NL/ES/SE/CH: Austria, Belgium, Czech Republic, Denmark, France, Germany, Italy, Netherlands, Spain, Sweden, Switzerland.