| Literature DB >> 25993344 |
Nahid Darvishi1, Mehran Farhadi2, Tahereh Haghtalab1, Jalal Poorolajal3.
Abstract
BACKGROUND: Several original studies have investigated the effect of alcohol use disorder (AUD) on suicidal thought and behavior, but there are serious discrepancies across the studies. Thus, a systematic assessment of the association between AUD and suicide is required.Entities:
Mesh:
Substances:
Year: 2015 PMID: 25993344 PMCID: PMC4439031 DOI: 10.1371/journal.pone.0126870
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Flow of information through the different phases of the systematic review.
Summary of studies results.
| Newcastle Ottawa Score | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 1st author | Country | Age | Gender | Population | Study | Estimate | Sample | Sel | Com | E/O |
| Agrawal 2013 | USA | 18–27 | Female | General | Cross-sectional | Crude | 3,787 | **** | * | ** |
| Akechi 2006 | Japan | 40–69 | Male | General | Cohort | Adjusted | 43,383 | **** | ** | *** |
| Andreasson 1991 | Sweden | 18–21 | Male | General | Cohort | Adjusted | 49,464 | *** | ** | ** |
| Aseltine 2009 | USA | 11–19 | Both | General | Cross-sectional | Adjusted | 32,217 | ** | ** | ** |
| Bagge 2013 | USA | 18–64 | Both | General | Case-Control | Adjusted | 192 | **** | ** | ** |
| Beck 1989 | USA | 29.9 | Both | General | Case-Control | Adjusted | 413 | *** | ** | ** |
| Bernal 2007 | Europe | 18+ | Both | General | Cross-sectional | Adjusted | 21,425 | *** | ** | ** |
| Bunevicius 2014 | Lithuania | 18–89 | Both | General | Cross-sectional | Adjusted | 998 | *** | ** | ** |
| Coelho 2010 | Brazil | 18+ | Both | General | Cross-sectional | Adjusted | 1,464 | ** | ** | ** |
| Donald 2006 | Australia | 18–24 | Both | General | Case-Control | Adjusted | 380 | **** | ** | ** |
| Elizabeth 2009 | USA | 13–18 | Both | General | Cross-sectional | Crude | 31,953 | ** | * | * |
| Feodor 2014 | Denmark | 16+ | Both | General | Cohort | Adjusted | 32,010 | **** | ** | *** |
| Flensborg 2009 | Denmark | 20–93 | Both | General | Cohort | Adjusted | 18,146 | **** | ** | *** |
| Grossman 1991 | USA | 14.4 | Both | General | Cross-sectional | Adjusted | 6,637 | *** | ** | *** |
| Gururaj 2004 | India | 15–60 | Both | General | Case-Control | Crude | 538 | **** | * | ** |
| Kaslow 2000 | USA | 18–64 | Female | General | Case-Control | Crude | 285 | *** | * | ** |
| Kettl 1993 | Alaska | 30.8 | Both | General | Case-Control | Crude | 66 | ** | * | *** |
| Lesage 1994 | Canada | 18–35 | Male | General | Case-Control | Crude | 150 | **** | * | *** |
| Méan 2005 | Switzerland | 16–21 | Both | General | Cohort | Adjusted | 148 | *** | ** | * |
| Morin 2013 | Sweden | 70–91 | Both | General | Case-Control | Adjusted | 515 | *** | ** | ** |
| Orui 2011 | Japan | 20+ | Both | General | Cross-sectional | Adjusted | 770 | *** | ** | ** |
| Petronis 1990 | USA | Adults | Both | General | Cohort | Adjusted | 13,673 | FTU | FTU | FTU |
| Pridemore 2013 | Russia | 25–54 | Male | General | Case-Control | Adjusted | 1,640 | **** | ** | ** |
| Randall 2014 | Benin | 12–16 | Both | General | Cross-sectional | Adjusted | 2,690 | ** | ** | ** |
| Rossow 1995 | Norway | 19+ | Male | Conscripts | Cohort | Crude | 41,399 | **** | * | *** |
| Rossow 1999 | Sweden | Middle-aged | Male | General | Cohort | Adjusted | 46,490 | **** | ** | *** |
| Shoval 2014 | Israel | 21–45 | Both | General | Cross-sectional | Adjusted | 1,237 | *** | ** | ** |
| Swahn 2012 | France | 19-Nov | Both | General | Cross-sectional | Adjusted | 13,187 | ** | ** | ** |
| Swahn 2012 | USA | 19-Nov | Both | General | Cross-sectional | Adjusted | 15,136 | ** | ** | ** |
| Tidemalm 2008 | Sweden | 37.7 | Both | General | Cohort | Adjusted | 39,685 | **** | ** | *** |
| Zhang 2010 | China | 34–60 | Male | General | Cross-sectional | Adjusted | 454 | ** | ** | ** |
| Zonda 2006 | Hungary | 52.1 | Both | General | Case-Control | Crude | 200 | *** | * | ** |
Sel: Selection; Com: Comparability; E/O: Exposure/Outcome; FTU: Full text unavailable
Adjusted means controlled for one or more of the following factors: age, gender, race, mental disorder, drug abuse, smoking, marital status, body mass index, educational level, employment status, income, living alone
Fig 2Forest plot of the association between alcohol use disorder and suicide ideation.
Fig 3Forest plot of the association between alcohol use disorder and suicide attempt.
Fig 4Forest plot of the association between alcohol use disorder and completed suicide.
Fig 5Funnel plot of included studies assessing the publication bias in studies addressing the association between alcohol use disorder and suicide ideation.
Fig 7Funnel plot of included studies assessing the publication bias in studies addressing the association between alcohol use disorder and completed suicide.
Fig 6Funnel plot of included studies assessing the publication bias in studies addressing the association between alcohol use disorder and suicide attempt.
Analysis of meta-regression exploring sources of heterogeneity considering mean age, sex, adjusted versus unadjusted effect estimates, and studies with a high risk of bias versus those with a low risk of bias as covariates based on logarithmic scale.
| Variables | Coefficient | SE | 95% CI |
|
|---|---|---|---|---|
|
| ||||
| Mean age (yr) | -0.043 | 0.032 | -0.182, 0.096 | 0.313 |
| Gender (% of men) | 0.783 | 1.822 | -7.058, 8.625 | 0.709 |
| Adjustment (0 = unadjusted; 1 = adjusted) | -0.115 | 0.995 | -4.396, 4.165 | 0.918 |
| Risk of bias (0 = high risk; 1 = low risk) | 1.263 | 1.011 | -3.089, 5.616 | 0.338 |
| Constant | 0.804 | 0.963 | -3.341, 4.949 | 0.482 |
|
| ||||
| Mean age (yr) | 0.015 | 0.010 | -0.009, 0.040 | 0.195 |
| Gender (% of men) | 0.836 | 0.633 | -0.623, 2.297 | 0.223 |
| Adjustment (0 = unadjusted; 1 = adjusted) | 0.061 | 0.345 | -0.736, 0.859 | 0.863 |
| Risk of bias (0 = high risk; 1 = low risk) | 0.345 | 0.482 | -0.766, 1.457 | 0.494 |
| Constant | 0.159 | 0.469 | -0.923, 1.241 | 0.743 |
|
| ||||
| Mean age (yr) | -0.017 | 0.017 | -0.057, 0.022 | 0.357 |
| Gender (% of men) | -0.072 | 0.857 | -2.011, 1.867 | 0.935 |
| Adjustment (0 = unadjusted; 1 = adjusted) | -0.015 | 0.394 | -0.908, 0.876 | 0.969 |
| Risk of bias (0 = high risk; 1 = low risk) | 0.591 | 0.460 | -0.450, 1.634 | 0.231 |
| Constant | 1.126 | 1.174 | -1.529, 3.782 | 0.363 |