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Gender Differences in Psychiatric & Substance Use Disorders Among Substance Users in Barcelona

Explore how gender impacts psychiatric & substance disorders among substance users in Barcelona. Investigate lifetime diagnoses & factors associated with these disorders. Findings reveal significant variations in prevalence & outcomes by gender.

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Gender Differences in Psychiatric & Substance Use Disorders Among Substance Users in Barcelona

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  1. Gender differences in lifetime psychiatric and substance use disorders among people who use substances in Barcelona Frem Y, Domingo-Salvany A, Torrens M, Gilchrist G Reader in Addictions Healthcare Research Gail.Gilchrist@kcl.ac.uk

  2. Declaration • No conflict of interest

  3. Background • Psychiatric disorders are higher among people who use substances than among people who do not (Flynn and Brown, 2008; Torrens et al., 2015; Kingston et al., 2016), with mood, anxiety and personality disorders being the most common disorders • People who use substances and have a co-occurring mental health disorder who compared to those who do not, have poorer outcomes for both disorders(Boden and Moos, 2009; Flynn and Brown, 2008; Maguraet al., 2009). • Generally, women report higher prevalence than men of the following disorders: depression, anxiety, eating disorders and borderline personality disorder, and men are more likely to report higher prevalence of antisocial personality disorder, psychosis and attention deficit and hyperactivity disorder (ADHD) (e.g. for recent reviews see Torrens et al., 2015; Kingston et al., 2016). • Biological and psychosocial differences between men and women influence the “prevalence, presentation, comorbidity, and treatment of substance use disorders”(Back et al., 2006).

  4. Aims • While strong evidence of gender differences in comorbidity exists, there is a gap in understanding of the relationships between specific mental disorders and specific substance use disorders (Torrens et al., 2015), by gender. • Sordo et al. (2012) argue that “few studies have evaluated whether there are different predictive factors for men and women” and that such information is required to inform prevention, diagnosis and treatment. • This study examined gender differences in lifetime substance use and non-substance use (non-SUD) psychiatric disorders among illicit drug users and determined factors associated with non-SUD psychiatric disorders independently for males and for females

  5. Secondary analysis of five cross-sectional studies conducted during 2000-2006 in Barcelona: • 115 from detoxification unit (Nocon et al., 2007) • 189 consecutive admissions to methadone treatment (Astals et al., 2008) • 149 current regular heroin users (Rodriguez-Llera et al., 2006) • 139 current regular cocaine users (Herrero et al., 2008) • 39 ecstasy users (Martin-Santos et al., 2010)

  6. Methods • Lifetime DSM-IV substance use (SUD) and non-SUD psychiatric diagnoses assessed using the Spanish Psychiatric Research Interview for Substance and Mental Disorders (Torrens et al., 2004) • 629 people who use substances (68% male) recruited from treatment (n=304) and out of treatment (n=325) settings. • Odds ratios (OR) and 95% confidence intervals (CI) were calculated using binary logistic regression. • .

  7. SUD and non-SUD psychiatric diagnoses assessed • .

  8. Results • Sample consisted of 428 men (68%) and 201 females • Women were significantly younger than men (27.4 years vs 29-2 years) • The odds of being married or cohabiting, or squatting or being homeless were two times higher among men than women • Women were less likely to be employed or studying, and less likely to have ever been in prison than men

  9. Lifetime abuse or dependence disorders

  10. Lifetime abuse ordependencedisorders • Women were less likely than men to have the following disorders: • Opiates • Cannabis • Alcohol Women met criteria for less substance disorders than men (3.4 vs 3.6 drugs disorders) No gender differences in cocaine or other stimulant disorders, hallucinogen disorders or sedative disorder

  11. Results • The prevalence of any lifetime psychiatric (non-SUD) disorder was 41.8%, with major depression (17%) and antisocial personality disorder (17%) being the most prevalent disorders • The prevalence of axis I substance-induceddisorderswassubstantiallylower (15%) thanprimaryorindependentpsychiatricdisorders (64%) • The odds of having any non-SUD were over two times greater for females than males even after adjusting for age and study (OR 2.11; 95%CI 1.50, 2.96)

  12. Psychiatric disorders (OR 95%CI for females compared to males)

  13. After adjusting for age, sex of participant and study, the odds for having a lifetime Axis I psychiatric disorder in multivariate analyses were higher among participants who: • Had lifetime poly SUD (OR 2.76; 95% CI 1.62, 4.69) • Had lifetime borderline personality disorder (OR 2.69; 95% CI 1.54, 4.72) • Were female (OR 2.09; 95% CI 1.48, 2.96) • Had a criminal history (OR 1.66; 95% CI 1.13, 2.43) • Were hepatitis C seropositive (OR 1.50; 95% CI 1.02,2.22)

  14. Factors associated with Axis I psychiatric disorder [Independent analysis for males and females] • After adjusting for age and study: • women who met criteria for a lifetime Axis I non-SUD psychiatric disorder were more likely than those who did not to have ever been in prison or to be HCV seropostitive; • and for men lower educational attainment or ever been in prison (marginally significant) were associated with a lifetime Axis I non-SUD psychiatric disorder.

  15. Associations between SUD and non-SUD disorders by gender M = male; F = female

  16. Discussion • Psychiatric disorders are common among people who use substances, with gender differences reported for specific disorders • Almost 4 in 10 men and over 5 in 10 womenmetcriteriaforanylifetime axis 1 psychiatric (non-SUD) disorder, and over 2 in 10 men and womenmetcriteriaforanylifetimeantisocial or borderline personality disorder. • Potential explanations for these gender differences have include that women who use substances have often experienced greater adverse events in childhood and adulthood (including abuse, intimate partner violence, sex trading) than men who use substances • Whilelifetimemood and anxietydisorderswere more likely to be independentdisorders, psychoticdisordersalthoughlessprevalent, were more likely to be substanceinduceddisorders

  17. Implications • Treatment systems are often separated for mental health and substance use (Saitz et al., 2008). Evidence supports the integration of treatment for people who use substances with co-existing psychiatric disorders (Kelly and Daley, 2013).  • While women-only treatment is not necessarily more effective than mixed-gender treatment, some greater effectiveness has been demonstrated by treatments that address problems more common to women or that are designed for specific subgroups of this population(Greenfield et al., 2009). • Gender-sensitive integrated treatment (including trauma-informed) approaches are required to prevent and address comorbidity psychiatric disorders among this population • .

  18. Acknowledgements • This work was funded by grants FIS G03/005, FIS-Red de Trastornos Adictivos, RD16/0017/0010/, the Department of Universities, Research and Information Society (2005SGR00008; 2005SGR 00322; 2009SGR25) (“Generalitat de Catalunya”), FIS 00/0777, PNSD (INT/2001,2002,2004). • We are grateful to the authors of the original studies

  19. Frem et al. (2017) Advances in Dual Diagnosis. 10(2): 45-56 doi.org/10.1108/ADD-01-2017-0002

  20. Why is comorbidity higher among females? (Kessler, 2003) • Female gender, younger age, lower educational level, and unemployment were associated with comorbid anxiety and mood disorders but not with pure mood disorders (De Graaf et al., 2002) • Some theories about the reasons for gender differences in depression emphasize the importance of differential persistence. For example, sex-role theories suggest that the chronic stresses associated with traditional female roles lead to a higher prevalence of depression among women than men (Mirowsky & Ross, 1989) • A number of consistently significant risk factors have been found, including family history, childhood adversity, various aspects of personality, social isolation, and exposure to stressful life experiences (see Kessler, 1997 for a review).

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