Heart Disease Risk Following Mental Disorders

This is the second in a series looking at the recent study of physical illness in those with a diagnosis of a mental disorder.

Today, I am published a chart of the mental disorders associated with increased risk for report of heart disease at a later time.

Alcohol and drug dependence diagnoses are associated with the highest risk of later heart disease. The odds ratio estimates this increase at better two and three times higher than those without an alcohol or drug dependence diagnosis.

Two specific anxiety disorder conditions also show association with later heart disease, panic disorder and PTSD.

Additionally, bulimia nervosa and bipolar disorder also show greater rates of heart disease although these associations are at around 60% to 80% higher rates.

These associations do not prove causality. For example heart disease may share susceptibility genes with some mental disorders.

Nevertheless, these associations should prompt rigorous medical heart disease surveillance in those with substance abuse and anxiety disorders. 

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Chart is an original figure created using data from the manuscript cited below.

Scott KM, Lim C, Al-Hamzawi A, Alonso J, Bruffaerts R, Caldas-de-Almeida JM, Florescu S, de Girolamo G, Hu C, de Jonge P, Kawakami N, Medina-Mora ME, Moskalewicz J, Navarro-Mateu F, O'Neill S, Piazza M, Posada-Villa J, Torres Y, & Kessler RC (2015). Association of Mental Disorders With Subsequent Chronic Physical Conditions: World Mental Health Surveys From 17 Countries. JAMA psychiatry, 1-9 PMID: 26719969

Stroke Risk Following Mental Disorders

An important recent manuscript published in JAMA Psychiatry looked at medical illnesses rates following diagnosis of a brain (mental) disorder.

This very large international study examined over 47,000 subjects followed between 2001 and 2011.

Baseline psychiatric assessment was completed using the Composite International Diagnostic Interview. Physical illness was assessed using a self-report of physician's diagnosis.

The manuscript is not free but I was able to obtain a professional courtesy copy of the manuscript from the lead author. 

The study found that a diagnosis of a mental disorder increased rates for a variety of later physical conditions.

I have put together a graph of the mental disorders associated with higher rates of later stroke (above).

Bulimia nervosa showed a three fold increase in later stroke. I am not aware of this association previously being noted. Alcohol and drug use disorders are known to increase stroke risk and this was found in the study lending face validity support.

Additional mental disorders associated with later stroke were bipolar disorder and panic/agoraphobia. 

Bipolar disorder has been linked to higher risk of hypertension and smoking.

The implications of these findings include need for enhanced medical illness screening and risk factor reduction in those with a mental disorder diagnosis. 

I will look at some the other individual medical conditions in future posts.

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Scott KM, Lim C, Al-Hamzawi A, Alonso J, Bruffaerts R, Caldas-de-Almeida JM, Florescu S, de Girolamo G, Hu C, de Jonge P, Kawakami N, Medina-Mora ME, Moskalewicz J, Navarro-Mateu F, O'Neill S, Piazza M, Posada-Villa J, Torres Y, & Kessler RC (2015). Association of Mental Disorders With Subsequent Chronic Physical Conditions: World Mental Health Surveys From 17 Countries. JAMA psychiatry, 1-9 PMID: 26719969

Treatment Guidelines for Problem Gambling

Basal ganglia may be involving in gambling disorder

Problem gambling effects a number of individuals who engage in gambling behavior.

Gambling behavior that meets criteria as a Gambling Disorder according to the criteria of DSM-5 includes four or more of the following over a consecutive 12 month period of time:

1. Increased quantity of money gambled to achieve excitement
2. Restlessness/irritability when attempting to cut down gambling behavior
3. Repeated unsuccessful attempts to cut down or stop gambling
4. Preoccupation with gambling
5. Gambling common in response to feelings of distress
6. Chases losses by returning to gambling in attempt to get even
7. Lies about the amount of gambling behavior
8. Loss of relationships, jobs or other significant life opportunities
9. Uses money from other people to attempt to solve gambling-induced financial problems

DSM-5 notes clinicians should be sure to rule out mania as a primary cause for gambling as this is a common feature of bipolar disorder.

There are few published guidelines for the treatment of gambling disorder. One helpful guideline is the Management of Gambling Disorders published by the Singapore Ministry of Health in 2011.

Here is a summary of some of the recommendations that meet the higher grades of evidence in support of the action:

• Gambling screening is appropriate in high-risk populations including chronic psychological or physical problems, alcohol or substance abuse or mental disorders
• A comprehensive treatment plan that is multidisciplinary and multi-modal
• No specific drugs have been approved to treat gambling disorder-patients should be told pharmacological treatments are off-label and may have side effects
• Opioid antagonists such as naltrexone may reduce gambling urges and thoughts
• SSRI drugs such as fluvoxamine or paroxetine may also reduce gambling urges and thoughts
• Psychological treatments are important and can include motivational enhancement therapy, self-help books, cognitive behavioral therapy (CBT) and mindfulness therapy
• Family members should be engaged in treatment to reduce facilitating behaviors

Additionally, any alcoholism or drug use must be addressed in gambling disorders as they can block effects of treatment and contribute to relapse risk.

Individuals seeking treatment for gambling problems should make sure elements of treatment outlined above are available as part of a comprehensive treatment program.

Figure is a screen shot from the iPad 3D Brain app of basal ganglia thought to be involved in reward and impulsive behaviors like gambling.

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Readers with more interest in this topic can find the free full-text manuscript by clicking on the PMID link below.

Lee KM, Chan HN, Cheah B, Gentica GF, Guo S, Lim HK, Lim YC, Noorul F, Tan HS, Teo P, & Yeo HN (2011). Ministry of Health clinical practice guidelines: management of gambling disorders. Singapore medical journal, 52 (6) PMID: 21732000

Brain Reward and Anabolic Steroids

Pine Cone and Peacocks from Vatican Museum

Testosterone displays effects on brain function in both males and females.

Emanuela Mhillaj and colleagues recently published a nice summary of what is currently known about the effects of anabolic-androgen steroids (AAS) on the brain.

Their review highlighted the potential for AAS to modulate brain reward function and potentially lead to a drug dependence type of abuse pattern.

Here are some of my notes on their discussion of AAS and the brain reward system:

• Studies of brain reward and AAS use in humans is confounded by perceived user benefits in appearance, strength and athletic performance
• Animal models of AAS and brain reward provide a model free of these confounding effects
• Conditioned place preference (CPP) is a relevant model for reward study in rodents
• Synthetic AAS compounds including nandrolone and drostanolone show rewarding CPP in both male mice and rats
• This effect can be blocked by dopamine antagonists--dopamine pathways are key in reward modulation
• Testosterone brain injections or implants produce reward response behaviors in rodents
• Hamster models show reward behavior with intravenous AAS injection but not oral ingestion
• PET imaging in rodents has shown upregulation of dopamine transporter protein
• The endogenous opioid system may modulate reward and reinforcement mechanisms of AAS
• Beta endorphin levels increase in brain regions of rats treated with AAS
• In humans, AAS use is commonly associated with abuse of other substances including including alcohol, cocaine, opiates, cannabis and ecstasy

This multi-drug abuse pattern in humans with AAS complicates the assessment of AAS effects on dependence and behavior. It is possible that brain reward mechanisms and risk for abuse and dependence vary among humans. Risk for alcohol, drug or nicotine dependence may be a marker for higher AAS abuse risk in humans.

Additionally, in a study that I conducted, antisocial personality traits were increased in humans with illicit AAS use. Antisocial personality is a risk factor for alcohol and drug abuse as well as aggressive behavior.

Readers with more interest in the review article can access the free full-text manuscript by clicking on the PMID link in the citation below.

Photo of peacocks and pine cone is from the author's files.

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Mhillaj E, Morgese MG, Tucci P, Bove M, Schiavone S, & Trabace L (2015). Effects of anabolic-androgens on brain reward function. Frontiers in neuroscience, 9 PMID: 26379484

Yates WR, Perry PJ, & Andersen KH (1990). Illicit anabolic steroid use: a controlled personality study. Acta psychiatrica Scandinavica, 81 (6), 548-50 PMID: 2378247

Conduct Disorder as a Substance Abuse Risk Factor

In this series of research reviews on conduct disorder several important findings are evident.

1. Conduct disorder (CD) commonly evolves into adult antisocial personality disorder
2. Conduct disorder in children often presents along with attention deficit hyperactivity disorder and learning problems
3. CD in childhood and adolescence raises risk for alcohol, drug and nicotine dependence.

Margaret Sibley and colleagues recently published a study of CD and ADHD and later initiation and escalation of the use of alcohol, cigarettes and cannabis.

In her study, 113 children with ADHD were assessed between the ages of 5 and 18 years of age. A control group of 65 children without ADHD were similarly assessed during this developmental period.

Twelve percent of the childhood ADHD later met criteria for a diagnosis of CD. This contrasts with only 1.5% of the control group. Also noteworthy was the high rate of oppositional defiant disorder in the ADHD group (59%) compared to only 5% of the control group.

Significant differences emerged in substance use. These key findings included the following:

• ADHD adolescents were more likely to have ever smoked a cigarette (47% v 28%) and were much more likely to be daily smokers (27% v 6%).
• ADHD adolescents were not more likely not more likely to have ever tried marijuana (53% v 51%) but were more likely to use on at least a weekly frequency (23% v 8%).
• There were no differences in the ADHD group compared to controls in ever use of alcohol or frequent drinking
• Maternal drinking in early childhood was the strongest predictor of adolescent alcohol use

The authors also found another important finding:

"escalating CD symptoms in childhood were viewed as a mediator of the relationship between ADHD and cigarette and marijuana use."

The authors noted in the longitudinal data analysis that increasing ADHD symptom endorsement predicted more CD symptoms. More CD symptoms was the strongest predictor of later substance use.

The take home message for clinicians is early identification and treatment of ADHD in children is important. Early identification and treatment of ADHD holds the promise for modifying later CD and substance use morbidity.

This is an important study teasing out some of the issues in ADHD/CD overlap and later substance use risk. Readers with more interest in this topic can access the free full-text manuscript by clicking on the PMID link in the citation below.

Graphic figure is an original created by the author using Canva.

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Sibley MH, Pelham WE, Molina BS, Coxe S, Kipp H, Gnagy EM, Meinzer M, Ross JM, & Lahey BB (2014). The role of early childhood ADHD and subsequent CD in the initiation and escalation of adolescent cigarette, alcohol, and marijuana use. Journal of abnormal psychology, 123 (2), 362-74 PMID: 24886010

Male Depression Risk Via Childhood Conduct Disorder

Conduct disorder represents an important childhood-onset condition that commonly persists into adulthood.

Adult antisocial personality disorder and substance abuse are known risks associated with conduct disorder.

A recent study by Kenneth Kendler and Charles Gardner identified male conduct disorder as a risk factor for adult major depression.

Their study using the Virginia Twin Registry examined 20 developmental risk factors in male and female twins for presence of recent adult major depression.

A key finding in their study was gender specificity for several of the developmental risk factors. Many of the developmental risk factors increased risk for later depression in both males and females.

However, several developmental risk factors showed a predominant effect in males. These male predominant risk factors included the following variables:

• Conduct disorder
• History of childhood sexual abuse
• Drug abuse
• Past major depression
• Stressful life events

Conduct disorder and presence of drug abuse were classified as having moderate effect size in male gender predominance.

Specific types of stressful life events were noted to have a strong male predominance. Stressful life events that included financial loss, occupational difficulty and legal problems were more commonly found in the male twins with depression.

The authors note:

"Our results with externalizing psychopathology are consistent with a wide range of studies finding that men have higher rates of conduct disorder and drug abuse and that both of these disorders are associated with a higher risk for major depression."

The take home message for clinicians is that assessment of childhood conduct disorder is important in children, adolescents and adults. In adult males, childhood conduct disorder represents an important risk factor for adult major depression.

Readers with more interest in this research can access the free full-text abstract and manuscript by clicking on the DOI link in the citation below.

Photo of electus parrot pair is from the author's files.

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Kendler, K., & Gardner, C. (2014). Sex Differences in the Pathways to Major Depression: A Study of Opposite-Sex Twin Pairs American Journal of Psychiatry, 171 (4), 426-435 DOI: 10.1176/appi.ajp.2013.13101375

Tracking Ecstasy Abuse with Google Trends

I’ve been interested in the possibility of using Google Trends to monitor patterns of drug abuse in the U.S. and throughout the world.  My hypothesis is that drug abuse patterns will be reflected by the number and geographic distribution of Google searches for a drug key word. Google Trends monitors the number of search engine key words.  Countries and cities are ranked based on the relative number of searches.  If a country or city has more than their expected number of searches, their ranking in increased.   Patterns are summarized across time and broken down into geographic patterns.  The chart above is a portion of a screen shot of a Google Trends summary using the key word ecstasy.


Countries can be compared with each other and a top 10 ranking is produced.  The top ten country ranking for the ecstasy search term is reproduced here.

If my hypothesis is correct, the top drug abuse countries for ecstasy will be reflected in the Google Trends ranking--i.e. the top countries for ecstasy use Australia, Canada, the United States, Denmark and Brazil.

You can also set Google Trends to a specific country and then get a ranking of the top cities for the search term. I have inserted the top 10 rank list for ecstasy in the U.S. below.  If my hypothesis is correct, there is significant ecstasy use in Rancho Santa Margarita CA, Irvine, CA, Los Angeles, CA etc.


This approach is obviously an indirect type of sampling for drug abuse.  The high search rate for ecstasy in Rancho Santa Margarita, CA could by explained by a something like a large high school class being assigned a term paper on ecstasy.  But perhaps suppose this is the case--the assignment might reflect a problem with the drug in the city.

If Google Trends can supply country and city specific data on the relative rates of drug use/abuse it could be very helpful tool.  Most national survey studies do not get nearly enough data to provide information at the city level.  


A recent high ecstasy survey cited below grouped ecstasy use rates by U.S. regions and ranked the highest use in the South and West with lower rates in the Northeast and Midwest.  If Google Trends is a valid estimation tool, it would be able to provide more specific information that might be helpful to public health officials.

Google Trends has been proposed as a tool for tracking other types of illnesses (influenza) and pharmaceutical drug use (statins).  I’d be interested in any comments from readers who might be able to corroborate the Google Trends rankings for ecstasy.


Screen shots of Google Trends Courtesy of Yates Photography

Keyes KM, Martins SS, & Hasin DS (2008). Past 12-month and lifetime comorbidity and poly-drug use of ecstasy users among young adults in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Drug and alcohol dependence, 97 (1-2), 139-49 PMID: 18524499


Corley CD, Cook DJ, Mikler AR, & Singh KP (2010). Using web and social media for influenza surveillance. Advances in experimental medicine and biology, 680, 559-64 PMID: 20865540


Schuster NM, Rogers MA, & McMahon LF Jr (2010). Using search engine query data to track pharmaceutical utilization: a study of statins. The American journal of managed care, 16 (8) PMID: 20690788