Antipsychotics - The New Valium?

Antipsychotics, originally designed to control the hallucinations and delusions seen in schizophrenia, have been expanding their domain in recent years.

Nowadays, they're widely used in bipolar disorder, depression, and as a new paper reveals, increasingly in anxiety disorders as well.

The authors, Comer et al, looked at the NAMCS survey, which provides yearly data on the use of medications in visits to office-based doctors across the USA.

Back in 1996, just 10% of visits in which an anxiety disorder was diagnosed ended in a prescription for an antipsychotic. By 2007 it was over 20%. No atypical is licensed for use in anxiety disorders in the USA, so all of these prescriptions are off-label.

Not all of these prescriptions will have been for anxiety. They may have been prescribed to treat psychosis, in people who also happened to be anxious. However, the increase was accounted for by the rise in non-psychotic patients, and there was a rise in the rate of people with only anxiety disorders.

The increase was driven by the newer, "atypical" antipsychotics.

Whether the modern trend for prescribing antipsychotics for anxiety is a good or a bad thing, is not for us to say. The authors discuss various concerns ranging from the side effects (obesity, diabetes and more), to the fact that there have only been a few clinical trials of these drugs in anxiety.

But what's really disturbing about these results, to me, is how fast the change happened. Between 2000 and 2004, use doubled from 10% to 20% of anxiety visits. That's an astonishingly fast change in medical practice.

Why? It wasn't because that period saw the publication of a load of large, well-designed clinical trials demonstrating that these drugs work wonders in anxiety disorders. It didn't.

But as Comer et al put it:

An increasing number of office-based psychiatrists are specializing in pharmacotherapy to the exclusion of psychotherapy. Limitations in the availability of psychosocial interventions may place heavy clinical demands on the pharmacological dimensions of mental health care for anxiety disorder patients.

In other words, antipsychotics may have become popular because they're the treatment for people who can't afford anything better.

These data show that antipsychotics were over twice as likely to be prescribed to African American patients; the poor i.e. patients with public health insurance; and children under 18.

Comer JS, Mojtabai R, & Olfson M (2011). National Trends in the Antipsychotic Treatment of Psychiatric Outpatients With Anxiety Disorders. The American journal of psychiatry PMID: 21799067

Antipsychotics - The New Valium?

Antipsychotics, originally designed to control the hallucinations and delusions seen in schizophrenia, have been expanding their domain in recent years.

Nowadays, they're widely used in bipolar disorder, depression, and as a new paper reveals, increasingly in anxiety disorders as well.

The authors, Comer et al, looked at the NAMCS survey, which provides yearly data on the use of medications in visits to office-based doctors across the USA.

Back in 1996, just 10% of visits in which an anxiety disorder was diagnosed ended in a prescription for an antipsychotic. By 2007 it was over 20%. No atypical is licensed for use in anxiety disorders in the USA, so all of these prescriptions are off-label.

Not all of these prescriptions will have been for anxiety. They may have been prescribed to treat psychosis, in people who also happened to be anxious. However, the increase was accounted for by the rise in non-psychotic patients, and there was a rise in the rate of people with only anxiety disorders.

The increase was driven by the newer, "atypical" antipsychotics.

Whether the modern trend for prescribing antipsychotics for anxiety is a good or a bad thing, is not for us to say. The authors discuss various concerns ranging from the side effects (obesity, diabetes and more), to the fact that there have only been a few clinical trials of these drugs in anxiety.

But what's really disturbing about these results, to me, is how fast the change happened. Between 2000 and 2004, use doubled from 10% to 20% of anxiety visits. That's an astonishingly fast change in medical practice.

Why? It wasn't because that period saw the publication of a load of large, well-designed clinical trials demonstrating that these drugs work wonders in anxiety disorders. It didn't.

But as Comer et al put it:

An increasing number of office-based psychiatrists are specializing in pharmacotherapy to the exclusion of psychotherapy. Limitations in the availability of psychosocial interventions may place heavy clinical demands on the pharmacological dimensions of mental health care for anxiety disorder patients.

In other words, antipsychotics may have become popular because they're the treatment for people who can't afford anything better.

These data show that antipsychotics were over twice as likely to be prescribed to African American patients; the poor i.e. patients with public health insurance; and children under 18.

Comer JS, Mojtabai R, & Olfson M (2011). National Trends in the Antipsychotic Treatment of Psychiatric Outpatients With Anxiety Disorders. The American journal of psychiatry PMID: 21799067

Britain's Not Getting More Mentally Ill

There's a widespread belief that mental illness is getting more common, or that it has got more common in recent years.

A new study in the British Journal of Psychiatry says: no, it's not. They looked at the UK APMS mental health surveys, which were done in 1993, 2000 and 2007. Long-time readers will remember these.

The authors of the new paper analyzed the data by birth cohort, i.e. when you were born, and by age at the time of the survey. If mental illness were rising, you'd predict that people born more recently would have higher rates of mental illness at any given age.

The headline finding: there was no cohort effect, implying that rates of mental illness aren't changing. There was a strong age effect: in men, rates peak at about age 50; in women the data is rather messy but in general the rate is flat up to age 50 and then it falls off, like in men. But there's no evidence that those born recently are at higher risk.

The only exception was that men born after 1950 were at somewhat higher risk than those born earlier as shown by the "break" on the graph above. The effect for women was smaller. The most recent cohort, those born after 1985, were also above the curve but there was only one datapoint there, so it's hard to interpret.

We also get a rather cute graph showing how life changes with age:

As you get older, you get less irritable and, if you're a woman, you'll worry less. But sleep problems and, in men, fatigue, increase. Overall, 50 is the worst age in terms of total symptoms. After that, it gets better. Well, that's nice to know. Or not, depending on your age.

Overall, the authors say:

Our finding of subsequently stable rates contradicts popular media stories of a relentlessly rising tide of mental illness, at least for men. Stable prevalence in the male population, together with peaking of the prevalence of common mental disorder at about age 50 years, indicates that a large increase in projected rates of poor mental health is unlikely in the male population in the near future....

Trends in women are less clearly identified, with considerable increases in the prevalence of sleep problems, but no clear increase or even some decrease in other measures. Further research is needed to relate these age and cohort differences to drivers of mental health such as employment status and family composition.

Caution's warranted, though, because the APMS data were based on self-reported symptoms of mental illness assessed by lay interviewers. As I've argued before, self-report is problematic, but this is true of almost all of these kinds of studies.

More unusual is that this study didn't attempt to assign formal diagnoses, it just looked at total symptoms on the CIS Scale; a total of 12 or more was considered to indicate "probable disorder".

Purists would say that this is a weakness and that you ought to be making full DSM-IV diagnoses, but honestly, it's got its own problems, and I think this is no worse.

Finally, this study only looked at "common mental disorders" i.e. depression and various kinds of anxiety symptoms. Things like schizophrenia and bipolar disorder weren't included, but from what I remember they're not rising either.

Spiers N, Bebbington P, McManus S, Brugha TS, Jenkins R, & Meltzer H (2011). Age and birth cohort differences in the prevalence of common mental disorder in England: National Psychiatric Morbidity Surveys 1993-2007. The British journal of psychiatry : the journal of mental science, 198, 479-84 PMID: 21628710

Britain's Not Getting More Mentally Ill

There's a widespread belief that mental illness is getting more common, or that it has got more common in recent years.

A new study in the British Journal of Psychiatry says: no, it's not. They looked at the UK APMS mental health surveys, which were done in 1993, 2000 and 2007. Long-time readers will remember these.

The authors of the new paper analyzed the data by birth cohort, i.e. when you were born, and by age at the time of the survey. If mental illness were rising, you'd predict that people born more recently would have higher rates of mental illness at any given age.

The headline finding: there was no cohort effect, implying that rates of mental illness aren't changing. There was a strong age effect: in men, rates peak at about age 50; in women the data is rather messy but in general the rate is flat up to age 50 and then it falls off, like in men. But there's no evidence that those born recently are at higher risk.

The only exception was that men born after 1950 were at somewhat higher risk than those born earlier as shown by the "break" on the graph above. The effect for women was smaller. The most recent cohort, those born after 1985, were also above the curve but there was only one datapoint there, so it's hard to interpret.

We also get a rather cute graph showing how life changes with age:

As you get older, you get less irritable and, if you're a woman, you'll worry less. But sleep problems and, in men, fatigue, increase. Overall, 50 is the worst age in terms of total symptoms. After that, it gets better. Well, that's nice to know. Or not, depending on your age.

Overall, the authors say:

Our finding of subsequently stable rates contradicts popular media stories of a relentlessly rising tide of mental illness, at least for men. Stable prevalence in the male population, together with peaking of the prevalence of common mental disorder at about age 50 years, indicates that a large increase in projected rates of poor mental health is unlikely in the male population in the near future....

Trends in women are less clearly identified, with considerable increases in the prevalence of sleep problems, but no clear increase or even some decrease in other measures. Further research is needed to relate these age and cohort differences to drivers of mental health such as employment status and family composition.

Caution's warranted, though, because the APMS data were based on self-reported symptoms of mental illness assessed by lay interviewers. As I've argued before, self-report is problematic, but this is true of almost all of these kinds of studies.

More unusual is that this study didn't attempt to assign formal diagnoses, it just looked at total symptoms on the CIS Scale; a total of 12 or more was considered to indicate "probable disorder".

Purists would say that this is a weakness and that you ought to be making full DSM-IV diagnoses, but honestly, it's got its own problems, and I think this is no worse.

Finally, this study only looked at "common mental disorders" i.e. depression and various kinds of anxiety symptoms. Things like schizophrenia and bipolar disorder weren't included, but from what I remember they're not rising either.

Spiers N, Bebbington P, McManus S, Brugha TS, Jenkins R, & Meltzer H (2011). Age and birth cohort differences in the prevalence of common mental disorder in England: National Psychiatric Morbidity Surveys 1993-2007. The British journal of psychiatry : the journal of mental science, 198, 479-84 PMID: 21628710

The Media and Numbers: "It's Complicated".

According to everyone in the British media, 25% of young men are worried about the amount of porn they watch online and men watch an average of 2 hours per week.


Says who? The BBC apparently "teamed up with doctors from the Portman Clinic", a London specialist mental health hospital, to do the study. The actual survey was done online by a certain market research company, which I am not going to name, because they've already got free advertising in every newspaper.

What does this tell us about pornography? Nothing. Dr Petra Boynton explains why in a long and excellent deconstruction. In order to properly interpret these results, we'd need to know lots of details about the study design, which we weren't told. Of course this doesn't stop us from going ahead and interpreting them improperly. 25%! 2 hours. Ooh, that's a lot. Is it? This online porn, eh. Tut tut.

So, sure, 25% could be The True Proportion Of Men Who Worry About Online Porn. Or it might not be. Or the whole question might be so fraught as to be meaningless. The point is, we don't know, we cannot possibly know from the limited amount of information we were given, and we weren't meant to know, because numbers like these are essentially pornographic themselves - they're just for show.

Numbers very rarely make a good news story. When you look into it, the vast majority of them only make sense to people who know all of the background, and by definition, if you have to spend a few pages explaining the background, it's not a good news story. A good news story is one which anyone who can read can immediately understand, and get angry/scared/amused by.

Yet journalists also love numbers because everyone knows, on some level, that numbers matter. The very fact that a story has numbers in it, makes that story better. Indeed, very often, there would be no story without them. Someone doing a survey and finding some numbers can make a news story out of nothing. "Modern online pornography worries some people and is a complicated issue" isn't news; "25% of men..." is news.

So what we end up with is lots of news stories which have numbers in them, but which don't, actually, tell us anything about the world, which is what numbers are supposed to do. Numbers to most of the media are like an attractive trophy wife. They like to be seen with them in public. But deep down they're not all that attached.

The Media and Numbers: "It's Complicated".

According to everyone in the British media, 25% of young men are worried about the amount of porn they watch online and men watch an average of 2 hours per week.


Says who? The BBC apparently "teamed up with doctors from the Portman Clinic", a London specialist mental health hospital, to do the study. The actual survey was done online by a certain market research company, which I am not going to name, because they've already got free advertising in every newspaper.

What does this tell us about pornography? Nothing. Dr Petra Boynton explains why in a long and excellent deconstruction. In order to properly interpret these results, we'd need to know lots of details about the study design, which we weren't told. Of course this doesn't stop us from going ahead and interpreting them improperly. 25%! 2 hours. Ooh, that's a lot. Is it? This online porn, eh. Tut tut.

So, sure, 25% could be The True Proportion Of Men Who Worry About Online Porn. Or it might not be. Or the whole question might be so fraught as to be meaningless. The point is, we don't know, we cannot possibly know from the limited amount of information we were given, and we weren't meant to know, because numbers like these are essentially pornographic themselves - they're just for show.

Numbers very rarely make a good news story. When you look into it, the vast majority of them only make sense to people who know all of the background, and by definition, if you have to spend a few pages explaining the background, it's not a good news story. A good news story is one which anyone who can read can immediately understand, and get angry/scared/amused by.

Yet journalists also love numbers because everyone knows, on some level, that numbers matter. The very fact that a story has numbers in it, makes that story better. Indeed, very often, there would be no story without them. Someone doing a survey and finding some numbers can make a news story out of nothing. "Modern online pornography worries some people and is a complicated issue" isn't news; "25% of men..." is news.

So what we end up with is lots of news stories which have numbers in them, but which don't, actually, tell us anything about the world, which is what numbers are supposed to do. Numbers to most of the media are like an attractive trophy wife. They like to be seen with them in public. But deep down they're not all that attached.

Who Gets Autism?

According to a major new report from Australia, social and family factors associated with autism are associated with a lower risk of intellectual disability - and vice versa. But why?


The paper is from Leonard et al and it's published in PLoS ONE, so it's open access if you want to take a peek. The authors used a database system in the state of Western Australia which allowed them to find out what happened to all of the babies born between 1984 and 1999 who were still alive as of 2005. There were 400,000 of them.

The records included information on children diagnosed with either an autism spectrum disorder (ASD), intellectual disability aka mental retardation (ID), or both. They decided to only look at singleton births i.e. not twins or triplets.

In total, 1,179 of the kids had a diagnosis of ASD. That's 0.3% or about 1 in 350, much lower than more recent estimates, but these more recent studies used very different methods. Just over 60% of these also had ID, which corresponds well to previous estimates.

There were about 4,500 cases of ID without ASD in the sample, a rate of just over 1%; the great majority of these (90%) had mild-to-moderate ID. They excluded an additional 800 kids with ID associated with a "known biomedical condition" like Down's Syndrome.

So what did they find? Well, a whole bunch, and it's all interesting. Bullet point time.

• Between 1984 to 1999, rates of ID without ASD fell and rates of ASD rose, although there was a curious sudden fall in the rates of ASD without ID just before the end of the study. In 1984, "mild-moderate ID" without autism was by far the most common diagnosis, with 10 times the rate of anything else. By 1999, it was exactly level with ASD+ID, and ASD without ID was close behind. Here's the graph; note the logarithmic scale:
  

• Boys had a much higher rate of autism than girls, especially when it came to autism without ID. This has been known for a long time.
  
• Second- and third- born children had a higher rate of ID, and a lower rate of ASD, compared to firstborns.
  
• Older mothers had children with more autism - both autism with and without ID, but the trend was bigger for autism with ID. But they had less ID. For fathers, the trend was the same and the effect was even bigger. Older parents are more likely to have autistic children but less likely to have kids with ID.
  

• Richer parents had a strongly reduced liklihood of ID. Rates of ASD with ID were completely flat, but rates of ASD without ID were raised in the richer groups, though it was not linear (the middle groups were highest. - and effect was small.)
  

To summarize: the risk factors for autism were in most cases the exact opposite of those for ID. The more “advantaged” parental traits like being richer, and being older, were associated with more autism, but less ID. And as time went on, diagnosed rates of ASD rose while rates of ID fell (though only slightly for severe ID).

Why is this? The simplest explanation would be that there are many children out there for whom it's not easy to determine whether they have ASD or ID. Which diagnosis any such child gets would then depend on cultural and sociological factors - broadly speaking, whether clinicians are willing to give (and parents willing to accept) one or the other.

The authors note that autism has become a less stigmatized condition in Australia recently. Nowdays, they say, a diagnosis of ASD may be preferable to a diagnosis of "just" "plain old" ID, in terms of access to financial support amongst other things. However, it is also harder to get a diagnosis of ASD, as it requires you to go through a more extensive and complex series of assessments.

Clearly some parents will be better able to achieve this than others. In other countries, like South Korea, autism is still one of the most stigmatized conditions of childhood, and we'd expect that there, the trend would be reversed.

The authors also note the theory that autism rates are rising because of some kind of environmental toxin causing brain damage, like mercury or vaccinations. However, as they point out, this would probably cause more of all neurological/behavioural disorders, including ID; at the least it wouldn't reduce the rates of any.

These data clearly show that rates of ID fell almost exactly in parallel with rates of ASD rising, in Western Australia over this 15 year period. What will the vaccine-vexed folks over at Age of Autism make of this study, one wonders?

Leonard H, Glasson E, Nassar N, Whitehouse A, Bebbington A, Bourke J, Jacoby P, Dixon G, Malacova E, Bower C, & Stanley F (2011). Autism and intellectual disability are differentially related to sociodemographic background at birth. PloS one, 6 (3) PMID: 21479223

Who Gets Autism?

According to a major new report from Australia, social and family factors associated with autism are associated with a lower risk of intellectual disability - and vice versa. But why?


The paper is from Leonard et al and it's published in PLoS ONE, so it's open access if you want to take a peek. The authors used a database system in the state of Western Australia which allowed them to find out what happened to all of the babies born between 1984 and 1999 who were still alive as of 2005. There were 400,000 of them.

The records included information on children diagnosed with either an autism spectrum disorder (ASD), intellectual disability aka mental retardation (ID), or both. They decided to only look at singleton births i.e. not twins or triplets.

In total, 1,179 of the kids had a diagnosis of ASD. That's 0.3% or about 1 in 350, much lower than more recent estimates, but these more recent studies used very different methods. Just over 60% of these also had ID, which corresponds well to previous estimates.

There were about 4,500 cases of ID without ASD in the sample, a rate of just over 1%; the great majority of these (90%) had mild-to-moderate ID. They excluded an additional 800 kids with ID associated with a "known biomedical condition" like Down's Syndrome.

So what did they find? Well, a whole bunch, and it's all interesting. Bullet point time.

• Between 1984 to 1999, rates of ID without ASD fell and rates of ASD rose, although there was a curious sudden fall in the rates of ASD without ID just before the end of the study. In 1984, "mild-moderate ID" without autism was by far the most common diagnosis, with 10 times the rate of anything else. By 1999, it was exactly level with ASD+ID, and ASD without ID was close behind. Here's the graph; note the logarithmic scale:
  

• Boys had a much higher rate of autism than girls, especially when it came to autism without ID. This has been known for a long time.
  
• Second- and third- born children had a higher rate of ID, and a lower rate of ASD, compared to firstborns.
  
• Older mothers had children with more autism - both autism with and without ID, but the trend was bigger for autism with ID. But they had less ID. For fathers, the trend was the same and the effect was even bigger. Older parents are more likely to have autistic children but less likely to have kids with ID.
  

• Richer parents had a strongly reduced liklihood of ID. Rates of ASD with ID were completely flat, but rates of ASD without ID were raised in the richer groups, though it was not linear (the middle groups were highest. - and effect was small.)
  

To summarize: the risk factors for autism were in most cases the exact opposite of those for ID. The more “advantaged” parental traits like being richer, and being older, were associated with more autism, but less ID. And as time went on, diagnosed rates of ASD rose while rates of ID fell (though only slightly for severe ID).

Why is this? The simplest explanation would be that there are many children out there for whom it's not easy to determine whether they have ASD or ID. Which diagnosis any such child gets would then depend on cultural and sociological factors - broadly speaking, whether clinicians are willing to give (and parents willing to accept) one or the other.

The authors note that autism has become a less stigmatized condition in Australia recently. Nowdays, they say, a diagnosis of ASD may be preferable to a diagnosis of "just" "plain old" ID, in terms of access to financial support amongst other things. However, it is also harder to get a diagnosis of ASD, as it requires you to go through a more extensive and complex series of assessments.

Clearly some parents will be better able to achieve this than others. In other countries, like South Korea, autism is still one of the most stigmatized conditions of childhood, and we'd expect that there, the trend would be reversed.

The authors also note the theory that autism rates are rising because of some kind of environmental toxin causing brain damage, like mercury or vaccinations. However, as they point out, this would probably cause more of all neurological/behavioural disorders, including ID; at the least it wouldn't reduce the rates of any.

These data clearly show that rates of ID fell almost exactly in parallel with rates of ASD rising, in Western Australia over this 15 year period. What will the vaccine-vexed folks over at Age of Autism make of this study, one wonders?

Leonard H, Glasson E, Nassar N, Whitehouse A, Bebbington A, Bourke J, Jacoby P, Dixon G, Malacova E, Bower C, & Stanley F (2011). Autism and intellectual disability are differentially related to sociodemographic background at birth. PloS one, 6 (3) PMID: 21479223

BBC: Something Happened, For Some Reason

According to the BBC, the British recession and spending cuts are making us all depressed.


They found that between 2006 and 2010, prescriptions for SSRI antidepressants rose by 43%. They attribute this to a rise in the rates of depression caused by the financial crisis. OK there are a few caveats, but this is the clear message of an article titled Money woes 'linked to rise in depression'. To get this data they used the Freedom of Information Act.

What they don't do is to provide any of the raw data. So we just have to take their word for it. Maybe someone ought to use the Freedom of Information Act to make them tell us? This is important, because while I'll take the BBC's word about the SSRI rise of 43%, they also say that rates of other antidepressants rose - but they don't say which ones, by how much, or anything else. They don't say how many fell, or stayed flat.

Given which it's impossible to know what to make of this. Here are some alternative explanations:

• This just represents the continuation of the well-known trend, seen in the USA and Europe as well as the UK, for increasing antidepressant use. This is my personal best guess and Ben Goldacre points out that rates rose 36% during the boom years of 2000-2005.
  
• Depression has not got more common, it's just that it's more likely to be treated. This overlaps with the first theory. Support for this comes from the fact that suicide rates haven't risen - at least not by anywhere near 40%.
  
• Mental illness is no more likely to be treated, but it's more likely to be treated with antidepressants, as opposed to other drugs. There was, and is, a move to get people off drugs like benzodiazepines, and onto antidepressants. However I suspect this process is largely complete now.
• Total antidepressant use isn't rising but SSRI use is because doctors increasingly prescribe SSRIs over opposed to other drugs. This was another Ben Goldacre suggestion and it is surely a factor although again, I suspect that this process was largely complete by 2007.
  
• People are more likely to be taking multiple different antidepressants, which would manifest as a rise in prescriptions, even if the total number of users stayed constant. Add-on treatment with mirtazapine and others is becoming more popular.
• People are staying on antidepressants for longer meaning more prescriptions. This might not even mean that they're staying ill for longer, it might just mean that doctors are getting better at convincing people to keep taking them by e.g. prescribing drugs with milder side effects, or by referring people for psychotherapy which could increase use by keeping people "in the system" and taking their medication. This is very likely. I previously blogged about a paper showing that in 1993 to 2005, antidepressant prescriptions rose although rates of depression fell, because of a small rise in the number of people taking them for very long periods.
  
• Mental illness rates are rising, but it's not depression: it's anxiety, or something else. Entirely plausible since we know that many people taking antidepressants, in the USA, have no diagnosable depression and even no diagnosable psychiatric disorder at all.
• People are relying on the NHS to prescribe them drugs, as opposed to private doctors, because they can't afford to go private. Private medicine in the UK is only a small sector so this is unlikely to account for much but it's the kind of thing you need to think about.
• Rates of depression have risen, but it's nothing to do with the economy, it's something else which happened between 2007 and 2010: the Premiership of Gordon Brown? The assassination of Benazir Bhutto? The discovery of a 2,100 year old Japanese melon?
  

Personally, my money's on the melon.

BBC: Something Happened, For Some Reason

According to the BBC, the British recession and spending cuts are making us all depressed.


They found that between 2006 and 2010, prescriptions for SSRI antidepressants rose by 43%. They attribute this to a rise in the rates of depression caused by the financial crisis. OK there are a few caveats, but this is the clear message of an article titled Money woes 'linked to rise in depression'. To get this data they used the Freedom of Information Act.

What they don't do is to provide any of the raw data. So we just have to take their word for it. Maybe someone ought to use the Freedom of Information Act to make them tell us? This is important, because while I'll take the BBC's word about the SSRI rise of 43%, they also say that rates of other antidepressants rose - but they don't say which ones, by how much, or anything else. They don't say how many fell, or stayed flat.

Given which it's impossible to know what to make of this. Here are some alternative explanations:

• This just represents the continuation of the well-known trend, seen in the USA and Europe as well as the UK, for increasing antidepressant use. This is my personal best guess and Ben Goldacre points out that rates rose 36% during the boom years of 2000-2005.
  
• Depression has not got more common, it's just that it's more likely to be treated. This overlaps with the first theory. Support for this comes from the fact that suicide rates haven't risen - at least not by anywhere near 40%.
  
• Mental illness is no more likely to be treated, but it's more likely to be treated with antidepressants, as opposed to other drugs. There was, and is, a move to get people off drugs like benzodiazepines, and onto antidepressants. However I suspect this process is largely complete now.
• Total antidepressant use isn't rising but SSRI use is because doctors increasingly prescribe SSRIs over opposed to other drugs. This was another Ben Goldacre suggestion and it is surely a factor although again, I suspect that this process was largely complete by 2007.
  
• People are more likely to be taking multiple different antidepressants, which would manifest as a rise in prescriptions, even if the total number of users stayed constant. Add-on treatment with mirtazapine and others is becoming more popular.
• People are staying on antidepressants for longer meaning more prescriptions. This might not even mean that they're staying ill for longer, it might just mean that doctors are getting better at convincing people to keep taking them by e.g. prescribing drugs with milder side effects, or by referring people for psychotherapy which could increase use by keeping people "in the system" and taking their medication. This is very likely. I previously blogged about a paper showing that in 1993 to 2005, antidepressant prescriptions rose although rates of depression fell, because of a small rise in the number of people taking them for very long periods.
  
• Mental illness rates are rising, but it's not depression: it's anxiety, or something else. Entirely plausible since we know that many people taking antidepressants, in the USA, have no diagnosable depression and even no diagnosable psychiatric disorder at all.
• People are relying on the NHS to prescribe them drugs, as opposed to private doctors, because they can't afford to go private. Private medicine in the UK is only a small sector so this is unlikely to account for much but it's the kind of thing you need to think about.
• Rates of depression have risen, but it's nothing to do with the economy, it's something else which happened between 2007 and 2010: the Premiership of Gordon Brown? The assassination of Benazir Bhutto? The discovery of a 2,100 year old Japanese melon?
  

Personally, my money's on the melon.

Depressed or Bereaved? (Part 2)

In Part 1, I discussed a paper by Jerome Wakefield examining the issue of where to draw the line between normal grief and clinical depression.


The line moved in the American Psychiatric Association's DSM diagnostic system when the previous DSM-III edition was replaced by the current DSM-IV. Specifically, the "bereavement exclusion" was made narrower.

The bereavement exclusion says that you shouldn't diagnose depression in someone whose "depressive" symptoms are a result of grief - unless they're particularly severe or prolonged when you should. DSM-IV lowered the bar for "severe" and "prolonged", thus making grief more likely to be classed as depression. Wakefield argued that the change made things worse.

But DSM-V is on its way soon. The draft was put up online in 2010, and it turns out that depression is to have no bereavement exclusion at all. Grief can be diagnosed as depression in exactly the same way as depressive symptoms which come out of the blue.

The draft itself offered just one sentence by way of justification for this. However, big cheese psychiatrist Kenneth S. Kendler recently posted a brief note defending the decision. Wakefield has just published a rather longer paper in response.

Wakefield starts off with a bit of scholarly kung-fu. Kendler says that the precursors to the modern DSM, the 1972 Feighner and 1975 RDC criteria, didn't have a bereavement clause for depression either. But they did - albeit not in the criteria themselves, but in the accompanying how-to manuals; the criteria themselves weren't meant to be self-contained, unlike the DSM. Ouch! And so on.

Kendler's sole substantive argument against the exclusion is that it is "not logically defensible" to exclude depression induced by bereavement, if we don't have a similar provision for depression following other severe loss or traumatic events, like becoming unemployed or being diagnosed with cancer.

Wakefield responds that, yes, he has long made exactly that point, and that in his view we should take the context into account, rather than just looking at the symptoms, in grief and many other cases. However, as he points out, it is better to do this for one class of events (bereavement), than for none at all. He quotes Emerson's famous warning that "A foolish consistency is the hobgoblin of little minds". It's better to be partly right, than consistently wrong.

Personally, I'm sympathetic to Wakefield's argument that the bereavement exclusion should be extended to cover non-bereavement events, but I'm also concerned that this could lead to underdiagnosis if it relied too much on self-report.

The problem is that depression usually feels like it's been caused by something that's happened, but this doesn't mean it was; one of the most insidious features of depression is that it makes things seem much worse than they actually are, so it seems like the depression is an appropriate reaction to real difficulties, when to anyone else, or to yourself looking back on it after recovery, it was completely out of proportion. So it's a tricky one.

Anyway, back to bereavement; Kendler curiously ends up by agreeing that there ought to be a bereavement clause - in practice. He says that just because someone meets criteria for depression does not mean we have to treat them:

...diagnosis in psychiatry as in the rest of medicine provides the possibility but by no means the requirement that treatment be initiated ... a good psychiatrist, on seeing an individual with major depression after bereavement, would start with a diagnostic evaluation.

If the criteria for major depression are met, then he or she would then have the opportunity to assess whether a conservative watch and wait approach is indicated or whether, because of suicidal ideation, major role impairment or a substantial clinical worsening the benefits of treatment outweigh the limitations.

The final sentence is lifted almost word for word from the current bereavement clause, so this seems to be an admission that the exclusion is, after all, valid, as part of the clinical decision-making process, rather than the diagnostic system.

OK, but as Wakefield points out, why misdiagnose people if you can help it? It seems to be tempting fate. Kendler says that a "good psychiatrist" wouldn't treat normal, uncomplicated bereavement as depression. But what about the bad ones? Why on earth would you deliberately make your system such that good psychiatrists would ignore it?

More importantly, scrapping the bereavement criterion would render the whole concept of Major Depression meaningless. Almost everyone suffers grief at some point in their lives. Already, 40% of people meet criteria for depression by age 32, and that's with a bereavement exclusion.

Scrap it and, I don't know, 80% will meet criteria by that age - so the criteria will be useless as a guide to identifying the people who actually have depression as opposed to the ones who have just suffered grief. We're already not far off that point, but this would really take the biscuit.

Wakefield JC (2011) Should Uncomplicated Bereavement-Related Depression Be Reclassified as a Disorder in the DSM-5? The Journal of nervous and mental disease, 199 (3), 203-8 PMID: 21346493

Depressed or Bereaved? (Part 2)

In Part 1, I discussed a paper by Jerome Wakefield examining the issue of where to draw the line between normal grief and clinical depression.


The line moved in the American Psychiatric Association's DSM diagnostic system when the previous DSM-III edition was replaced by the current DSM-IV. Specifically, the "bereavement exclusion" was made narrower.

The bereavement exclusion says that you shouldn't diagnose depression in someone whose "depressive" symptoms are a result of grief - unless they're particularly severe or prolonged when you should. DSM-IV lowered the bar for "severe" and "prolonged", thus making grief more likely to be classed as depression. Wakefield argued that the change made things worse.

But DSM-V is on its way soon. The draft was put up online in 2010, and it turns out that depression is to have no bereavement exclusion at all. Grief can be diagnosed as depression in exactly the same way as depressive symptoms which come out of the blue.

The draft itself offered just one sentence by way of justification for this. However, big cheese psychiatrist Kenneth S. Kendler recently posted a brief note defending the decision. Wakefield has just published a rather longer paper in response.

Wakefield starts off with a bit of scholarly kung-fu. Kendler says that the precursors to the modern DSM, the 1972 Feighner and 1975 RDC criteria, didn't have a bereavement clause for depression either. But they did - albeit not in the criteria themselves, but in the accompanying how-to manuals; the criteria themselves weren't meant to be self-contained, unlike the DSM. Ouch! And so on.

Kendler's sole substantive argument against the exclusion is that it is "not logically defensible" to exclude depression induced by bereavement, if we don't have a similar provision for depression following other severe loss or traumatic events, like becoming unemployed or being diagnosed with cancer.

Wakefield responds that, yes, he has long made exactly that point, and that in his view we should take the context into account, rather than just looking at the symptoms, in grief and many other cases. However, as he points out, it is better to do this for one class of events (bereavement), than for none at all. He quotes Emerson's famous warning that "A foolish consistency is the hobgoblin of little minds". It's better to be partly right, than consistently wrong.

Personally, I'm sympathetic to Wakefield's argument that the bereavement exclusion should be extended to cover non-bereavement events, but I'm also concerned that this could lead to underdiagnosis if it relied too much on self-report.

The problem is that depression usually feels like it's been caused by something that's happened, but this doesn't mean it was; one of the most insidious features of depression is that it makes things seem much worse than they actually are, so it seems like the depression is an appropriate reaction to real difficulties, when to anyone else, or to yourself looking back on it after recovery, it was completely out of proportion. So it's a tricky one.

Anyway, back to bereavement; Kendler curiously ends up by agreeing that there ought to be a bereavement clause - in practice. He says that just because someone meets criteria for depression does not mean we have to treat them:

...diagnosis in psychiatry as in the rest of medicine provides the possibility but by no means the requirement that treatment be initiated ... a good psychiatrist, on seeing an individual with major depression after bereavement, would start with a diagnostic evaluation.

If the criteria for major depression are met, then he or she would then have the opportunity to assess whether a conservative watch and wait approach is indicated or whether, because of suicidal ideation, major role impairment or a substantial clinical worsening the benefits of treatment outweigh the limitations.

The final sentence is lifted almost word for word from the current bereavement clause, so this seems to be an admission that the exclusion is, after all, valid, as part of the clinical decision-making process, rather than the diagnostic system.

OK, but as Wakefield points out, why misdiagnose people if you can help it? It seems to be tempting fate. Kendler says that a "good psychiatrist" wouldn't treat normal, uncomplicated bereavement as depression. But what about the bad ones? Why on earth would you deliberately make your system such that good psychiatrists would ignore it?

More importantly, scrapping the bereavement criterion would render the whole concept of Major Depression meaningless. Almost everyone suffers grief at some point in their lives. Already, 40% of people meet criteria for depression by age 32, and that's with a bereavement exclusion.

Scrap it and, I don't know, 80% will meet criteria by that age - so the criteria will be useless as a guide to identifying the people who actually have depression as opposed to the ones who have just suffered grief. We're already not far off that point, but this would really take the biscuit.

Wakefield JC (2011) Should Uncomplicated Bereavement-Related Depression Be Reclassified as a Disorder in the DSM-5? The Journal of nervous and mental disease, 199 (3), 203-8 PMID: 21346493

Depressed Or Bereaved? (Part 1)

Part 2 is now out here.

My cat died on Tuesday. She may have been a manipulative psychopath, but she was a likeable one. She was 18.On that note, here's a paper about bereavement.

It's been recognized since forever that clinical depression is similar, in many ways, to the experience of grief. Freud wrote about it in 1917, and it was an ancient idea even then. So psychiatrists have long thought that symptoms, which would indicate depression in someone who wasn't bereaved, can be quite normal and healthy as a response to the loss of a loved one. You can't go around diagnosing depression purely on the basis of the symptoms, out of context.

On the other hand, sometimes grief does become pathological - it triggers depression. So equally, you can't just decide to never diagnose depression in the bereaved. How do you tell the difference between "normal" and "complicated" grief, though? This is where opinions differ.

Jerome Wakefield (of Loss of Sadness fame) and colleagues compared two methods. They looked at the NCS survey of the American population, and took everyone who'd suffered a possible depressive episode following bereavement. There were 156 of these.

They then divided these cases into "complicated" grief (depression) vs "uncomplicated" grief, first using the older DSM-III-R criteria, and then with the current DSM-IV ones. Both have a bereavement exclusion for the depression criteria - don't diagnose depression if it's bereavement - but they also have criteria for complicated grief which is depression, exclusions to the exclusion.

The systems differ in two major ways: the older criteria were ambiguous but at the time, they were generally interpreted to mean that you needed to have two features out of a possible five; prolonged duration was one of the list and anything over 12 months was considered "prolonged". In DSM-IV, however, you only need one criterion, and anything over 2 months is prolonged.

What happened? DSM-IV classified many more cases as complicated than the older criteria - 80% vs 45%. That's no surprise there because the criteria are obviously a lot broader. But which was better? In order to evaluate them, they compared the "complicated" vs "normal" episodes on six hallmarks of clinical depression - melancholic features, seeking medical treatment, etc.

They found that "complicated" cases were more severe under both criteria but the difference was much more clear cut using DSM-III-R.

Wakefield et al are not saying that the DSM-III-R criteria were perfect. However, it was better at identifying the severe cases than the DSM-IV, which is worrying because DSM-IV was meant to be an improvement on the old system.

Hang on though. DSM-V is coming soon. Are they planning to put things back to how they were, or invent an even better system? No. They're planning to, er, get rid of the bereavement criteria altogether and treat bereavement just like non-bereavement. Seriously. In other words they are planning to diagnose depression purely on the basis of the symptoms, out of context.

Which is so crazy that Wakefield has written another paper all about it (he's been busy recently), which I'm going to cover in an upcoming post. So stay tuned.

Wakefield JC, Schmitz MF, & Baer JC (2011). Did narrowing the major depression bereavement exclusion from DSM-III-R to DSM-IV increase validity? The Journal of nervous and mental disease, 199 (2), 66-73 PMID: 21278534

Depressed Or Bereaved? (Part 1)

Part 2 is now out here.

My cat died on Tuesday. She may have been a manipulative psychopath, but she was a likeable one. She was 18.On that note, here's a paper about bereavement.

It's been recognized since forever that clinical depression is similar, in many ways, to the experience of grief. Freud wrote about it in 1917, and it was an ancient idea even then. So psychiatrists have long thought that symptoms, which would indicate depression in someone who wasn't bereaved, can be quite normal and healthy as a response to the loss of a loved one. You can't go around diagnosing depression purely on the basis of the symptoms, out of context.

On the other hand, sometimes grief does become pathological - it triggers depression. So equally, you can't just decide to never diagnose depression in the bereaved. How do you tell the difference between "normal" and "complicated" grief, though? This is where opinions differ.

Jerome Wakefield (of Loss of Sadness fame) and colleagues compared two methods. They looked at the NCS survey of the American population, and took everyone who'd suffered a possible depressive episode following bereavement. There were 156 of these.

They then divided these cases into "complicated" grief (depression) vs "uncomplicated" grief, first using the older DSM-III-R criteria, and then with the current DSM-IV ones. Both have a bereavement exclusion for the depression criteria - don't diagnose depression if it's bereavement - but they also have criteria for complicated grief which is depression, exclusions to the exclusion.

The systems differ in two major ways: the older criteria were ambiguous but at the time, they were generally interpreted to mean that you needed to have two features out of a possible five; prolonged duration was one of the list and anything over 12 months was considered "prolonged". In DSM-IV, however, you only need one criterion, and anything over 2 months is prolonged.

What happened? DSM-IV classified many more cases as complicated than the older criteria - 80% vs 45%. That's no surprise there because the criteria are obviously a lot broader. But which was better? In order to evaluate them, they compared the "complicated" vs "normal" episodes on six hallmarks of clinical depression - melancholic features, seeking medical treatment, etc.

They found that "complicated" cases were more severe under both criteria but the difference was much more clear cut using DSM-III-R.

Wakefield et al are not saying that the DSM-III-R criteria were perfect. However, it was better at identifying the severe cases than the DSM-IV, which is worrying because DSM-IV was meant to be an improvement on the old system.

Hang on though. DSM-V is coming soon. Are they planning to put things back to how they were, or invent an even better system? No. They're planning to, er, get rid of the bereavement criteria altogether and treat bereavement just like non-bereavement. Seriously. In other words they are planning to diagnose depression purely on the basis of the symptoms, out of context.

Which is so crazy that Wakefield has written another paper all about it (he's been busy recently), which I'm going to cover in an upcoming post. So stay tuned.

Wakefield JC, Schmitz MF, & Baer JC (2011). Did narrowing the major depression bereavement exclusion from DSM-III-R to DSM-IV increase validity? The Journal of nervous and mental disease, 199 (2), 66-73 PMID: 21278534

Earthquakes And Antipsychotics

According to a clever little paper just out from Italy, prescriptions for antipsychotic drugs skyrocketed in the months following a major earthquake. But there are some surprising details.


On 6th April 2009, an earthquake hit L'Aquila, a medium-sized city in central Italy. Out of about 100,000 people living in the L'Aquila area, over 600 died and over 60,000 were displaced: a major disaster for the local people.

Rossi et al from the University of L'Aquila looked at medication prescription in the 6 months following the earthquake and compared them to the previous 6 months. This is not an ideal method, it would have been better to compare L'Aquila to a neighboring district unaffected by the earthquake to control for nationwide changes; but over a few months we wouldn't expect large changes.

Anyway - they found that the number of "new" antidepressant prescriptions rose by 37%. However, prescriptions of non-psychiatric drugs like statins and anti-diabetic medications also rose by up to 50%. This is a bit sketchy but it suggests that the increase in antidepressants might just reflect increased post-disaster medical care for everyone in the area.

There was one big finding though: rates of antipsychotic prescribing more than doubled to 833 prescriptions, a 130% increase.

Does this mean that more people experienced psychosis in the aftermath of the trauma? That's one possibility - but a closer look reveals that the "extra" antipsychotics were given almost entirely to elderly people: just 0.3% of people under 45 got a new antipsychotic prescription but 1% of those 65-75 did and in those 75+ it reached 2.7% in men and a dizzying 3.8% of women.

Unfortunately Rossi et al couldn't tell what the drugs were being prescribed for, because their dataset was based on drug sales. However, it's known that schizophrenia and other forms of psychosis generally strike younger people, not the elderly. However, antipsychotics are often used as sedatives in elderly people especially those suffering dementia.

As the authors point out, this is a controversial practice:

A further observation concerns the appropriateness of prescribed drugs to a potentially vulnerable group such as the elderly. The majority of prescriptions were made by primary care physicians. This may partly explain the somewhat unusual increase in prescriptions for antipsychotic medications. It has been reported that antipsychotic medications are disproportionately prescribed to elderly subjects and need further regulation. This is particularly true in emergency and disaster situations.

In the UK a 2009 government report warned that antipsychotics were being used too freely in people with dementia, at the risk of causing significant harm, and said that they should be reserved for the most serious cases only. This study raises concerns that already questionable prescribing might get even worse following disasters.

Rossi A, Maggio R, Riccardi I, Allegrini F, & Stratta P (2011). A quantitative analysis of antidepressant and antipsychotic prescriptions following an earthquake in Italy. Journal of traumatic stress, 24 (1), 129-32 PMID: 21351173

Earthquakes And Antipsychotics

According to a clever little paper just out from Italy, prescriptions for antipsychotic drugs skyrocketed in the months following a major earthquake. But there are some surprising details.


On 6th April 2009, an earthquake hit L'Aquila, a medium-sized city in central Italy. Out of about 100,000 people living in the L'Aquila area, over 600 died and over 60,000 were displaced: a major disaster for the local people.

Rossi et al from the University of L'Aquila looked at medication prescription in the 6 months following the earthquake and compared them to the previous 6 months. This is not an ideal method, it would have been better to compare L'Aquila to a neighboring district unaffected by the earthquake to control for nationwide changes; but over a few months we wouldn't expect large changes.

Anyway - they found that the number of "new" antidepressant prescriptions rose by 37%. However, prescriptions of non-psychiatric drugs like statins and anti-diabetic medications also rose by up to 50%. This is a bit sketchy but it suggests that the increase in antidepressants might just reflect increased post-disaster medical care for everyone in the area.

There was one big finding though: rates of antipsychotic prescribing more than doubled to 833 prescriptions, a 130% increase.

Does this mean that more people experienced psychosis in the aftermath of the trauma? That's one possibility - but a closer look reveals that the "extra" antipsychotics were given almost entirely to elderly people: just 0.3% of people under 45 got a new antipsychotic prescription but 1% of those 65-75 did and in those 75+ it reached 2.7% in men and a dizzying 3.8% of women.

Unfortunately Rossi et al couldn't tell what the drugs were being prescribed for, because their dataset was based on drug sales. However, it's known that schizophrenia and other forms of psychosis generally strike younger people, not the elderly. However, antipsychotics are often used as sedatives in elderly people especially those suffering dementia.

As the authors point out, this is a controversial practice:

A further observation concerns the appropriateness of prescribed drugs to a potentially vulnerable group such as the elderly. The majority of prescriptions were made by primary care physicians. This may partly explain the somewhat unusual increase in prescriptions for antipsychotic medications. It has been reported that antipsychotic medications are disproportionately prescribed to elderly subjects and need further regulation. This is particularly true in emergency and disaster situations.

In the UK a 2009 government report warned that antipsychotics were being used too freely in people with dementia, at the risk of causing significant harm, and said that they should be reserved for the most serious cases only. This study raises concerns that already questionable prescribing might get even worse following disasters.

Rossi A, Maggio R, Riccardi I, Allegrini F, & Stratta P (2011). A quantitative analysis of antidepressant and antipsychotic prescriptions following an earthquake in Italy. Journal of traumatic stress, 24 (1), 129-32 PMID: 21351173

Fat Genes Make You Happy?

Does being heavier make you happier?

An interesting new paper from a British/Danish collaboration uses a clever trick based on genetics to untangle the messy correlation between obesity and mental health.

They had a huge (53,221) sample of people from Copenhagen, Denmark. It measured people's height and weight to calculate their BMI, and asked them some simple questions about their mood, such as "Do you often feel nervous or stressed?"

Many previous studies have found that being overweight is correlated with poor mental health, or at least with unhappiness ("psychological distress"). And this was exactly what the authors found in this study, as well.

Being very underweight was also correlated with distress; perhaps these were people with eating disorders or serious medical illnesses. But if you set those small number of people aside, there was a nice linear correlation between BMI and unhappiness. When they controlled for various other variables like income, age, and smoking, the effect of BMI became smaller but it was still significant.

But that's just a correlation, and as we all know, "correlation doesn't imply causation". Actually, it does; something must be causing the correlation, it didn't just magically appear out of nowhere. The point is that shouldn't make simplistic assumptions about what the causal direction is.

It would be easy to make these assumptions. Maybe being miserable makes you fat, due to comfort eating. Or maybe being fat makes you miserable, because overweight is considered bad in our society. Or both. Or neither. We don't know.

Finding this kind of correlation and then speculating about it is where a lot of papers finish, but for these authors, it was just the start. They genotyped everyone for two different genetic variants known, from lots of earlier work, to consistently affect body weight (FTO rs9939609 and MC4R rs17782313).

They confirmed that they were indeed associated with BMI; no surprise there. But here's the surprising bit: the "fat" variants of each gene were associated with less psychological distress. The effects were very modest, but then again, their effects on weight are small too (see the graph above; the effects are in terms of z scores and anything below 0.3 is considered "small".)

The picture was very similar for the other gene.

This allows us to narrow down the possibilities about causation. Being depressed clearly can't change your genotype. Nothing short of falling into a nuclear reactor can change your genotype. It also seems unlikely that genotype was correlated with something else which protects against depression. That's not impossible; it's the problem of population stratification, and it's a serious issue with multi-ethnic samples, but this paper only included white Danish people.

So the author's conclusion is that being slightly heavier causes you to be slightly happier, even though overall, weight is strongly correlated with being less happy. This seems paradoxical, but that's what the data show.

That conclusion would fall apart, though, if these genes directly effect mood, and also, separately, make you fatter. The authors argue that this is unlikely, but I wonder. Both FTO and MC4R are active in the brain: they influence weight by making you eat more. If they can affect appetite, they might also affect mood. A quick PubMed search only turns up a couple of rather speculative papers about MC4R and its possible links to mood, so there's no direct evidence for this, but we can't rule it out.

But this paper is still an innovative and interesting attempt to use genetics to help get beneath the surface of complex correlations. It doesn't explain the observed correlation between BMI and unhappiness - it actually makes it more mysterious. But that's a whole lot better than just speculating about it.

Lawlor DA, Harbord RM, Tybjaerg-Hansen A, Palmer TM, Zacho J, Benn M, Timpson NJ, Smith GD, & Nordestgaard BG (2011). Using genetic loci to understand the relationship between adiposity and psychological distress: a Mendelian Randomization study in the Copenhagen General Population Study of 53,221 adults. Journal of internal medicine PMID: 21210875