Associations between individual antipsychotics and the risk of arrests and convictions of violent and other crime: a nationwide within-individual study of 74 925 persons.

BACKGROUND: Individuals diagnosed with psychiatric disorders who are prescribed antipsychotics have lower rates of violence and crime but the differential effects of specific antipsychotics are not known. We investigated associations between 10 specific antipsychotic medications and subsequent risks for a range of criminal outcomes. METHODS: We identified 74 925 individuals who were ever prescribed antipsychotics between 2006 and 2013 using nationwide Swedish registries. We tested for five specific first-generation antipsychotics (levomepromazine, perphenazine, haloperidol, flupentixol, and zuclopenthixol) and five second-generation antipsychotics (clozapine, olanzapine, quetiapine, risperidone, and aripiprazole). The outcomes included violent, drug-related, and any criminal arrests and convictions. We conducted within-individual analyses using fixed-effects Poisson regression models that compared rates of outcomes between periods when each individual was either on or off medication to account for time-stable unmeasured confounders. All models were adjusted for age and concurrent mood stabilizer medications. RESULTS: The relative risks of all crime outcomes were substantially reduced [range of adjusted rate ratios (aRRs): 0.50-0.67] during periods when the patients were prescribed antipsychotics v. periods when they were not. We found that clozapine (aRRs: 0.28-0.44), olanzapine (aRRs: 0.46-0.72), and risperidone (aRRs: 0.53-0.64) were associated with lower arrest and conviction risks than other antipsychotics, including quetiapine (aRRs: 0.68-0.84) and haloperidol (aRRs: 0.67-0.77). Long-acting injectables as a combined medication class were associated with lower risks of the outcomes but only risperidone was associated with lower risks of all six outcomes (aRRs: 0.33-0.69). CONCLUSIONS: There is heterogeneity in the associations between specific antipsychotics and subsequent arrests and convictions for any drug-related and violent crimes.

Doubly robust conditional logistic regression.

Epidemiologic research often aims to estimate the association between a binary exposure and a binary outcome, while adjusting for a set of covariates (eg, confounders). When data are clustered, as in, for instance, matched case-control studies and co-twin-control studies, it is common to use conditional logistic regression. In this model, all cluster-constant covariates are absorbed into a cluster-specific intercept, whereas cluster-varying covariates are adjusted for by explicitly adding these as explanatory variables to the model. In this paper, we propose a doubly robust estimator of the exposure-outcome odds ratio in conditional logistic regression models. This estimator protects against bias in the odds ratio estimator due to misspecification of the part of the model that contains the cluster-varying covariates. The doubly robust estimator uses two conditional logistic regression models for the odds ratio, one prospective and one retrospective, and is consistent for the exposure-outcome odds ratio if at least one of these models is correctly specified, not necessarily both. We demonstrate the properties of the proposed method by simulations and by re-analyzing a publicly available dataset from a matched case-control study on induced abortion and infertility.

Parental nicotine replacement therapy and offspring bronchitis/bronchiolitis and asthma - a nationwide population-based cohort study.

BACKGROUND: Prior evidence shows that environmental tobacco smoke is a risk factor for respiratory tract infections, wheeze, and asthma. Nicotine replacement therapy has been shown to increase smoking cessation. However, no prior studies have explored if parental use decreases the risk of bronchitis/bronchiolitis and asthma in the offspring. OBJECTIVE: To examine whether nicotine replacement therapy varenicline, given to parents, was associated with a reduction in bronchitis/bronchiolitis and/or asthma in their children. METHODS: This study is a population-based cohort study, linking data from nationwide registers, and using a within-individual design that minimizes selection effects and controls for time-invariant confounding factors. Participants included 37,420 parents with a collected prescription of varenicline with 72,392 offspring <18 years of age. Exposure was defined as collected prescriptions of varenicline among the parents. Primary outcomes were offspring hospital visits for bronchitis/bronchiolitis (ICD10: J20 or J21) and offspring hospital visits for asthma (ICD10: J45). RESULTS: Parental varenicline treatment was associated with a lower rate of visits for bronchitis/bronchiolitis in their children (incidence rate ratio [IRR]=0.67; 95% CI=0.50-0.91), but no association was found for asthma (IRR=1.08; 95% CI=0.97-1.19). The rate reduction of bronchitis/bronchiolitis was similar when we restricted data to children aged 0-3 years (IRR=0.71; 95% CI=0.52-0.97) and to maternal varenicline treatment (IRR=0.64; 95% CI=0.43-0.96). When restricting the outcomes to unplanned visits only (ie, excluding booked appointments, followups, and referrals), no associations were found (IRR=0.72, 95% CI=0.51-1.02). CONCLUSION: In this cohort study, nicotine replacement treatment in parents was associated with reduced hospital visits for bronchitis/bronchiolitis in their children.

Medications for Alcohol and Opioid Use Disorders and Risk of Suicidal Behavior, Accidental Overdoses, and Crime.

OBJECTIVE: The authors examined associations between medications for alcohol and opioid use disorders (acamprosate, naltrexone, methadone, and buprenorphine) and suicidal behavior, accidental overdoses, and crime. METHOD: In this total population cohort study, 21,281 individuals who received treatment with at least one of the four medications between 2005 and 2013 were identified. Data on medication use and outcomes were collected from Swedish population-based registers. A within-individual design (using stratified Cox proportional hazards regression models) was used to compare rates of suicidal behavior, accidental overdoses, and crime for the same individuals during the period when they were receiving the medication compared with the period when they were not. RESULTS: No significant associations with any of the primary outcomes were found for acamprosate. For naltrexone, there was a reduction in the hazard ratio for accidental overdoses during periods when individuals received treatment compared with periods when they did not (hazard ratio=0.82, 95% CI=0.70, 0.96). Buprenorphine was associated with reduced arrest rates for all crime categories (i.e., violent, nonviolent, and substance-related) as well as reduction in accidental overdoses (hazard ratio=0.75, 95% CI=0.60, 0.93). For methadone, there were significant reductions in the rate of suicidal behaviors (hazard ratio=0.60, 95% CI=0.40-0.88) as well as reductions in all crime categories. However, there was an increased risk for accidental overdoses among individuals taking methadone (hazard ratio=1.25, 95% CI=1.13, 1.38). CONCLUSIONS: Medications currently used to treat alcohol and opioid use disorders also appear to reduce suicidality and crime during treatment.

Confounders, Mediators, or Colliders: What Types of Shared Covariates Does a Sibling Comparison Design Control For?

The sibling comparison design is an important epidemiologic tool to control for unmeasured confounding, in studies of the causal effect of an exposure on an outcome. It is routinely argued that within-family associations are automatically controlled for all measured and unmeasured covariates that are shared (constant) within sets of siblings, such as early childhood environment and parental genetic makeup. However, an important lesson from modern causal inference theory is that not all types of covariate control are desirable. In particular, it has been argued that collider control always leads to bias, and that mediator control may or may not lead to bias, depending on the research question. In this article, we use directed acyclic graphs (DAGs) to distinguish between shared confounders, shared mediators and shared colliders, and we examine which of these shared covariates the sibling comparison design really controls for.

Carryover Effects in Sibling Comparison Designs.

A convenient way of dealing with confounding is the sibling comparison design, where the outcome in exposed individuals is compared with the outcome in their unexposed siblings. The standard analysis of sibling comparison designs assumes that the exposure and outcome of an individual do not affect the exposure and outcome of his/her siblings, sometimes referred to as an absence of sibling carryover or contagion effects. Unfortunately, there are many situations where carryover effects are likely to be present. In this article, we explore the consequences of carryover effects for sibling comparison designs. We show, using causal diagrams, when and why carryover effects lead to bias, and we investigate the sign and magnitude of this bias under various scenarios.

Model-based estimation of the attributable fraction for cross-sectional, case-control and cohort studies using the R package AF.

The attributable fraction (or attributable risk) is a widely used measure that quantifies the public health impact of an exposure on an outcome. Even though the theory for AF estimation is well developed, there has been a lack of up-to-date software implementations. The aim of this article is to present a new R package for AF estimation with binary exposures. The package AF allows for confounder-adjusted estimation of the AF for the three major study designs: cross-sectional, (possibly matched) case-control and cohort. The article is divided into theoretical sections and applied sections. In the theoretical sections we describe how the confounder-adjusted AF is estimated for each specific study design. These sections serve as a brief but self-consistent tutorial in AF estimation. In the applied sections we use real data examples to illustrate how the AF package is used. All datasets in these examples are publicly available and included in the AF package, so readers can easily replicate all analyses.

A Note on the Noncollapsibility of Rate Differences and Rate Ratios.

It is well known that the odds ratio is noncollapsible, in the sense that conditioning on a covariate that is related to the outcome typically changes the size of the odds ratio, even if this covariate is unrelated to the exposure. The risk difference and risk ratio do not have this peculiar property; we say that the risk difference and risk ratio are collapsible. However, noncollapsibility is not unique for the odds ratio; the rate difference and rate ratio are generally noncollapsible as well. This may seem paradoxical, since the rate can be viewed as a risk per unit time, and thus one would naively suspect that the rate difference/ratio should inherit collapsibility from the risk difference/ratio. Adding to the confusion, it was recently shown that the exposure coefficient in the Aalen additive hazards model is collapsible. This may seem to contradict the fact that the rate difference is generally noncollapsible, since the exposure coefficient in the Aalen additive hazards model is a rate difference. In this article, we use graphical arguments to explain why the rate difference/ratio does not inherit collapsibility from the risk difference/ratio. We also explain when and why the exposure coefficient in the Aalen additive hazards model is collapsible.

Doubly robust methods for handling confounding by cluster.

In clustered designs such as family studies, the exposure-outcome association is usually confounded by both cluster-constant and cluster-varying confounders. The influence of cluster-constant confounders can be eliminated by studying the exposure-outcome association within (conditional on) clusters, but additional regression modeling is usually required to control for observed cluster-varying confounders. A problem is that the working regression model may be misspecified, in which case the estimated within-cluster association may be biased. To reduce sensitivity to model misspecification we propose to augment the standard working model for the outcome with an auxiliary working model for the exposure. We derive a doubly robust conditional generalized estimating equation (DRCGEE) estimator for the within-cluster association. This estimator combines the two models in such a way that it is consistent if either model is correct, not necessarily both. Thus, the DRCGEE estimator gives the researcher two chances instead of only one to make valid inference on the within-cluster association. We have implemented the estimator in an R package and we use it to examine the association between smoking during pregnancy and cognitive abilities in offspring, in a sample of siblings.

Selective Serotonin Reuptake Inhibitors and Violent Crime: A Cohort Study.

BACKGROUND: Although selective serotonin reuptake inhibitors (SSRIs) are widely prescribed, associations with violence are uncertain. METHODS AND FINDINGS: From Swedish national registers we extracted information on 856,493 individuals who were prescribed SSRIs, and subsequent violent crimes during 2006 through 2009. We used stratified Cox regression analyses to compare the rate of violent crime while individuals were prescribed these medications with the rate in the same individuals while not receiving medication. Adjustments were made for other psychotropic medications. Information on all medications was extracted from the Swedish Prescribed Drug Register, with complete national data on all dispensed medications. Information on violent crime convictions was extracted from the Swedish national crime register. Using within-individual models, there was an overall association between SSRIs and violent crime convictions (hazard ratio [HR] = 1.19, 95% CI 1.08-1.32, p < 0.001, absolute risk = 1.0%). With age stratification, there was a significant association between SSRIs and violent crime convictions for individuals aged 15 to 24 y (HR = 1.43, 95% CI 1.19-1.73, p < 0.001, absolute risk = 3.0%). However, there were no significant associations in those aged 25-34 y (HR = 1.20, 95% CI 0.95-1.52, p = 0.125, absolute risk = 1.6%), in those aged 35-44 y (HR = 1.06, 95% CI 0.83-1.35, p = 0.666, absolute risk = 1.2%), or in those aged 45 y or older (HR = 1.07, 95% CI 0.84-1.35, p = 0.594, absolute risk = 0.3%). Associations in those aged 15 to 24 y were also found for violent crime arrests with preliminary investigations (HR = 1.28, 95% CI 1.16-1.41, p < 0.001), non-violent crime convictions (HR = 1.22, 95% CI 1.10-1.34, p < 0.001), non-violent crime arrests (HR = 1.13, 95% CI 1.07-1.20, p < 0.001), non-fatal injuries from accidents (HR = 1.29, 95% CI 1.22-1.36, p < 0.001), and emergency inpatient or outpatient treatment for alcohol intoxication or misuse (HR = 1.98, 95% CI 1.76-2.21, p < 0.001). With age and sex stratification, there was a significant association between SSRIs and violent crime convictions for males aged 15 to 24 y (HR = 1.40, 95% CI 1.13-1.73, p = 0.002) and females aged 15 to 24 y (HR = 1.75, 95% CI 1.08-2.84, p = 0.023). However, there were no significant associations in those aged 25 y or older. One important limitation is that we were unable to fully account for time-varying factors. CONCLUSIONS: The association between SSRIs and violent crime convictions and violent crime arrests varied by age group. The increased risk we found in young people needs validation in other studies.

Varenicline and risk of psychiatric conditions, suicidal behaviour, criminal offending, and transport accidents and offences: population based cohort study.

OBJECTIVE: To examine associations between varenicline and the incidence of a range of adverse outcomes. DESIGN: Population based cohort study using within person analyses to control for confounding by indication. SETTING: Whole population of Sweden. PARTICIPANTS: 7,917,436 people aged 15 and over, of whom 69,757 were treated with varenicline between 2006 and 2009. MAIN OUTCOME MEASURES: Incidence of new psychiatric conditions, suicidal behaviour, suspected and convicted criminal offending, transport accidents, and suspected and convicted traffic offences. RESULTS: In the whole population, 337,393 new psychiatric conditions were diagnosed during follow-up. In addition, 507,823 suspected and 338,608 convicted crimes, 40,595 suicidal events, 124,445 transport accidents, and 99,895 suspected and 57,068 convicted traffic crimes were recorded. Within person analyses showed that varenicline was not associated with significant hazards of suicidal behaviour, criminal offending, transport accidents, traffic offences, or psychoses. However, varenicline was associated with a small increase in the risk of anxiety conditions (hazard ratio 1.23, 95% confidence interval 1.01 to 1.51) and mood conditions (1.31, 1.06 to 1.63), which was only seen in people with pre-existing psychiatric disorders. CONCLUSIONS: Concerns that varenicline is associated with an increased risk of many adverse outcomes, including suicidality and accidents, are not supported in this observational study. The small increase in risk of two psychiatric conditions in people with pre-existing psychiatric disorders needs to be confirmed using other research designs.

Antipsychotics, mood stabilisers, and risk of violent crime.

BACKGROUND: Antipsychotics and mood stabilisers are prescribed widely to patients with psychiatric disorders worldwide. Despite clear evidence for their efficacy in relapse prevention and symptom relief, their effect on some adverse outcomes, including the perpetration of violent crime, is unclear. We aimed to establish the effect of antipsychotics and mood stabilisers on the rate of violent crime committed by patients with psychiatric disorders in Sweden. METHODS: We used linked Swedish national registers to study 82,647 patients who were prescribed antipsychotics or mood stabilisers, their psychiatric diagnoses, and subsequent criminal convictions in 2006-09. We did within-individual analyses to compare the rate of violent criminality during the time that patients were prescribed these medications versus the rate for the same patients while they were not receiving the drugs to adjust for all confounders that remained constant within each participant during follow-up. The primary outcome was the occurrence of violent crime, according to Sweden's national crime register. FINDINGS: In 2006-09, 40,937 men in Sweden were prescribed antipsychotics or mood stabilisers, of whom 2657 (6·5%) were convicted of a violent crime during the study period. In the same period, 41,710 women were prescribed these drugs, of whom 604 (1·4 %) had convictions for violent crime. Compared with periods when participants were not on medication, violent crime fell by 45% in patients receiving antipsychotics (hazard ratio [HR] 0·55, 95% CI 0·47-0·64) and by 24% in patients prescribed mood stabilisers (0·76, 0·62-0·93). However, we identified potentially important differences by diagnosis-mood stabilisers were associated with a reduced rate of violent crime only in patients with bipolar disorder. The rate of violence reduction for antipsychotics remained between 22% and 29% in sensitivity analyses that used different outcomes (any crime, drug-related crime, less severe crime, and violent arrest), and was stronger in patients who were prescribed higher drug doses than in those prescribed low doses. Notable reductions in violent crime were also recorded for depot medication (HR adjusted for concomitant oral medications 0·60, 95% CI 0·39-0·92). INTERPRETATION: In addition to relapse prevention and psychiatric symptom relief, the benefits of antipsychotics and mood stabilisers might also include reductions in the rates of violent crime. The potential effects of these drugs on violence and crime should be taken into account when treatment options for patients with psychiatric disorders are being considered. FUNDING: The Wellcome Trust, the Swedish Prison and Probation Service, the Swedish Research Council, and the Swedish Research Council for Health, Working Life and Welfare.

Medication for attention deficit-hyperactivity disorder and criminality.

BACKGROUND: Attention deficit-hyperactivity disorder (ADHD) is a common disorder that has been associated with criminal behavior in some studies. Pharmacologic treatment is available for ADHD and may reduce the risk of criminality. METHODS: Using Swedish national registers, we gathered information on 25,656 patients with a diagnosis of ADHD, their pharmacologic treatment, and subsequent criminal convictions in Sweden from 2006 through 2009. We used stratified Cox regression analyses to compare the rate of criminality while the patients were receiving ADHD medication, as compared with the rate for the same patients while not receiving medication. RESULTS: As compared with nonmedication periods, among patients receiving ADHD medication, there was a significant reduction of 32% in the criminality rate for men (adjusted hazard ratio, 0.68; 95% confidence interval [CI], 0.63 to 0.73) and 41% for women (hazard ratio, 0.59; 95% CI, 0.50 to 0.70). The rate reduction remained between 17% and 46% in sensitivity analyses among men, with factors that included different types of drugs (e.g., stimulant vs. nonstimulant) and outcomes (e.g., type of crime). CONCLUSIONS: Among patients with ADHD, rates of criminality were lower during periods when they were receiving ADHD medication. These findings raise the possibility that the use of medication reduces the risk of criminality among patients with ADHD. (Funded by the Swedish Research Council and others.).