The finding that roughly one-tenth of US adults suffer from a diagnosable personality disorder (including those with PD NOS) is broadly consistent with the three earlier US studies that, although based on less representative samples, used rigorous semi-structured clinical assessments to diagnose PDs in well-characterized non-patient samples. Similar results have been obtained in two European studies (Coid et al 2006
; Torgersen et al 2001
). A recent report based on a very large US national survey found a considerably higher prevalence of any PD despite omitting borderline, schizotypal, and narcissistic PDs (Grant et al 2004
). This result must be viewed with caution, though, as it was based on a newly developed fully structured diagnostic interview carried out by lay interviewers rather than clinicians that lacked any accompanying validity data.
Estimates of relative prevalence of individual PDs in previous community studies based on rigorous clinical assessments are much less consistent than estimates of overall PD prevalence. Two of the three such studies found Cluster B to be more prevalent than Clusters A or C (Lenzenweger et al 1997
; Samuels et al 2002
), while the third found Cluster C to be more prevalent than Clusters A or B (Crawford et al 2005
). Our study found Clusters A and C to be more prevalent than Cluster B. Specific differences across the studies with respect to each cluster are interesting to note. For the three prior US studies (Crawford et al 2005
; Lenzenweger et al 1997
; Samuels et al 2002
), prevalence rates for Cluster A disorders ranged from 2.1% to 6.8% and our rate of 5.7% falls within this range. Similarly for Cluster C, the range across these three studies was 2.6% to 10.6%, and our rate of 6.0% for Cluster C accords well. Our rate for Cluster B disorders of 1.5% falls outside the range of 4.5% to 6.1% for the three prior studies. These discrepancies are not due to differences in diagnostic assessment, as three of the four studies used the IPDE to make diagnoses. Differences in sample composition are consequently the most plausible explanation for these discrepancies. For example, the Crawford et al. (2005)
and Lenzenweger et al. (1997)
study assessed subjects who were 22 and 18 years old respectively, whereas our study covered a broader age range and this may have impacted Cluster B rates as Cluster B disorders are more frequently diagnosed in younger people.
The rate of Cluster A disorders (5.7%) we found is interesting given the common clinical impression that such disorders are rare in hospital or clinic samples. Cluster A affected individuals may indeed be relatively rare in clinical samples owing to their tendency not to seek treatment. It is quite possible that the rate of Cluster A disorders is higher in the general population. Similar discrepancies have been noted for some Axis I disorders, such as pure generalized anxiety disorder and agoraphobia without panic disorder, both of which are much less common in comparative perspective in clinical than community samples due to treatment selection bias. In the same vein, our prevalence rate for Cluster B disorders (1.5%) might strike some as somewhat low in light of impressions based on clinic samples, however Cluster B disorders might actually be overrepresented in clinic samples owing to their tendency to display striking and clinically salient symptomatology (e.g., suicidal attempts, self mutilation, aggression and impulsive dyscontrol). Cluster B disorders may quite possibly have a lower rate in the general population, particularly when a wide age range is sampled.
Little previous research has examined socio-demographic correlates of PDs, making it difficult to place in perspective our finding of weak socio-demographic correlates. The finding that young and poorly educated people have the highest prevalence of Cluster B PDs is generally consistent with the results of previous research on ASPD (Bland et al 1988
; Meyers et al 1984
; Morizot and Le Blanc 2003
; Pevalin et al 2003
) and BPD (Samuels et al 2002
; Zimmerman and Coryell 1989
), although our failure to find age differences in other PDs is inconsistent with the strong inverse association typically found in clinical samples (Mattia and Zimmerman 2001
; Zimmerman and Coryell 1989
). The DSM-IV (American Psychiatric Association 1994
) suggests that borderline, histrionic and dependent PDs are more prevalent among women than men and that schizoid, schizotypal, narcissistic, paranoid, antisocial and obsessive-compulsive PDs are more prevalent among men than women (Corbitt and Widiger 1995
). Such differences are generally found in clinical studies, especially with regard to antisocial, borderline, and dependent PDs (Corbitt and Widiger 1995
; Loranger 1996
; Reich 1987
). Absence of significant sex differences in the NCS-R is consequently striking. These discrepancies could be due to ascertainment bias, base rate differences, or systematic differences in help-seeking related to socio-demographic factors in the clinical samples (Corbitt and Widiger 1995
; Loranger 1996
). For example, we did not find a sex difference in the rate of BPD in our study, whereas many clinical samples have found the diagnosis of BPD to be increased in women versus men. It may be, however, that the sex differences observed for the rate of BPD in clinical samples may actually reflect different base rates of men and women in such samples (e.g., Corbitt and Widiger 1995
). We note Torgersen et al. (2001)
and Zimmerman and Coryell (1989)
did not find a sex difference for the rate of BPD in their large-scale nonclinical population studies as well. In sum, our data serve to extend and, perhaps, amend clinical impressions regarding the presumed relations of the PDs with various sociodemographic correlates by utilizing a large, randomly ascertained non-clinical population sample.
The finding that PDs are strongly comorbid with a wide range of Axis I disorders is broadly consistent with the results of previous, mostly clinical, studies (Dahl 1986
; Dolan-Sewell et al 2001
; Goodwin et al 2005
; Johnson et al 2005a
; Koenigsberg et al 1985
; Loranger 1990
; McGlashan et al 2000
; Oldham et al 1995
; Tyrer et al 1997
; Zimmerman and Coryell 1989
; Zimmerman et al 2005
). Consistent with the NCS-R results, all forms of Axis I disorder have been found to be associated with higher levels of all three DSM PD clusters in these earlier studies. The NCS-R finding that little differentiation exists in the strength of comorbidity across different Axis I disorders for any given PD is also broadly consistent with the results of earlier studies, although it is important to note that many earlier studies focused on only selected Axis I disorders or evaluated PDs in samples of patients with Axis I disorders that had unusual features (e.g., among patients with panic disorder and suicidal behavior). However, the NCS-R results are inconsistent with the results of a comprehensive literature review that found Cluster B PDs to be more often comorbid with substance use disorders and major depression than with other Axis I disorders (Dolan-Sewell et al 2001
). Given the evidence of good validity of the NCS-R assessments of both PDs and Axis I disorders, this discrepancy with earlier studies is likely to be due more to differences in sample composition than to differences in measurement.
It is noteworthy that the odds-ratios found in the NCS-R between PDs and Axis I disorders are comparable in magnitude to the odds-ratios found in separate NCS-R analyses between pairs of Axis I disorders (Kessler et al 2005b
). This observation raises the possibility that PDs reflect variants on processes common to Axis I disorders and that PDs have been somewhat arbitrarily separated from Axis I disorders in the DSM nomenclature (Siever and Davis 1991
; Widiger 2003
). This is an important difference between the DSM and ICD systems, as the latter does not treat PDs as a separate Axis from other disorders (World Health Organization 1992
). Our finding that comorbidity is much higher for Cluster B than Clusters A or C is an interesting variant on this theme. One possible explanation for this difference is that the dysregulation in underlying negative affect and constraint systems that affects the erratic and impulsive symptoms of Cluster B PDs (Depue and Lenzenweger 2001
; Depue and Lenzenweger 2005
) might be a more important determinant of Axis I disorders than of Clusters A or C PDs in the general population. That this specification has not been found in clinical studies could be due to a greater restriction in the variance of underlying dysregulation in clinical samples than the general population.
A plausible interpretation of this discrepancy between the NCS-R results and the results of clinical studies is that functional impairment might influence help-seeking more strongly among patients with pure personality disorders than among those with Axis I disorders (mindful that such help-seeking may be prompted by spouses, other family members, or employers rather than by the patients themselves), while distress affects help-seeking more among patients with Axis I disorders than among those with pure personality disorders. If these differences in determinants of seeking treatment exist, they could lead to a bias in treatment samples for PDs to be associated with impairment independent of Axis I disorders even though this pattern is much weaker in the general population.
This possibility is indirectly consistent with our finding that help-seeking among people with PDs is strongly affected by Axis I comorbidity. Indeed, further analysis of these data (results available on request) showed that the effects of Axis I comorbidity in accounting for treatment among people with PDs is explained by the high role impairment associated with highly Axis I comorbidity. Importantly, Axis I disorders, unlike PDs, were found to continue to be associated with significantly elevated odds of treatment even after controlling for role impairment, presumably reflecting effects of clinically significant psychological distress on help-seeking. Finally, we note our findings regarding the relative impact of Axis I comorbidity on functional impairment alert us to the fact that prior findings on this issue derived from clinical samples may not generalize to the population.
The NCS-R results have to be interpreted in the context of the limitation that PDs were assessed comprehensively only in the sub-sample of respondents who received IPDE clinical reappraisal interviews. Clinical diagnoses of DSM-IV/IPDE PDs were imputed in the larger sample. Concern about this limitation is reduced by the fact that the AUC of the imputation equations was consistently quite high, which means that the imputed diagnoses are likely to be very similar to the diagnoses we would have obtained if full IPDE interviews had been administered to all respondents. In addition, the MI method adjusts for the imprecision in parameter estimates introduced by imputation. Prevalence is estimated without bias using MI, while MI estimates of associations involving PDs are conservative. The NCS-R finding that PD is a relatively common form of psychopathology can consequently be considered reliable, while the findings of high Axis I comorbidity and impairment can be considered conservative. Another potential limitation concerns the possibility that the strength of association between PD screening questions and true diagnoses varies by respondent age, sex, or other variables examined as correlates of PDs. The clinical reappraisal sample was too small to investigate the possibility of such variation. To the extent that it exists, this variation would bias estimates of associations even though the prevalence estimates themselves are not biased. Future epidemiological research could address this problem either by including a clinical reappraisal sample large enough to estimate such interactions powerfully or by administering clinical interviews to the entire sample. A final limitation concerns the possibility that individuals with a PD might have declined to participate more often in this study and this would lead to an underestimation of PD prevalence rates. Although we did not address this directly, our data were weighted to account for an under-representation of those declining to participate due to Axis I disorders and given the comorbidity of Axis I and Axis II disorders, this methodological refinement may have helped to offset, in part, any tendency of PD affected persons to be non-responders. It remains conceivable, nonetheless, that our PD prevalence rates are somewhat underestimated.
The finding that Axis I comorbidity accounts for the impairment and help-seeking associated with PDs could be somewhat overstated due to the conservative bias in MI estimates of PD effects. However, this bias is likely to be small in light of the high AUC of the imputation equations. Based on this fact, it seems likely that PDs have only modest effects on functional impairment independent of Axis I disorders in the general population. Given the high comorbidity of PDs with Axis I disorders, though, and the especially high odds-ratios of PDs with high Axis I comorbidity, the possibility exists that PDs affect the onset, persistence, and severity of comorbid Axis I disorders. An investigation of this possibility was beyond the scope of our analysis because no information was collected in the NCS-R about age of onset or persistence of PDs in relation to age of onset and persistence of Axis I disorders. However, these results argue strongly that the investigation of PD effects on Axis I disorders should be a focus of future longitudinal epidemiological research on personality disorders.