Mate similarity for substance dependence and antisocial personality disorder symptoms among parents of patients and controls

Drug and Alcohol Dependence 75 (2004) 165–175

Mate similarity for substance dependence and antisocial personality disorder symptoms among parents of patients and controls夽 J.T. Sakai a,∗ , M.C. Stallings b , S.K. Mikulich-Gilbertson a , R.P. Corley b , S.E. Young b , C.J. Hopfer a , T.J. Crowley a a

b

Division of Substance Dependence, Department of Psychiatry, University of Colorado School of Medicine, 4200 E. Ninth Avenue, C268-35, Denver, CO 80262, USA The Institute for Behavioral Genetics, University of Colorado, Campus Box 447, 1480 30th Street, Boulder, CO 80309, USA Received 27 March 2003; received in revised form 19 January 2004; accepted 29 January 2004

Abstract Substance dependence (SD) and antisocial personality disorder (ASPD) are highly comorbid and aggregate in families. Mating assortment may be an important process contributing to this familial aggregation. Hypothesis: Symptom counts of substance dependence, antisocial personality disorder, and retrospectively assessed conduct disorder (CD) will be correlated significantly among parents of youth in treatment for substance use and conduct problems and, separately, among parents of community controls. Methods: We examined SD, ASPD, and CD among 151 pairs of parents of adolescents in treatment for substance use and conduct problems, and in 206 pairs of parents of control subjects. Results: For average dependence symptoms (ADS) (the sum of across-drug substance dependence symptoms divided by the number of substance categories meeting minimum threshold use) mother–father correlations were 0.40 for patients and 0.28 for controls. Mother–father correlations for ASPD symptom count were 0.33 for patients and 0.26 for controls and for CD symptom count were 0.31 for patients (all P < 0.01) and 0.10 for controls (P = 0.14). Conclusions: Spousal correlations for ADS and ASPD, suggest substantial non-random mating. Results support gender differences in homogamy for SD. Behavior genetic studies of these disorders need to account for assortment to avoid biases in estimates of genetic and environmental effects. © 2004 Elsevier Ireland Ltd. All rights reserved. Keywords: Substance dependence; Antisocial personality disorder; Assortative mating; Family; Comorbidity

1. Introduction Substance use disorders and antisocial behavior are highly comorbid and cluster within families (Lahey et al., 1988). Both disorders are influenced by genetic traits (Vanyukov et al., 1996) and studies suggest a common genetic risk for both disorders (Grove et al., 1990; Slutske et al., 1998; Vanyukov et al., 1996). Other research supports that substance dependence (SD) and antisocial behavior represent different manifestations of a common latent factor such as behavioral disinhibition (Young et al., 2000; Krueger et al., 2002), which may in part explain the high comorbid-

夽 Portions of this paper were previously presented at the annual meeting of the College on Problems of Drug Dependence (Scottsdale, AZ, 2001). ∗ Corresponding author. Tel.: +1-303-315-1516; fax: +1-303-315-0394. E-mail address: [email protected] (J.T. Sakai).

ity within individuals and the clustering of these disorders within families. Assortative mating may further drive the co-occurrence of these two disorders (Crow and Felsenstein, 1968; Vandenberg, 1972; Eaves, 1973; Eaves et al., 1984; Allison et al., 1996; Baker et al., 1996). Assortment, as opposed to random mating, involves partners selecting each other from the population based in part on the presence or absence of particular traits shared by the partners. Assortment is important to understand because it influences the distribution of genetic and environmental influences on disorders. If persons with substance use disorders and antisocial behavior are more likely to mate with one another, then their offspring have a greater chance of receiving “risk” genes as well as “risk” environments for substance use and antisocial behaviors (Vanyukov and Tarter, 2000; Crow and Felsenstein, 1968). Characterizing assortative mating is also important so that twin and adoption studies can appropriately model genetic

0376-8716/$ – see front matter © 2004 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.drugalcdep.2004.01.015

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and environmental influences on substance use and antisocial behaviors. If assortative mating occurs and is not properly taken into account, twin studies will underestimate genetic effects (using the most common assumptions) and adoption studies will overestimate them (Allison et al., 1996; Krueger et al., 1998). Mate similarity, also known as homogamy, is suggestive of non-random mating. Mate similarity may result from couples choosing partners who are similar to themselves (phenotypic assortment) (Reynolds et al., 1996), from similar environments driving mate similarity (social homogamy) (Rao et al., 1974; Eaves et al., 1989), or from couples becoming more similar over time through spouse–spouse influences (cohabitation effects) (Caspi and Herbener, 1990). Mate similarity has been described for cognitive abilities (Jensen, 1978; Reynolds et al., 1996), social attitudes (Eaves et al., 1999), and personality (Lake et al., 2000), as well as for a wide range of psychiatric disorders (Merikangas, 1982). Previous authors have reported substantial homogamy for antisocial behavior among selected men and their partners (correlation of 0.7) (Cloninger et al., 1975) and selected women and their partners (concordance rates of 0.26) (Crowe, 1974). Similarly, general population samples have shown homogamy for antisocial behavior (Krueger et al., 1998; Galbaud Du Fort et al., 2002). Moderate spousal similarity (correlation = 0.24–0.35) has been described for a history of adolescent conduct disorder (CD) (Meyer et al., 2000; Vanyukov et al., 1994) and moderate to strong spousal correlations (correlation = 0.47–0.63) have also been shown for alcohol consumption (Price and Vandenberg, 1980; Kolonel and Lee, 1981). We find only one study addressing spousal similarity for substance use disorders in general (Vanyukov et al., 1994), in which drug abusing males (n = 66), alcoholism-only males (n = 22), control males (n = 76) and their wives were recruited from clinical facilities and through advertisements. A tetrachoric correlation of 0.61 was found for substance use disorders across groups (patients and controls) (Vanyukov et al., 1994), suggesting substantial assortment for substance use disorders. However, it was limited by a relatively small sample size and the authors did not examine patients and controls separately. Analyses within an over-sampled affected group of patient families, and matching analyses within a community sample of control families might increase the generalizability of results. Another limitation of the current literature is that no studies have addressed cross-variable assortment for substance dependence and antisocial personality disorder (ASPD). Cross-variable assortment occurs when there is cross-variable spousal similarity that is not explained by other correlated variables. For example a substance dependent woman may be more likely to pair with an antisocial man, even after accounting for the effect of other correlated variables. This will cause both disorders to cluster within families and will increase the likelihood of these disorders being comorbid in offspring. In addition, if it is

true that substance dependence and antisocial behavior are different manifestations of the same latent factor, then both cross-variable and within-variable assortment would impact homogamy for this latent factor. Cross-variable assortment has been examined for alcoholism, generalized anxiety disorder, major depression, panic disorder, and phobias (Maes et al., 1998) but we find no studies examining cross-variable assortment for substance dependence and antisocial personality disorder. Finally, we find no studies examining whether gender differences exist in assortment for illicit substance dependence or antisocial behavior. Gender differences in mate selection have been described for alcohol use disorders. For example female alcoholic probands are likely to have an alcoholic spouse (concordance rates of 0.16–0.55) (Windle, 1997), with rates higher than the concordance rates found for male alcoholic probands (0.0–0.33) (Jacob and Bremer, 1986). We report on mate similarity for substance dependence, antisocial behavior, and adolescent conduct disorder symptoms in a sample of parents of adolescents in treatment for substance use and conduct problems, as well as in parents of control adolescents. We also test for cross-variable assortment and gender differences in assortment for substance dependence.

2. Methods This study reports on data from a family study of adolescent substance use and conduct disorder collected from 1993 to 2001. We interviewed family members of these adolescents in treatment, as well as family members of control adolescents (including parents, siblings, half siblings or any other relative or cohabitant who had lived with adolescent patients or controls for 1 year or more). This study examines the parents of these patients and controls. 2.1. Patient–parent sample An adolescent patient sample was drawn from admissions to a substance abuse treatment facility in the Denver Metropolitan Area that offers outpatient, day treatment and residential services. Participants, 13–18 years old, were referred for serious substance involvement and conduct problems; most were referred from social services and juvenile justice agencies. Adolescents were excluded from the study if they were judged by clinical staff to have severe cognitive impairment, or to be currently psychotic or imminently dangerous to themselves or others. Of adolescent patients who met inclusion criteria for the main study, less than 13% refused participation. Miles et al. (1998) compared a subset of these patient and control adolescents for substance use disorders, and conduct disorder and the reader is referred to this citation for further information on this adolescent sample. All available parents were given the opportunity to voluntarily participate in this research and those who gave

J.T. Sakai et al. / Drug and Alcohol Dependence 75 (2004) 165–175

written consent were enrolled in the study. The patient–parent sample used in this report consists of patient families with both parents directly interviewed (n = 151 mother–father pairs). All parents were reported to be the biological parents of these adolescent patients. DNA tests were utilized to verify paternity of the identified “biological” father. The family’s report agreed with DNA testing 97.9% of the time. Among patient families there were 151 (36%) families in which both parents were interviewed, 236 (57%) in which only the mother was interviewed, and 31 (7%) in which only the father was interviewed. Of those parents of patients not interviewed, 15% were deceased; this high rate of deceased patient parents not interviewed may relate to selecting families at high risk for heavy substance involvement and antisocial behavior. 2.2. Control–parent sample Community control adolescents were recruited to be similar to the adolescent patient sample in terms of (1) gender, (2) age, (3) ethnicity, and (4) zip code of residence. Community controls were not excluded based on their psychiatric or substance use history. Thus, it was our aim to recruit a population-based sample of families within the matched demographic profile. Control family members were also interviewed but were not directly matched to treatment relatives. All available parents of controls were given the opportunity to voluntarily participate in this research and those who gave written consent were enrolled in the study. The control–parent sample used in this report consists of control families with both parents directly interviewed (n = 206 mother–father pairs). Among control parents both parents were interviewed in 206 (72%) families, only the mother was interviewed in 61 (21%) families and only the father was interviewed in 18 (6%) families. 2.3. Assessment All interviewers were formally trained in the administration of the study instruments. Direct face-to-face interviews were conducted with all available and consenting parents of patients and controls. Subjects received a modest payment for participating in the study. Parents were interviewed separately with no requirement that they currently be living together. All consent forms and research protocols were approved by the University of Colorado Institutional Review Board. Subjects completed the Composite International Diagnostic Interview, Substance Abuse Module (CIDI-SAM) (Robins et al., 1988), a structured 30–60 min interview designed for administration by trained lay interviewers which provides lifetime DSM III-R (American Psychiatric Association, 1987) substance dependence symptom counts and substance dependence diagnoses. The CIDI has shown good inter-rater reliability (Wittchen et al., 1991), test–retest

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reliability (Cottler et al., 1989) and validity of diagnoses (Cottler et al., 1991; Janca et al., 1992; Wittchen, 1994). Subjects also completed portions of the diagnostic interview schedule (DIS), which has shown good inter-rater reliability (Robins et al., 1981), test–retest reliability (Robins et al., 1981) and predictive validity (Helzer et al., 1987), and provides DSM III-R (American Psychiatric Association, 1987) lifetime antisocial personality disorder and conduct disorder symptom counts and ASPD and CD diagnoses. During data collection instruments were updated to generate DSM-IV diagnoses (American Psychiatric Association, 1994). Without changing the order of questions or scoring, we inserted questions from the previous DSM III-R version to allow analyses with the already collected sample. We did not test whether this modification altered the instrument functioning. Both dimensional and diagnostic measurements of substance dependence and antisocial personality disorder were used. Dimensional measures may better represent the continuous liability of complex traits such as antisocial behavior and substance problems. Diagnostic measures may provide more practical information to individuals who use diagnoses, such as clinicians. The extent of substance involvement was measured by whether the parents ever met criteria for substance dependence. We utilized substance dependence diagnoses in these analyses because substance dependence may represent a more stable diagnosis (Schuckit et al., 2001) and many instruments have shown greater diagnostic concordance coefficients for substance dependence as opposed to substance abuse/harmful use diagnoses (Ustun et al., 1997). In addition, concordance between DSM III-R and DSM-IV substance abuse diagnoses has been poor with Kappa values as low as 0.05–0.13 (Schuckit et al., 1994). Substance dependence has generally shown Kappa’s greater than those seen for substance abuse (Rounsaville et al., 1993). We also used a quantitative measure, which was an index of substance dependence vulnerability (average dependence symptoms (ADS), the sum of DSM III-R dependence symptoms across ten CIDI-SAM defined substance categories, divided by the number of substance categories meeting the CIDI-SAM defined threshold for minimum use (i.e. at least five times)). This measure is related to “dependence vulnerability”, a measure that has been shown to be a heritable, genetically relevant phenotype in adolescents (Corley et al., 2001; Stallings et al., 2003; Crowley et al., 2003). ADS differs from dependence vulnerability in that it is not age and sex corrected, not adjusted to the population mean and not expressed in standard deviation units. The measures of antisocial personality were ASPD (DSM III-R lifetime diagnosis of antisocial personality disorder) and ASPD-SC (the lifetime ASPD symptom counts). The measures of conduct disorder were CD (DSM III-R lifetime diagnosis of conduct disorder) and CD-SC (lifetime CD symptom counts). Finally, family history information was also obtained by interview, utilizing an instrument designed by the

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researchers. This survey included questions about antisocial behavior, alcohol dependence symptoms and drug dependence symptoms based on DSM-IV criteria. 2.4. DSM-III-R versus DSM-IV We utilized DSM III-R diagnoses and symptoms counts for the analyses presented because data collection began prior to the availability of DSM-IV assessments. The DSM III-R differs from the DSM-IV and it is important to emphasize these differences to help with the interpretation of results. First, for SD the DSM III-R version makes experiencing characteristic withdrawal symptoms and using to relieve such symptoms two distinct criteria, where DSM-IV treats them as one. The DSM III-R recognizes continued substance use despite persistent or recurrent social problems (criteria A6); the DSM-IV does not (criteria A7). The III-R version also includes one additional criteria: frequent intoxication or withdrawal interferes with major role obligations and/or substance use occurs in physically hazardous situations. ASPD differences include: (1) the criteria for consistent irresponsibility in DSM-IV is divided into two criteria in the DSM III-R (the inability to sustain consistent work, and repeatedly fails to honor financial obligations); (2) the DSM III-R includes one criterion for lacking the ability to function as a responsible parents and one criterion for never having sustained a totally monogamous relationship for more than 1 year; (3) the III-R version provides detailed examples for some criteria (impulsivity), whereas DSM-IV allows some interpretation; and (4) four criteria are required for diagnosis in version III-R, while three are required in the DSM-IV. For CD the DSM-IV includes two criteria that are not in version III-R: (1) often bullies, threatens or intimidates others; and (2) often stays out at night despite parental prohibitions, beginning before the age of 13. The DSM-IV also requires that truancy begin before the age of 13 to be counted. 2.5. Data analysis We utilized family history information to test for a potential selection bias among parents of patients, because in 57% of the patient families fathers were not interviewed. Using direct interview information on mother–father pairs we conducted mean comparisons on demographic, diagnostic and dimensional measures. We expected the prevalence of antisocial behavior and substance problems to differ between parents of patients and parents of controls because: (1) adolescent patients were selected for substance and conduct problems, and community control adolescents were not; and (2) antisocial behavior and substance use disorders are familial (Lahey et al., 1988). Chi square analyses were utilized to examine differences for categorical variables, but when expected counts were less than five for at least one cell, Fisher’s exact test was used. Independent t-tests were utilized to compare means; when variables deviated appreciably from normality, Mann–Whitney U-statistics were also calculated.

To test for mate similarity, Spearman rank ordered correlations (dimensional) and tetrachoric correlations (diagnostic) were computed. Fisher’s Z-transformations of estimated correlation coefficients were computed to test whether differences between correlations were significant. Multiple regression analyses were conducted to assess the significance of a cross-spouse cross-domain variable while adjusting for a cross-spouse within-domain variable. All hypothesis testing was two tailed with a significance level of 0.05.

3. Results 3.1. Family history data We examined family history data collected on this sample to see if patient families in which one parent was interviewed differed significantly from families in which both parents were interviewed. Family history information was only available on a subset of parents of patients (n = 469; 56%), as this assessment was added to the battery midway through collection of the overall sample. Mothers of patients from families with one parent interviewed did not differ significantly from mothers from families with both parents interviewed (alcohol dependence χ12 = 0.22; any illicit drug dependence χ12 = 0.12 ASPD χ12 = 2.38). However, fathers from families where one parent was interviewed were more likely to have alcohol dependence (χ12 = 8.02) and ASPD (χ12 = 5.33) but not any illicit drug dependence (χ12 = 0.56) when compared with fathers from families with both parents interviewed. This suggests that by requiring direct interviews of both parents we may have under-sampled fathers with alcohol dependence and ASPD in patient families. 3.2. Demographics Parents of adolescent patients differed on a number of demographic variables compared with parents of controls (Table 1). About half of mothers of clinical patients were under 40 years old, as opposed to about one fifth of mothers of controls. Within control families, most parents (93.6% of mothers, 95.1% of fathers) were currently married and most (92.2%) were still married to the proband’s biological mother–father. Among patient families about two thirds (67.1% of mothers, 64.4% of fathers) of parents were currently married and about half (47%) were still married to the proband’s biological mother–father. About 30% of mothers and fathers of patients had produced a child with two or more partners, while less than 11% of controls had. Parents of patients and controls had similar numbers of children but about 45% of mothers of patients had their first child at 10–19 years old, as opposed to about 13% of mothers of controls. Due to non-normality Mann–Whitney U-statistics were also examined but did not change significance.

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Table 1 Parent demographics—mothers and fathers of adolescents admitted to a substance abuse treatment facility and mothers and fathers of control adolescents Fathers

Age Mean

Mothers

Patient (n = 149)

Control (n = 204)

44.3

46.3 95.1% (194)

Currently married Yes 64.4% (96)

Currently married to proband’s biological mother–father Yes 47.0% (70) 92.2% (188) Number of partners with 1 74.5% 2 21.5% 3 2.7% 4 or more 1.4% Mean

Total number of children Mean 3.2

Mean a

Control (n = 204)

t349 = 2.85a

40.5

44.3

t348 = 6.69a

χ12 = 55.6a

67.1% (100)

93.6% (191)

χ12 = 42.6a

χ12 = 89.8a

47.0% (70)

92.2% (188)

χ12 = 89.3a

69.8% 23.5% 5.4% 1.4%

94.6% (193) 5.4% (11) 0% (0) 0% (0)

whom produced a child (111) 89.2% (182) (32) 10.3% (21) (4) 0% (0) (2) 0% (0)

1.3

Age when had first child 10–19 16.6% 20–29 69.6% 30–39 12.4% 40–49 1.4%

Patient (n = 149)

(24) (101) (18) (2)

1.1

t199.1 = −3.82a

1.4

1.1

t169.3 = −5.57a

3.0

t352 = −0.87

3.2

3.0

t351 = −1.71

8.1% 65.7% 25.2% 1.0%

24.2

(104) (35) (8) (2)

(16) (130) (50) (2) t342 = 3.43a

26.2

44.8% (65) 52.4% (76) 2.8% (4) 0% (0)

12.5% (25) 74.0% (148) 13.5% (27) 0% (0)

20.7

24.5

t343 = 7.85a

Significant with P < 0.01.

3.3. Rates of lifetime diagnoses As shown in Table 2, rates of dependence on nicotine, alcohol, and cannabis among parents of patients were approximately twice the rates in parents of controls. As expected from studies of epidemiological samples (Anthony et al., 1994), nicotine and alcohol dependence were the most prevalent diagnoses. However, dependence on cannabis, cocaine, and stimulants were also common among parents of patients. Parents of patients had significantly higher rates of CD than parents of controls (Table 3). In addition, fathers of patients showed significantly higher rates of progression from

CD to ASPD; about twice as many fathers of patients met criteria for CD than fathers of controls but about 10 times as many fathers of patients met criteria for ASPD. 3.4. Symptom severity Table 4 shows that mothers and fathers of patients had significantly greater mean counts for ADS, ASPD-SC, and CD-SC than mothers and fathers of controls, respectively. Again, Mann–Whitney U-statistics were calculated when appropriate but agreed with parametric tests regarding whether significance was met.

Table 2 Parents meeting DSM-IIIR substance dependence lifetime diagnosis Fathers

Any substance dependence Nicotine Alcohol Cannabis Cocaine Stimulants Opioid Sedatives Hallucinogens Phencyclidine Inhalants ∗

Fisher’s exact test.

Mothers

Patient (n = 151)

Control (n = 206)

χ12

69.5% 48.3% 43.0% 19.9% 17.2% 11.9% 9.9% 4.0% 6.6% 0.7% 1.3%

50% (103) 35.0% (72) 24.3% (50) 10.7% (22) 2.4% (5) 4.4% (9) 2.9% (6) 0.5% (1) 2.9% (6) 0.5% (1) 0.5% (1)

13.7 (0.01) 6.5 (0.01) 14.1 (0.01) 5.9 (0.02) 24.0 (0.01) 7.1 (0.01) 7.8 (0.01) ∗ (0.05) 2.8 (0.09) ∗ (>0.99) ∗ (0.58)

(105) (73) (65) (30) (26) (18) (15) (6) (10) (1) (2)

(P)

Patient (n = 151)

Control (n = 206)

χ12 (P)

57.0% (86) 50.3% (76) 17.2% (26) 9.3% (14) 9.3% (14) 6.0% (9) 3.3% (5) 0.7% (1) 2.0% (3) 0.6% (1) 0% (0)

24.3% (50) 20.4% (42) 6.8% (14) 2.4% (5) 1.5% (3) 1.5% (3) 0% (0) 0.5% (1) 0.5% (1) 0.0% (0) 0% (0)

39.5 (0.01) 35.3 (0.01) 9.5 (0.01) 8.1 (0.01) 11.7 (0.01) 5.4 (0.02) ∗ (0.01) ∗ (>0.99) ∗ (0.32) ∗ (0.42)

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J.T. Sakai et al. / Drug and Alcohol Dependence 75 (2004) 165–175

Table 3 Parents with DSM-IIIR defined conduct disorder (as children) and antisocial personality disorder Fathers

CD ASPD Progression from CD to ASPD ∗

Mothers

Patient (n = 151)

Control (n = 206)

χ12

29.1% (44) 17.9% (27) 61.4%

12.1% (25) 1.5% (3) 12%

16.4 (0.001) 30.8 (0.001) 15.8 (0.001)

(P)

Patient (n = 151)

Control (n = 206)

χ12 (P)

9.9% (15) 0.7% (1)

1.5% (3) 0.5% (1)

13.1 (0.001) ∗ (>0.99)

Fisher’s exact test.

Table 4 Parent average dependence symptoms (ADS), antisocial personality disorder symptom count (ASPD-SC), and conduct disorder symptom count (CD-SC): mean (S.D.)

ADS ASPD-SC CD-SC a

Patient mothers (n = 151)

Control mothers (n = 206)

1.87 (1.61) 1.29 (1.41) 1.10 (1.30)

0.88 (1.26) 0.51 (0.87) 0.54 (0.86)

t275.1 = −6.327a t231.6 = −6.039a t241.1 = −4.568a

Patient fathers (n = 151)

Control fathers (n = 206)

2.41 (1.59) 2.76 (1.87) 2.21 (2.19)

1.59 (1.48) 1.21 (1.32) 1.47 (1.68)

t355 = −5.016a t252.4 = −8.686a t268.0 = −3.472a

Significant with P < 0.01.

3.5. Spouse correlations Table 5 shows significant positive mother–father correlations for ADS and ASPD-SC for both parents of patients and controls. The ADS correlation for parents of patients was 0.40 and for parents of controls was 0.28 (DSM-IV substance dependence symptoms were available on a subset of the sample; ADS correlations using DSM-IV symptoms were of a similar magnitude and level of significance for both parents of patients and controls). The ASPD-SC correlation for parents of patients was 0.33 and for parents of controls was 0.26. Within mothers and separately within fathers, we adjusted ADS and ASPD-SC for age, and race for both parents of

patients and then for parents of controls; we computed mate correlations for these adjusted variables. Within parents of patients, correlations for ADS and ASPD-SC were similar to unadjusted correlations (see Table 5) (adjusted-ADS 0.38, P < 0.01; adjusted-ASPD-SC 0.28, P < 0.01). For parents of controls, correlations also remained similar to unadjusted correlations (adjusted-ADS 0.20, P < 0.01; adjusted ASPD-SC 0.27, P < 0.01). Patient and control families were divided into those in which the biological parents of adolescent patients were married to each other at the time of assessment and those families where the biological parents were not married at assessment. Correlations were computed within these two groups for ADS, ASPD-SC, and CD-SC. These three sets of

Table 5 Spearman’s rank ordered correlations for average dependence symptoms (ADSa ), antisocial personality disorder symptom count (ASPD-SC), and conduct disorder symptom count (CD-SC) (lower triangle represents patient families (n = 151 pairs), upper triangle represents control families (n = 206 pairs))

J.T. Sakai et al. / Drug and Alcohol Dependence 75 (2004) 165–175

correlations were compared between groups using Fisher’s Z-transformation. Among parents of patients and controls, correlations for ADS did not differ significantly by the still-married criterion; among parents of patients, ASPD-SC correlations also did not differ significantly. Among parents of controls, the ASPD-SC correlation was significantly higher in parents not still married to each other. CD-SC was significantly correlated for parents of patients but not parents of controls. Within patient families the CD-SC correlation was of a similar magnitude to that of the ASPD-SC correlation. With few exceptions (patient family: mother ADS, father ASPD-SC; and control family: mother ADS, father CD-SC), the cross-variable spouse correlations were also significant ranging from 0.17 to 0.28 for parents of patients and from 0.14 to 0.20 for parents of controls. Spouse–spouse tetrachoric correlations were significant for SD diagnosis in both the parents of patients (correlation = 0.55, S.E. = 0.11) and community control parents (correlation = 0.35, S.E. = 0.11). Because of relatively low cell sizes for CD and ASPD, tetrachoric correlations were not reported for these diagnostic measures. To test whether lower levels of alcohol dependence among non-interviewed fathers of patients biased our sample correlations, tetrachoric correlations were computed between spouses for “any alcohol or illicit drug dependence diagnosis” generated from the family history data. Using Fisher’s Z-transformation the correlation for “any alcohol or illicit drug dependence” in families with only one parent interviewed did not differ significantly from the correlation

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for “any alcohol or illicit drug dependence” in families with both parents interviewed. 3.6. Homogamy by gender and SD or ASPD diagnosis Within families of patients, if the mother had SD, 84% (72/86) of the corresponding fathers had SD. In patient families with substance dependent fathers, 69% (72/105) of the corresponding mothers had SD. A test of proportions for gender differences in parents of patients (χ12 = 5.95), suggests that mothers with SD were significantly more likely than fathers with SD to have a mate with SD. A similar pattern was seen for parents of controls, where 68% (34/50) of mothers with SD had a mate with SD and 33% (34/103) of fathers with SD had a mate with SD. Among parents of controls, mothers with SD were significantly more likely to have a mate with SD, when compared with fathers with SD (χ12 = 16.69). In patient families some mother–father comparisons were initially suggestive of cross-variable assortment by diagnosis. When mothers in patient families had SD, 23% (20/86) of the corresponding fathers had ASPD. When fathers had ASPD in patient families, 74% (20/27) had a mate with SD. Interestingly, mothers of patients were just as likely to have SD whether the father had SD or ASPD; but 93% (25/27) of fathers of patients with ASPD also had SD, making it difficult to assess cross-variable assortment by diagnosis. Low rates of ASPD among mothers of patients and parents of controls limited power to examine cross-variable assortment by diagnosis for other parents.

Table 6 Multiple linear regressions—evaluating the effects of within-domain and cross-domain independent variables on predicting spouse’s average dependence symptoms (ADS) and antisocial personality disorder symptom count (ASPD-SC) Regression number

Dependent variable

Independent variable

B (S.E.)

95% CI B

Standardized betas

rp

P<

Patients 1

Mother ADS

Father ADS Father ASPD-SC

0.402 (0.088) −0.096 (0.075)

0.228–0.577 −0.244–0.052

0.397 −0.112

0.351 −0.099

0.01∗ 0.20

2

Father ADS

Mother ADS Mother ASPD-SC

0.310 (0.082) 0.085 (0.093)

0.148–0.472 −0.099–0.270

0.314 0.076

0.292 0.070

0.01∗ 0.36

3

Mother ASPD-SC

Father ASPD-SC Father ADS

0.197 (0.067) 0.056 (0.079)

0.065–0.329 −0.100–0.212

0.262 0.064

0.232 0.056

0.01∗ 0.48

4

Father ASPD-SC

Mother ASPD-SC Mother ADS

0.408 (0.113) −0.047 (0.099)

0.185–0.631 −0.242–0.149

0.307 −0.040

0.285 −0.037

0.01∗ 0.64

Mother ADS

Father ADS Father ASPD-SC

0.192 (0.063) 0.023 (0.071)

0.067–0.317 −0.117–0.164

0.225 0.025

0.206 0.022

0.01∗ 0.74

6

Father ADS

Mother ADS Mother ASPD-SC

0.241 (0.082) 0.217 (0.119)

0.080–0.402 −0.017–0.452

0.205 0.127

0.200 0.124

0.01∗ 0.07

7

Mother ASPD-SC

Father ASPD-SC Father ADS

0.139 (0.048) 0.052 (0.043)

0.043–0.234 −0.033–0.138

0212 0.090

0.194 0.082

0.01∗ 0.23

8

Father ASPD-SC

Mother ASPD-SC Mother ADS

0.357 (0.107) 0.064 (0.073)

0.147–0.567 −0.081–0.208

0.234 0.061

0.227 0.059

0.01∗ 0.39

Controls 5

∗

Significant with P < 0.01; B, unstandardized coefficient.

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3.7. Spouse prediction: within and across average dependence symptoms and antisocial personality disorder symptom count Table 6 shows significant within-domain mother–father relationships. For example in regression 1, mother ADS is significantly associated with father ADS, suggesting a within domain (ADS) relationship. To test for cross-variable assortment we utilized standard regression analyses and included both the cross-spouse cross-domain variable and the cross-spouse within-domain variable as independent variables. For example in regression 1, the dependent variable is mother ADS, the cross-spouse cross-domain variable is father ASPD-SC and the cross-spouse within-domain variable is father ADS. In every regression, the cross-spouse cross-domain variable yielded non-significant estimates of the regression coefficient (B) after adjusting for the cross-spouse within-domain variable. Thus, the cross-spouse cross-domain association described in Table 5 can be better explained by comorbidity than by cross assortment.

4. Discussion This study resulted in four main findings: (1) we found significant spousal correlations for average dependence symptoms and antisocial personality disorder symptoms in both clinical and control families, providing evidence of non-random mating; (2) we demonstrated significant spousal correlations for retrospective symptoms of conduct disorder among parents of patients but not among parents of controls, suggesting that assortment occurs for “life-course persistent” antisocial behavior but not “adolescent limited” conduct disorder (Moffitt, 1993); (3) we did not find evidence of cross-variable assortment (over-and-above the within domain assortment); and (4) we found significant gender differences in homogamy for substance dependence. 4.1. Spousal similarity for substance involvement and antisocial behavior Strong spousal correlations in both the clinical and control samples suggest that people have mates who are similar to themselves in terms of their substance use patterns and antisocial behavior. This supports the notion that assortment contributes to the clustering of substance dependence and antisocial personality disorder within families. This study extends previous research by (1) adding to the very limited work on assortative mating for substance dependence. In addition (2) we examined spousal homogamy in both patient and community control families. (3) Our study did not require that spouses were married or living together as has been the practice in other studies. Our study was not specifically designed to determine whether this spousal similarity is the result of phenotypic assortment, social homogamy or cohabitation effects but

some additional analyses were conducted to explore this issue. Mate similarity for age and race explained only a small portion of the observed spousal similarity for average dependence symptoms and antisocial personality disorder symptom counts. Although other environmental factors that we did not test may drive observed spousal correlations, our analyses do not support either age or race as a major explanation for mate similarity regarding substance involvement and antisocial behavior. Another possible influence on mate similarity is cohabitation, where partners become more similar through living together. We did not have information on whether spouses cohabitate but did have information on whether biological parents were currently married. Biological parents married at time of assessment were not significantly more similar in terms of average dependence symptoms and antisocial personality disorder symptom count when compared with parents not married. 4.2. Spousal similarity for conduct disorder Number of conduct disorder symptoms was significantly correlated between parents of patients, but not between parents of controls. As shown in Table 3, fathers of patients had high rates of progression from CD to ASPD, suggesting that they were more likely to have a “life-course persistent” form of antisocial behavior (Moffitt, 1993). In contrast, fathers of controls with conduct disorder were less likely to progress to antisocial personality disorder, suggesting that control fathers were more likely to have an “adolescent limited” form of this disorder (Moffitt, 1993). Mothers of patients have a high within-individual CD-SC and ASPD-SC correlation (0.43), when compared with mothers of controls (0.22), which again is suggestive of greater persistence of antisocial behavior in patient families. One interpretation is that assortment does not occur for the “adolescent limited” form of this disorder but does for “life course persistent” antisocial behavior. Although we cannot rule out cohabitation effects, since conduct disorder, by definition, has its onset in childhood and adolescence (American Psychiatric Association, 1994; Kuperman et al., 2001), it is likely that antisocial behavior pre-dated many pairings. 4.3. Cross-variable assortment Cross-spouse cross-variable (ASPD-SC and ADS) correlations were significant in both patient and control families, indicating the possibility of cross-variable assortment. But within-individual ASPD-SC and ADS correlations are highly significant and are of a magnitude equal to or greater than the within-individual correlations between ASPD-SC and CD-SC. The high cross-spouse cross-variable (ASPD-SC and ADS) correlations observed, may result from cross-variable assortment, or within-variable assortment accompanied by high within-individual comorbidity of SD and ASPD.

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We found significant gender differences in spousal similarity for substance use. Previous studies of alcohol consumption have demonstrated that there are gender differences in spousal similarity; that is, women with alcohol use disorders are more likely to have a spouse with an alcohol use disorder, when compared with men with alcohol use disorders. Results for SD diagnosis suggests that, for both patients and controls, women with SD were more likely to have partners with SD than were males with SD. This might mean that women with SD have limited mating options (men without SD are less likely to mate with them), while men with SD have more mating options (women without SD are willing to mate with them). An alternative explanation is that women with SD choose from a pool of available mates with a higher prevalence of SD (base rates for SD vary by gender and are consistently higher for men) (Kessler et al., 1994). Thus, as has been seen for alcohol dependence, base rates of alcohol dependence must be accounted for before generalizations about gender differences can be made; such adjustments must be done carefully as differences in estimated base rate may alter the conclusions drawn (Jacob and Bremer, 1986). Still a clinical implication of this result is that patients, especially women, with substance dependence are very likely to have a mate or spouse with a substance use disorder.

but from spouses becoming more similar over time through cohabitation (Caspi and Herbener, 1990). Our analyses did not support social homogamy (age and race only) or cohabitation (by the “still married” criterion only) as a major factor in the observed spousal similarity. Rigorous methods have been described to estimate the most likely cause of spousal similarity (Heath and Eaves, 1985; Nagoshi et al., 1987; Truett et al., 1994) and generally require twins and their spouses. Unfortunately, our research design cannot determine absolutely whether the mate similarity for ADS and ASPD is a product of phenotypic assortment, social homogamy, cohabitation or some combination of these processes, and future research should focus on this question. A substantial number of fathers of patients were not interviewed, potentially biasing our results. Examination of fathers of patients suggests that this was non-random with respect to alcohol dependence and antisocial personality disorder. But our analyses of family history data regarding “any alcohol or illicit drug dependence diagnosis” suggest that this bias did not significantly influence our average dependence symptoms correlations in patient families. Also, judging from our available family history data our methods apparently produced no selection bias against illicit substance dependence. It is important that potential selection bias be considered in future family studies of this and other clinical samples. Family history methods may provide additional information that help to reduce this bias. We utilized DSM-III-R criteria and it is impossible to know how well these results generalize to DSM-IV diagnoses. These criteria are quite similar to the DSM-IV but have distinct differences (see Section 2) that may limit the generalizability of our results to studies using current DSM diagnostic systems. However, available data suggest high concordance between the DSM III-R and the DSM-IV for substance dependence (Rounsaville et al., 1993; Schuckit et al., 1994; Grant, 1996) and antisocial personality disorder (Blais et al., 1997; Sunday et al., 2001).

5. Limitations

6. Conclusions

Our study has three important limitations. First, it could not discriminate between three different processes that may lead to spousal similarity. Second, a substantial number of fathers of patients were not interviewed, potentially biasing our results. Finally, we utilized DSM-III-R criteria and it is impossible to know how well these results generalize to DSM-IV diagnoses. Observed spousal similarity, homogamy, may be the result of one of three processes. Phenotypic assortment involves the pairing of mates in a manner that can lead to genetic correlations between spouses if the phenotype is heritable (Reynolds et al., 1996). With social homogamy, environmental factors, rather than genes, drive spousal correlations (Rao et al., 1974; Eaves et al., 1989). Finally, spousal correlations may result not from true assortment

In both clinical families and control families, mate similarity for SD and ASPD was greater than would be expected under random mating. If phenotypic assortment contributes to the described mate similarity, this will produce offspring with greater genetic loading for these disorders. Furthermore, families in which both parents have antisocial traits and substance dependence may create substantially more adverse rearing environments than if only one parent had these characteristics. Marital discord and hostility are associated with conduct problems in offspring (Rutter and Quinton, 1984) and family maladaptation influences offspring phenotype through environmental mechanisms (Meyer et al., 2000). Therefore, mate similarity, whatever its cause, likely plays an important role in the clustering and perpetuation of SD and ASPD within families. Assortment should be

Regression analyses (Table 6), which model the potentially comorbid symptoms, show that the cross variable spouse correlations are not likely to be driven by true cross variable assortment. Although previous research has shown cross-variable assortment for some psychiatric disorders (Maes et al., 1998), we did not find evidence supporting cross-variable assortment for substance dependence and antisocial behavior. 4.4. Gender differences

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modeled in behavior genetic studies of this population to avoid this substantial bias.

Acknowledgements This research was supported by NIDA grants DA09842, DA11015, DA12845, DA015522, DA000357, and NIMH grant 5T32MH15442.

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