Abstract
A family history (FH) of psychiatric and substance use problems is a potent risk factor for common internalizing and externalizing disorders. In a large web-based assessment of mental health in college students, we developed a brief set of screening questions for a FH of alcohol problems (AP), drug problems (DP) and depression-anxiety in four classes of relatives (father, mother, aunts/uncles/grandparents, and siblings) as reported by the student. Positive reports of a history of AP, DP, and depression-anxiety were substantially correlated within relatives. These FH measures predicted in the student, in an expected pattern, dimensions of personality and impulsivity, alcohol consumption and problems, smoking and nicotine dependence, use of illicit drugs, and symptoms of depression and anxiety. Using the mean score from the four classes of relatives was more predictive than using a familial/sporadic dichotomy. Interactions were seen between the FH of AP, DP, and depression-anxiety and peer deviance in predicting symptoms of alcohol and tobacco dependence. As the students aged, the FH of AP became a stronger predictor of alcohol problems. While we cannot directly assess the validity of these FH reports, the pattern of findings suggest that our brief screening items were able to assess, with some accuracy, the FH of substance misuse and internalizing psychiatric disorders in relatives. If correct, these measures can play an important role in the creation of developmental etiologic models for substance and internalizing psychiatric disorders which constitute one of the central goals of the overall project.
Keywords: family history, college students, alcohol, tobacco, illicit drugs
INTRODUCTION
All major psychiatric and substance use disorders are familial [Kendler and Eaves, 2005]. Because a positive family history (FH) is one of the strongest and most consistent risk factors for many psychiatric syndromes, it is difficult to develop comprehensive etiological models of risk without the inclusion of measures of familial liability.
Meeting this requirement in large-scale longitudinal studies raises three practical problems. First, directly interviewing relatives of a large subject sample is very resource intensive and often impractical. Therefore, FH methods, where the proband is asked about psychiatric and substance use problems in their relatives, is a more viable option despite methodological limitations [Andreasen et al., 1977; Kendler et al., 1991]. Second, large scale surveys often attempt to cover a wide array of disorders and risk factors. FH assessments that ask detailed questions about each relative one at a time—like the Family History Research Diagnostic Criteria [Endicott et al., 1975]—are therefore often impractical. Briefer assessments that cover groups of relatives (e.g., siblings, aunts/uncles) are more feasible. Third, ethical questions have been raised about the appropriateness of asking one individual to reveal potentially sensitive information about a second person without that second person’s consent [Coy, 2001; Kendler, 2001; Pelias, 2001]. Therefore, some ethical committees in the United States require that FH questions focus on the subject’s opinion of the possible “problems” of relatives rather than specific nature of the relative’s symptoms or signs.
A major goal of the Spit for Science survey, now on-going for all in-coming freshmen at a large public US university [Dick et al., 2014], is to develop comprehensive etiologic models for the common externalizing and internalizing symptoms and disorders that occur in young adulthood. We wished to include measures of FH both because of the strong evidence of the importance of familial factors in large adult samples [Kendler and Eaves, 2005] as well as specific evidence of the importance of a positive FH in the prediction of the use and misuse of alcohol, tobacco and illicit drugs in college students [Spielberger et al., 1983; Perkins, 1985; Kushner and Sher, 1993; Hestick et al., 2001; Baer, 2002]. Facing the difficulties noted above in FH assessment, we decided to utilize brief screening items directed at three key psychiatric/substance use syndromes in relatives: alcohol problems, drug problems and the internalizing disorders of depression and anxiety. We asked single questions asking the student respondent their opinion about whether four classes of relatives (mother, father, aunts/uncles/grandparents, and siblings) had any of these problems. Utilizing information from the first three cohorts of Spit for Science (approximate n of ~ 7,000 students), we examine the performance of these items with a focus on the prediction of alcohol and cigarette related outcomes and their associated risk factors. We hope to evaluate the potential utility of such brief measures so that others designing similar surveys can make informed decisions about whether to include them.
MATERIALS AND METHODS
As described elsewhere [Dick et al., 2014], the “Spit for Science” project attempted to enroll all incoming freshman, who were 18 years of age or older, at Virginia Commonwealth University, a diverse, urban US public university. The study design involves multiple waves of data collection including two in the freshman year, the first initiated as the freshman prepare to arrive on campus in the fall and the second in the middle of the spring semester. Further waves of data collection then occur yearly in the spring. The study is on-going and the present paper focuses on results from wave one for cohorts one through three. We also examine results from waves two and three of cohort one. DNA collection is part of the protocol but not involved in the present analyses.
Study data were collected and managed using REDCap electronic data capture tools hosted at Virginia Commonwealth University [Harris et al., 2009]. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing: (i) an intuitive interface for validated data entry; (ii) audit trails for tracking data manipulation and export procedures; (iii) automated export procedures for seamless data downloads to common statistical packages; and (iv) procedures for importing data from external sources.
Cooperation at the first wave ranged from 57–60% across the first three cohorts. Retention rates were 80% in cohort one, and 76% in cohort two at wave two, and 59% in cohort one at wave three. Cohort one (typical for the other cohorts) was 60.3%female with a mean age (SD) of 18.5 (0.5) with the following ethnic self-identifications: American Indian/Native Alaskan (n=10, 0.5%), Asian (n=311, 15.1%), Black/African American (n=395, 19.2%), Hispanics/Latino (n=120, 5.8%),Native Hawaiian/Pacific Islander (n=17, 0.8%), White (n=1056, 51.4%), and more than one race (n=109, 5.3%), which is representative of the overall university demographics.
At wave one for all our cohorts, we assessed FH of alcohol problems (AP), drug problems (DP), and depression and anxiety (Dep–Anx) for four types of relatives: mother, father, aunts/uncles/grandparents, and siblings. Here is how the three items appeared for mothers:
Do you think your biological mother has ever had problems with alcohol? (By problems with alcohol we mean that her alcohol use caused problems at home, at work, with her health, or with the police, or that she received alcohol treatment.
Do you think your biological mother has ever had problems with other drugs? (By problems with drugs we mean that her drug use caused problems at home, at work, with her health, or with the police, or that she received drug treatment.
Do you think your biological mother has ever had problems with depression or anxiety?
These three questions were then repeated for “biological father,” aunts/uncles/grandparents, and “biological siblings.”
From the responses to each of these three questions for the four categories of relatives, we constructed two FH “scores.” The first, which was used throughout our analyses, was the standardized mean of the responses for all four categories of relatives. The second, used in one analysis, reflected whether a positive FH was reported in any of the four relative groups. We termed this the familial/sporadic measure.
At wave one, peer group deviance (PGD) was assessed by six items obtained from two validated instruments [Johnston et al., 1982; Tarter and Hegedus, 1991] that assessed the proportion of the respondent’s friends who engaged in specific deviant behaviors such as smoking cigarettes, getting drunk, having problems with alcohol, and smoking marijuana.
Personality was assessed by shortened scales from the big five inventory (BFI) [John and Srivastava, 1999]. We also utilized shortened forms of the four subscales of the UPPS Impulsive Behavior Scales from Whiteside and Lynam [Whiteside and Lynam, 2001; Lynam et al., 2006,Lynam et al., 2006]. These scales were used in the first wave of data collection only in the second and third cohorts. We also utilized DSM-IV criteria (American Psychiatric Association, 1994) for Alcohol Abuse and Dependence (here termed Alcohol Use Disorder) and the Fagerström Scale for the assessment of symptoms of nicotine dependence [Heatherton et al., 1991]. Symptoms of anxiety and depression within the last 30 days were assessed using items from the SCL [Derogatis et al., 1973]. Illicit drug use was assessed by summing yes/no responses to ever use of cannabis, sedatives, stimulants, cocaine or opioids (exclusive of those prescribed by a doctor).
For all analyses, missingness was quite modest. We analyzed the mean response for all individuals who answered ≥30% of the items. All continuous scales were then z-transformed for ease of interpretation.
RESULTS
Descriptive Statistics
The mean endorsement rates across the four groups of relatives were considerably higher for Depression or Anxiety (Dep–Anx) (42.0 ± 0.4%) than for Alcohol Problems (AP) (26.2 ± 0.3%) which in turn were higher than for Drug Problems (DP) (16.7 ± 0.3%). Table I shows the specific responses by relative class. Comparing mothers and fathers, we see the expected higher rates of Dep–Anx in mothers and higher rates of AP and DP in fathers. The very high rate of AP in any aunts/uncles/grandparents is noteworthy. Only in the siblings are rates of DP higher than rates of AP.
TABLE I. Proportion of Positive Family History Reports by Relative Class (n = 6,032–7169).
Relatives | % Alcohol problems | % Drug problems | % Depression or anxiety |
---|---|---|---|
Mother | 8.7 ± 0.3 | 5.8 ± 0.3 | 44.8 ± 0.6 |
Father | 23.9 ± 0.5 | 14.0 ± 0.4 | 30.0 ± 0.6 |
Aunts/Uncles/Grandparents | 59.8 ± 0.6 | 34.8 ± 0.6 | 54.7 ± 0.6 |
Siblings | 11.4 ± 0.4 | 12.3 ± 0.4 | 32.6 ± 0.6 |
The total FH scores were substantially inter-correlated. The Pearson correlations (N~ 7,300) were highest for AP and DP (+ 0.56), intermediate for AP and Dep–Anx (+ 0.46), and lowest for DP and Dep–Anx (+ 0.42). Tables II and III depict the tetrachoric correlations for FH Report of AP, DP, and Dep–Anx across the four different relative groups. The correlations were highest for Dep–Anx (with a mean inter-relative correlation of + 0.63), intermediate for DP (with a mean of + 0.44) and lowest for AP (with a mean of + 0.40).
TABLE II. Tetrachoric Correlations for Family History Report of Alcohol Problems (above the Diagonal) and Drug Problems (below the Diagonal) in Different Groups of Relatives (n = 5511–6476).
Relatives | Mother | Father | Aunts, Uncles and Grandparents | Siblings |
---|---|---|---|---|
Mother | − | + 0.36 ± 0.03 | + 0.41 ± 0.03 | + 0.41 ± 0.03 |
Father | + 0.56 ± 0.03 | − | + 0.49 ± 0.02 | + 0.37 ± 0.03 |
Aunts/Uncles/Grandparents | + 0.45 ± 0.03 | +0.51 ± 0.02 | − | + 0.37 ± 0.03 |
Siblings | + 0.42 ± 0.03 | + 0.34 ± 0.03 | + 0.34 ± 0.03 | − |
TABLE III. Tetrachoric Correlations for Family History Report of Depression and Anxiety in Different Groups of Relatives (n = 5244–5723).
Relatives | Mother | Father | Aunts, uncles and grandparents | Siblings |
---|---|---|---|---|
Mother | − | +0.61 ± 0.02 | +0.71 ± 0.01 | +0.61 ± 0.02 |
Father | − | +0.68 ± 0.02 | +0.57 ± 0.02 | |
Aunts/uncles/grandparents | − | +0.63 ± 0.02 | ||
Siblings | − |
Associations with Family History Scores
We next explored the associations between the FH scores and certain key predictor and outcome variables in the study when both predictor and dependent variables were standardized. Table IV shows that the associations with personality assessed by the five factor model were generally quite modest. A FH of AP and DP were weakly and negatively associated with conscientiousness and agree-ableness, and weakly and positively associated with openness, extraversion and neuroticism. The strongest finding was the association between a FH of Dep–Anx and high neuroticism levels.
TABLE IV. Prediction of Personality from Aggregate Indices of Family History for Alcohol Problems, Drug Problems and Depression and Anxiety (n = 7,181–7,285).
Family history of | Openness | Conscientiousness | Extraversion | Agreeableness | Neuroticism |
---|---|---|---|---|---|
Alcohol problems | +0.07# | −0.02 | +0.03+ | −0.06# | +0.09# |
Drug problems | +0.08# | −0.04+ | +0.05# | −0.06# | +0.07# |
Depression or anxiety | +0.14# | −0.09# | −0.01 | −0.06# | +0.21# |
All variables are standardized. Controlling for cohort.
p< 0.05
p<0.01
p<0.001
p<0.0001.
As seen in Table V, a FH of AP and DP were associated with modestly higher levels of all the impulsivity dimensions. Unexpectedly, a FH of Dep–Anx was even more strongly associated with the impulsivity, although not with sensation seeking.
TABLE V. Prediction of Dimensions of Impulsivity from Aggregate Indices of Family History for Alcohol Problems, Drug Problems and Depression and Anxiety (n = 3,891–3,924).
Family history of | Negative urgency | Lack of premeditation | Lack of perseverance | Positive urgency | Sensation seeking |
---|---|---|---|---|---|
Alcohol problems | +0.08# | +0.11# | +0.06& | +0.04* | +0.03 |
Drug problems | +0.07# | +0.09# | +0.06& | +0.04+ | +0.04* |
Depression or anxiety | +0.14# | +0.12# | +0.09# | +0.06& | +0.00 |
All variables are standardized. Controlling for cohort.
p< 0.05
p<0.01
p<0.001
p<0.0001.
We then examined, in the upper part of Table VI, the association between our aggregate FH measures averaged across all four classes of relatives and six substance use and problem outcomes, and symptoms of depression and anxiety. These measures were, in general, more robust than those seen with the personality and personality-like constructs. For example, one standard deviation increase in our FH measure of AP was associated with a 59% increased risk of initiating drinking and increased of nearly a fifth of a standard deviation in the level of alcohol consumption and number of endorsed alcohol use disorder criteria. The effect of a FH of DP and Dep–Anx on these alcohol related outcomes were slightly weaker.
TABLE VI. Prediction of Alcohol Consumption and Symptoms of Alcohol Use Disorder and Nicotine Dependence from Aggregate Indices or Dichotomies of the Family History for Alcohol Problems, Drug Problems and Depression and Anxiety.
Family history of | Index (I) or dichotomy (D)~ |
Ever drank alcohol@ |
Alcohol Consumption^ |
Number of aud symptoms^ |
Ever smoked cigarettes@ |
Symptoms of nicotine dependence^ |
Number of illicit drugs used^ |
Symptoms of depression^ |
Symptoms of anxiety^ |
---|---|---|---|---|---|---|---|---|---|
Alcohol problems | I | 1.59# | +0.18# | +0.17# | 1.39# | +0.13# | +0.22# | +0.16# | +0.14# |
Drug problems | I | 1.45# | +0.14# | +0.16# | 1.34# | +0.16# | +0.24# | +0.14# | +0.14# |
Depression or anxiety | I | 1.36# | +0.15# | +0.18# | 1.49# | +0.14# | +0.25# | +0.30# | +0.25# |
| |||||||||
Alcohol problems | D | 1.44# | +0.17# | +0.13# | 1.32# | +0.07# | +0.16# | +0.13# | +0.10# |
Drug problems | D | 1.41# | +0.14# | +0.13# | 1.33# | +0.12# | +0.21# | +0.13# | +0.12# |
Depression or anxiety | D | 1.36# | +0.16# | +0.16# | 1.41# | +0.09# | +0.21# | +0.23# | +0.18# |
N | 7,117–7,213 | 6,990–7,085 | 5,845–5,917 | 7,169–7,270 | 6,506–6,596 | 5,763–5,840 | 5,753–5,823 | 5,754–5,824 |
Controlling for cohort.
p< 0.05
p<0.01
p<0.001
p<0.0001. ffi - linear regression, beta presented;
logistic regression, OR presented.
The dichotomy means that families were divided into those that had one or more versus no relatives with Alcohol Problems, Drug Problems and Depression and Anxiety.
Given that these were our primary outcomes of interest, we examined whether the predictive effect of FH varied by the sex of the student. For the six continuous dependent variables in Table V (alcohol consumption, and number of AUD and nicotine dependence symptoms, number of illicit drugs used and number of depressive and anxious symptoms), we interacted sex with our three FH measures. None of the 18 interactions were significant indicating no evidence for cross-sex differential prediction from FH measures.
Smoking initiation was most strongly predicted by a FH of Dep–Anx followed by AP and then DP. A one standard deviation increase in our FH measure of Dep–Anx was associated with a 49% increased risk of initiating smoking. Symptoms of nicotine dependence were most strongly predicted by a FH of DP.
Each of our three FH measures was associated with a moderately increased risk of illicit drug use. Symptoms of anxiety and depression were relatively strongly predicted by a FH of Dep–Anx and more weakly by family histories of AP and DP.
In the lower half of Table VI, we repeated these analyses applying a familial/sporadic dichotomy to our FH scores. We were interested in seeing how much predictive power would have been lost by down-coding our data to a simple “familial/sporadic” dichotomy. Nearly all of the regression coefficients were modestly to moderately lower than those seen where we used an average score across our four classes of relatives.
We then examined how FH reports about different classes of relatives predicted three of our key drug outcome measures: alcohol consumption, and symptoms of alcohol and nicotine abuse/dependence. As seen in Table VII, there was relatively modest variation across the different reports. Reports from aunts/uncles/grandparents were among the strongest predictors of our two alcohol-related outcomes, but the weakest in predicting symptoms of nicotine dependence.
TABLE VII. Relative Strength of the Prediction of Alcohol Consumption and Symptoms of Alcohol Use Disorder and Nicotine Dependence from a History of for Alcohol Problems, Drue Problems and Depression and Anxietu in Mother, Father, Aunts/uncles/grandparents (GP) and Siblings.
Beta coefficient (± se) for alcohol consumption (n = 5,785–6,808) |
Beta coefficient (± se) for number of aud symptoms (n = 4,822–5,677) |
Beta coefficient (± se) for symptoms of nicotine dependence (n = 5,379-6,386) |
||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Family history of |
Mother | Father | Aunts, uncles, GPs |
Siblings | Mother | Father | Aunts, uncles, GPs |
Siblings | Mother | Father | Aunts, uncles, GPs |
Siblings |
Alcohol problems | + 0.10# (± 0.01) |
+ 0.11# (± 0.01) |
+ 0.15# (± 0.01) |
+ 0.09# (± 0.01) |
+ 0.10# (± 0.01) |
+ 0.10# (± 0.01) |
+ 0.12# (± 0.01) |
+ 0.12# (± 0.01) |
+ 0.09# (± 0.01) |
+ 0.07# (± 0.01) |
+ 0.07# (± 0.01) |
+ 0.10# (± 0.01) |
Drug problems | + 0.08# (± 0.01) |
+ 0.08# (± 0.01) |
+ 0.12# (± 0.01) |
+ 0.10# (± 0.01) |
+ 0.09# (± 0.01) |
+ 0.10# (± 0.01) |
+ 0.11# (± 0.01) |
+ 0.12# (± 0.01) |
+ 0.12# (± 0.01) |
+ 0.11# (± 0.01) |
+ 0.09# (± 0.01) |
+ 0.13# (± 0.01) |
Depression or anxiety |
+ 0.12# (± 0.01) |
+ 0.11# (± 0.01) |
+ 0.15# (± 0.01) |
+ 0.11# (± 0.01) |
+ 0.13# (± 0.01) |
+ 0.13# (± 0.01) |
+ 0.17# (± 0.01) |
+ 0.16# (± 0.01) |
+ 0.10# (± 0.01) |
+ 0.12# (± 0.01) |
+ 0.09# (± 0.01) |
+ 0.12# (± 0.01) |
All variables are standardized
p< 0.05
p<0.01
p<0.001
p<0.0001.
In Table VIII, we examined whether those at familial risk for AP, DP or Dep–Anx were more sensitive to the effects of peer deviance in predicting three substance-related outcomes: alcohol consumption, and symptoms of alcohol and nicotine abuse/dependence. Of the nine analyses, six demonstrated significant interactions all in the expected direction—that FH factors had a stronger impact on substance use measures when the respondent reported high levels of peer deviance.
TABLE VIII. Interactions between Family History for Alcohol Problems, Drug Problems and Depression and Anxiety and Peer Deviance in the Prediction of Alcohol Consumption, and Symptoms of Symptoms of Alcohol Use Disorder (AUD) and Nicotine Dependence.
Alcohol consumption (n = 6,962–7,057) |
Number of AUD symptoms (n = 5,823–5,892) |
Symptoms of nicotine dependence (n = 6,486–6,576) |
|||||||
---|---|---|---|---|---|---|---|---|---|
Family History of | FH measure | Peer deviance | Interaction | FH measure | Peer deviance | Interaction | FH measure | Peer deviance | Interaction |
Alcohol problems | + 0.05# | + 0.52# | −0.01 | + 0.08# | + 0.41# | + 0.03* | + 0.06# | + 0.26# | + 0.05# |
Drug problems | + 0.03# | + 0.53# | −0.04# | + 0.09# | + 0.42# | 0.00 | + 0.09# | + 0.25# | + 0.05# |
Depression or anxiety | + 0.01 | + 0.53# | 0.00 | + 0.08# | + 0.41# | +0.08# | + 0.07# | + 0.25# | + 0.07# |
All variables are standardized
p< 0.05
p<0.01
p<0.001
p<0.0001.
Finally, we examined in Table IX whether FH measures obtained at wave one early in the freshman year became a better predictor of substance use related outcomes over the next two years of college. For alcohol consumption, our FH measures actually became less predictive over time. However, FH of both AP and Dep–Anx became more predictive of symptoms of alcohol use disorder and nicotine dependence over the first three years of college.
TABLE IX. Prediction of Alcohol Consumption and Symptoms of Alcohol Use Disorder and Nicotine Dependence Across the First Three Years of College from Aggregate Indices of Family History for Alcohol Problems, Drug Problems and Depression and Anxiety.
Beta coefficient (± se) for alcohol consumption |
BEta coefficient (± se) for number of alcohol use disorder symptoms |
Beta coefficient (± se) for symptoms of nicotine dependence |
|||||||
---|---|---|---|---|---|---|---|---|---|
Family history of | Year 1 | Year 2 | Year 3 | Year 1 | Year 2 | Year 3 | Year 1 | Year 2 | Year 3 |
Alcohol problems | + 0.17# (± 0.02) |
+ 0.16# (± 0.03) |
+ 0.13# (± 0.03) |
+ 0.16# (± 0.02) |
+ 0.18# (± 0.03) |
+ 0.23# (± 0.03) |
+ 0.11# (± 0.02) |
+ 0.14# (± 0.03) |
+ 0.15# (± 0.03) |
Drug problems | + 0.12# (± 0.02) |
+ 0.12# (± 0.03) |
+ 0.09+ (± 0.03) |
+ 0.14# (± 0.02) |
+ 0.15# (± 0.03) |
+ 0.13# (± 0.03) |
+ 0.15# (± 0.02) |
+ 0.19# (± 0.03) |
+ 0.16# (± 0.03) |
Depression or anxiety | + 0.12# (± 0.02) |
+ 0.12# (± 0.03) |
+ 0.10+ (± 0.03) |
+ 0.15# (± 0.02) |
+ 0.16# (± 0.03) |
+ 0.19# (± 0.03) |
+ 0.15# (± 0.02) |
+ 0.18# (± 0.03) |
+ 0.21# (± 0.03) |
N | 2366–2405 | 1200–1226 | 898–923 | 1966–1996 | 1055–1077 | 823–845 | 2230–2269 | 1042–1064 | 838–860 |
All variables are standardized
p< 0.05
p<0.01
p<0.001
p<0.0001.
DISCUSSION
The goal of this paper was to explore the utility of brief FH screening items for AP, DP, and Dep–Anx in a large sample of college students. Because we have no direct information about the diagnostic status of relatives of these students, we could not directly address the validity of these measures. Rather, we have to judge their potential value more indirectly.
Before we turn to the potential validity of these measures, some more practical observations are in order. Our four categories of relatives were heterogeneous. Two of them (mother and father) involved single relatives and two of them multiple relative (aunts/uncles/grandparents, and siblings). To save time, we did ask the student to record the total number of siblings or aunts/uncles/grandparents they had. Three of the categories (mother, father, and aunts/uncles/grandparents) included older relatives who would have largely lived through their age at risk for AP, DP, and mood and anxiety disorders, and one category (siblings) would have been much younger and still at future risk for these syndromes. Finally, one of the categories (aunts/uncles/grandparents) consisted of second degree relatives while the other three were all first degree relatives. In light of these substantial differences, it was rather surprising that all the categories were, to an approximately similar degree inter-correlated. No one category stood out as particularly poorly related to the others. Furthermore, in examining the prediction of key drug-related outcome variables, none of the four categories were consistently more poorly related to these outcomes than the others. Despite their heterogeneity, it would appear as each of these four categories of relatives provided useful information about family risk. This conclusion was verified when we “down-coded” our results across the four classes of relatives into a simple familial/sporadic dichotomy. We lost, for nearly all of our outcomes, a modest to moderate amount of predictive power.
Turning to the potential validity of our measures, we note that, consistent with epidemiological evidence [Kessler et al., 1994], our FH measures produced the expected differences in rates of disorders in mothers versus fathers with the former having higher rates of Dep–Anx and the latter of AP and DP. Interestingly, we see cohort effects with the ratio of DP to AP only exceeding unity in siblings—those of the same generation as the student respondents. Consistent with our findings, prior reports have noted positive genetic correlations between alcohol problems and personality measures of negative emotionality and undercontrol [Slutske et al., 2002] as well as between drug use and misuse, and neuroticism, extraversion, and sensation seeking [Agrawal et al., 2004]. A large literature on the children of alcoholics has noted, congruent with our findings, that they often have higher levels of extraversion, impulsivity, and neuroticism [Sher, 1997]. While the observed associations between our FH measures and personality-like traits are small, they are in the expected direction. The modest predictive ability of our FH measures might in part be explained by the lower stability of personality measures in late adolescence compared to adulthood [Caspi and Roberts, 2001].
Consistent with prior studies in college students [Spielberger et al., 1983; Perkins, 1985; Kushner and Sher, 1993; Hestick et al., 2001; Baer, 2002], we found more robust associations between our FH measures and psychoactive substance use and problems. Given the evidence for substantial sharing of familial vulnerability to AP and DP [Kendler et al., 2003; Hicks et al., 2004; Kendler et al., 2011a], our observations of cross-prediction (e.g., a FH of DP predicts alcohol use and problems and a FH of AP predicts illicit substance use) was expected. Our observed association of a FH of Dep–Anx and smoking are also congruent with prior studies showing a relatively robust genetic relationship between vulnerability to MD and smoking [Kendler et al., 1993b; Lyons et al., 2008].
In accord with a large body of work showing substantial familial/genetic influences on depression and anxiety [Sullivan et al., 2000; Hettema et al., 2001], a FH of Dep–Anx was moderately correlated with self-report symptoms of depression and anxiety. Consistent with prior studies showing only partial overlap of familial/genetic risk for depression and alcohol use disorders [Kendler et al., 1993a], the association of familial AP with depressive and anxious symptoms was quite a bit weaker than that observed for a FH for Dep–Anx. A range of prior studies found that individuals at high familial/genetic risk for drug or alcohol problems were more sensitive to the pathogenic effects of high levels of peer deviance [Dick et al., 2007; Harden et al., 2008; Kendler et al., 2011b; Kendler et al., 2014]. We tested this using our FH measures, attempting to predict alcohol intake and symptoms of alcohol use disorder and nicotine dependence. Three of the six analyses were significant and in the expected direction. We also found that a high familial risk for Dep–Anx also increased sensitivity to deviant peers in the prediction of symptoms of alcohol use disorder and nicotine dependence.
Several studies have suggested that the impact of genetic factors on alcohol and nicotine intake and/or problems increase over the years of late adolescence and early adulthood [Koopmans et al., 1997; White et al., 2003; Malone et al., 2004; Kendler et al., 2008; McGue et al., 2014]. We explored whether we might see a similar effect utilizing our FH measures. We partially replicated these prior findings. In particular, our FH measures of AP and Dep–Anx became more predictive of both symptoms of alcohol use disorder and nicotine dependence over the first three years of college.
A large literature has suggested that psychopathology can be usefully divided into two broad categories of internalizing and externalizing disorders [Krueger, 1999; Krueger et al., 2001] and that this division is in part the result of the genetic factors [Kendler et al., 1995; Kendler et al., 2011a]. Of our FH measures, two—AP and DP—were clearly externalizing syndromes and one—Dep–Anx— was clearly internalizing. We had expected that family histories of AP and DP would be consistently more strongly associated with externalizing symptoms and problems in our student probands than the FH of Dep–Anx. For most externalizing outcomes this was not the case as they were frequently predicted nearly as strongly by a FH of Dep–Anx as of AP and/or DP. We also expected that a FH of Dep–Anx would be more robustly associated with internalizing traits and symptoms in our students than a family background characterized by AP and DP. Here our results were consistent with expectation. Dep–Anx in relatives predicted the classical internalizing personality trait —neuroticism —and symptoms of anxiety and depression much more strongly than a FH of AP and DP. We currently have no compelling explanation for this asymmetry in relationships and will be particularly curious to see if it changes as the students age.
Waldron et al. [2012] recently reported that across relative agreement for FH reports of alcohol problems were lower in African–American (AA) versus European–American (EA) families. We therefore examined interactions between EA vs AA status and aggregate FH measures for AP, DP and Dep–Anx for the six continuous dependent measures in table V. Of the 18 analyses, six were significant at P< 0.01 in the same direction indicating weaker prediction in AA vs EA families and all involved prediction of nicotine dependence or drug abuse/dependence. These results, unlikely due to chance effects, are consistent with findings from Waldron et al suggesting that FH measures may be less predictive in AA families.
Limitations
The main methodological limitation of this study relates to the FH measures themselves. Prior research has demonstrated that, in general, when validated against personal interviews, FH measures typically have high specificity (i.e., generate few false positives) but moderate sensitivity (generates many false negatives) [Andreasen et al., 1977; Thompson et al., 1982; Gershon and Guroff, 1984; Andreasen et al., 1986]. Prior work has also suggested that FH methods work better for drug related disorders than for mood or anxiety disorders, perhaps because the former often have more overt and easily observable behavioral consequences than the latter [Kosten et al., 1992; Roy et al., 1996]. However, further research had demonstrated other potential biases. For example, respondents are generally more accurate in reporting on psychiatric problems in their parents than in reporting on their own children [Roy et al., 1996; Mendlewicz et al., 1975]. Most importantly, there is evidence for a potentially complex set of “projection biases” on FH reports. For major depression or generalized anxiety disorder, affected individuals are more likely to report that diagnosis in relatives than unaffected individuals [Kendler et al., 1991; Chapman et al., 1994; Roy et al., 1996). In one of the most careful studies of this question to date [Kendler et al., 2002] which included structural modeling of personal interview, FH diagnosis and potential projection biases in twin pairs showed that the latent liability to illness was somewhat better indexed by personal interview for major depression, generalized anxiety disorder and drug abuse but alcohol use disorders was better indexed by the FH report. Furthermore, projection biases were positive for major depression and generalized anxiety disorder but negative for alcohol and drug use disorders! One way to understand these results is that once an individual has suffered from depression or anxiety she is more sensitive to seeing those problems in relatives. However, someone who heavily uses drugs or alcohol is more likely to consider heavy use to be normative and very high levels of problems would be needed in a relative from then to consider them disordered.
CONCLUSIONS
In a large sample of college students attending a public US University, we found that simple questions that inquired about the history of AP, DP, and Dep–Anx from four relative classes were highly inter-correlated, with each class of relatives contributing useful information. These scores modestly predicted personality, impulsivity and sensation seeking in a manner consistent with prior literature. FH measures somewhat more strongly predicted alcohol and nicotine use and abuse/dependence, illicit drug use and symptoms of depression and anxiety in patterns broadly consistent with prior findings. The measures of AP and Dep–Anx interacted with peer deviance in the prediction of alcohol and nicotine outcomes and became stronger predictors of symptoms of alcohol and nicotine dependence over the first three years of college. We cannot determine the degree to which these observed associations with our FH variables result from positive projection bias on the part of the student respondents versus the true impact of familial vulnerability. Both the prior literature and the overall pattern of our findings however suggest that a substantial part of the predictive power of these measures derive from their ability to accurately assess the FH of substance misuse and internalizing psychiatric disorders. If correct, these measures will play an important role in the creation of developmental etiologic models for substance and internalizing psychiatric disorders which constitute one of the central goals of the Spit for Science study.
ACKNOWLEDGMENTS
Spit for Science: The VCU Student Survey is funded by R37AA011408 (to KSK) from the National Institute on Alcohol Abuse and Alcoholism, with support for DMD through K02AA018755. Additional support for the project was obtained through National Institutes of Health P20 AA107828, K01 AA021399, Virginia Commonwealth University, and UL1RR031990 from the National Center for Research Resources and National Institutes of Health Roadmap for Medical Research. We would like to thank the VCU students for making this study a success, as well as the many VCU faculty, students, and staff who contributed to the design and implementation of the project.
Footnotes
Conflict of interest: None of the authors has any conflicting financial interests to disclose.
REFERENCES
- Agrawal A, Jacobson KC, Prescott CA, Kendler KS. A twin study of personality and illicit drug use and abuse/dependence. Twin Res. 2004;7:72–81. doi: 10.1375/13690520460741462. [DOI] [PubMed] [Google Scholar]
- American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders. Fourth Edition American Psychiatric Association; Washington, DC: 1994. [Google Scholar]
- Andreasen NC, Endicott J, Spitzer RL, Winokur G. The family history method using diagnostic criteria. Reliability and validity. Arch Gen Psychiatry. 1977;34:1229–1235. doi: 10.1001/archpsyc.1977.01770220111013. [DOI] [PubMed] [Google Scholar]
- Andreasen NC, Rice J, Endicott J, Reich T, Coryell W. The family history approach to diagnosis. How useful is it? Arch Gen Psychiatry. 1986;43:421–429. doi: 10.1001/archpsyc.1986.01800050019002. [DOI] [PubMed] [Google Scholar]
- Baer JS. Student factors: Understanding individual variation in college drinking. J Stud Alcohol Suppl. 2002:40–53. doi: 10.15288/jsas.2002.s14.40. [DOI] [PubMed] [Google Scholar]
- Caspi A, Roberts BW. Personality development across the life course: The argument for change and continuity. Psychol Inq. 2001;12:49–66. [Google Scholar]
- Chapman TF, Mannuzza S, Klein DF, Fyer AJ. Effects of informant mental disorder on psychiatric family history data. Am J Psychiatry. 1994;151:574–579. doi: 10.1176/ajp.151.4.574. [DOI] [PubMed] [Google Scholar]
- Coy KL. The current privacy environment: Implications for third-party research. J Contin Educ Health Prof. 2001;21:203–214. doi: 10.1002/chp.1340210404. [DOI] [PubMed] [Google Scholar]
- Derogatis LR, Lipman RS, Covi L. SCL-90: An outpatient psychiatric rating scale-preliminary report. Psychopharmacol Bull. 1973;9:13–28. [PubMed] [Google Scholar]
- Dick DM, Nasim A, Edwards AC, Salvatore J, Cho SB, Adkins A, Meyers J, Yan J, Cooke M, Clifford J, Goyal N, Halberstadt L, Ailstock K, Neale Z, Opalesky J, Hancock L, Donovan KK, Sun C, Riley B, Kendler KS. Spit for Science: Launching a longitudinal study of genetic and environmental influences on substance use and emotional health at a large US university. Front Genet. 2014;5:1–12. doi: 10.3389/fgene.2014.00047. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Dick DM, Pagan JL, Viken R, Purcell S, Kaprio J, Pulkkinen L, Rose RJ. Changing environmental influences on substance use across development. Twin Res Hum Genet. 2007;10:315–326. doi: 10.1375/twin.10.2.315. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Endicott J, Andreasen N, Spitzer RL. Family History-Research Diagnostic Criteria. New York State Psychiatric Institute, Biometrics Research Department; New York: 1975. [Google Scholar]
- Gershon ES, Guroff JJ. Information from relatives. Diagnosis of affective disorders. Arch Gen Psychiatry. 1984;41:173–180. doi: 10.1001/archpsyc.1984.01790130069010. [DOI] [PubMed] [Google Scholar]
- Harden KP, Hill JE, Turkheimer E, Emery RE. Gene-environment correlation and interaction in peer effects on adolescent alcohol and tobacco use. Behav Genet. 2008;38:339–347. doi: 10.1007/s10519-008-9202-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)-a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–381. doi: 10.1016/j.jbi.2008.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addiction. 1991;86:1119–1127. doi: 10.1111/j.1360-0443.1991.tb01879.x. [DOI] [PubMed] [Google Scholar]
- Hestick H, Perrino SC, Rhodes WA, Sydnor KD. Trial and lifetime smoking risks among African American college students. J Am Coll Health. 2001;49:213–219. doi: 10.1080/07448480109596306. [DOI] [PubMed] [Google Scholar]
- Hettema JM, Neale MC, Kendler KS. A review and meta-analysis of the genetic epidemiology of anxiety disorders. Am J Psychiatry. 2001;158:1568–1578. doi: 10.1176/appi.ajp.158.10.1568. [DOI] [PubMed] [Google Scholar]
- Hicks BM, Krueger RF, Iacono WG, McGue M, Patrick CJ. Family transmission and heritability of externalizing disorders: a twin-family study. Arch Gen Psychiatry. 2004;61:922–928. doi: 10.1001/archpsyc.61.9.922. [DOI] [PubMed] [Google Scholar]
- John OP, Srivastava S. The Big-Five Trait Taxonomy: History, Measurement, and Theoretical Perspectives. In: Pervin LA, editor. Handbook of personality: Theory and research. 2nd ed. Guilford Press; New York: 1999. pp. 102–139. Second Edition. [Google Scholar]
- Johnston LD, Bachman JG, O’Malley PM. Monitoring the future: Questionnaire responses from the nation’s high school seniors 1981. Institute for Social Research; Ann Arbor, MI: 1982. Reference Volume 1-286. [Google Scholar]
- Kendler KS. Family history information in biomedical research. J Contin Educ Health Prof. 2001;21:215–223. doi: 10.1002/chp.1340210405. [DOI] [PubMed] [Google Scholar]
- Kendler KS, Aggen SH, Knudsen GP, Roysamb E, Neale MC, Reichborn-Kjennerud T. The Structure of Genetic and Environmental Risk Factors for Syndromal and Subsyndromal Common DSM-IV Axis I and All Axis II Disorders. Am J Psychiatry. 2011a;168:29–39. doi: 10.1176/appi.ajp.2010.10030340. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kendler KS, Eaves LJ. Psychiatric Genetics, Review of Psychiatry. Vol. 24. American Psychiatric Publishing, Inc.; Arlington, VA: 2005. [Google Scholar]
- Kendler KS, Gardner C, Dick DM. Predicting alcohol consumption in adolescence from alcohol-specific and general externalizing genetic risk factors, key environmental exposures and their interaction. Psychol Med. 2011b;41:1507–1516. doi: 10.1017/S003329171000190X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kendler KS, Heath AC, Neale MC, Kessler RC, Eaves LJ. Alcoholism and major depression in women. A twin study of the causes of comorbidity. Arch Gen Psychiatry. 1993a;50:690–698. doi: 10.1001/archpsyc.1993.01820210024003. [DOI] [PubMed] [Google Scholar]
- Kendler KS, Neale MC, MacLean CJ, Heath AC, Eaves LJ, Kessler RC. Smoking and major depression. A causal analysis. Arch Gen Psychiatry. 1993b;50:36–43. doi: 10.1001/archpsyc.1993.01820130038007. [DOI] [PubMed] [Google Scholar]
- Kendler KS, Ohlsson H, Sundquist K, Sundquist J. Peer Deviance, Parental Divorce, and Genetic Risk in the Prediction of Drug Abuse in a Nationwide Swedish Sample: Evidence of Environment-Environment and Gene-Environment Interaction. JAMA Psychiatry. 2014;71:439–445. doi: 10.1001/jamapsychiatry.2013.4166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kendler KS, Prescott CA, Jacobson K, Myers J, Neale MC. The joint analysis of personal interview and family history diagnoses: Evidence for validity of diagnosis and increased heritability estimates. Psychol Med. 2002;32:829–842. doi: 10.1017/s0033291702005858. [DOI] [PubMed] [Google Scholar]
- Kendler KS, Prescott CA, Myers J, Neale MC. The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Arch Gen Psychiatry. 2003;60:929–937. doi: 10.1001/archpsyc.60.9.929. [DOI] [PubMed] [Google Scholar]
- Kendler KS, Schmitt E, Aggen SH, Prescott CA. Genetic and environmental influences on alcohol, caffeine, cannabis, and nicotine use from early adolescence to middle adulthood. Arch Gen Psychiatry. 2008;65:674–682. doi: 10.1001/archpsyc.65.6.674. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kendler KS, Silberg JL, Neale MC, Kessler RC, Heath AC, Eaves LJ. The family history method: Whose psychiatric history is measured? Am J Psychiatry. 1991;148:1501–1504. doi: 10.1176/ajp.148.11.1501. [DOI] [PubMed] [Google Scholar]
- Kendler KS, Walters EE, Neale MC, Kessler RC, Heath AC, Eaves LJ. The structure of the genetic and environmental risk factors for six major psychiatric disorders in women. Phobia, generalized anxiety disorder, panic disorder, bulimia, major depression, and alcoholism. Arch Gen Psychiatry. 1995;52:374–383. doi: 10.1001/archpsyc.1995.03950170048007. [DOI] [PubMed] [Google Scholar]
- Kessler RC, McGonagle KA, Zhao S, Nelson CB, Hughes M, Eshleman S, Wittchen HU, Kendler KS. Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Arch Gen Psychiatry. 1994;51:8–19. doi: 10.1001/archpsyc.1994.03950010008002. [DOI] [PubMed] [Google Scholar]
- Koopmans JR, van Doornen LJ, Boomsma DI. Association between alcohol use and smoking in adolescent and young adult twins: A bivariate genetic analysis. Alcohol Clin Exp Res. 1997;21:537–546. [PubMed] [Google Scholar]
- Kosten TA, Anton SF, Rounsaville BJ. Ascertaining psychiatric diagnoses with the family history method in a substance abuse population. J Psychiatr Res. 1992;26:135–147. doi: 10.1016/0022-3956(92)90005-9. [DOI] [PubMed] [Google Scholar]
- Krueger RF. The structure of common mental disorders. Arch Gen Psychiatry. 1999;56:921–926. doi: 10.1001/archpsyc.56.10.921. [DOI] [PubMed] [Google Scholar]
- Krueger RF, McGue M, Iacono WG. The higher-order structure of common DSM mental disorders: Internalization, externalization, and their connections to personality. Person Indiv Diff. 2001;30:1245–1259. [Google Scholar]
- Kushner MG, Sher KJ. Comorbidity of alcohol and anxiety disorders among college students: effects of gender and family history of alcoholism. Addict Behav. 1993;18:543–552. doi: 10.1016/0306-4603(93)90070-p. [DOI] [PubMed] [Google Scholar]
- Lynam DR, Smith GT, Whiteside SP. Technical Report. Purdue University; West Lafayette, IN: 2006. The UPPS-P: Assessing five personality pathways to impulsive behavior. [Google Scholar]
- Lyons M, Hitsman B, Xian H, Panizzon MS, Jerskey BA, Santangelo S, Grant MD, Rende R, Eisen S, Eaves L, Tsuang MT. A twin study of smoking, nicotine dependence, and major depression in men. Nicotine Tob Res. 2008;10:97–108. doi: 10.1080/14622200701705332. [DOI] [PubMed] [Google Scholar]
- Malone SM, Taylor J, Marmorstein NR, McGue M, Iacono WG. Genetic and environmental influences on antisocial behavior and alcohol dependence from adolescence to early adulthood. Dev Psychopathol. 2004;16:943–966. doi: 10.1017/s0954579404040088. [DOI] [PubMed] [Google Scholar]
- McGue M, Malone S, Keyes M, Iacono WG. Parent-offspring similarity for drinking: a longitudinal adoption study. Behav Genet. 2014;44:620–628. doi: 10.1007/s10519-014-9672-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mendlewicz J, Fleiss JL, Cataldo M, Rainer JD. Accuracy of the family history method in affective illness. Comparison with direct interviews in family studies. Arch Gen Psychiatry. 1975;32:309–314. doi: 10.1001/archpsyc.1975.01760210043002. [DOI] [PubMed] [Google Scholar]
- Pelias MZ. Federal regulations and the future of research in human and medical genetics. J Contin Educ Health Prof. 2001;21:238–246. doi: 10.1002/chp.1340210407. [DOI] [PubMed] [Google Scholar]
- Perkins HW. Religious traditions, parents, and peers as determinants of alcohol and drug use among college students. Rev Relig Res. 1985;27:15–31. [Google Scholar]
- Roy MA, Walsh D, Kendler KS. Accuracies and inaccuracies of the family history method: a multivariate approach. Acta Psychiatr Scand. 1996;93:224–234. doi: 10.1111/j.1600-0447.1996.tb10639.x. [DOI] [PubMed] [Google Scholar]
- Sher KJ. Psychological characteristics of children of alcoholics. Alcohol Health Res World. 1997;21:247–254. [PMC free article] [PubMed] [Google Scholar]
- Slutske WS, Heath AC, Madden PA, Bucholz KK, Statham DJ, Martin NG. Personality and the genetic risk for alcohol dependence. J Abnorm Psychol. 2002;111:124–133. [PubMed] [Google Scholar]
- Spielberger CD, Jacobs GA, Crane RS, Russell SF. On the relation between family smoking habits and the smoking behavior of college students. Appl Psychol. 1983;32:53–69. [Google Scholar]
- Sullivan PF, Neale MC, Kendler KS. Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry. 2000;157:1552–1562. doi: 10.1176/appi.ajp.157.10.1552. [DOI] [PubMed] [Google Scholar]
- Tarter RE, Hegedus A. The drug use screening inventory: It’s application in the evaluation and treatment of alcohol and drug abuse. Alcohol Health Res W. 1991;15:65–75. [Google Scholar]
- Thompson WD, Orvaschel H, Prusoff BA, Kidd KK. An evaluation of the family history method for ascertaining psychiatric disorders. Arch Gen Psychiatry. 1982;39:53–58. doi: 10.1001/archpsyc.1982.04290010031006. [DOI] [PubMed] [Google Scholar]
- Waldron M, Madden PA, Nelson EC, Knopik VS, Glowinski AL, Grant JD, Lynskey MT, Jacob T, Sher KJ, Bucholz KK, Heath AC. The interpretability of family history reports of alcoholism in general community samples: Findings in a midwestern U.S. twin birth cohort. Alcohol Clin Exp Res. 2012;36:1091–1098. doi: 10.1111/j.1530-0277.2011.01698.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- White VM, Hopper JL, Wearing AJ, Hill DJ. The role of genes in tobacco smoking during adolescence and young adulthood: A multivariate behaviour genetic investigation. Addiction. 2003;98:1087–1100. doi: 10.1046/j.1360-0443.2003.00427.x. [DOI] [PubMed] [Google Scholar]
- Whiteside SP, Lynam DR. The Five Factor Model and Impulsivity: Using a structural model of personality to understand impulsivity. Person Indiv Diff. 2001;30:669–689. [Google Scholar]