Scherrer JF, Xian H, Shah KR, Volberg R, Slutske W, Eisen SA. Effect of Genes, Environment, and Lifetime Co-occurring Disorders on Health-Related Quality of Life in Problem and Pathological Gamblers. Arch Gen Psychiatry. 2005;62(6):677-683. doi:10.1001/archpsyc.62.6.677
Copyright 2005 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.2005
Problem and pathological gambling are associated with many impairments in quality of life, including financial, family, legal, and social problems. Gambling disorders commonly co-occur with other psychiatric disorders, such as alcoholism and depression. Although these consequences and correlates have been reported, little is known about the health-related functional impairment associated with gambling.
To model differences in the health-related quality of life (HRQoL) among non–problem gamblers, problem gamblers, and pathological gamblers after controlling for lifetime co-occurring substance use disorders, psychiatric disorders, sociodemographics, and genetic and family environmental influences.
Cohort and co-twin studies.
Nationally distributed community sample.
Male twin members of the Vietnam Era Twin Registry: 53 pathological gamblers, 270 subclinical problem gamblers, and 1346 non–problem gamblers (controls).
We obtained HRQoL data, via the 8-Item Short-Form Health Survey, from all participants. Data from a subset of twin pairs discordant for gambling behavior was used to control for genetic and family environmental effects on HRQoL and problem gambling.
Main Outcome Measure
Health-related quality of life.
Results from adjusted logistic regression analyses suggest little difference across groups in the physical domains of the health survey; however, for each mental health domain, pathological gamblers had lower HRQoL scores than problem gamblers (P<.05), who in turn had lower scores than non–problem gamblers (P<.05). After controlling for genes and family environment, no significant differences existed between the non–problem gambling twins and their problem or pathological gambling brothers, but adjusted co-twin analyses resulted in statistically significant differences in 4 of 8 subscales.
Pathological and problem gambling are associated with significant decrements in HRQoL. This association is partly explained by genetic and family environmental effects and by lifetime co-occurring substance use disorders. Implications for clinicians, health care utilization, and public health issues are discussed.
Problem and pathological gambling have considerable negative economic and psychological effects on individuals and families. The average annual economic impact on the individual has been estimated to be $1200 for pathological gambling and $715 for problem gambling.1 In a recent national survey,1 14% of individuals with pathological gambling have lost at least 1 job in their lifetime, 19% have declared bankruptcy, 32% have been arrested, 21% have been incarcerated, and 54% have been divorced. Among individuals with problem gambling, 11% have lost a job, 10% have declared bankruptcy, 36% have been arrested, 10% have been incarcerated, and 40% have been divorced. All of these rates are significantly elevated compared with those of non–problem gamblers.1
Pathological gambling has been associated with a variety of psychiatric disorders. Estimates of the prevalence of comorbid alcoholism among gamblers in treatment range from 10% to 52%,2,3 and approximately half report a history of chemical dependency.2,4,5 Comorbid psychiatric disorders commonly observed in pathological gamblers include antisocial personality disorder,6 major depression,2,4 agoraphobia, panic disorder, and simple phobias.7 Suicide attempts and suicidal ideation are also elevated in pathological gamblers.8,9
Given the many adverse life events (eg, financial and family problems) and comorbid substance use and psychiatric disorders associated with long-lasting effects on physical health either as a result of the disorder itself (ie, alcoholism) or because of associated behaviors, such as chronic smoking in depression, it is expected that persons with problem or pathological gambling would report reduced health-related quality of life (HRQoL). The HRQoL is a measure of perceived health and the effect of disease on day-to-day functioning.10 However, although an extensive literature reports the life consequences and comorbidity associated with pathological gambling, as of this writing, only 2 studies11,12 have reported on HRQoL among gamblers. Black et al11 found substantially poorer scores among 30 volunteers with pathological gambling compared with a US population sample on the 36-Item Short-Form Health Survey (SF-36) subscales of physical functioning (PF), bodily pain (BP), general health (GH), and mental health (MH). The small sample size might have contributed to the lack of differences for the remaining SF-36 subscales. An SF-36 assessment of lottery players found lower social functioning scores among individuals who spent more money on the British National Lottery.12 This study assessed problem and pathological gambling. Further study of HRQoL in problem and pathological gambling is warranted.
Of particular importance to the present design, Romeis et al13 found that genetic effects account for 33% to 44% of the variance in self-reported health among members of the Vietnam Era Twin (VET) Registry. The same researchers10 found that the association between 4 subscales of the SF-36 and alcoholism could be partly explained by genetic effects. This suggests that at least a portion of the HRQoL differences observed between gamblers and nongamblers in published studies may be explained by genetic and family environmental experiences.
Given that inherited factors contribute to HRQoL measures and that pathological gamblers experience substantial life consequences and psychiatric comorbidity, we analyzed data from middle-aged male twin members of the VET Registry to accomplish the following objectives: (1) using a cohort design, to determine whether HRQoL, measured using the SF-8, differs among problem gambling, pathological gambling, and non–problem gambling individuals; (2) using a monozygotic (MZ) co-twin discordant design, to determine the extent to which genetic and family environmental factors affect HRQoL in non–problem gambling index twins compared with their problem or pathological gambling identical brothers; (3) within the cohort and co-twin designs, to adjust for the effects of sociodemographics, lifetime co-occurring substance dependence, and psychiatric disorders on HRQoL among problem and pathological gambling participants; and (4) to discuss potential clinical, public health, and health service utilization consequences of HRQoL in problem and pathological gambling.
The VET Registry consists of 7375 male MZ and dizygotic (DZ) twin pairs born between 1939 and 1955 in which both siblings served on active military duty during the Vietnam era (1965-1975). The characteristics of the VET Registry and the method of zygosity determination have been reported elsewhere.14- 16
In 2002, 1200 MZ and DZ twin pairs (2400 individuals) were invited to participate in a computer-assisted telephone interview of the Diagnostic Interview Schedule,17 which included questions to derive 12-month and lifetime diagnoses of DSM-IV problem gambling (1-4 symptoms) and pathological gambling (≥5 symptoms). The Diagnostic Interview Schedule17 has been shown to have good validity,18 and Stinchfield19 reported satisfactory reliability, validity, and classification accuracy when operationalizing interview questions for DSM-IV criteria gambling disorder. Twins were invited to participate in the 2002 survey if at least 1 member of the pair had 1 or more symptoms of DSM-III-R pathological gambling identified from a previous 1992 Diagnostic Interview Schedule (n = 456 pairs). A random sample of non–problem gambling pairs (ie, no symptoms in both members of a pair) (n = 744 pairs) were invited to participate in 2002.
Of the 2400 eligible individuals, 252 were not contacted because they were dead, not located, unavailable, incarcerated, on active military duty, or incapacitated. Of the 2148 individuals who could be reached by telephone, 1675 were successfully interviewed, yielding a 78% casewise response rate. Respondents were aged 45 to 60 years at the time of data collection. Interviewing was conducted by trained, experienced staff from the Institute for Survey Research, Temple University, Philadelphia, Pa. Interviewers contacted twins and began interviewing after verbal informed consent was obtained, a method approved by the institutional review boards at the participating institutions.
As part of the 2002 gambling assessment, we also collected correlates of gambling behavior, including HRQoL. The assessment of HRQoL covered the 12 months before the interview. The SF-820 is a standardized instrument consisting of 8 subscales and 2 summary scales. The 8 subscales are PF, role limitations–physical (RP), BP, GH, vitality (VT), social function (SF), role limitations–emotional (RE), and MH. The PF, RP, BP, and GH subscales assess HRQoL in relation to physical well-being, whereas the VT, SF, RE, and MH subscales assess HRQoL associated with social and mental well-being. The summary scales are computed using regression weights to aggregate scores across all subscales, thereby producing a physical and mental summary score.
For the cohort design, we created 3 comparison groups of twins and singletons: non–problem gamblers (n = 1346), problem gamblers (n = 270), and pathological gamblers (n = 53). One-way analyses of variance were used to compare mean SF-8 subscale and summary scale scores across groups. We then used a multivariate model to adjust for potential confounding from variables obtained in the 1992 interview (lifetime DSM-III-R criteria alcohol dependence, nicotine dependence, drug dependence, and any psychiatric disorder) and variables obtained as part of the 2002 gambling assessment (age, education, income, and twin closeness; eg, twins live together, twins see each other or talk every day . . . twins never see or contact each other). We adjusted for twin closeness because we hypothesized that twins who lived together or talked to each other daily may be more likely to model each other’s perceived health status and to participate in more activities together, including gambling. The prevalences of the covariates were computed separately for the cohort and co-twin designs.
Because twin pair data are not statistically independent, standard errors are underestimated in the cohort design. Appropriate error estimates were generated based on the Huber robust variance estimator using a software package (Stata; Stata Corp, College Station, Tex). Post hoc tests compared differences in mean scores between each comparison group.
For the MZ co-twin design, we computed unadjusted and adjusted (controlling for the same variables as in the cohort design) co-twin control linear regression models for MZ twin pairs discordant for problem or pathological gambling (n = 101 pairs). Owing to the small number of MZ discordant pathological gambling pairs, we collapsed problem and pathological gambling into 1 group. The MZ co-twin control design compares the SF-8 responses of non–problem gambling index twins with those of their co-twins with lifetime diagnoses of problem or pathological gambling. Because MZ twins share 100% of their genes and 100% of their family environmental experiences, the discordant MZ co-twin design controls for genetic and family environmental effects on the association between HRQoL and problem or pathological gambling. Differences observed between MZ twin pairs are the result of unique environmental experiences.
The prevalence of covariates differed across the non–problem gambling, problem gambling, and pathological gambling groups. Statistically significant differences were observed for age, income, substance dependence, and psychiatric disorders (Table 1). Younger participants were more likely to be classified as problem and pathological gamblers. Alcohol, nicotine, and drug dependence and psychiatric disorders increased in prevalence from non–problem gambling to problem gambling to pathological gambling (P<.001). Unlike in the cohort design, there were no statistically significant differences between non–problem gambling index twins and their problem or pathological gambling identical brothers (Table 2). This suggests that familial effects overlap in problem and pathological gambling and pertinent covariates.
Unadjusted mean scores for non–problem gambling participants were statistically significantly higher compared with the problem and pathological gambling groups for all SF-8 subscales except the PF subscale, for which only pathological gamblers differed from non–problem gamblers (Table 3). Non–problem gamblers had statistically significantly higher RP and BP mean scores than the problem and pathological gambling groups, yet the problem gambling group did not statistically significantly differ from the pathological gambling group on these subscales. For the GH, VT, SF, RE, and MH subscales, means differed among each group. The mean scores statistically significantly decreased across groups so that non–problem gambling individuals had the highest GH, VT, SF, RE, and MH subscale scores, followed by participants with problem gambling, who in turn had higher subscale scores than those with pathological gambling. Non–problem gambling individuals differed significantly from the problem and pathological gambling groups on the physical summary score, whereas all groups were statistically significantly different from one another for the mental summary score.
After adjusting for covariates, differences among groups for the PF and BP subscales were no longer statistically significant (Table 3). Similarly, differences between problem and pathological gambling on the GH subscale were no longer statistically significant. After adjustment, differences among non–problem gambling, problem gambling, and pathological gambling remained statistically significant for the VT, SF, RE, and MH subscales and for the mental summary score. For these subscales, the largest mean differences were observed between the non–problem gambling and pathological gambling groups, with mean differences ranging from 3.5 for the VT subscale to 7.8 for the mental summary score.
Table 4 provides the results for the MZ co-twin control design. After controlling for 100% of genetic and family environmental effects on the association between problem and pathological gambling, there were no significant differences in mean subscale or summary scale scores in affected twins compared with their non–problem gambling identical twin brothers. After adjustment for covariates, the RP, SF, RE, and MH mean subscale scores and the mean mental summary score differed significantly between non–problem gambling index twins and affected co-twins (P<.05).
In a nationally distributed, middle-aged male community cohort, we found significant deficits in HRQoL, as measured using the SF-8, among problem and pathological gamblers compared with non–problem gamblers. After adjusting for lifetime co-occurring substance use and psychiatric disorders and sociodemographics, the physical domains of RP and GH remained lower for problem and pathological gambling compared with non–problem gambling. Adjusted analyses suggest that non–problem gamblers have significantly higher scores on all mental HRQoL subscales (ie, VT, SF, RE, and MH) compared with those with problem gambling, who in turn have significantly higher scores than those with pathological gambling.
Results of previous research suggest2- 7 that problem and pathological gambling are often comorbid with psychiatric disorders. This would be consistent with our finding of lower scores on the mental subscales among affected co-twins compared with non–problem gamblers. It is also logical that the RP and GH subscale scores were lower among problem and pathological gamblers. This may not be a direct result of gambling but would likely stem from health behaviors such as smoking and alcoholism, which have long-term adverse health consequences and are correlated with psychiatric conditions associated with problem and pathological gambling.21- 23
After controlling for 100% of the genetic and family environmental effects using the co-twin control design, our results suggest that genetic factors and family environment account for the differences between non–problem gambling twins and their identical brothers who have either problem or pathological gambling.
After adjustment for the previously mentioned covariates in the co-twin design, lifetime co-occurring alcoholism, nicotine dependence, and drug dependence seem to contribute to increased mean differences for some SF-8 subscales. Before adjustment, the negative effects of substance dependence on quality of life affects both members of the twin pair. By adjusting for substance dependence, the mean differences for the RP, SF, RE, and MH subscales and the mental summary score increase in magnitude as a direct effect of problem or pathological gambling. Another way to examine the effect of covariates is to consider their high prevalence in the index twin and the co-twin. For example, the prevalence of alcoholism is higher than that found in the VET Registry as a whole among non–problem gambling index twins and affected co-twins (49.5% and 61.4%, respectively). Similarly, there is no significant difference in the prevalence of nicotine and drug dependence or psychiatric disorders. The high and equal prevalence of these disorders in index twins and co-twins acts to reduce SF-8 scores for the non–problem gambling twin and the co-twin and thus contributes to reductions in mean differences. By removing the adverse effects of substance dependence and psychiatric disorders in the adjusted analyses, the mean differences become larger owing to the direct effect of problem or pathological gambling.
Results of the present cohort analyses (Table 3) differ somewhat from those of the assessment by Black et al11 of HRQoL in a volunteer sample of 30 individuals assessed for problem gambling via the South Oaks Gambling Screen. The volunteers’ SF-36 scores were compared with those of a US general population sample. Our unadjusted results are consistent with those of Black and colleagues11 in that individuals with problem gambling had significantly poorer scores on the PF, BP, GH, and MH subscales, but our unadjusted results differ in that Black et al11 found that problem gamblers had higher scores on the SF subscale and did not differ from the general population sample on the RE subscale. As with the research of Black et al,11 we found the largest mean subscale score difference for the MH subscale. In general, differences in assessment of problem and pathological gambling, differences in sample selection, and use of the SF-8 compared with the SF-36 limit comparison to the only extant HRQoL study in problem gamblers.
An evaluation of the utility and validity of the SF-8 by Turner-Bowker et al24 reported the following subscale scores for self-reported migraine and depression: migraine—PF = 47.5, RP = 46.9, BP = 48.3, GH = 49.3, VT = 49.4, SF = 47.8, RE = 46.1, and MH = 47.6; and depression—PF = 45.1, RP = 43.6, BP = 47.1, GH = 45.4, VT = 43.1, SF = 40.8, RE = 36.9, and MH = 35.9. In light of the study by Turner-Bowker and colleagues,24 our results in Table 3 suggest that individuals with pathological gambling have lower SF-8 scores than a cohort with migraines but higher scores on 6 of 8 subscales compared with a cohort with depression. Because Turner-Bowker et al24 did not adjust for the same covariates as in our study, further research controlling for the same covariates is necessary to make direct comparisons of the HRQoL in pathological gambling compared with other physical and psychiatric conditions.
The present results should be interpreted in light of potential limitations. First, the sample is not representative of all persons with gambling disorders. These results should not be generalized to women or to clinical populations. Second, the narrow age range (45-60 years) limits generalizability to much older and much younger cohorts. Third, the lifetime diagnoses of gambling problems and lifetime co-occurring conditions prevent us from establishing the temporal relationship between active symptoms and SF-8 scores. Owing to the strong genetic and environmental effects, it is possible that many of the SF-8 subscales (ie, those that were not statistically significant after adjustment in the co-twin design: PF, BP, GH, and VT) capture a trait of men with gambling problems and not a deficit in HRQoL that is a direct result of problem or pathological gambling. In addition, the lifetime co-occurring disorders were derived from data collected in 1992. We did not determine whether incident diagnoses or other unmeasured covariates may affect our results. We also did not determine whether poor HRQoL is a direct result of problem or pathological gambling, in which case impaired social functioning may be a direct result of preoccupation with gambling, yet much of the HRQoL deficits may be due to the health effects of correlated disorders, such as alcohol, nicotine, and drug dependence. As discussed in other publications with members of the VET Registry, this cohort is healthier than the general population owing to the minimum health requirements for military service; therefore, our finding of differences in HRQoL before accounting for genetic and environmental effects is likely a conservative estimate. This is evident when comparing SF-8 norms19 for men aged 50 to 54 years (mean age of this study cohort = 53.1 years) with the means reported for non–problem gambling individuals in Table 3. The norms for each subscale among men aged 50 to 54 years are 47.4 (PF), 47.6 (RP), 49.5 (BP), 49.2 (GH), 50.4 (VT), 48.0 (SF), 47.3 (RE), and 50.2 (MH). Except for BP, which is nearly identical to the 49.4 obtained for our non–problem gambling sample, the other SF-8 norms are lower than those reported for non–problem gambling individuals in Table 3.
Because our measure of HRQoL was queried for the 12 months before the interview and problem gambling in the present study is a lifetime measure, we conducted additional analyses to test whether SF-8 scores for 12-month problem gambling (n = 143) and pathological gambling (n = 34) differed from lifetime problem and pathological gambling. Except for the VT subscale, we found no statistically significant differences in mean scores between lifetime and 12-month problem and pathological gambling. Individuals with current pathological gambling had a mean VT score of 50.7 compared with those with lifetime pathological gambling, who had a mean score of 46.2 (P = .048).
The co-twin design is a unique strength of the present analyses. By controlling for a host of unmeasurable genetic factors and family-rearing experiences, the design provides potentially the best natural experiment in epidemiology. The standardized method of data collection and the use of computer-assisted telephone interviews and structured clinical instruments likely reduced potential bias and enhanced the validity of self-reported gambling problems and HRQoL scores. Last, the sample is not subject to bias inherent to clinical populations that tend to be more severely affected, and we avoided volunteer bias.
Problem and pathological gamblers have statistically significantly poorer HRQoL scores than non–problem gamblers. This effect is most pronounced for mental health domains. However, the HRQoL of gamblers seems to be largely explained by genetic or environmental effects on perceived health status in addition to significant contributions from lifetime co-occurring substance use disorders for the RP, SF, RE, and MH subscales and mental summary score. Future research is warranted to determine, prospectively, whether changes in gambling behavior may result in improved HRQoL or, as suggested by our co-twin design, whether reducing problem gambling may have little effect on perceived health status among those affected for most of the physical domains of HRQoL. However, findings from the adjusted co-twin analyses suggest that reducing lifetime co-occurring substance use problems contributes to better HRQoL in the domains of RP, SF, RE, and MH.
In summary, our results confirm those of a previous study11 in which the HRQoL in problem gamblers is poorer than that in controls. These differences seem to be explained almost entirely by differences in genetic and childhood family environmental experiences and the effect of lifetime co-occurring substance use disorders. Potential clinical implications include the need to be aware of the high rate of co-occurring disorders that impact the quality of life of problem and pathological gamblers; the potential physical consequences associated with this disorder, such as alcoholic drinking and chronic smoking; the potential for increased prevalence due to legalized gambling; and the lack of treatment seeking for problem and pathological gambling. Due partially to the high prevalence of co-occurring substance use disorders, the health needs of persons with problem or pathological gambling are likely to be similar to those for individuals with other mental disorders. Several studies have found that mental illness is associated with excess health care utilization,25,26 and poor perceived health predicts hospitalization and mortality.27,28 The medical community should anticipate that the increases in the prevalence of problem and pathological gaming that have been demonstrated for the adult US population during the past 20 years29 will contribute to more patients being diagnosed as having problem and pathological gambling and will be associated with an increase in morbidity and mortality rates among patients with a history of problem or pathological gambling. Little attention has been paid to this potential public health issue. As gambling becomes more available throughout the United States, research is needed to quantify the health care needs and costs that are a function of the poor perceived health status of problem and pathological gamblers. It may become prudent to screen patients with depression or substance use problems for problem and pathological gambling to increase opportunities for treatment and prevention.
Correspondence: Jeffrey F. Scherrer, PhD, Research Service, St Louis Veterans Affairs Medical Center, 151-JC, 915 N Grand Blvd, St Louis, MO 63106 (firstname.lastname@example.org).
Submitted for Publication: August 9, 2004; final revision received October 27, 2004; accepted November 16, 2004.
Funding/Support: This study was supported by the Department of Veterans Affairs Health Services Research and Development Service (Hines, Ill) and by grant MH60426 (Pathological Gambling: Courses, Consequences and Causes) from the National Institute of Mental Health (Bethesda, Md). The United States Department of Veterans Affairs has provided financial support for the development and maintenance of the VET Registry.
Acknowledgment: We thank the members of the VET Registry and their families for their continued cooperation and participation and the numerous organizations that have provided invaluable assistance in the conduct of this study, including the Department of Defense (Washington, DC); National Personnel Records Center (St Louis, Mo); National Archives and Records Administration (College Park, Md); Internal Revenue Service (Washington); National Opinion Research Center (Chicago, Ill); National Research Council (Washington); National Academy of Sciences (Washington); and Institute for Survey Research, Temple University (Philadelphia, Pa).