AT-RISK DRINKING AMONG PATIENTS IN AN OCCUPATIONAL MEDICINE CLINIC

Susan J. Curry1,2,*, Evette Ludman1, Louis Grothaus1, Tim Gilmore3 and Dennis Donovan4

1 Center for Health Studies, Group Health Cooperative,
2 Department of Health Services, School of Public Health and Community Medicine, University of Washington,
3 Occupational Medicine Clinic, Group Health Cooperative and
4 Alcohol and Drug Abuse Institute and Department of Psychiatry, School of Medicine, University of Washington, USA

Received 31 July 2001; in revised form 5 November 2001; accepted 28 November 2001


    ABSTRACT
 TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGEMENTS
 REFERENCES
 
— This study described the prevalence and characteristics of at-risk drinkers among adults receiving care at an urban occupational medicine clinic. Comparisons were also made between occupational medicine and primary care patients. Among occupational medicine patients, prevalences were: 11% at-risk drinking; 51% light–moderate drinking; 38% abstinence. Abstainers differed from alcohol users with regard to race (fewer Caucasian) and marijuana use (lower rates). Compared to light–moderate drinkers, at-risk drinkers were more likely to be smokers. Compared to a primary care sample, non-at-risk drinkers in occupational medicine reported poorer health, more activity limitations, higher rates of smoking and more stress and depressive symptoms. In contrast, at-risk drinkers in occupational medicine were quite similar to those in primary care. Occupational medicine clinics are viable settings in which to screen for at-risk drinking patterns and to implement primary and secondary prevention strategies.


    INTRODUCTION
 TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGEMENTS
 REFERENCES
 
Alcohol use is one of the top three causes of premature morbidity and mortality in the USA (McGinnis and Foege, 1993Go). Non-alcoholic heavy drinkers have mortality ratios of >=2, in comparison to moderate drinkers and abstainers (Nathan, 1988Go; McGinnis and Foege, 1999Go). Individuals with moderate patterns of alcohol use increase their risk of death, injury and negative social consequences through occasional patterns of binge drinking (consuming five or more drinks on a single occasion) or of driving after consuming three or more alcoholic beverages (Engstrom, 1984Go; Wechsler et al., 1994Go).

Misuse of alcohol was estimated to cause productivity losses of $119 billion in 1995 (Harwood et al., 1998Go). Although some of these costs are due to use of alcohol on the job, a sizeable proportion result from impaired performance, absenteeism, medical costs and disability that are associated with alcohol use outside of work (Mangione et al., 1999Go). Several studies found that factors such as job-related stress and work–family conflict contribute to the misuse of alcohol among employed individuals (Frone et al., 1996Go; Grunberg et al., 1999Go). A recent Swedish study found problem drinking and drinking and driving to be strong predictors of receipt of disability pension and levels of work absenteeism in a cohort of young men followed from 1969 through 1991 (Upmark et al., 1999Go). Data from a study in the USA indicate that patients at risk for alcohol problems have more than twice the worker's compensation claim costs as their peers (Musich et al., 2001Go).

Even if alcohol use does not contribute to the original work-related medical problem, patients receiving occupational medicine care may be at increased risk for risky drinking patterns through efforts to self-medicate for chronic pain or through increased social isolation resulting from extended periods of unemployment.

In the USA, patients with occupational injuries or illnesses are treated under a set of laws and medical algorithms distinctly different from the usual primary care patient. This group of patients constitutes 1–2% of out-patient care. Extensive administrative requirements have convinced many physicians to drop care of these patients from their primary care practices, with occupational medicine becoming a specialty for others. Secondary gain, or payment for staying ill, results in a need for close monitoring of medical progress and a different approach to medical care, also creating pressure for this medical specialty. Occupational medicine clinics in health care systems and within worksites may be an untapped resource for screening and intervening with at-risk drinking patterns.

As an adjunct to a primary-care-based randomized trial of interventions to reduce at-risk drinking practices, we conducted population-based screening in an occupational medicine clinic. This paper reports the results of this screening. In addition to reporting the prevalence and patterns of alcohol use, we compared the characteristics of patients with light–moderate alcohol use to those who reported at-risk drinking patterns. We also compared at-risk and non-at-risk drinkers in the occupational medicine patient population to the corresponding groups among a primary-care-based sample of patients.


    SUBJECTS AND METHODS
 TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGEMENTS
 REFERENCES
 
Overview
Data were from screening surveys conducted as an adjunct to a randomized controlled trial evaluating an out-patient, office-based, at-risk drinker intervention versus usual care. The study was conducted in the central region occupational medicine clinic at Group Health Cooperative (GHC) in Seattle, Washington, USA. GHC is a non-profit, consumer-governed health maintenance organization that provides health care to over 450 000 residents of western Washington. The methods described in this paper are identical to those reported in the study entitled, ‘At-risk drinking among patients making routine primary care visits', and the primary-care-based comparison sample presented in this paper is taken from that study (Curry et al., 2000Go).

Participants
Patients with advance appointments to see one of three occupational medicine practitioners (two physicians and one physician's assistant) comprised the base sample for this study. Over a 20-week period, we abstracted the names of all patients with advance appointments at least 4 days before the day of the visit from automated appointment files. Study personnel provided lists of potential participants to the practitioners who checked them for the following exclusion criteria: (a) known to be alcoholic, (b) pregnant; (c) terminally ill; or (d) cognitively impaired. Eligible patients were contacted by telephone, and provided oral consent to: (a) complete a 10–15 min telephone interview that asked about general health behaviours, including alcohol consumption, use of tobacco, diet and exercise; (b) receive written health care information and calls from a health educator; (c) participate in follow-up health surveys by telephone 3 and 12 months after the first survey; and (d) a review of their medical records by study staff. Consent to share their survey information with their practitioner and to receive assistance for changing health risk habits during their upcoming visit was obtained at the end of the survey.

Measures
The screening survey used published items to assess demographics, health status [perceived health, activity limitations (Centers for Disease Control and Prevention, 1998Go)], health behaviours and other substance use (Turner et al., 1992Go; Curry et al., 1995Go), psychosocial factors [stress (Cohen et al., 1983Go), depression (Derogotis et al., 1974Go; Von Korff et al., 1988Go), social support (Cohen et al., 1985Go)], drinking patterns (Cahalan and Room, 1974Go; Centers for Disease Control and Prevention, 1998Go), and family history of alcohol problems (Turner et al., 1992Go). Participants whose reported drinking patterns qualified them for the randomized trial completed an extended set of alcohol-related questions, including the AUDIT (Saunders and Aasland, 1987Go; Babor et al., 1989Go), stage of change (Rollnick et al., 1992Go), decisional balance, and type of motivation to change drinking patterns (Curry et al., 1997Go).

Selection of at-risk drinking patterns
We screened for patients whose drinking patterns fell in the moderate–substantial range on the continuum of alcohol consumption and patterns that was published in a report by the Institute of Medicine (1990). Using epidemiological data to operationally define cut-off points just below the threshold for negative health and psychosocial consequences, we defined the following three drinking patterns: (a) consumed an average of two or more alcoholic drinks per day in the past month (chronic drinking); (b) had two or more episodes of binge drinking (defined as consuming five or more drinks on a single occasion) in the past month; (c) in the past month, had one or more episodes of driving after consuming three or more drinks. Quantity–frequency was assessed using modified Cahalan questions about number of days per week consuming alcohol and average number of drinks on drinking days (Cahalan and Room, 1974Go). Behavioural Risk Factor Survey questions assessed binge drinking with a single question asking about the number of times in the past month the participant had consumed five or more drinks on a single occasion, and drinking and driving with a question that asked how many times in the past month the participant had driven after consuming more than two drinks (Centers for Disease Control and Prevention, 1998Go). These questions occurred in the first part of the survey and were embedded with questions on other health behaviours.

Statistical analysis
Amount of ethanol consumed was summarized in grams per week. This measure was chosen to be consistent with published meta-analyses (Turner, 1990Go) and we used the United States Department of Agriculture (1995) conversion metric of 14 g per standard drink unit. For all comparisons, we used t-tests to compare means on continuous measures and {chi}2-analyses to compare proportions. First, t-tests were used to compare abstainers to all drinkers and then, among drinkers, to compare the at-risk group to the non-at-risk group. Because of the large number of variables being examined, P <= 0.01 was considered statistically significant.


    RESULTS
 TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGEMENTS
 REFERENCES
 
Prevalence of at-risk drinking patterns
We identified 283 occupational medicine patients. A total of 27 patients (9.5%) were excluded from screening by their provider, leaving 256 patients who were eligible for screening surveys. (We did not require providers to indicate the reason for exclusion.) Surveys were completed with 158 patients. Of the 98 patients who did not complete surveys, two started but did not complete the survey, 51 (20%) could not be reached prior to their medical appointment, 28 (11%) refused when contacted, and 17 (7%) were ineligible due to language problems, being too ill to complete the survey or cancellation of their medical appointment, resulting in an adjusted response and consent rate of 66% (158/239).

Table 1Go summarizes the prevalence of alcohol use and at-risk drinking patterns among screened patients. Of the 158 patients who completed the survey, 60 (38%) reported no alcohol consumption in the prior 6 months (abstainers); 81 (51%) reported consuming alcohol in the prior 6 months, but did not meet any of the at-risk drinking criteria (light– moderate drinkers); and 17 (11%) met one or more at-risk drinking criteria (at-risk). As noted in Table 1Go, drinking and driving was the most frequently reported at-risk pattern, followed by binge and chronic drinking.


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Table 1. Distribution of alcohol use and of at-risk drinking patterns among patients in an occupational medicine clinic
 
Comparisons among abstainers, light–moderate and at-risk drinkers
Our sample of 158 patients had a female majority (55%), averaged 44 years of age, 65% of whom were Caucasian, 72% had some post-high-school education, 60% were married or living as married, 81% were employed full- or part-time and 61% reported household incomes greater than $35 000/year. With regard to health status, 43% rated their health as excellent or very good, 68% reported an activity limitation in the past year and 48% had made a routine doctor visit in the past year. Sixty-nine per cent of the sample reported that they exercised at least monthly, 25% reported current smoking, and marijuana and cocaine use in the past year were reported by 14 and 1% respectively. For family history of alcohol problems, 54% reported that they had a blood relative who was a problem drinker or alcoholic, 31% reported living with a problem drinker or alcoholic before age 18 years, and 28% reported being married to, or living with, a problem drinker or alcoholic as an adult. Participants reported moderate levels of perceived stress (M = 2.2), depressive symptoms (M = 1.2) and social support (M = 4.2).

Patients reporting no alcohol consumption in the past 6 months differed significantly from those reporting any pattern of alcohol use on two measures. As indicated in Table 2Go, abstainers were less likely than alcohol users to be Caucasian (47 versus 77%, P < 0.001) and to have used marijuana in the past year (3 versus 21%, P < 0.002).


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Table 2. Demographics, health status, health behaviours, family history of alcohol problems, and psychosocial characteristics of abstainers and drinkers among patients in an occupational medicine clinic
 
Table 3Go summarizes comparisons between light–moderate and at-risk drinkers. Rates of cigarette smoking were significantly higher among at-risk than among light–moderate drinkers. At-risk drinkers also reported higher rates of use of marijuana in the past year (P = 0.02), higher levels of perceived stress (P = 0.05) and lower rates of monthly exercise (P = 0.03), but these did not reach our criterion value of P <= 0.01 for statistical significance.


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Table 3. Demographics, health status, health behaviours, family history of alcohol problems, and psychosocial characteristics by pattern of alcohol use among patients in an occupational medicine clinic
 
Comparisons between primary care and occupational medicine samples
Non-at-risk drinkers. The primary care (n = 3059) and occupational medicine (n = 141) patients who did not report any at-risk drinking patterns differed on several demographic, health status, health behaviour and psychosocial variables. Overall, occupational medicine patients were less likely to be female (57 versus 68%, P < 0.007), to have post-high-school education (73 versus 86%, P < 0.001) and to be Caucasian (63 versus 73%, P < 0.01). As expected, a smaller proportion rated their health as excellent or very good (41 versus 58%, P < 0.001), and they reported more activity limitations in the past 12 months (68 versus 25%, P < 0.001). Occupational medicine patients had a higher smoking prevalence (21 versus 10%, P < 0.001) and a higher proportion reported ever being married to, or living with, a problem drinker or alcoholic as an adult (30 versus 18%, P < 0.001). Occupational medicine patients reported higher levels of perceived stress (2.24 versus 2.06%, P < 0.01) and more depressive symptoms (1.23 versus 1.03%, P < 0.004). Among non-at-risk drinkers, a higher proportion of occupational medicine than primary care patients reported abstaining from alcohol in the previous 6 months (42 versus 29%, P < 0.001).

At-risk drinkers. Table 4Go summarizes comparisons between the at-risk drinkers identified in occupational medicine and primary care clinics. In these samples, occupational medicine patients were less likely to have post-high school education and more likely to report activity limitations in the past year than primary care patients. Notably, at-risk drinkers in both samples did not differ with regard to perceived health, tobacco and other substance use, or psychosocial factors. Table 4Go also shows that the two samples were similar with regard to alcohol use, consequences and motivation for change.


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Table 4. Comparison of at-risk drinkers identified in primary care vs occupational medicine clinics
 

    DISCUSSION
 TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGEMENTS
 REFERENCES
 
We assessed the prevalence and characteristics of at-risk drinking patterns among patients receiving care in an occupational medicine clinic. Our comprehensive screening survey allowed us to make comparisons on a wide-ranging and in-depth set of variables, including perceived health, family history of problem drinking and alcoholism and psychosocial factors related to stress, depression and social support. First, we assessed the combined and individual rates of three distinct at-risk drinking practices. Second, we compared abstainers, light–moderate drinkers and at-risk drinkers. Third, we compared this occupational medicine sample to an identically screened sample from primary care clinics.

Among patients with advance appointments for occupational medicine care, we observed an 11% prevalence of at-risk drinking. This is within the range of primary-care-based prevalence estimates reported in the literature (Fleming et al., 1998Go), and identical to the proportion identified in our primary-care-based screening (Curry et al., 2000Go). We used an average of two drinks per day to define chronic drinking among men and women rather than different criteria by sex. Recently published guidelines for moderate drinking include two drinks per day as a cut-off for men in contrast to one drink per day for women. However, none of the men identified as at-risk drinkers would have been reclassified if we increased our daily drinking cut-off to an average of three drinks per day for men. The wording on our binge drinking question specified five or more drinks per day, so we were unable to ascertain whether any additional women would have been included in the at-risk drinking sample if we lowered the criterion number of drinks per occasion from five to four for females. Because we instructed physicians to exclude patients from the screening survey who were known to be alcoholic, we are unable to estimate the prevalence of alcoholic drinking among patients. However, unpublished data from a previous study at Group Health showed relative risks of 1.96 for alcohol misuse and 1.6 for smoking in injured workers compared to their peers in primary care (I. T. Gilmore, 2001, personal communication). Notably, we found a similar relative risk for smoking in this study.

There were relatively few differences between abstainers and those who had consumed alcohol within the past 6 months. Notably, we did not observe gender, education, and employment differences that have been reported elsewhere. This may simply reflect a more homogeneous patient population in occupational medicine than in primary care. Of some note is the relatively high prevalence of marijuana use (>20%) reported by occupational medicine patients who had consumed alcohol during the past 6 months. Moreover, self-reported marijuana use was more than double among at-risk, compared to light–moderate, drinkers. In this study we assessed use in the past year. Given the high rates reported in our sample, this merits further study. Also notable are the very high rates of smoking in this population. Smoking prevalence among non-at-risk drinkers in occupational medicine was double that observed in primary care, and more than half of the at-risk drinkers in occupational medicine reported current smoking.

Observed differences between occupational medicine and primary care patients with regard to gender, education, perceived health and activity limitations probably reflect true differences between patient pools. Male blue-collar workers may be more likely to experience work-related injuries, and those with injuries are more likely to have to reduce their activity and perceive their health to be poorer. It is interesting that there were fewer differences between at-risk drinkers identified in both settings, which suggests that the risk factors and characteristics of individuals who are at risk for negative consequences from drinking do not differ by clinical setting.

We added screening in an occupational medicine clinic to our primary-care-based study to explore the feasibility of expanding screening and intervention for at-risk drinking patterns to different clinical settings for future research. Our consent procedures asked patients to agree to screening and to the possibility for intervention and follow-up. This may have resulted in a lower response rate to the screening survey, but it does suggest that a high proportion of patients are willing to receive both screening and intervention for health-risk behaviours. Because this was a feasibility study, our sample size is modest and the small number of at-risk drinkers identified precluded more detailed comparisons within that subsample. When we made these comparisons in our larger, primary care-based sample, we found the characteristics of individuals with these three drinking patterns to be relatively distinct (Curry et al., 2000Go). Those with two or more at-risk drinking patterns were more likely to be male, and they reported significantly higher levels of alcohol consumption, higher AUDIT scores, and more motivation to change their drinking patterns. Among patients who reported only one at-risk pattern, binge drinkers stood out in several ways. They had multiple behavioural risk factors, including high rates of tobacco and marijuana use, were more likely to be younger and unmarried and reported surprisingly poor perceived health. Although binge drinkers had relatively modest levels of weekly alcohol consumption, they reported the highest AUDIT scores and the highest prevalence of negative consequences from drinking.

Occupational medicine clinics are viable settings in which to screen for patients with at-risk drinking patterns. The characteristics of patients identified in this study suggest that this clinical setting provides an important opportunity for primary and secondary prevention efforts, not only with regard to alcohol consumption, but also to the use of tobacco and marijuana. Since occupational medicine patients often see the same provider many times, the patient–provider relationship may provide a fertile ‘teachable setting’ in which to motivate and encourage changes in drinking and other health risk behaviours.


    ACKNOWLEDGEMENTS
 TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGEMENTS
 REFERENCES
 
The authors wish to thank Malia Oliver, Jason Petteway, Ella Thompson, Nancy Monroe, Dan Rosner, Bonner Reinking and Peggy Tobin for their outstanding work on this project. This study would not have been possible without the collaborative involvement of the providers and clinic staff at the Group Health Cooperative Occupational Medicine Clinic and the generosity of our patient participants. This study was supported by NIAAA Grant # R01 AA09175.


    FOOTNOTES
 TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGEMENTS
 REFERENCES
 
* Author to whom correspondence should be addressed at: Health Policy and Research Centers, University of Illinois at Chicago, 850 West Jackson Boulevard, Suite 400, Chicago, IL 60607, USA. Back


    REFERENCES
 TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGEMENTS
 REFERENCES
 
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