THE USE OF AUDIT TO ASSESS LEVEL OF ALCOHOL PROBLEMS IN RURAL VIETNAM

Alcohol & Alcoholism Vol. 40, No. 6, pp. 578 583, 2005 Advance Access publication 22 August 2005 doi:10.1093/alcalc/agh198 THE USE OF AUDIT TO ASSESS LEVEL OF ALCOHOL PROBLEMS IN RURAL VIETNAM KIM BAO GIANG 1,3, FREDIK SPAK 2, TRUONG VIET DZUNG 1,4 and PETER ALLEBECK 2,3 * 1 Faculty of Public Health, Hanoi Medical University, Vietnam, 2 Department of Social Medicine, Gothenburg University, Sweden, 3 Department of Public Health Science, Karolinska Institutet, Sweden and 4 Department of Science and Training, Ministry of Health, Vietnam (Received 22 June 2005; first review notified 06 July 2005; in revised form 21 July 2005; accepted 26 July 2005; advance access publication 22 August 2005) Abstract Aims: To assess the accuracy and performance of AUDIT in detecting alcohol problems, as defined by ICD-10 and DSM-IV, in a rural district in Vietnam. Methods: The study was conducted in a rural district of Vietnam. Five hundred men and women aged 18 60 were randomly selected for interview with AUDIT and CIDI 2.1. The ICD-10 and DSM-IV criteria for harmful use/alcohol abuse and alcohol dependence were used to evaluate AUDIT. Results: Due to few cases of alcohol problems observed among women (1/282), we could only evaluate the validity of AUDIT in men. At cut-off point 7/8, AUDIT had a sensitivity of 81.8% and a specificity of 76.1% for detecting at-risk drinking. At this cut-off point, using ICD-10 criteria, the sensitivity was 100% for harmful use and 93.8% for alcohol dependence; the specificity was 69.9% for harmful use and 87.4% for alcohol dependence. The area under the ROC curve was 0.91 (0.84 0.98) for harmful use and 0.84 (0.74 0.94) for alcohol dependence (ICD-10). The agreement between ICD-10 and DSM-IV was higher for diagnosing alcohol dependence than alcohol abuse (Kappa coefficient: 0.98 vs 0.68). Conclusion: We confirmed that AUDIT is feasible to use in a rural community in a developing country. Different cut-off points are appropriate for different purposes, but for general population screening of at-risk drinking we found a cut-off point 7/8 to be optimal. INTRODUCTION Alcohol-related problems has since long been recognized as one of the major public health problems in the western world, but in recent years, increased attention has been paid to the role of alcohol as a public health problem also in developing countries, although much less systematically analysed (World Health Organisation, 2002a). The World Health Report 2002 pointed out that alcohol causes 3.2% of all deaths (1.8 million), globally (World Health Organisation, 2002b). The role of alcohol worldwide was also highlighted in the Global Burden of Disease study (Room et al., 2005). According to recent figures from this study, the proportion of the years of life lost to disability due to alcohol problems overall is 4%, and it is higher in developing countries in America and Asia Pacific (6.2%). In Vietnam, hospital records have indicated an increase of severe mental disorders due to alcohol misuse during the past decades (Thiem, 2004). The Vietnamese government also has started to pay attention to policy development to reduce the health and social burden due to alcohol misuse (National Commission of Social Affairs of Vietnam, 2003). However, data on alcohol consumption and alcohol problems in the general population are limited, as is the case in most developing countries. Knowledge of the pattern of drinking and problem levels in the community is important for planning intervention and treatment programs. Thus, there is a need to develop and adapt instruments to measure alcohol problems in the general population in Vietnam. Instruments are also needed to help general practitioners and other health care workers to identify excessive drinkers and reduce problem drinking. Many instruments have been developed over the past decades to assess alcohol consumption and alcohol problems (National Institute on Alcohol Abuse and Alcoholism, 1995). However, the use of these is particularly limited in developing countries (Babor et al., 2001). There is a need to adapt these *Author to whom correspondence should be addressed at: Department of Public Health Sciences, Norrbacka, Karolinska Instituet, SE-171 76 Stockholm, Sweden. E-mail: Peter.Allebeck@phs.ki.se and develop capacity for using these at the outpatient and community level in developing countries, and the next step is to implement the use of these as a part of programmes for secondary prevention in the health services. AUDIT has been found in many studies to be a valid and convenient instrument to screen for alcohol problems in primary care settings in many countries (Saunders et al., 1993b; Allen et al., 1997; McPherson and Hersch, 2000; Babor et al., 2001; Reinert and Allen, 2002). The present study is part of an epidemiological community survey in rural Vietnam. A number of health problems have been addressed through regular screening surveys of the general population (Chuc and Diwan, 2003). Since mental health problems and alcohol abuse by local people were reported to be important health problems in the area, although not systematically analysed, development work is ongoing to assess these problems in the community. This study aims (i) to adapt the Vietnamese version of AUDIT for identifying alcohol problems in Vietnam; (ii) to assess the accuracy and performance of AUDIT in detecting alcohol problems, as defined by ICD-10 and DSM-IV diagnostic criteria, in a rural setting in Vietnam. METHODS Setting The setting was a rural district in the North of Vietnam. The study was conducted within a longitudinal demographic surveillance system in a district with a land area of 410 km 2 and a population of 240 000 persons, the so-called FilaBavi project (Chuc and Diwan, 2003). In this system, all households were firstly visited as part of a census, to collect all background information such as date of birth, education, and occupation of all household members. Then, every 3 months the households are visited to collect information regarding migration, deaths, births, marital status changes, and health related information for specific research projects. Every 3 years a re-census is conducted to update the background information of these households. 578 Ó The Author 2005. Published by Oxford University Press on behalf of the Medical Council on Alcohol. All rights reserved

THE USE OF AUDIT IN RURAL VIETNAM 579 In this district, almost 80% of the population are farmers, some are handicraft-makers (6%), small traders (3%), and government staff (2%). The illiteracy rate among people >15 years is 0.4%. As in other rural areas of Vietnam, the most common use of alcoholic beverage is rice wine, which generally is self-produced, sold cheaply, and is easily accessible. Translation of instruments The AUDIT instrument consists of 10 questions, which have a possible maximum score of 40. The questions 1 8 may score 0 4 points, and questions 9 and 10 may score 0, 2, or 4 points. The English version of AUDIT was translated in to Vietnamese. Back-translation procedures were performed through several steps in order to keep the translated version in concordance with the original and to be adaptable to Vietnamese culture. We followed the procedures described by Room et al. (1996). The Composite International Diagnostic Interviews (CIDIs) (12 months) were used as a validation instrument. The CIDI was developed by the World Health Organisation to assess different mental disorders according to the definition and criteria in the International Classification of Diseases version 10 (ICD-10) and to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). Section J consists of 23 questions regarding alcohol use, alcohol abuse, withdrawal, and alcohol dependence conditions. The English version of CIDI, 12-month core version 2.1, section J was translated in to Vietnamese, was checked and refined in several steps of back-translation in a similar process as for the Vietnamese version of AUDIT described above. Sampling A total of three communes representative of three main geographical areas (lowland, highland, and mountainous) of the Bavi district were randomly selected from 32 communes. In these communes 500 people aged from 18 to 60 years were randomly selected using an identification number list that is available from the demographic surveillance system. Of the 500 subjects invited to participate in the study, only fifteen were absent during the data collection. The distribution with regard to sex, age, and other demographic characteristics did not differ significantly from the total population. Data collection Interviewers who work for the longitudinal epidemiological surveillance system performed the data collection. The interviewers were inhabitants of the district and had high school education or finished secondary medical education. Six interviewers were trained to perform interviews with AUDIT and eight interviewers were trained to assess alcohol use and alcohol problems by interviews with the CIDI 2.1, section J. The CIDI interviews were performed shortly after the interviews with AUDIT, and the interviewers were blind to the preceding interview results. The interviewers used hand cards to facilitate the interviewee s estimation of alcohol intake. The hand card had pictures of common beverages in the setting and the corresponding units for standard drinks. The data collection was performed during 3 months from December 2002 to February 2003. This study was approved both by the Research Ethics Committee at Gothenburg University and by the Scientific and Ethical Committee at Hanoi Medical University. All selected interviewees were informed about the study and gave consent to participate. Definitions Standard drink refers to the amount of 12.6 g pure alcohol, which equals 330 ml of 5% beer, or 40 ml of 40% liquor, or 130 ml of 12% wine, etc. Measures of alcohol problems Non-drinkers were defined as having consumed less than a total of 12 standard drinks during the previous 12 months. Non-problem drinkers were people who used alcohol but did not meet the criteria for problem drinkers defined as at-risk drinkers, as harmful use/alcohol abuse, or as alcoholdependent. According to the level of alcohol consumption in CIDI interviews, we defined at-risk drinkers as people who drank a daily average of >30 g alcohol (2.4 standard drinks) for a man and >20 g (1.6 standard drinks) for a woman. Harmful use was defined according to the criteria for harmful use in the ICD-10 and refers to alcohol consumption that results in consequences for physical and mental health. Alcohol abuse was defined according to the criteria in DSM-IV, which include also the social consequences caused by alcohol consumption. Alcohol dependence was classified according to the ICD-10 and DSM-IV criteria. These include a strong desire to drink alcohol, impaired control over its use, persistent drinking despite harmful consequences, a higher priority given to drinking over other activities, increased alcohol tolerance, and a physical withdrawal reaction when alcohol use was discontinued (Hasin, 2003). Educational level was divided into three categories: primary consisted of people who had one to five schooling years; secondary included people who had six to nine schooling years; high school referred to individuals with ten or more than ten years of schooling. Seventy-one percent of the population was counted as farmers since they were mainly doing farming. Due to a few observations, the rest were classified as non-farmers, which included government staff, small traders, handicraft-makers, housewives, etc. Statistical analyses Data analyses were performed using STATA 8.0. First, we examined the validity of AUDIT in detecting at-risk drinkers. Then, the validity of AUDIT was assessed using ICD-10 diagnostic criteria for harmful use and alcohol dependence. We also performed a validation using DSM-IV criteria for alcohol abuse and alcohol dependence. The agreements between ICD-10 and DSM-IV in giving diagnosis of harmful use/alcohol abuse and alcohol dependence were examined by the Kappa test. We calculated sensitivity, specificity, and correct classification rate of AUDIT compared to ICD-10 and DSM-IV. We estimated the means of AUDIT scores with 95% confidence interval, adjusted for age. We compared results of AUDIT in different categories of alcohol use, and tested the differences in means of AUDIT score by analysis of covariance (ANOVA test), adjusting for age, and socio-economic and demographic groups.

580 K. B. GIANG et al. Receiver operating characteristic (ROC) analysis was applied to assess the ability of AUDIT in discriminating cases and non-cases of at-risk drinking, harmful use, alcohol abuse, and alcohol dependence. ROC curves were obtained by plotting sensitivity against the false positive (1-specificity) at each cut-off point. The area under the ROC curve (AUC) was used as an indicator of test performance. Values of this area range from 0.5 to 1. A value of 1 indicates that the instrument gives a perfect discrimination between case and noncase, and a value of 0.5 implies an ability to discriminate no better than chance (Hajian-Tilaki et al., 1997). We calculated the AUC of AUDIT for detecting at-risk drinking, harmful use, alcohol abuse, and alcohol dependence. Firstly, we evaluated the ability of AUDIT to discriminate between nonproblem drinkers (including non-drinkers and non-problem drinkers) and at-risk drinkers. Then, we assessed the ability of AUDIT in differentiating subjects with harmful use from subjects without harmful use and without alcohol dependence. We finally evaluated the ability of AUDIT to discriminate between alcohol dependence (according to ICD-10) and all other categories. Similar analyses were also applied for the use of AUDIT in detecting alcohol abuse and alcohol dependence using DSM-IV criteria. We further compared the AUCs in different population groups with regard to educational level, occupation, marital status, and age. Since the prevalence of drinking among women was very low, we only report the validity of the instrument in detecting alcohol problems in men. RESULTS In the sample, 58% were women. The mean age was 41 years with no sex difference. Socio-demographic characteristics are shown in Table 1. Table 2 shows the 12-month prevalence of different categories of alcohol problem according to ICD-10 and DSM-IV. More men than women were current drinkers (89.7% vs 12.8%). A much lower prevalence of alcohol problems was found among women than among men. Among men, according to ICD-10, 16.3% were at-risk drinkers, 1.97% was harmful use and 7.9% were alcohol dependants. The use of DSM-IV yielded 1 more case of alcohol dependence compared to ICD-10. There were eight cases of alcohol abuse according to the DSM-IV, while only four cases were defined as harmful use according to ICD-10. The agreement between ICD-10 and DSM-IV in diagnosing harmful use/ alcohol abuse was Kappa equal to 0.68 (SE = 0.06), and the agreement between two diagnostic criteria in diagnosing alcohol dependence was Kappa equal to 0.98 (SE = 0.07). Due to few cases of alcohol problems observed among women (1/282), we could only evaluate the validity of AUDIT in men. Table 3 shows crude and age-adjusted mean of AUDIT score for alcohol problems, as well as results from the covariance analysis. The AUDIT scores were higher for alcohol problems. Age-adjusted mean scores of AUDIT increased markedly by increasing level of alcohol problems. Similar results also were found when DSM-IV criteria were followed. The AUDIT scores seemed to be influenced by age since age-adjusted means differed from crude means. The analysis of covariance with age as covariate found only Table 1. Socio-demographic background data of subjects included in the study Men Women (n = 203) (n = 282) Age distribution Mean age 41.9 (SD = 10.9) 40.4 (SD = 10.9) 18 39 77 (38.0%) 121 (42.9%) 40 60 126 (62.0%) 161 (57.1%) Educational level Primary school and below 18 (8.9%) 37 (13.1%) Secondary school 130 (64.0%) 205 (72.7%) High school and above 55 (27.1%) 40 (14.2%) Occupation Farmer 143 (70.4%) 239 (84.8%) Non-farmer 60 (29.6%) 43 (15.2%) Marital status Single 136 (6.4%) 29 (10.3%) Married 188 (92.6%) 210 (74.5%) Widowed/divorced/separated 2 (1.0%) 43 (15.2%) Table 2. Prevalence of alcohol use and problem drinking Men Women Men and women Categories N=203 % N=282 % N=485 % According to ICD-10 Non-drinker 21 10.3 246 87.2 267 55.1 Non-problem drinker 129 63.6 35 12.4 164 33.8 At-risk drinker 33 16.3 1 0.4 34 7.0 Harmful use 4 1.97 0 0 4 0.8 Alcohol dependence 16 7.9 0 0 16 3.3 According to DSM-IV Non-drinker 21 10.3 246 87.2 267 55.1 Non-problem drinker 124 61.1 35 12.4 159 32.8 At-risk drinker 33 16.3 1 0.4 34 7.0 Harmful use 8 3.9 0 0 8 1.6 Alcohol dependence 17 8.4 0 0 17 3.5 alcohol problem as the main effect. There was a statistically significant interaction between alcohol problem and age, while there was no other significant interaction effect. The analyses using DSM-IV classification gave almost the same results to the ICD-10. The validity indices of AUDIT against both ICD-10 and DSM-IV are presented in Table 4. As a predictor for at-risk drinkers, AUDIT had a sensitivity of 81.8%; specificity of 76.1%, and a correct classification rate of 77.3% at the cut off point of 7/8. This cut-off point was optimal as it was closest to the upper-left point (100% sensitivity and 0% false positive) (Fig. 1). Using ICD-10 as criterion, the cut-off point 9/10 showed the best specificity of 83.6% at 100% of sensitivity and a 83.9% correct classification rate for harmful use among men. For screening of alcohol dependence, a score of 8 seemed to be optimal with a sensitivity of 87.5%, a specificity of 76.5%, and a correct classification rate of 77.3%. AUDIT had higher validity indices when both sexes were included in the analyses (data not shown). Compared to DSM-IV criteria, the AUDIT had somewhat lower sensitivity but higher specificity for predicting alcohol

THE USE OF AUDIT IN RURAL VIETNAM 581 Table 3. Age-adjusted AUDIT means for categories of alcohol use among men according to ICD-10 and DSM-IV criteria ICD-10 DSM-IV Non-adjusted means Age-adjusted means Non-adjusted means Age-adjusted means Alcohol use category Non-drinker 0.71 1.26 0.71 1.36 (0.36 1.46) (0.02 2.3) (0.41 1.46) (0.03 2.41) Non-problem drinker 4.35 4.62 4.24 4.51 (3.67 4.93) (4.02 5.22) (3.67 4.81) (3.89 5.13) At-risk drinker 10.06 7.86 10.06 7.86 (8.14 11.90) (7.17 8.55) (8.14 11.90) (7.17 8.55) Harmful use (ICD-10)/ alcohol abuse (DSM-IV) 13.00 11.03 9.75 10.53 (4.28 21.70) (9.87 12.1) (4.07 15.42) (9.43 11.64) Alcohol dependence 12.12 14.23 11.94 13.61 (9.04 15.21) (12.5 15.20) (9.03 14.85) (12.01 15.20) Analysis of covariance Main effects Alcohol problems F = 3.24 P = 0.01 F = 4.76 P = 0.001 Age F = 0.11 P = 0.74 F = 0.22 P = 0.64 Education level F = 0.16 P = 0.85 F = 0.60 P = 0.55 Occupation F = 1.48 P = 0.23 F = 2.76 P = 0.27 Marital status F = 0.16 P = 0.85 F = 0.21 P = 0.81 Interaction Alcohol problems age F = 5.55 P = 0.0023 F = 5.55 P = 0.0003 Marital status age F = 0.25 P = 0.81 F = 0.25 P = 0.78 Education age F = 0.46 P = 0.64 F = 0.46 P = 0.63 Occupation age F = 3.19 P = 0.04 F = 3.19 P = 0.04 Table 4. Sensitivity, specificity of AUDIT as the predictor of at-risk drinking, harmful use, alcohol abuse, and alcohol dependence in men according to ICD-10 and DSM-IV Cut-off 3/4 4/5 5/6 6/7 7/8 8/9 9/10 10/11 At risk Sensitivity 95.4 95.4 88.6 84.1 81.8 72.7 65.9 54.6 Specificity 38.9 50.3 59.8 67.9 76.1 83.7 89.9 92.5 Correctly classified 51.2 60.1 66.0 71.4 77.3 81.3 84.7 84.2 Harmful use ICD-10 Sensitivity 100 100 100 100 100 100 100 75.0 Specificity 34.4 44.3 54.1 62.3 69.9 78.1 83.6 86.9 Correctly classified 35.8 45.5 55.1 63.1 70.6 78.6 83.9 86.6 Alcohol abuse DSM-IV Sensitivity 87.5 75.0 62.5 62.5 62.5 62.5 62.5 50.5 Specificity 34.8 44.4 53.9 62.4 70.2 78.7 84.3 87.1 Correctly classified 37.1 45.7 54.3 62.4 69.9 77.9 83.3 85.5 Alcohol dependence ICD-10 Sensitivity 93.8 93.8 93.8 93.8 93.8 87.5 68.7 56.3 Specificity 72.9 76.9 81.0 84.4 87.4 90.6 92.8 94.2 Correctly classified 73.6 77.5 81.4 84.7 87.6 90.5 91.9 92.9 Alcohol dependence DSM-IV Sensitivity 94.1 94.1 94.1 94.1 88.2 70.6 52.9 47.1 Specificity 43.6 53.2 61.3 68.8 76.9 82.3 85.5 88.7 Correctly classified 47.8 56.7 64.0 70.9 77.8 81.3 82.8 85.2 dependence at all thresholds. AUDIT had a lower sensitivity for detecting alcohol abuse compared to that for harmful use. Figure 1 presents the trade-off between sensitivity and false positive (1-specificity) at different cut-off points and the AUCs of AUDIT for at-risk drinkers, harmful use, alcohol abuse, and alcohol dependence. The smallest AUC was 0.82 (0.72 0.91) for alcohol abuse and the largest was 0.91(0.84 0.98) for harmful use. There was no significant variation in AUC by age, educational level, occupation, and marital status (data not shown). DISCUSSION The AUDIT has been assessed in several primary care and hospital settings but has been rarely evaluated for the use in a general population (Saunders et al., 1993a, b; Conigrave et al., 1995a, b; Allen et al., 1997; Piccinelli et al., 1997; Volk et al., 1997; Cherpitel, 1998; Reid et al., 1999; Daeppen et al., 2000; Fiellin et al., 2000; Leung and Arthur, 2000; Babor et al., 2001; Reinert and Allen, 2002; Rumpf et al., 2002; Mei Chu Tsai, 2005). In this study we assessed

582 K. B. GIANG et al. Sensitivity (true positives) 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 0.5 1 1 - Specificity (false positives) Sensitivity (true positives) 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 0.5 1 1 - Specificity (false positives) --*-- at risk:auc=.85(.78-.93) --+-- abuse-dsm-iv:auc=.82(.72-.91) --o-- dependence-dsm-iv: AUC=.85(.75-.94) -- -- harmful use-icd-10: AUC=.91(.84-.98) -- --dependence-icd-10: AUC=.84(.74-.94) Fig. 1. ROC curves and AUCs of AUDIT for alcohol abuse and dependence among men according to DSM-IV; harmful use and dependence according to ICD-10; and at-risk drinking. the accuracy and the performance of AUDIT as an indicator of alcohol problems in a rural population. The AUDIT was found to be feasible to use in the rural population in Vietnam since it takes a short time to complete and can be easily administered by lay interviewers. Furthermore, the questions were considered to be easy to understand and to answer by the subjects. The discussions with researchers in the primary stage of the instrument adaptation indicated that the contents of the AUDIT were relevant and adaptable for the purpose of detecting alcohol problems in Vietnam. This is in agreement with other studies that have shown that AUDIT is a brief and convenient questionnaire when used in clinical and primary care settings (Conigrave et al., 1995a; Allen et al., 1997; Leung and Arthur, 2000; Babor et al., 2001). According to our results, the AUDIT score significantly increased by increasing the level of alcohol problems (from at-risk drinking to harmful use/alcohol abuse, and to alcohol dependence). This suggests that the AUDIT is valuable instrument in recognizing alcohol problems in our setting. Robert et al. indicated significant interactions between alcohol problem and gender, and between alcohol problem and ethnicity, while we found an interaction between age and alcohol problem, and between occupation and age (Volk et al., 1997). Higher prevalence of alcohol problems among men, and more current drinking among farmers are possible explanations for our findings. In our study, the cut off point of 7/8 gave an acceptable sensitivity and specificity for detecting alcohol problems. AUDIT had a lower sensitivity for prediction of alcohol abuse, but had high sensitivity for detecting harmful use. Difficulty in defining alcohol as cause of medical problems might be the explanation for this. In several studies from Australia, Bulgaria, Kenya, Mexico, Norway, USA (Saunders et al., 1993b; Bradley et al., 1998; Daeppen et al., 2000; Fiellin et al., 2000; Reinert and Allen, 2002) Hong Kong (Leung and Arthur, 2000), the cut-off point of 7/8 had a sensitivity and specificity of around 80%. Some studies even reported such high sensitivity and specificity at a cut-off of 4/5 (Piccinelli et al., 1997; Daeppen et al., 2000). For instance, Piccinelli et al. (1997) reported a sensitivity of 84% and a specificity of 90%. However, Hans et al. in Germany found a low sensitivity of 33%; 37% for at-risk drinking and for current alcohol misuse at the cut-off point of 7/8 (Rumpf et al., 2002). The cut-off point of 7/8 has been found and used as an optimal threshold in several studies, and was called standard cut-off point elsewhere (Conigrave et al., 1995a). The cutoff of 7/8 has been suggested for use in primary care (Babor et al., 2001). Choosing a cut-off point normally depends on the purpose of each specific work. Lower cut-off points are preferably used in general population surveys and for two-stage surveys. Higher cut-off points can be used when the aim is to identify severe cases who need further diagnostic evaluation and treatment (Babor et al., 2001). We used both ICD-10 and DSM-IV to validate AUDIT. The Kappa test showed a high level of agreement between two sets of criteria for dependence (0.98) but lower agreement for alcohol abuse (0.68). This is understandable since ICD-10 just limits harmful use to the medical problems caused by alcohol, while DSM-IV includes social problems resulting from alcohol (Hasin, 2003). A limitation was the small number of women (n = 282), among whom the prevalence of alcohol problems was low. We could thus analyse performance of AUDIT only in men. Also, the study was conducted in a typical rural community in the North of Vietnam that might not be representative for other communities, e.g. urban, in Vietnam. In conclusion, we confirmed that AUDIT is feasible for use in a rural community in a developing country. Different cut-off points are appropriate for different purposes, but for general population screening of at-risk drinking we found a cut-off point of 7/8 to be optimal, and this will be used for further prevalence studies in this population.

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