|Year : 2015 | Volume
| Issue : 2 | Page : 135-139
Alcohol use and alcohol use disorder among male outpatients in a primary care setting in rural Puducherry
Akkilagunta Sujiv, Palanivel Chinnakali, Karthik Balajee, Subitha Lakshminarayanan, S Ganesh Kumar, Gautam Roy
Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
|Date of Web Publication||4-May-2016|
Departments of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, 4th Floor, Admin Block, Dhanvantari Nagar, Puducherry - 605 006
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Context: Alcohol use contributes to considerable morbidity and mortality worldwide. Screening for alcohol use and alcohol use disorder (AUD) at the primary care level can help in reducing this burden. While several community studies have been conducted to estimate the AUD, there apparently are no studies on opportunistic screening in a primary care setting in India. Aims: The aim was to estimate the prevalence of alcohol use and AUD in a primary care setting. Settings and Design: A hospital-based cross-sectional study was conducted among adult male outpatients in a primary care setting in Puducherry, South India. Subjects and Methods: Male outpatients aged 18 and above were interviewed for alcohol use. Current alcohol users were screened for AUD using World Health Organization - AUD identification test (AUDIT) questionnaire, respectively. Statistical Analysis Used: Proportions were used to describe the study population and the main study findings. The Chi-square test was used to find out the association between sociodemographic factors and alcohol use. Results: Of 256 subjects studied, 39.8% were found to be current alcohol users and 10.9% had AUD (AUDIT score ≥8). The sociodemographic factors did not show any association with an alcohol use in the current setting. Conclusion: Based on the findings of the present study, four current alcohol users are to be screened to identify one patient with AUD. Screening at the primary health care level can help in identifying the risk group and thus help in reducing the morbidity and mortality due to alcohol use in the population.
Keywords: Alcohol drinking, alcohol use disorder identification test, alcoholism, primary health care
|How to cite this article:|
Sujiv A, Chinnakali P, Balajee K, Lakshminarayanan S, Kumar S G, Roy G. Alcohol use and alcohol use disorder among male outpatients in a primary care setting in rural Puducherry. Ind Psychiatry J 2015;24:135-9
|How to cite this URL:|
Sujiv A, Chinnakali P, Balajee K, Lakshminarayanan S, Kumar S G, Roy G. Alcohol use and alcohol use disorder among male outpatients in a primary care setting in rural Puducherry. Ind Psychiatry J [serial online] 2015 [cited 2019 Nov 17];24:135-9. Available from: http://www.industrialpsychiatry.org/text.asp?2015/24/2/135/181711
Alcohol use is currently an emerging public health threat. According to the Global Burden of Disease Study 2010, alcohol is the third largest risk factor with respect to its contribution to the global disability adjusted life-years (DALYs). It had contributed to 4.9 million deaths and 5.5% of the global DALYs in 2010. The World Health Organization (WHO) described the “reduction of the social and health burden due to harmful alcohol use” as one of the priorities in the recent global status report on alcohol.
In India, several community-based studies have reported on the prevalence of alcohol use. The prevalence of alcohol use was found to be 29.6% in a nationally representative study. Prevalence from studies reported from south India range between 16.7% and 46.8%,,, Development of disease due to alcohol depends on the pattern of drinking., Hence, not all alcohol users would be in need of medical intervention. Simple screening tools can be used to identify individuals with alcohol use disorder (AUD) (problem drinking) and alcohol dependence.
The AUD identification test (AUDIT) is a tool designed to screen for problem drinking and make appropriate intervention. Several community-based studies estimated the prevalence of AUD between 7.1% and 14.2% using the AUDIT tool.,, The same studies reported the proportion with AUD among current alcohol users between 28.1% and 42.2%. Compared to population-based screening, hospital-based screening can be relatively rapid and valuable in giving a timely intervention.
Several hospital-based studies have been conducted in India to assess the prevalence of AUD among admitted male in-patients. The prevalence of AUD in the study population ranged between 14.6% and 30.5% in these studies.,,, These studies were conducted in a tertiary care setting where specialist Psychiatry services were readily available. Under the National Mental Health Program (NMHP) in India, specialist psychiatry services are available only at the district level. It may not be sufficient to deal with the burden of alcohol since the majority of the patients visit primary care settings for routine care. Opportunistic screening with simple intervention given at primary care level can help in reducing the gap in the alcohol de-addiction services. A thorough search of PubMed and IndMed did not reveal any study assessing alcohol use or AUD in a primary health care setting in India.
We, therefore, aimed to assess the prevalence of alcohol use and AUD s and the association of sociodemographic factors with current alcohol use among outpatients in primary care setting.
| Subjects and Methods|| |
A cross-sectional study was conducted among male outpatients attending a Primary Health Centre in May 2014, Puducherry, South India. The Primary Health Centre is the rural field practice area of a Tertiary Care Teaching Institute. The health center provides preventive, promotive, and curative services for a population of 9100 spread across four villages. The health center is led by two medical officers. Medical interns (approximately 6–8 in number) posted for a period of 1-month are involved in providing round-the-clock health services under the supervision of the medical officer. Outpatient clinics are conducted on 6 days a week. Special clinics are conducted 3 days in a week for antenatal mothers, under-five children, and patients with chronic diseases. The average outpatient department (OPD) attendance of males (including children and adults) is 30–35/day. Psychiatry consultation services are provided once a week by a psychiatrist in the health center.
Adult male patients 18 years of age and above attending JIRHC OPD were included for the purpose of the study. Assuming α error of 5%, expected proportion of alcohol use among male outpatients as 30% and relative precision of 20%, the required sample size was 225. The eligible patients were initially provided medical care for their presenting illness. After taking an informed consent, they were interviewed using a pretested questionnaire. The questionnaire included sociodemographic details, family history of alcohol use, awareness of alcohol-related ill-effects and reason for initiation of drinking. The questions for describing alcohol use were derived from the WHO-STEPS instrument. The sociodemographic parameters included age, educational status, current occupation, the pattern of employment, type of family, and family income. International Standard Classification of Education (2011) was used to classify the educational status. Current employment status was classified as “employed” or “unemployed.” Subjects who were employed were further classified as “daily wage worker” or “salaried employee.” Socioeconomic status was classified based on Updated Modified Prasad Scale.
Alcohol use was categorized based on the STEPS  manual into lifetime abstainers, last year abstainers, and current users of alcohol. Lifetime abstainers were defined as those who never had alcohol in their lifetime. Last year abstainers were those who had alcohol at some point in their life but not in the past 12 months. Current alcohol use was defined as alcohol use in the past 12 months. AUDIT was administered to current alcohol users to screen for AUD.
The alcohol use disorder identification test is a set of 10 questions developed by the WHO in 1992 as a screening tool to assess the harmful pattern of drinking among alcohol users. Each question is scored from 0 to 4 with a maximum possible score of 40 for each individual. AUD was defined as an AUDIT score of more than or equal to 8. The screening tool was translated into Tamil. Back translation measures and piloting were undertaken before final implementation. Patients that were found to have AUD were managed as per the WHO recommendations.
Data were entered in MS Excel 2010 and analyzed using IBM SPSS version 20. Alcohol use and AUD were summarized as proportions. For numerical variables, the data are summarized as median (interquartile range [IQR]) or mean standard deviation. A Chi-square test of proportions was used to find out the association of sociodemographic factors with current alcohol use.
| Results|| |
A total of 256 adult male outpatients were interviewed in the study. Median (IQR) age was 50 (35–60) years, and 30% of them were aged 60 years and above [Table 1]. A large proportion of the patients (46.4%, n = 119) did not complete primary level of education. The majority of the study population were currently employed (78%, n = 206) with daily wage labor being the most common job pattern among them (70.4%, n = 145). Based on per capita income, approximately three-fourths (74.2%, n = 190) of the study participants were below the upper middle class of modified Prasad's classification.
|Table 1: Sociodemographic characteristics of male outpatients attending a rural Primary Health Centre in Puducherry, South India (May 2014)|
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Of total 256 participants, 58.6% (n = 150) reported lifetime use of alcohol, of which 39.8% (n = 102) were current users, and 18.8% (n = 48) were last year abstainers. After applying the AUDIT screening tool to the current alcohol users (n = 102), AUD was found among 27.5% (n = 27) [Figure 1]. Six (5.9%) of these patients were alcohol dependent with an AUDIT score of ≥20. Based on the study findings, four current alcohol users (or 10 adult male outpatients) are to be screened to identify one patient with AUD in a primary care setting.
The sociodemographic factors assessed in the present study, did not show any significant association with current alcohol use [Table 2]. However, there was a notable difference in alcohol use among subgroups based on marital status and job pattern. A higher proportion of widowed/separated men (50%) were current alcohol users when compared with unmarried (25%) and married men (40%) though this did not amount to statistical significance. Prevalence of current alcohol use was higher among salaried employees (49.2%) compared to that of daily wage workers (36.6%).
|Table 2: Association of sociodemographic characteristics with current alcohol use among male outpatients attending a rural Primary Health Centre in Puducherry, South India (May 2014) (n=256)|
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The family history of alcohol use did not show significant association with current alcohol use. Of the current alcohol users, 89.2% were aware of the ill effects of alcohol. Of those who were aware of ill effects, the majority were aware of the health effects (60%) followed by social problems (30%). Peer pressure was reported as the most common reason (27.3%) for initiation of drinking.
| Discussion|| |
Our study showed a prevalence of alcohol use among OPD patients in primary health care setting in Puducherry to be 39.8% (95% confidence interval – 33.8 – 45.8) and AUD to be 10.9% (n = 27). The proportion of AUD among current alcohol users was 27.5%. Our findings on the prevalence of alcohol use are similar to that of community-based studies done in Meerut  (29.6%) and rural areas of Tamil Nadu , (34.8–35.7%). However, the prevalence is relatively higher when compared to a community-based study conducted by Kumar et al. in the neighboring district of Tamil Nadu. The difference could be due to the inclusion of adolescents in the study by Kumar et al.
The prevalence of alcohol use among hospital-based studies did not vary greatly between the community-based studies and the present study. Murthy et al. and Srinivasan and Augustine  reported current alcohol use among male hospital in-patients to be 25.3% and 31.3%, respectively.
In the current study, no significant association was found for age, education, and socioeconomic status. The community-based study in Meerut  also reported similar findings for these factors. The study by Kumar et al. reported an increased risk of alcohol use in the age group 15–44 and among illiterate individuals. One of the reasons for the lack of such association could be a smaller sample size in the current study.
In the present study, a notable difference in alcohol use was observed with respect to marital status though it did not amount to statistical significance. Katyal et al. reported a statistically significant association between marital status and current alcohol use.
In the present study, 27.5% of the current users had AUD was similar to some of the community-based studies. The studies from Meerut  and certain rural areas in Tamil Nadu , reported the proportion of AUD among current users between 28.1% and 39.3%. The difference between hospital-based studies and community-based studies is pronounced with respect to the proportion of current alcohol users with AUD. When compared with the hospital-based studies by Srinivasan and Augustine  and Murthy et al. reported the proportion of current users with AUD as 65.6% and 67.2%, respectively.
While AUDIT score of ≥8 may include, even disorders at the trivial end of the spectrum AUDIT score ≥20 is termed as “probable alcohol dependence.” Alcohol dependence was higher among patients in a tertiary care setting (9.5%) when compared with the present setting (2.3%). The current study shows a similarity between the general population and primary care OPD patients with respect to the proportion of AUD among current users. However, the present study lacked sufficient power to find out the prevalence of AUD.
To the best of our knowledge, this is the only study estimating AUD conducted in a primary care setting in India in spite of smaller sample size. Social desirability bias and recall bias could have influenced the response for some of the questions in the screening tool.
A set of two simple questions on lifetime alcohol use and alcohol use in the past year would be sufficient to identify current alcohol users. Hence, screening for AUD among current alcohol users can be a feasible approach in a primary care setting.
Alcohol is a known behavioral risk factor for several noncommunicable diseases such as coronary artery disease, cancer, and mental health disorders. Based on the principle of early diagnosis and treatment, identifying alcohol disorder at an early stage has greater potential for prevention. Moreover, given the fact that alcohol is the third largest risk factor in the world, the importance of screening for AUD cannot be overemphasized. Primary care settings allow us to identify mild forms of AUD where screening and intervention have maximum benefit. The availability of specialist services for alcohol de-addiction is often restricted to the district level. Strengthening primary care services through the incorporation of simple screening tools like AUDIT can be an efficient intervention to tackle the problem of alcohol use. Such initiatives from national programs such as NMHP and a national program for prevention and control of cancer, diabetes, cardiovascular disease, and stroke would remain a hope for the future.
| Conclusion|| |
The present study showed that two-fifths of the patients are current alcohol users, and one-tenth have AUD in a primary care setting. The study also shows that four patients with current alcohol use need to be screened to detect one patient with AUD. Adopting such simple screening tools for AUD in national programs could be a feasible strategy to reduce the burden of alcoholism.
We thank the following doctors - Chandramouli, Devada Sindhu, Diana Thomas, Divya Bharathi, Dudaka Anusha, Dwaipayan Chatterjee, Gokul Raj, and Preethi Prakash for their sincere efforts in data collection.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2]