|
 
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| REVIEW ARTICLE |
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| Year : 2022 | Volume
: 27
| Issue : 1 | Page : 8-18 |
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Systematic review: Rates and determinants of relapse to alcohol: A systematic review of Indian studies
Siddharth Sarkar1, Ashlyn Tom1, Sauvik Das2, Balaji Bharadwaj3, Abhishek Ghosh2
1 Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India
2 Department of Psychiatry, Drug De-Addiction and Treatment Centre, Postgraduate Institute of Medical Education and Research, Chandigarh, India
3 Department of Psychiatry, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| Date of Submission | 10-Nov-2020 |
| Date of Decision | 25-Dec-2020 |
| Date of Acceptance | 26-Dec-2020 |
| Date of Web Publication | 13-Aug-2022 |
Correspondence Address:
Dr. Abhishek Ghosh
Department of Psychiatry, Drug De-Addiction and Treatment Centre, Postgraduate Institute of Medical Education and Research, Chandigarh - 160 012
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jmhhb.jmhhb_191_20
Background and Aims: Relapse is a major clinical concern in alcohol use disorders. The magnitude of the problem, poor access and availability of treatment, and changing social milieu placed India in a challenging position. This was a systematic review of Indian studies on rates and determinants of relapse to alcohol. Methods: Systematic search (January 1980–May 2020) was carried out on PubMed and Google Scholar to select studies that presented either rates or predictors (or both) to alcohol. Relapse was broadly defined based on the characterization in the included articles. We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses standard for reporting systematic reviews. Results: Thirty-six studies were selected for the qualitative synthesis from the 68 studies. In the pooled sample of 2481 participants, the relapse rate ranged from 3.4% to 90%. The study duration varied from 1 to 36 months. Results suggested that the rates were overall higher in the observational than interventional studies and in studies from states with community prevalence of alcohol use >15% than in those <10%. There was significant heterogeneity among studies. Risk factors of relapse identified were demographic (e.g., younger age), psychological (e.g., craving), situational (e.g., peer influence), stressful life situations (e.g., financial problems), and family history of alcohol use. Conclusion: Relapse is likely in a substantial proportion of participants. Addressing the risk factors might help in delaying relapse. Future studies could concentrate on inclusive study design and robust methodology, to examine and understand the rates and risk factors of relapse.
Keywords: Alcohol use disorders, dependence, relapse, systematic review
How to cite this article:
Sarkar S, Tom A, Das S, Bharadwaj B, Ghosh A. Systematic review: Rates and determinants of relapse to alcohol: A systematic review of Indian studies. J Mental Health Hum Behav 2022;27:8-18 |
How to cite this URL:
Sarkar S, Tom A, Das S, Bharadwaj B, Ghosh A. Systematic review: Rates and determinants of relapse to alcohol: A systematic review of Indian studies. J Mental Health Hum Behav [serial online] 2022 [cited 2023 Mar 26];27:8-18. Available from: https://www.jmhhb.org/text.asp?2022/27/1/8/353753 |
| Introduction | |  |
Effective treatment strategies are available for treatment of patients with alcohol use disorders.[1],[2],[3] While short-term treatment has been shown to reduce withdrawal symptoms and complications of withdrawal, long-term treatment has been able to achieve abstinence and reduction in craving for alcohol.[3],[4],[5] Yet, it has been seen that many patients relapse to alcohol consumption after a period of cessation of use.[6],[7] The reasons include genetic proclivity, psychological vulnerabilities, and environmental cues.[7],[8],[9] Understanding these predictors of relapse would be helpful to clinicians to determine who is at greater risk, and offer more intensive treatment as required.
India has a unique sociocultural-historical background to alcohol use.[10] Alcohol contributes significantly in many state revenues, though there are states which have partial or complete ban on alcohol.[11],[12] On a population level, India is a largely abstinent country, though the proportion of heavy drinkers is high and seemingly alcohol initiation is occurring at an earlier age.[13] Problematic alcohol use may affect up to about 5% of the population in India, an estimated number of 57 million. The problem is compounded by a large treatment gap –2.6% of individuals with alcohol dependence sought treatment, as per the recently conducted national survey, and informal sectors (religious and spiritual organizations) catered to the largest proportion. There was a substantial variation in the prevalence of alcohol use (0.1% to 35.6%) and dependence, across the states. This variation might be a reflection of the legal status (and availability) and attitude toward alcohol in a particular state. The gender difference, too, was marked. Economic liberalization and globalization have brought about significant changes in the attitude toward alcohol in the last decade.[11],[12],[13],[14] The rates and risk factors for relapse to alcohol in Indian settings might be interesting to study because of the special sociocultural, demographic, legal, and attitudinal characteristics and a different help-seeking pattern. The relapse rate might also differ across states because of the varying attitude and availability of alcohol. Thus, caution would be exercised while drawing inferences of predictors of relapse from other situations to the Indian setting.
Several studies have been conducted in India that has looked at relapse rates of patients with alcohol use disorders.[15],[16],[17],[18] Studies were done from various states, and these were either observational or interventional; the duration of the studies was highly variable. A synthesis of evidence from the country would help to understand the overall relapse rates and risk factors. Thus, this review aimed to evaluate the rates and predictors of relapse to alcohol in India.
| Methods | | |
Search strategy
We searched three databases – PubMed, Google Scholar, and Cochrane databases. Additional articles were retrieved by searching the cross-references of the selected articles. Articles were retrieved from January 1980 to May 2020. We selectively looked for articles published in the English language and focused on alcohol relapse in human subjects. The search commenced in May 2020. The search terms of “alcohol use disorders” and other related terms (e.g., “alcohol dependence” and “alcohol abuse”) were added to the other term of interest, i.e., “relapse,” and “India” with the help of Boolean operators “AND” and “OR.” The search was built up in a PICO format – the population (subjects with alcohol use disorders), intervention (relapse determinants), and outcome (relapse). Controls were not required for studies to be included. The search details are given in [Table 1]. The overall search strategy was adapted from Sliedrecht et al.[19]
Study selection
Those studies published in academic journals and indexed in the abovementioned search engines were included if they included patients with alcohol use disorder, and provided quantitative information about the relapse rates, or any information about the predictors of relapse to alcohol. The review included both observational studies and intervention trials. Opinion pieces, editorials, and case reports were not included in the review. Studies with mixed drug use populations were also excluded. The study selection is depicted in [Figure 1].
Data extraction and analysis
Information was extracted from the included articles by two of the authors. Data were extracted regarding the author and year, location where the study was conducted, the study design, sample size, label used for alcohol-related problems, sample characteristics, intervention and control group, duration of follow-up, definition of relapse, rates of relapse, and correlates of relapse as applicable. Discrepancies if any were handled through mutual consensus.
Systematic risk assessment was done by the “risk of bias” (RoB2) tool.[20] The quality of the review work was checked by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method.[21] A PRISMA checklist is provided in [Supplementary Table 1].
| Results | | |
The search strategy is shown in [Figure 1]. The search yielded 68 articles, of which we excluded 32 articles as these did not provide specific data for alcohol or they did not report the proportion of patients who relapsed. Finally, we narrowed down to 36 full-text articles including 11 longitudinal observational studies, 14 cross-sectional studies, and 11 randomized or intervention studies. The details of the longitudinal studies, cross-sectional studies, and interventional studies are presented in [Table 2],[Table 3],[Table 4], respectively. Cross-sectional studies were case–control in design (relapsed vs. not relapsed population) and did not estimate the relapse rates. | Table 2: Longitudinal observational studies which have looked at alcohol relapse
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 | Table 3: Cross-sectional studies which have looked at predictors of relapse
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Qualitative synthesis of longitudinal observational studies
The findings from the longitudinal observation studies[15],[16],[17],[18],[22],[23],[24],[25],[26],[27],[28] are presented in [Table 2]. Among them, 2 were conducted in Bengaluru[24],[28] and 1 each in Mumbai,[15] Chandigarh,[16] Hyderabad,[22] Vellore,[25] Delhi,[23] Gurgaon,[27] and Ranny[17] whereas 2 studies did not mention the location of the study. The sample sizes of the individual studies ranged from 50 to 408. All the studies had a predominant male population, and the follow-up periods ranged from 1 month to 2 years, however, 1 study did not specify it. The relapse rates calculated from the studies ranged from as low as 9.6% to as high as 72.6%. However, the study which showed the lowest relapse rate was done in a gastroenterology unit in posttransplant patients with alcoholic liver disease. The definitions of relapse used in these studies were also highly variable, and only a few studies were able to clearly define a relapse. The various definitions are discussed in the tables.
The predictors of relapse identified through these studies included individual characteristics such as younger age of the individual, lower mean age at onset of dependence, lower average age of problem drinking, and lower mean age of day drinking. Other factors such as craving, peer pressure, poor coping style, negative life events, and external cues, family history of alcoholism, lower socioeconomic status, comorbid psychiatric disorders, and poor follow-up for treatment were also found to be predictors of early relapse.
Qualitative synthesis of cross-sectional studies
The 14 cross-sectional studies[29],[30],[31],[32],[33],[34],[35],[36],[37],[38],[39],[40],[41],[42] [Table 3] which looked at predictors of relapse had sample sizes in the range of 30–200. These studies had a predominant male population, and all studies were from different parts of India. Relapse was not defined in a few studies, while other studies defined relapse as a drinking pattern which was sufficient to qualify for the dependence criteria used for defining the sample after a period of abstinence or simply restarting drinking after a period of abstinence. Commonly identified predictors of relapse were craving, poor motivation, peer pressure, negative mood states, negative life events, poor social support, poor coping skills, family history of dependence, number of previous relapses, sleep disturbance, and physical illness.
Qualitative synthesis of intervention (experimental) studies
There were 11 intervention studies[43],[44],[45],[46],[47],[48],[49],[50],[51],[52],[53] [Table 4] included; 10 among these were randomized studies. Out of the 11 studies, 5 were done in Mumbai,[43],[44],[45],[46],[47] 2 in Bengaluru,[50],[51] and 1 study each in Delhi,[48] Ranchi,[49] and Kozhikode.[53] One study did not specifically mention the location. The sample sizes of the studies ranged from 32 to 122. The study populations were predominantly male, and the mean age of most studies was similar except for 2 studies, which were specifically looking into elderly and adolescent populations. Most studies were evaluating the effectiveness of various pharmacotherapies in preventing relapse, while 2 studies assessed various psychotherapeutic interventions, 1 study compared acamprosate and psychotherapy, and a single study assessed the effectiveness of transcranial magnetic stimulation in alcohol dependence for preventing relapse. Relapse was defined in 5 studies explicitly as more than 5 drinks in a 24-h period. Studies comparing the effectiveness of pharmacotherapeutic agents showed that disulfiram had lower relapse rates compared to other agents such as naltrexone, acamprosate, and topiramate. In another study comparing 3 drugs, the relapse rates from lowest to highest were in the order of topiramate, naltrexone, and acamprosate with rates of 18.4%, 30.8%, and 32.1%, respectively. In an open randomized study done by Gupta et al., 2017,[48] comparing relapse rates in baclofen and benfotiamine groups, baclofen had a significantly lower relapse rate. In a study comparing acamprosate and psychotherapy, relapse rates were found to be lower in the acamprosate group. In studies assessing the effectiveness of various psychotherapy interventions, better outcomes were seen in family intervention and dyadic relapse prevention techniques. In the only study which compared active repetitive transcranial magnetic stimulation with sham, the active group showed a lower relapse rate.
Relapse rates according to the study location
We also intended to examine whether relapse rates varied according to the study location? The relapse rates ranged from 9.6% to 90% in five studies conducted in locations where community prevalence of alcohol use disorder is more than 15% (states of Haryana, Delhi, Punjab, and Telangana). The relapse rate varied from 3.4% to 73.3% in eight studies conducted in Maharashtra, Karnataka, and Jharkhand where community prevalence of alcohol use disorder is <10%. Therefore, the rates of relapse were possibly higher in study locations where the population prevalence of alcohol use disorders was also high.
The excluded studies are presented in [Supplementary Table 2]. Out of them, 20 did not report the rates or predictors of relapse to alcohol, 8 did not present separate data for alcohol, and 4 did not use the term relapse specifically to denote the outcomes of alcohol.
A risk of bias assessment was done and is depicted in [Supplementary Table 3].
| Discussion | | |
The studies included in the systematic review were highly heterogeneous in terms of the sample characteristics (inpatient and outpatient), follow-up duration, designs (observational and experimental), and definition of the outcome (i.e., relapse). Systematic assessment of the risk of bias also revealed a “high -risk” for all but one of the experimental studies. The high heterogeneity and risk of bias precluded quantitative synthesis of the results.
The present review looked at the rates of relapse in patients with alcohol use disorders, and found a wide variation in the manner in which relapse has been conceptualized and the extent of rates of reported relapse. Looking at the world literature, different researchers have conceptualized relapse differently. As remarked by Fuller,[54] relapse has been defined from not being abstinence, to consuming in a particular threshold frequency, to consumption in a time interval, to facing adverse consequences like hospitalization. The rates of relapse are contingent upon the definition used for categorizing relapse.[55] In the present review, too, the definition of relapse varied across the studies. Harmonization of the definitions was not possible, and we took whatever definition the authors used for categorizing as relapse. However, we had to exclude some studies which did not mention relapse but did follow up patients and measured drinking outcomes.[56],[57],[58],[59]
The rates of relapse to alcohol varied in the reported studies from 9.6% to 90%. Looking at studies from elsewhere, rates of relapse or resumption of heavy drinking were found in this range in the naturalistic studies.[55],[57] Intervention studies had lower relapse rates than the observational studies. All the trials considered in the review were open-label trials between active drugs – naltrexone, acamprosate, disulfiram, and topiramate. A previous meta-analysis showed that naltrexone, acamprosate, and disulfiram reduced the chances and severity of relapse, and improved cumulative abstinence.[60],[61],[62],[63],[64] Disulfiram requires a special mention. A meta-analysis by Skinner et al.[64] found that disulfiram was more effective than controls only in open-label trials (not in blinded studies). All the Indian studies, as mentioned above, were open label. Additionally, in these studies supervised (by family members), disulfiram was prescribed, which had led to greater adherence.[45],[45] In contrast to the West, a greater family support in India and other SEAR countries would encourage the use of disulfiram. An overall lower relapse rate in intervention studies might also indicate other alternatives – systemic bias resulted from the open-label design and consequently participants' and researchers' expectancy and greater clinical attention by the research staff – Rosenthal's effect and Hawthorne's effect, respectively.[65]
The results showed higher relapse rates in those studies, where the community prevalence of alcohol use was greater (from the states of Haryana, Delhi, Punjab, and Telangana).[14] Higher prevalence of alcohol use at the population level suggests a permissive attitude toward alcohol and perhaps an easier access to alcohol as well. We speculated that these factors might have contributed to the higher propensity of relapse in the clinical population as well.
Several predictors of relapse were enumerated in the present study. Among the sociodemographic characteristics, younger age and distance from the treatment facility were predictors of relapse to alcohol. The effect of young age on relapse was difficult to assess because we could include only one study among adolescents or young adults.[45] Distance from a treatment facility is important in the Indian context, where the treatment gap is enormous, and there is difficult access and availability of treatment.[14] The Indian studies identified craving as a risk factor for relapse. Many patients reported stress as a reason of relapse, which has been reported in the literature from elsewhere as well.[66] Several issues such as family conflicts and financial stress have been linked to relapse in the present review. From the perspective of relapse precipitants, items classified as negative mood states and reduced cognitive vigilance (toward alcohol use) predicted relapse to alcohol. This suggests that individuals who have currently quit alcohol may be likely to restart when they face certain adverse life events or experience emotional distress. Having a family history of alcohol use disorder was a predictor of relapse. This could be due to the genetic vulnerability to alcohol use, or due to family-social environment which is permissive to alcohol use. Although the risk factors for relapse to alcohol appeared to be largely similar in the Indian and the studies from elsewhere,[19] there were a few factors such as family conflict (and resultant stress), family's influence on drinking behavior, and peer influence, which might have been overrepresented in Indian studies. The collectivistic nature of the Indian society and family, which places interdependence over individual's autonomy, might explain the greater role of family members' and peers' influence on relapse.[67]
Some characteristics of the studies need attention. It was seen that the study population in many studies consisted exclusively of males or had substantial male predominance. This is in line with the general treatment-seeking population in addiction treatment services, where men outnumber the women.[68],[69] The patients were generally in their mid-thirties to forties, which has been the usual age when patients with alcohol use disorders generally reach for treatment.[70] The patients were largely married. This also draws attention to the impact the alcohol use would be having on the family members. The studies were conducted in various parts of India, suggesting that alcohol use disorders and their relapse has been an important clinical and research consideration. Furthermore, the studies ranged in follow-up duration from a month to about 3 years. The duration of studies might involve feasibility of conduct, dropouts, changes in treatment over the time course, and other possible causes of attrition. Interestingly, we did not find a relationship of duration of the study and relapse rates.
The implications of the review for the clinicians are that a significant majority of patients with alcohol use disorders would relapse over the course of follow-up. The reasons for relapse would be individual specific. However, efforts require relapse prevention measures and adherence to treatment. Involvement of the family in the treatment process can be helpful in these aspects,[71] as reflected by findings of one of the studies in this review.[45] Disulfiram, when supervised, has been found to have good outcomes, and may be considered as a treatment measure when family members are available and patient willing for this medication. Craving and peer influence may be reported by patients during follow-up, which may need counseling sessions to deal with high-risk situations. Distance from the treatment facility as a determinant of relapse, highlighted the importance to improving the access and availability of substance use treatment across health facilities. The treatment for alcohol use disorders should be made available, accessible, and affordable to reduce the treatment gap and improved treatment outcome. In this regard, recently the Ministry of Social Justice and Empowerment, Government of India, has initiated schemes such as the drug treatment centers and addiction treatment facilities with focus on the outpatient and inpatient care, respectively.
The findings of this review should be contextualized in terms of strengths and limitations. The strengths are inclusion of varied types of studies from different parts of the countries, from different settings, and qualitative synthesis of relapse rates. The limitations include study heterogeneity and high risk of bias. Most of the studies were conducted among adult men, limiting the generalizability. Select databases were included in the review. Hand searches and contacting potential authors were not done as a part of the review.
| Conclusion | | |
The present review suggests that a substantial proportion of patients with alcohol use disorders relapse to alcohol during the course of treatment. Efforts are required to delay and avoid such relapse by effective treatment approaches. Predictors of relapse, identified in the study, could help the clinicians to prioritize the treatment plan. Our review indicated that the future research should concentrate on: (a) an inclusive study design (of sex, age groups, and comorbid substance use disorders), (b) a robust study methodology (starting with a valid definition of “relapse,” a well-designed randomization, and minimizing the missing outcomes), and (c) qualitative studies to capture the sociocultural factors contributing to relapse, unique to the Indian population.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Figure 1]
[Table 1], [Table 2], [Table 3], [Table 4]
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