|Year : 2019 | Volume
| Issue : 2 | Page : 155-160
A cross sectional study of cognitive impairment in patients of alcohol use disorder attending a tertiary health care center in Central India
Ajinkya Sureshrao Ghogare1, Ashish Vilas Saboo2
1 Department of Psychiatry, Datta Meghe Institute of Medical Sciences University, Sawangi, Maharashtra, India
2 Department of Psychiatry, Dr. Panjabrao Deshmukh Memorial Medical College, Amravati, Maharashtra, India
|Date of Submission||25-May-2019|
|Date of Decision||18-Jun-2019|
|Date of Acceptance||11-Jul-2019|
|Date of Web Publication||18-Dec-2019|
Dr. Ajinkya Sureshrao Ghogare
House Number 4, Shree Colony, Daryapur, Amravati - 444 803, Maharashtra
Source of Support: None, Conflict of Interest: None
Background: Alcohol use disorders (AUDs) have been prevalent among all societies and across the country. In India, the prevalence of AUD in 2010 as reported by the World Health Organization was 2.6% and 1.7% had reported heavy episodic drinking. AUD in India is especially important to watch out for because of consumption of country liquor and high rates of alcohol use in rural population. The aim of the study was to find the relation between AUD and cognitive impairment. Methods: The present study was carried out in the department of psychiatry of a tertiary health-care center and the data were collected from diagnosed cases of AUD. The sociodemographic profile and clinical variables were recorded in specific case report form prepared for this clinical study using Mini-Mental State Examination, Brief Cognitive Rating Scale (BCRS), and Bender Visual–Motor Gestalt Test Second Edition (BG II). Results: Of the 100 patients studied, most were young between the age groups of 18 and 30 (44.0%) years, followed by 31–40 years (40.0%), and 16.0% were above 40 years of age. Most of the patients had a history of alcohol use <10 years (43.0%) and 11–20 years (40.0%), whereas only 17% had it for over 20 years. Sociodemographic parameters such as age, marital status, family type, and residence and alcohol use parameters such as duration, pattern, type, severity, family history, and onset of alcohol use were significantly associated with the measures of cognitive function, i.e., Mini Mental State Examination (MMSE), BCRS, and BG II. Conclusions: Longer duration of alcohol use, severity of AUD, daily drinking, heavy drinking, country liquor consumption started early in age, and family history of alcoholism influence the cognitive dysfunction in patients of AUD.
Keywords: Alcohol use disorder, Bender Visual–Motor Gestalt Test Second Edition, Brief Cognitive Rating Scale, cognitive impairment, Mini-Mental State Examination
|How to cite this article:|
Ghogare AS, Saboo AV. A cross sectional study of cognitive impairment in patients of alcohol use disorder attending a tertiary health care center in Central India. Ann Indian Psychiatry 2019;3:155-60
|How to cite this URL:|
Ghogare AS, Saboo AV. A cross sectional study of cognitive impairment in patients of alcohol use disorder attending a tertiary health care center in Central India. Ann Indian Psychiatry [serial online] 2019 [cited 2023 Jan 31];3:155-60. Available from: https://www.anip.co.in/text.asp?2019/3/2/155/273376
| Introduction|| |
Alcohol use disorders (AUDs) have been prevalent among all societies and across the country. The pattern of alcohol use varies according to age, religion, education, type of drink, and other sociodemographic characteristics. The consumption pattern also varies between different cultures and societies, and the last 20 years has seen extensive changes. The World Health Organization (WHO) estimates that globally 5.9% of total deaths are attributable to alcohol consumption and nearly 16% of individuals aged 15 years and above are engaged in heavy episodic drinking. The prevalence of AUD in Indian males is 9.1%, while the prevalence of heavy episodic drinking in Indian male population (15+ years) and Indian male drinkers only (15+ years) is 28.4% and 55.1% respectively. Besides various social, economic, and physical consequences, alcoholism is also associated with deleterious effects on the central nervous system functions.
Chronic alcoholism is constantly associated with neuropsychological impairments with respect to cognitive flexibility, problem-solving, decision-making, risky behavior, and further aspects of cognitive function. Multiple factors determine the severity of cognitive impairment in AUD. These include demographic factors such as age, gender, relationship status, social class, family history, ethnicity, genetics, and other comorbid conditions. Besides these, alcohol misuse-related factors such as age of onset, binge drinking, type of alcohol, and other parameters also govern the severity of cognitive impairment in AUD.
Binge alcohol use is defined as five or more drinks on one occasion in the prior 30 days. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) asks a clinician to record the prior year severity of an AUD as mild (2–3 criteria endorsed), moderate (with 4–5 criteria met), or severe (with 6 or more of the 11 criteria met for AUD). Between 50% and 80% of patients with AUDs present with impaired cognitive functions that probably impact on their management.
Heavy drinking in early adolescence is associated with dysfunction of structures involved in behavioral, emotional, and cognitive regulation (e.g. the prefrontal cortex and limbic system) thereby predisposing these individuals to further alcohol use. Besides these demographic factors, alcohol-related factors such as duration, type of alcohol, the pattern of drinking, and family history of drinking also affect the neurocognitive outcome. It is known that the long-term and excessive use of alcohol may lead to structural and functional brain damage.
AUD in India is especially important to watch out for because of consumption of country liquor and high rates of alcohol use in rural population. There may also be differences in alcohol use by different religions in India. This may also be determining factors in outcomes of alcohol use. A study from East India reported current alcohol use in 19% of males and 2.4% of women from rural India. AUD has consistently been identified as a public health concern over the past 20 years, during which time per capita consumption of alcohol has increased by 55% and treatment gap for these affected has remained persistently high.
While searching literature on AUD and its effect on cognitive impairment, we found that there is a lack of knowledge on alcohol use and alcohol consumption pattern, and it is a barrier for alcohol education and intervention activities. Furthermore, there is a paucity of data on the pattern, associated factors of alcohol use, and its impact on cognitive impairment in Central India. The present study aims to find the relation between AUD and cognitive impairment.
| Methods|| |
The study was carried out in the department of psychiatry of a tertiary health-care center. A cross-sectional observational study design was used to find the relation between AUD and cognitive impairment during April 2016 and October 2017.
The study was approved by the Institutional Ethics Committee of Medical College and Hospital. The study participants were explained the nature of the study, and written informed consent was obtained from all the study participants. The patients admitted in psychiatry de-addiction ward in the age groups of 18–50 years and diagnosed as per DSM-5 diagnostic criteria for AUD, were included in the study. Patients with other psychotropic substance use disorders or comorbid physical or psychiatric illnesses were excluded.
The sample size for the study was calculated assuming the prevalence of cognitive impairment of 50% and 95% confidence interval with the absolute precision of 10%, which came out to be 100.
The sociodemographic profile and clinical variables were recorded in a specific case report form prepared for this clinical study. The psychological tests of cognitive function (MMSE, Brief Cognitive Rating Scale [BCRS], and Bender Visual–Motor Gestalt Test Second Edition [BG II]) were administered to patients in a single session of approximately 75–90-min duration.
The MMSE is one of the most commonly used cognitive screening measures because it is quick and easy to administer. The MMSE includes specific questions related to attention, orientation, memory, calculation, and language. The measure's scoring is based on 30 total points, and impairment is indicated by a score of 24 or lower. While this measure is often used to screen for memory function, it has a number of psychometric limitations, such as few executive function items. While the MMSE has good specificity (96%), the sensitivity is poor (64%), suggesting that cognitive changes remain undetected in a number of individuals.
The BCRS scale is designed specifically to assess the syndrome of cognitive decline. As a clinical rating instrument, it merges the judgment and skill of the clinician with objective rating criteria. The BCRS differs from virtually all other presently used clinical rating instruments for cognitive disturbances in that it includes mood changes such as anxiety, depression, agitation, and psychosis. Thus, the effects of interventions on cognition and associated functioning can be specifically assessed.
The BG II consists of 16 stimulus cards and the observation form. Two supplemental tests, the motor test and the perception test, aid in evaluating the examinee's performance on the BG II. The administration of the BG II involves two phases, the copy phase and the recall phase. The examinee is shown stimulus cards with different designs. In the copy phase, the examinee is asked to copy each of the designs on the blank sheet of paper. In the recall phase, the examinee is asked to redraw the designs from memory. Then, supplemental tests should be administered following the recall phase. The BG II measures visual-motor integration skills in children and adults from 4 to 85 + years of age. The purpose of the test is to evaluate problems associated with mentally retarded patients, organic brain abnormalities, and differentiation of functional and organic illnesses.
Each case was evaluated and discussed with a senior psychiatrist and analyzed, and results were drawn as per manuals of each psychological cognitive test. The relation of cognitive impairment and AUD parameters (duration, severity, pattern, type, and family history of alcohol use) was studied and evaluated.
The data were collected and analyzed using the SPSS software version 15.0 (IBM, Chicago, Illinois, United States of America). Categorical data were presented as frequency and percentages and tested for statistical significance by Chi-square test. Continuous data were presented as mean and standard deviation and tested for statistical significance using a Student's t-test for two groups' comparison and with one-way ANOVA using post hoc of Bonferroni for three groups' comparison. P < 0.05 was considered statistically significant.
| Results|| |
[Table 1] shows that most of the patients were young between the age groups of 18 and 30 (44.0%) years, followed by 31–40 years (40.0%), and 16.0% were above 40 years. The mean age was 33.55 ± 6.77 years. In our study, 60.0% of patients were Hindu, 20.0% were Muslims, whereas rest 20.0% were from other religions. About 47.0% were married, 39.0% were unmarried, and 14.0% were either separated or divorced. The family structure of patients shows that majority were from the nuclear family (68.0%) and 32.0% were from joint family. From the study participants, 54.0% and 46.0% were from urban and rural population, respectively.
[Table 2] shows the alcohol use-related parameters among AUD patients. Most of the patients had a history of alcohol use for <10 years (43.0%) and 11–20 years (40.0%), whereas only 17.0% had it for over 20 years. The mean duration of alcohol use was 12.44 ± 7.17 years. Nearly two-third (65) had daily drinking history and rest one-third (35) had binge drinking habit. An equal number of patients (50.0%) used country liquor or foreign liquor. Over half of the population had mild severity of AUD (51.0%), whereas 32.0% and 17.0% had moderate and severe AUD, respectively. About 67.0% had a family history of alcohol use. Almost 71.0% had started alcohol at an early age, i.e., age <25 years.
[Table 3] shows cognitive impairment based on MMSE score. Thirty-eight out of 100 study participants with AUD (38.0%) had questionably significant cognitive impairment. The prevalence of cognitive impairment in AUD according to MMSE score is 62%. Of 62 participants (62%) with significant cognitive impairment, 30 had mild, 20 had moderate, and 12 had severe cognitive impairment.
|Table 3: Cognitive impairment according to Mini-Mental State Examination total score in study population (n=100)|
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[Table 4] shows cognitive impairment according to BCRS total score. There was no cognitive decline in 36 study participants (36%). The prevalence of cognitive dysfunction in AUD according to BCRS score is 64%. Of the 64 study participants (64%) with cognitive impairment, 25, 16, 11, 3, and 9 participants had very mild, mild, moderate, moderately severe, and severe cognitive impairment, respectively.
|Table 4: Cognitive impairment according to Brief Cognitive Rating Scale total score in study population (n=100)|
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[Table 5] shows the association between sociodemographic parameters and scores on MMSE, BCRS, BG II copy phase, BG II recall phase, and BG II motor and perception supplemental tests. Age, marital status, family type, and residence were significantly associated with the score on MMSE, BCRS and BG II copy phase, recall phase, and BG II motor and perception supplemental tests. Religion was not associated with any one of the outcomes. There was no significant difference in score on MMSE, BCRS and BG II copy phase, recall phase, and BG II motor and perception supplemental tests in different religions.
|Table 5: Association of the sociodemographic parameters to scores on Mini-Mental State Examination, Brief Cognitive Rating Scale, Bender Visual-Motor Gestalt Test Second Edition copy phase, Bender Visual-Motor Gestalt Test Second Edition recall phase, and Bender Visual-Motor Gestalt Test Second Edition motor and perception supplemental tests|
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[Table 6] shows the association between alcohol use parameters and scores on MMSE, BCRS, BG II copy phase, BG II recall phase, and BG II motor and perception supplemental tests. Duration of alcohol use, pattern, type, severity, family history, and onset of alcohol use were significantly associated with the score on MMSE, BCRS, BG II copy phase, BG II recall phase, and BG II motor and perception supplemental tests. Patients with family history of alcohol use had significantly lower score on BG II perception supplemental test (P = 0.012), but no difference was seen in score on BG II motor supplemental test (P = 0.135). Early onset of alcohol use was associated with significantly lower score on BG II perception supplemental test (P = 0.007) but not on BG II motor supplemental test score (P = 0.089).
|Table 6: Association of alcohol use parameters to scores on Mini-Mental State Examination, Brief Cognitive Rating Scale, Bender Visual-Motor Gestalt Test Second Edition copy phase, Bender Visual-Motor Gestalt Test Second Edition recall phase, and Bender Visual-Motor Gestalt Test Second Edition motor and perception supplemental tests|
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| Discussion|| |
In the study, we found that there was a significant association between AUD and cognitive impairment. The prevalence of cognitive impairment in patients of AUD according to score on MMSE was 62%, and according to score on BCRS, the prevalence of cognitive impairment was 64%. This difference might be attributable to different domains of cognitive function assessed by MMSE and BCRS. Bates et al. observed a similar finding with 50%–80% of patients with AUD who presented impaired cognitive functions that probably affected their management. In this study, the mean age of the patients was 33.55 ± 6.77 years, and a nearly equal percentage of the patients were in the age range of 18–30 years (44.0%) and 31–40 years (40.0%). Leroi et al. observed a similar finding with 37.0% of patients in the age group of 18–30 years, 21% in the age group of 31–40 years, 12% in 41–50 years, and rest above 50 years of age. However, in their study, females outnumbered males (63% vs. 37%). This contrasts to our finding of males only. This is attributable to social and cultural differences in India and Western countries where alcohol use is less prevalent in Indian women.
Majority of the patients were from Hindu religion (60.0%) followed by Muslim (20.0%) and other religions (20.0%). Vaishnavi et al. observed similar results with 85.5% being Hindu, 7% Muslim, and 7.5% Christian. Among patients in the present study, 47.0% were married, 39.0% were unmarried, whereas 14.0% were separated or divorced. In this study, MMSE score was significantly low in separated or divorced patients compared to married (P < 0.0001) and unmarried (P = 0.017) patients, suggestive of more severe cognitive impairment among divorced and unmarried patients compared to married patients. In marital status, BCRS score was significantly higher in separated or divorced patients compared to married (P < 000.1) and unmarried (P = 0.006) patients. In marital status, BG II copy and recall phase scores as well as motor and perception supplemental test scores were significantly low in separated or divorced patients compared to married patients. Leonard and Eiden found that disturbance in marital life and marital separation is associated with an increase in severity of alcohol use. A study by Power et al. reported that divorced patients had the highest alcohol consumption levels and married patients had the lowest. They also found high rates of heavy drinking in unmarried men (19.1%) and women (5.2%).
We found, 68.0% of patients belonged to nuclear family, whereas 32.0% were from joint family. A study from South India by Vaishnavi et al. observed similar results with 56.0% of patients from nuclear families and 43.5% from joint families. Considering the residence of the patients, 46.0% and 54.0% belonged to rural and urban background, respectively. Esser et al. observed 69.8% population from rural areas and 30.2% from urban areas.
The mean duration of alcohol use in the study was 12.44 ± 7.17 years. A study from Fein et al. reported similar observations. Nearly one-third of patients were binge drinkers and two-thirds were daily drinkers. Esser et al. reported binge drinking in one-fourth of patients (24.5%), whereas 46.9% were abstainer and 28.6% were nonbinge drinkers.
In our study, we found a significant association between sociodemographic parameters (age, marital status, family type, and residence) and scores on MMSE, BCRS, BG II copy phase, BG II recall phase, and BG II motor and perception supplemental tests. In our study, significant difference was not found for MMSE, BCRS, and BG II scores on religion parameter.
We also found a significant association between alcohol use parameters (duration of alcohol use, pattern of drinking, type of liquor, severity of AUD, family history of alcohol use, and age at onset of alcohol use) and scores on MMSE, BCRS, BG II copy phase, BG II recall phase, and BG II motor and perception supplemental tests. While the family history of alcohol use and the age at onset of alcohol use were not associated with cognitive impairment on BG II motor supplemental test. The present study depicted that study participants with longer duration of alcohol use had poorer score on MMSE, BCRS, and BG II copy and recall phases as well as on BG II motor and supplemental tests, which indicated that as the duration of alcohol use increased, the severity of cognitive impairment was also increased. Loeber et al. found that patients with a longer duration of alcohol dependence were more impaired with regard to memory function than patients with a shorter duration of their dependence.
The findings of the present study should be taken into consideration keeping in view the following limitations: first, the analysis reported here should be regarded as exploratory, and second, the well-matched control group was not taken which weakens the comparative results. Therefore, the generalizability of results must be concluded with caution.
Due to the cross-sectional study design, temporal assessment cannot be done. Along with the nonconsideration of design effect in the calculation of sample size, the other fairly key drawbacks were recall bias and social desirability bias. As participants were questioned about details of past use of alcohol, they may have answered in such a way as to portray themselves in a good light; hence, social desirability bias could be present.
| Conclusions|| |
Alcohol dependence occurs with continued intake of alcohol over the years. Various factors were associated with cognitive impairment in patients of AUD. Demographically, higher age, rural background, divorced or separated from a spouse, and nuclear family influence the occurrence of alcohol-induced cognitive loss. Longer duration of alcohol, severity of AUD, daily drinking, heavy drinking, country liquor consumption started early in age, and family history of alcoholism influence the cognitive impairment in individuals with AUD.
We sincerely thank all the study participants who participated in the study for their cooperation. We also extend our thanks to all staff members from the department of psychiatry for their support.
This study was approved by Institutional Ethics Committee with reference number PDMMC/SS/Ethical 7371/2015 obtained on 28th December 2015.
Declaration of Patient Consent
Patient consent statement was taken from each patient as per institutional ethics committee approval along with consent taken for participation in the study and publication of the scientific results / clinical information /image without revealing their identity, name or initials. The patient is aware that though confidentiality would be maintained anonymity cannot be guaranteed.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Gupta PC, Saxena S, Pednekar MS, Maulik PK. Alcohol consumption among middle-aged and elderly men: A community study from Western India. Alcohol Alcohol 2003;38:327-31.
Global status report on alcohol and health 2018. Geneva: World Health Organization; 2018. Licence: CC BY-NC-SA 3.0 IGO.
Sachdeva A, Chandra M, Choudhary M, Dayal P, Anand KS. Alcohol-related dementia and neurocognitive impairment: A Review study. Int J High Risk Behav Addict 2016;5:e27976.
Moselhy HF, Georgiou G, Kahn A. Frontal lobe changes in alcoholism: A review of the literature. Alcohol Alcohol 2001;36:357-68.
Jauhar S, Marshall EJ, Smith ID. Alcohol and cognitive impairment. Adv Psychiatr Treatment 2014;20:304-13.
Strain EC. Substance – Related disorders. In: Sadock BJ, Sadock VA, Ruiz P, editors. Comprehensive Textbook of Psychiatry. 10th
ed. Philadelphia: Wolters Kluwer; 2017. p. 3255.
Schuckit MA. Substance – Related disorders. In: Sadock BJ, Sadock VA, Ruiz P, editors. Comprehensive Textbook of Psychiatry. 10th
ed. Philadelphia: Wolters Kluwer; 2017. p. 3259-60.
Bates ME, Voelbel GT, Buckman JF, Labouvie EW, Barry D. Short-term neuropsychological recovery in clients with substance use disorders. Alcohol Clin Exp Res 2005;29:367-77.
Barik A, Rai RK, Chowdhury A. Alcohol use-related problems among a rural Indian population of West Bengal: An application of the alcohol use disorders identification test (AUDIT). Alcohol Alcohol 2016;51:215-23.
National Institute on Alcohol and Alcoholism. Alcohol Use Disorder: A Comparison Between DSM – IV and DSM – 5. NIH Publication; 2013. p. 5-6.
Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189-98.
Reisberg B, Ferris SH. Brief cognitive rating scale (BCRS). Psychopharmacol Bull 1988;24:629-36.
Bender L. A visual motor gestalt test and its clinical use. American Orthopsychiatric Association, Research Monographs (No. 3). New York: American Orthopsychiatric Association; 1938.
Leroi I, Sheppard JM, Lyketsos CG. Cognitive function after 11.5 years of alcohol use: Relation to alcohol use. Am J Epidemiol 2002;156:747-52.
Vaishnavi R, Karthik MS, Balakrishnan R, Sathianathan R. Caregiver burden in alcohol dependence syndrome. J Addict 2017;2017:8934712.
Leonard KE, Eiden RD. Marital and family processes in the context of alcohol use and alcohol disorders. Annu Rev Clin Psychol 2007;3:285-310.
Power C, Rodgers B, Hope S. Heavy alcohol consumption and marital status: Disentangling the relationship in a national study of young adults. Addiction 1999;94:1477-87.
Esser MB, Gururaj G, Rao GN, Jernigan DH, Murthy P, Jayarajan D, et al.
Harms to adults from others' heavy drinking in five Indian states. Alcohol Alcohol 2016;51:177-85.
Fein G, Di Sclafani V, Cardenas VA, Goldmann H, Tolou-Shams M, Meyerhoff DJ. Cortical gray matter loss in treatment-naïve alcohol dependent individuals. Alcohol Clin Exp Res 2002;26:558-64.
Loeber S, Duka T, Welzel H, Nakovics H, Heinz A, Flor H, et al.
Impairment of cognitive abilities and decision making after chronic use of alcohol: The impact of multiple detoxifications. Alcohol Alcohol 2009;44:372-81.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
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