# Factors Associated with Problematic Alcohol Consumption among Adults in Putalibazar Municipality of Syangja District, Nepal

Authors: Rajeev Nepal; Jyoti Priyanka; Pradip Chhetri; Suruchi Godar; Pratigya Timsina; Saroj Doranga
Journal: Advances in Public Health
 (2022)

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## Abstract

Background. According to the WHO STEPS survey 2013 in Nepal, 17% of the surveyed population had consumed alcohol within the last 30 days. Alcohol consumption in Nepal is socially and culturally accepted in many ethnic groups. The purpose of this study was to determine various factors associated with problematic alcohol consumption among adults in Putalibazar Municipality of Syangja district. Methods. A community-based cross-sectional study was conducted between September 2020 and January 2021 among 300 adults between ages of 18–64 years in Putalibazar Municipality of Syangja district of Nepal. Using a pretested semistructure questionnaire, a face-to-face interview was performed for collecting the data. An Alcohol Use Disorder Identification Test (AUDIT) developed by the World Health Organization (WHO) was used as a guiding tool to determine the audit-risk level category among adults according to their drinking status. Respondents with scores 0–7 in AUDIT scores were considered as nonproblematic drinkers, while respondents scoring 8–40 in the AUDIT scores were considered as problematic drinkers. Bivariate and multivariable analysis was performed to find out the association between dependent and independent variables. Variables which were found statistically significant at 95% CI (p ≤ 0.05) during bivariate analysis were further analyzed using the logistic regression model in multivariable analysis to identify determinants associated with problematic alcohol consumption among adults. Results. The mean age of participants was 36.72 years with a ±10.81 standard deviation. A total of 56.3% of adults were problematic drinkers. The multivariable regression analysis model identified adults within the age group of 25–34 years and 35–44 years along with males significantly associated with problematic alcohol consumption. Adults within the age group of 25–34 years and 35–44 years were 7.4 times (AOR = 7.4, CI: 1.97–27.60) and 5.7 times (AOR = 5.7, CI: 1.58–20.56) more likely to be problematic drinkers than their counterparts who were from the age group of 55–64 years. Males were 6.9 times more likely to be (AOR = 6.9, CI: 3.35–14.26) problematic drinkers than females. Conclusion. Problematic alcohol consumption among males was common and significantly associated within the age group of 25–34 years and 35–44 years. This study concerns the need for policy makers to launch awareness programs and community-based interventional programs considering identified factors associated with excessive drinking.


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## Body

## 1. Background

Globally, 3 million deaths worldwide (2.3 million among men and 0.7 million among women) and 132 million DALYs (106 million among men and 26 million among women) were attributable to alcohol, representing 5.3% of all deaths and 5% of all DALYs in 2016 [1]. Alcohol consumption is considered as the 7th leading risk factor for both mortality and morbidity [2]. The per capita alcohol consumption in the world’s population rose from 5.5 L of alcohol in 2005 to 6.4 L in 2010 [2], and it is expected to reach 7.6 L by 2030 [3]. A systematic analysis of the Global Burden of Disease 2016 suggested that no amount of alcohol consumption is safe [4]. The International Agency for Research on Cancer (IARC) has determined a causal link between alcohol consumption and cancers, including oral cavity, pharynx, larynx, esophagus, liver, colorectal, and female breast cancer [5].According to the finding of Nepal’s NDHS 2016, almost three out of four women whose husbands often get drunk have experienced spousal physical, sexual, or emotional violence (74%), compared with less than one in five women (18%) whose husbands do not drink alcohol [6]. Alcohol use is the eleventh most leading risk factor for Disability Adjusted Life Years (DALYs) in Nepal. According to the WHO STEPS survey 2013 in Nepal; 17% of the surveyed population (male 28%, female 7.1%) had consumed alcohol within the last 30 days; of these, 18.6% male and 2.9% female were having binge drinking [7]. Alcohol consumption in Nepal is socially and culturally accepted in many ethnic groups, and the consumption has been increasing over the years across all ethnicities and age groups [8].While these surveys provide data on the statement of problems and disease burden, they do not assess cultural beliefs and determining factors in the social context where alcohol use behavior occurs. Therefore, this study was mainly conducted to identify various factors associated with problematic alcohol consumption. This study also aims to provide valuable information for other researchers, health service providers, and policy makers in developing interventional programs for the achievement of Goal 3 of Sustainable Development Goals (SDGs) [9] focusing on ensuring good health and wellbeing at all ages by 2030, which significantly strides for good mental health and denotes prevention and treatment of the harmful use of alcohol [10].


## 2. Materials and Methods

### 2.1. Study Design and Source of Population

A community-based cross-sectional study was conducted between September 2020 and January 2021 among 300 adults between ages of 18–64 years in Putalibazar Municipality of Syangja district of Nepal. Permanent inhabitants or respondents who stayed more than 5 years in Putalibazar municipality were included in this study. Similarly, respondents who refused to participate in the study, respondents aged <18 years and >64 years, and those who had severe mental problem were set as exclusion criteria.


### 2.2. Sample Size Determination and Sampling Technique

The sample size was 300 which was calculated by using formulan = Z2pq/L2 [11] with 95% level of confidence interval, critical value Z = 1.96, 5% margin of error, 7% nonresponse rate, and the prevalence of alcohol consumption among adults was found to be 23.9% [12]. Hence, n = Z2pq/L2 = (1.96)2∗ (0.24) ∗ (0.76)/(0.05)2 = 280, by adding 7% nonresponse rate, the final sample size of the study was 300. Stratified random sampling was used for the sampling technique. There are 13 wards in the Putalibazar municipality. Each ward was considered as single strata. By using disproportionate stratified sampling techniques, equal 23 samples were taken from wards 1 to 12, and 24 samples were taken from ward no. 13. Moreover, households were selected from each ward by using the lottery method.


### 2.3. Setting

Putalibazar municipality is located in Syangja district, Gandaki Province of Nepal. Putalibazar municipality consists of 13 wards [13] and scattered across 147 square kilometers of geographical area [14]. As per 2011 population census, the total population of this municipality was 44,876, and the overall ratio of male to female population in Putalibazar municipality was 0.78 with 43.76% (19,638) of males and 56.24% (25,238) of females. In addition, Putalibazar had total 11,882 households (3.78 persons per household) [15], and the overall literacy rate was found to be 76.61% [14].


### 2.4. Data Collection Procedures, Validity, and Reliability

Using a pretested semistructure questionnaire, a face-to-face interview was performed for collecting the data. A principal investigator self involved in collecting data of the respondents. The questionnaire was translated into Nepali and again retranslated into English language to find misinterpretation, and then correction was made. All the filled questionnaires were reviewed and checked by the principal investigator on a regular basis. In order to maintain the reliability of the questionnaire, the researcher used a reliability analysis test through Cronbach’s alpha by taking 8% (n = 24) of the total sample size during pretesting in Galyang municipality which found 0.81 as Cronbach’s alpha value that proved that questionnaire was reliable.


### 2.5. Measure of Practice of Alcohol Consumption

In this study, the practice of alcohol refers to the intake of alcoholic beverages, i.e., beer, wine, spirits (vodka/rum/whisky), change/jand, and aila by adults in any phase of life. An Alcohol Use Disorder Identification Test (AUDIT) developed by the World Health Organization (WHO) was used as a guiding tool to determine the audit-risk level category (Table1) which determines Zone I (low-risk drinking), Zone II (higher-risk drinking), Zone III (harmful and hazardous drinking), and Zone IV (possible alcohol dependence) among adults according to their drinking status [16].Table 1
AUDIT-risk level category.
Audit-risk levelAUDIT scoreZone I (low risk drinking)0–7Zone II (higher risk drinking)8–15Zone III (harmful and hazardous drinking)16–19Zone IV (possible alcohol dependence)20–40In this study, respondents with scores 0–7 in AUDIT scores were considered as nonproblematic drinkers, while respondents scoring 8–40 in the AUDIT scores were considered as problematic drinkers.


### 2.6. Data Processing and Analysis

Editing, classifying, coding, and entry of data were carried out using Microsoft Excel and exported to Statistical Package for Social Science (SPSS) software version 20 for further analysis. Descriptive and inferential statistics such as mean, median, mode, and standard deviation were applied. The ultimate effect measure (a measure of association) was an odds ratio, and 95% confidence intervals were used to determine statistical significance. Bivariate and multivariable analysis was performed to find out the association between dependent and independent variables. Variables which were found statistically significant at 95% CI (p ≤ 0.05) during bivariate analysis were further analyzed using the logistic regression model in multivariable analysis to identify determinants associated with problematic alcohol consumption among adults.


### 2.7. Ethical Consideration

From the outset of the study, the principles of the Helsinki Declaration were applied, and ethical permission was obtained from the Institutional review committee of UCMS-TH (UCMS/IRC/103/20) and DHO Syangja to conduct this study. Confidentiality of the respondent was maintained. The study was explained to participants, and written informed consent with their signature was obtained for data collection. Withdrawal from the study at any time was accepted, and local language was used during the face-to-face interview.


### 2.8. Limitation of the Study

This study explored the practice towards alcoholic drinks; the study participants may have been subjected to recall bias. Syangja district constitutes of five municipalities (Nagarpalika) and six rural municipalities (Guanpalika) [17]. As we have conducted this research in Putalibazar municipality, these study findings cannot be generalized to the whole district.


## 2.1. Study Design and Source of Population

A community-based cross-sectional study was conducted between September 2020 and January 2021 among 300 adults between ages of 18–64 years in Putalibazar Municipality of Syangja district of Nepal. Permanent inhabitants or respondents who stayed more than 5 years in Putalibazar municipality were included in this study. Similarly, respondents who refused to participate in the study, respondents aged <18 years and >64 years, and those who had severe mental problem were set as exclusion criteria.


## 2.2. Sample Size Determination and Sampling Technique

The sample size was 300 which was calculated by using formulan = Z2pq/L2 [11] with 95% level of confidence interval, critical value Z = 1.96, 5% margin of error, 7% nonresponse rate, and the prevalence of alcohol consumption among adults was found to be 23.9% [12]. Hence, n = Z2pq/L2 = (1.96)2∗ (0.24) ∗ (0.76)/(0.05)2 = 280, by adding 7% nonresponse rate, the final sample size of the study was 300. Stratified random sampling was used for the sampling technique. There are 13 wards in the Putalibazar municipality. Each ward was considered as single strata. By using disproportionate stratified sampling techniques, equal 23 samples were taken from wards 1 to 12, and 24 samples were taken from ward no. 13. Moreover, households were selected from each ward by using the lottery method.


## 2.3. Setting

Putalibazar municipality is located in Syangja district, Gandaki Province of Nepal. Putalibazar municipality consists of 13 wards [13] and scattered across 147 square kilometers of geographical area [14]. As per 2011 population census, the total population of this municipality was 44,876, and the overall ratio of male to female population in Putalibazar municipality was 0.78 with 43.76% (19,638) of males and 56.24% (25,238) of females. In addition, Putalibazar had total 11,882 households (3.78 persons per household) [15], and the overall literacy rate was found to be 76.61% [14].


## 2.4. Data Collection Procedures, Validity, and Reliability

Using a pretested semistructure questionnaire, a face-to-face interview was performed for collecting the data. A principal investigator self involved in collecting data of the respondents. The questionnaire was translated into Nepali and again retranslated into English language to find misinterpretation, and then correction was made. All the filled questionnaires were reviewed and checked by the principal investigator on a regular basis. In order to maintain the reliability of the questionnaire, the researcher used a reliability analysis test through Cronbach’s alpha by taking 8% (n = 24) of the total sample size during pretesting in Galyang municipality which found 0.81 as Cronbach’s alpha value that proved that questionnaire was reliable.


## 2.5. Measure of Practice of Alcohol Consumption

In this study, the practice of alcohol refers to the intake of alcoholic beverages, i.e., beer, wine, spirits (vodka/rum/whisky), change/jand, and aila by adults in any phase of life. An Alcohol Use Disorder Identification Test (AUDIT) developed by the World Health Organization (WHO) was used as a guiding tool to determine the audit-risk level category (Table1) which determines Zone I (low-risk drinking), Zone II (higher-risk drinking), Zone III (harmful and hazardous drinking), and Zone IV (possible alcohol dependence) among adults according to their drinking status [16].Table 1
AUDIT-risk level category.
Audit-risk levelAUDIT scoreZone I (low risk drinking)0–7Zone II (higher risk drinking)8–15Zone III (harmful and hazardous drinking)16–19Zone IV (possible alcohol dependence)20–40In this study, respondents with scores 0–7 in AUDIT scores were considered as nonproblematic drinkers, while respondents scoring 8–40 in the AUDIT scores were considered as problematic drinkers.


## 2.6. Data Processing and Analysis

Editing, classifying, coding, and entry of data were carried out using Microsoft Excel and exported to Statistical Package for Social Science (SPSS) software version 20 for further analysis. Descriptive and inferential statistics such as mean, median, mode, and standard deviation were applied. The ultimate effect measure (a measure of association) was an odds ratio, and 95% confidence intervals were used to determine statistical significance. Bivariate and multivariable analysis was performed to find out the association between dependent and independent variables. Variables which were found statistically significant at 95% CI (p ≤ 0.05) during bivariate analysis were further analyzed using the logistic regression model in multivariable analysis to identify determinants associated with problematic alcohol consumption among adults.


## 2.7. Ethical Consideration

From the outset of the study, the principles of the Helsinki Declaration were applied, and ethical permission was obtained from the Institutional review committee of UCMS-TH (UCMS/IRC/103/20) and DHO Syangja to conduct this study. Confidentiality of the respondent was maintained. The study was explained to participants, and written informed consent with their signature was obtained for data collection. Withdrawal from the study at any time was accepted, and local language was used during the face-to-face interview.


## 2.8. Limitation of the Study

This study explored the practice towards alcoholic drinks; the study participants may have been subjected to recall bias. Syangja district constitutes of five municipalities (Nagarpalika) and six rural municipalities (Guanpalika) [17]. As we have conducted this research in Putalibazar municipality, these study findings cannot be generalized to the whole district.


## 3. Results

### 3.1. Sociodemographic-Related Findings

A total of 300 adults within the age group of 18–64 years were participated in the study (Table2). The mean age of respondents was found to be 36.72 years with a ±10.81 standard deviation. Among study participants, 109 (36.3%) respondents fell within the age group of 25–34 years, 206 (68.7%) respondents were male, 158 (52.7%) belonged to Janajati,. 84 (28%) were involved in business, 190 (63.3%) were living in a nuclear family, 76 (25.3%) had educational qualification of bachelor degree, 211 (70.3%) were married, and 120 (40%) respondent’s family monthly income fell within NPR 21,000 to 40,000.Table 2
Distribution of background-related characteristics of study population (n = 300).
VariablesNo. of respondents (n)Percentage (%)Age15–24 years3712.325–34 years10936.335–44 years782645–54 years571954–64 years196.3Mean age 36.72 years, SD± 10.81, Max 64 Years, and Min 18 YearsGenderMale20668.7Female9431.3EthnicityJanajati15852.7Brahmin8227.3Dalit5016.7Kshetri103.3OccupationBusiness8428Private job5919.7Student4615.3Government job3712.3Agriculture268.7Housewife217Bricklayer206.7Tailor72.3Family typeNuclear19063.3Joint7826Extended3210.7Educational qualificationIlliterate124Nonformal education3010Primary level268.7Lower secondary level237.7Secondary level3411.3Higher secondary level5317.7Bachelor level7625.3Master’s level or above4615.3Marital statusMarried21170.3Unmarried8026.7Widowed93Family monthly income (NPR)≤20,0005819.321,000–40,0001204041,000–60,0008528.3>60,0003712.3Mean income NPR 39523.33, SD ± 17762.916, Min. NPR 10,000, and Max NRP 90,000


### 3.2. Practice-Related Findings

Most 169 (56.3%) of respondents were problematic drinkers, and rest 131 (43.7%) respondents were found nonproblematic drinkers on the basis of AUDIT scores (Table3).Table 3
Distribution of respondents on the AUDIT-risk level and practice towards alcohol consumption (n = 300).
AUDIT-risk levelAUDIT scoreNo. of respondents (n)Percentage (%)Zone-I (low-risk drinking)0 to 713143.7Zone-II (higher-risk drinking)8 to 155117Zone-III (harmful and hazardous drinking)16 to 198327.7Zone-IV (possible alcohol dependence)20 to 403511.7Practice on alcohol consumptionNonproblematic drinkers0–713143.7Problematic drinkers7–4016956.3Mean of AUDIT score 11.825, SD ± 8.831.Table4 describes the distribution of the current drinkers with a reason for the first intake, continuation of alcohol drinking, and alcohol beverages consumed. Most 85 (45.5%) respondents responded that curiosity to test was a reason for intake of the first drink, and almost four-fifths 156 (83.4%) respondents were habitual to an alcoholic drink. Majority of 152 (81.3%) respondents have consumed beer followed by 124 (66.3%) wine, 84 (44.9%) spirits (vodka/rum/whisky), 60 (32.1%) chang/jand, and rest 19 (10.2%) respondent have consumed Aila respectively.Table 4
Distribution of respondents by reason for the first intake, continuation of drinking alcohol, and alcohol beverages consumed (n = 187).
Reason for first intakeNo. of respondents (n)Percentage (%)Curiosity to test8545.5Peer pressure4222.5To confirm to social norms5529.4To relieve stress/pressure52.7∗Reasons for continuationNow drinking alcohol is habitual15683.4To celebrate happiness13270.6To forget worries9450.3To obey social norms and values7439.6Peer pressure6333.7To reduce workload4725.1∗Alcohol beverages consumedBeer15281.3Wine12466.3Spirits (Vodka/Rum/Whisky)8444.9Chang/Jand6032.1Aila1910.2∗Multiple responses.


### 3.3. Associations between Different Variables

Table5 presents the multiple regression analysis of practice towards alcohol consumption with associated factors. A total of 56.3% of adults were problematic drinkers, and the rest 43.7% were nonproblematic drinkers. Results from bivariate analysis revealed age of respondents, gender, ethnicity, and occupation were having a significant association with alcohol drinking practices with p value less than or equal to 0.05, and these variables were further entered into the multivariable regression analysis model for confounding adjustment. However, variables such as family type, education status, marital status, and family monthly income were not found significant with alcohol practice. Results from the multivariable regression analysis model identified adults within the age group of 25–34 years and 35–44 years along with males significantly associated with problematic alcohol consumption. Adults within the age group 25–34 years and 35–44 years were 7.4 times (AOR = 7.4, CI: 1.97–27.60) and 5.7 times (AOR = 5.7, CI: 1.58–20.56) more likely to be problematic drinkers than their counterparts who were from the age group of 55–64 years. Males were 6.9 times more likely to be problematic drinkers (AOR = 6.9, CI: 3.35–14.26) than females. After being subjected to the multivariable model, ethnicity and occupation of respondents were not found to be associated with problematic consumption, which was as seen significant in bivariate analysis.Table 5
Factors associated with alcohol consumption among adults in multiple regression analysis (n = 300).
VariablesPractice on alcohol consumptionp valueCOR95% CIAOR95% CIp valueNonproblematic drinkersn = 131 (43.7%)Problematic drinkersn = 169 (56.3%)Agen%n%15–24 years2259.51540.50.003∗1.50.46–4.751.80.38–8.190.4725–34 years4036.76963.33.71.31–10.607.41.97–27.600.003∗35–44 years2633.35266.74.31.48–12.715.71.58–20.560.008∗45–54 years3052.62747.41.90.65–5.852.50.66–9.230.1855–64 years1368.4631.611Gendern%n%Male703413666<0.001∗3.62.15–6.06.93.35–14.26<0.001∗Female6164.93335.111Ethnicityn%n%Brahmin506132390.40.11–1.630.40.08–2.150.29Janajati7346.28553.8<0.001∗0.80.21–2.860.70.14–3.310.62Dalit4846927.71.51–38.986.90.87–53.830.07Kshetri44066011Occupationn%n%Agriculture1453.81246.20.040.005–0.390.280.02–3.570.32Business3845.24654.80.060.008–0.500.20.02–2.410.21Government job1745.92054.10.0150.060.007–0.510.20.01–2.330.19Private job2644.13355.90.070.008–0.531.70.01–1.980.16Housewife1047.61152.40.060.007–0.510.50.04–7.060.65Student2452.22247.80.050.006–0.390.20.02–2.890.26Tailor114.3685.70.30.02–5.850.10.003–1.610.09Bricklayer15199511Family typen%n%Nuclear8544.710555.30.3180.60.25–1.25Joint3646.24253.80.50.22–1.27Extended1031.22268.81Education statusn%n%Illiterate866.7433.30.60.17–2.47Nonformal education1136.71963.32.20.87–5.78Primary level623.12076.84.31.47–12.79Lower secondary level730.41669.60.0773.01.03–8.60Secondary level1647.11852.91.50.6–3.56Higher secondary level2241.53158.51.80.82–4.07Bachelor level3546.14153.91.50.73–3.18Masters level2656.52043.51Marital statusn%n%Married9143.112056.90.3672.60.64–10.83Unmarried3442.54657.52.70.63–11.59Widowed666.7333.31Family monthly income (in NPR)n%n%≤20,0001932.83967.23.41.42–7.9821,000–40,0004940.87159.20.062.41.12–5.0841,000–60,0004047.14552.91.80.84–4.07>60,0002362.21437.81


## 3.1. Sociodemographic-Related Findings

A total of 300 adults within the age group of 18–64 years were participated in the study (Table2). The mean age of respondents was found to be 36.72 years with a ±10.81 standard deviation. Among study participants, 109 (36.3%) respondents fell within the age group of 25–34 years, 206 (68.7%) respondents were male, 158 (52.7%) belonged to Janajati,. 84 (28%) were involved in business, 190 (63.3%) were living in a nuclear family, 76 (25.3%) had educational qualification of bachelor degree, 211 (70.3%) were married, and 120 (40%) respondent’s family monthly income fell within NPR 21,000 to 40,000.Table 2
Distribution of background-related characteristics of study population (n = 300).
VariablesNo. of respondents (n)Percentage (%)Age15–24 years3712.325–34 years10936.335–44 years782645–54 years571954–64 years196.3Mean age 36.72 years, SD± 10.81, Max 64 Years, and Min 18 YearsGenderMale20668.7Female9431.3EthnicityJanajati15852.7Brahmin8227.3Dalit5016.7Kshetri103.3OccupationBusiness8428Private job5919.7Student4615.3Government job3712.3Agriculture268.7Housewife217Bricklayer206.7Tailor72.3Family typeNuclear19063.3Joint7826Extended3210.7Educational qualificationIlliterate124Nonformal education3010Primary level268.7Lower secondary level237.7Secondary level3411.3Higher secondary level5317.7Bachelor level7625.3Master’s level or above4615.3Marital statusMarried21170.3Unmarried8026.7Widowed93Family monthly income (NPR)≤20,0005819.321,000–40,0001204041,000–60,0008528.3>60,0003712.3Mean income NPR 39523.33, SD ± 17762.916, Min. NPR 10,000, and Max NRP 90,000


## 3.2. Practice-Related Findings

Most 169 (56.3%) of respondents were problematic drinkers, and rest 131 (43.7%) respondents were found nonproblematic drinkers on the basis of AUDIT scores (Table3).Table 3
Distribution of respondents on the AUDIT-risk level and practice towards alcohol consumption (n = 300).
AUDIT-risk levelAUDIT scoreNo. of respondents (n)Percentage (%)Zone-I (low-risk drinking)0 to 713143.7Zone-II (higher-risk drinking)8 to 155117Zone-III (harmful and hazardous drinking)16 to 198327.7Zone-IV (possible alcohol dependence)20 to 403511.7Practice on alcohol consumptionNonproblematic drinkers0–713143.7Problematic drinkers7–4016956.3Mean of AUDIT score 11.825, SD ± 8.831.Table4 describes the distribution of the current drinkers with a reason for the first intake, continuation of alcohol drinking, and alcohol beverages consumed. Most 85 (45.5%) respondents responded that curiosity to test was a reason for intake of the first drink, and almost four-fifths 156 (83.4%) respondents were habitual to an alcoholic drink. Majority of 152 (81.3%) respondents have consumed beer followed by 124 (66.3%) wine, 84 (44.9%) spirits (vodka/rum/whisky), 60 (32.1%) chang/jand, and rest 19 (10.2%) respondent have consumed Aila respectively.Table 4
Distribution of respondents by reason for the first intake, continuation of drinking alcohol, and alcohol beverages consumed (n = 187).
Reason for first intakeNo. of respondents (n)Percentage (%)Curiosity to test8545.5Peer pressure4222.5To confirm to social norms5529.4To relieve stress/pressure52.7∗Reasons for continuationNow drinking alcohol is habitual15683.4To celebrate happiness13270.6To forget worries9450.3To obey social norms and values7439.6Peer pressure6333.7To reduce workload4725.1∗Alcohol beverages consumedBeer15281.3Wine12466.3Spirits (Vodka/Rum/Whisky)8444.9Chang/Jand6032.1Aila1910.2∗Multiple responses.


## 3.3. Associations between Different Variables

Table5 presents the multiple regression analysis of practice towards alcohol consumption with associated factors. A total of 56.3% of adults were problematic drinkers, and the rest 43.7% were nonproblematic drinkers. Results from bivariate analysis revealed age of respondents, gender, ethnicity, and occupation were having a significant association with alcohol drinking practices with p value less than or equal to 0.05, and these variables were further entered into the multivariable regression analysis model for confounding adjustment. However, variables such as family type, education status, marital status, and family monthly income were not found significant with alcohol practice. Results from the multivariable regression analysis model identified adults within the age group of 25–34 years and 35–44 years along with males significantly associated with problematic alcohol consumption. Adults within the age group 25–34 years and 35–44 years were 7.4 times (AOR = 7.4, CI: 1.97–27.60) and 5.7 times (AOR = 5.7, CI: 1.58–20.56) more likely to be problematic drinkers than their counterparts who were from the age group of 55–64 years. Males were 6.9 times more likely to be problematic drinkers (AOR = 6.9, CI: 3.35–14.26) than females. After being subjected to the multivariable model, ethnicity and occupation of respondents were not found to be associated with problematic consumption, which was as seen significant in bivariate analysis.Table 5
Factors associated with alcohol consumption among adults in multiple regression analysis (n = 300).
VariablesPractice on alcohol consumptionp valueCOR95% CIAOR95% CIp valueNonproblematic drinkersn = 131 (43.7%)Problematic drinkersn = 169 (56.3%)Agen%n%15–24 years2259.51540.50.003∗1.50.46–4.751.80.38–8.190.4725–34 years4036.76963.33.71.31–10.607.41.97–27.600.003∗35–44 years2633.35266.74.31.48–12.715.71.58–20.560.008∗45–54 years3052.62747.41.90.65–5.852.50.66–9.230.1855–64 years1368.4631.611Gendern%n%Male703413666<0.001∗3.62.15–6.06.93.35–14.26<0.001∗Female6164.93335.111Ethnicityn%n%Brahmin506132390.40.11–1.630.40.08–2.150.29Janajati7346.28553.8<0.001∗0.80.21–2.860.70.14–3.310.62Dalit4846927.71.51–38.986.90.87–53.830.07Kshetri44066011Occupationn%n%Agriculture1453.81246.20.040.005–0.390.280.02–3.570.32Business3845.24654.80.060.008–0.500.20.02–2.410.21Government job1745.92054.10.0150.060.007–0.510.20.01–2.330.19Private job2644.13355.90.070.008–0.531.70.01–1.980.16Housewife1047.61152.40.060.007–0.510.50.04–7.060.65Student2452.22247.80.050.006–0.390.20.02–2.890.26Tailor114.3685.70.30.02–5.850.10.003–1.610.09Bricklayer15199511Family typen%n%Nuclear8544.710555.30.3180.60.25–1.25Joint3646.24253.80.50.22–1.27Extended1031.22268.81Education statusn%n%Illiterate866.7433.30.60.17–2.47Nonformal education1136.71963.32.20.87–5.78Primary level623.12076.84.31.47–12.79Lower secondary level730.41669.60.0773.01.03–8.60Secondary level1647.11852.91.50.6–3.56Higher secondary level2241.53158.51.80.82–4.07Bachelor level3546.14153.91.50.73–3.18Masters level2656.52043.51Marital statusn%n%Married9143.112056.90.3672.60.64–10.83Unmarried3442.54657.52.70.63–11.59Widowed666.7333.31Family monthly income (in NPR)n%n%≤20,0001932.83967.23.41.42–7.9821,000–40,0004940.87159.20.062.41.12–5.0841,000–60,0004047.14552.91.80.84–4.07>60,0002362.21437.81


## 4. Discussion

This study shows that about two-fifth (43.7%) respondents fall under low-risk drinking (Zone I), 17% higher-risk drinking (Zone II), 27.7% harmful and hazardous drinking (Zone III), while rest 11.7% were under possible alcohol dependence (Zone IV) under the guidance of AUDIT-risk level category. This study contradicts with the study done by Davis et al. [18] which stated 32% respondent’s low-risk drinkers and 26% respondents as high-risk drinkers. Another study done by Dunne et al. [19] stated 12.0% respondents had hazardous drinking, 0.9% harmful drinking, and 0.6% as probable alcohol dependence. These rates were found lowest than our study. Such discrepancy in the AUDIT zone might be connected with variation in practice towards alcohol drinking in different parts of the world and might be linked with a selection of study design and study method conducted. This present study revealed that most of the respondents (45.5%) initiated alcohol drinking was owing to the curiosity of test followed by peer pressure (22.5%). In addition, most of the respondents (83.4%) became habitual to drinking, while 70.6% were drinking continuously to celebrate happiness. These findings were found dissimilar with the study done by Katyal et al. [20] who explored the most common reason for first intake being peer pressure (66.7%) and curiosity to drink (2.1%) and reasons for continuing alcohol drinking to be peer pressure (38.5%) and to be sociable (32.3%). Also, these present study findings were found inconsistent with other studies [21–26]. This discrepancy might be linked with various multiple factors which influence alcohol drinking in different study settings.In this present study, respondents within the age group of 25–34 years and 35–44 years along with gender were having a significant association with problematic alcohol consumption (p < 0.05), and also males were found 6.9 times more likely to be problematic drinkers than females. This study is in line with study done by Ganesh Kumar et al. [27] who found adults within the age group 11–44 years and gender having a significant association with alcohol use (p < 0.05). However, males were found 11.23 times more likely to use alcohol in comparison with female. This study result is found inconsistent with the study done by Mekonen et al. [28] who stated sex was not having any association with problematic drinking while variables like having alcohol user intimate friend, ever use of substance, academic achievement, and probable social phobia having a significant association with problematic drinking (p < 0.001). This discrepancy might be due to difference in practice status among respondents in different study settings and methodology adopted. In this study, about four-fifth (81.3%) respondents drank beer followed by two-thirds (66.3%) wine and spirits (44.9%). This finding was found dissimilar to a study conducted by Tomkins et al. [29] in Izhevsk, Russia, which found 79% respondents drank spirits and 8% drank surrogates occasionally in the past year, while 25% drank spirits and 4% drank surrogates at least weekly. This discrepancy might link with social and culture aspects of drinking. Moreover, this study result found similar with Esther and Jackson [30] and Pham et al. [31] who reported beer as the most common type of alcoholic beverage consumed. This study stated that two-fifth (43.7%) of the respondents were nonproblematic drinkers, while 56.3% respondents were problematic drinkers. This study finding disagreed with the findings of cross-sectional study conducted by Chaudhary et al. [32] which revealed 12.7% problem drinkers and 87.3% participants were nonproblematic drinkers. The numbers of problematic drinkers were high in this study. The discrepancy in finding might be linked to the difference in the practice level of alcohol in multiple ethnic groups that exist in Nepal.


## 5. Conclusion

Problematic alcohol consumption among males was common and significantly associated within the age group of 25–34 years and 35–44 years. This study concerns the need for policy makers to lunch awareness programs and community-based interventional programs considering identified factors associated with excessive drinking.



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*Source: 7588153-2022-02-02.xml*