Age- and sex-standardized prevalence of alcohol consumption and its determinants in the western region of Iran, Ilam: a cross-sectional study

Abstract

Background and objective

In recent years, alcohol consumption in different parts of Iran has increased. However, this growth was dramatic in deprived regions. The percent study aimed to determine the age-sex standardized prevalence of alcohol consumption and related factors in the general population of Ilam city during 2021–2022.

Method

This population-based cross-sectional study was conducted in the general population of Ilam city located in western Iran. A total of 1,431 individuals over the age of 15 were included in the study using multi-stage cluster sampling. Alcohol consumption was assessed using a Persian version of high-risk behavior questionnaire (Cronbach’s alpha > 73%). Analysis was done by Stata version 11 and R Software. Logistic regression analysis was used for data analysis and calculating odds ratio (OR), and a significance level of 0.05 was considered.

Results

In total 1,431 individuals completed the questionnaire. The mean ± standard deviation (SD) age of the study participants was 43.40 ± 15.51 years. The age-sex standardized prevalence with 95% confidence interval (CI) of alcohol consumption was 4.05% (95% CI: 3.09 to 5.20). Based on multiple logistic model, having a bachelor’s degree (OR: 7.13; 95% CI: 1.89 to 26.76), cigarette smoking (OR: 6.92; 95% CI: 2.94 to 16.29), hookah smoking (OR: 7.34; 95% CI: 3.09 to 17.47) and drug abuse (OR: 2.88; 95% CI: 1.38 to 5.99) had a positive association with alcohol consumption. Furthermore, having a high economic status 0.62 (OR: 0.62; 95% CI: 0.26 to 1.48) had a negative association with alcohol consumption. The most powerful determinants (according to standardized coefficient) for alcohol consumption were hookah smoking (standardized coefficient: 0.588) and high education level (0.743).

Conclusion

Considering the prevalence of alcohol consumption in the population over 15 years old, it is necessary to take preventive and intervention measures, with more attention from health policymakers and other sectors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-024-21087-3.

Introduction

Alcohol consumption has a complex association with health [1] and its prevalence varies significantly across different regions and cultures. Some societies have accepted alcohol while others have adopted more restrictive attitudes towards its consumption [2]. This diversity in acceptance is influenced by multiple factors, including religious beliefs, cultural norms, legal regulations, and historical practices [3]. However, these changes have not been without consequences, as they often lead to challenges in public health [4].

Alcohol consumption is a significant public health issue that often begins in early adulthood [5]. The prevalence of this varies significantly across different regions depending on socioeconomic and cultural factors [6–14], the important thing is its consequence. According to the Global Burden of Disease reports in 2016, alcohol consumption was the seventh leading risk factor for mortality and years lived with disability [15]. Global estimates indicate that one in five adults reports at least one episode of heavy episodic alcohol consumption in the past month, increasing the risk of acute harm [16]. The burden of alcohol-related disease is particularly high among young adults, accounting for 7.2% of all premature deaths [15]. Furthermore, the alcohol consumption trend showed that from 1990 to 2017, global adult per-capita consumption increased from 5·9 to 6·5 litter and is forecasted to reach 7·6 litter (6·5–10·2) by 2030 [17]. In addition, while the prevalence of current drinking increased from 45% in 1990 to 47% in 2017, projections showed the trend will continue and the proportion of current drinkers increasing to 50% (46–53) by 2030 [17, 18]. This showed global goals for reducing the harmful use of alcohol are unlikely to be achieved.

It is expected that alcohol consumption leads to significant adverse effects and mortality. Besides alcohol use that is associated with several disorders such as depression, severe anxiety [19, 20], insomnia, suicide [20], and illegal drug use [9, 21–25]; continuous alcohol consumption also initiates several non-communicable diseases including heart disease, stroke, cancers, liver cirrhosis and digestive disorders [23]. Excessive alcohol consumption also plays a significant role in accidents, road injuries, violence, and public disorders, imposing considerable economic costs on health systems and communities [20, 26–28].

The prevalence of alcohol consumption is influenced by various factors such as socioeconomic status, gender, age, and cultural norms [29]. Among Muslim-majority countries, including Iran, the per capita alcohol consumption is at its lowest [6, 20, 21, 28]. Although alcohol consumption is low in Muslim countries [6, 12, 20, 21, 28], overall alcohol consumption has increased due to various reasons such as the availability of alcohol in the market, globalization, and potential changes in social-cultural norms [30, 31]. Alcohol consumption in Iran is lower compared to non-Islamic countries [6, 13, 20, 21, 28, 32], but it is relatively prevalent, especially among young men [33]. Despite low alcohol consumption in Iran, its adverse consequences such as substance use disorders, aggression, and relatively common harms raise serious concerns for public health [34]. The main concern about alcohol consumption in Iran is that most available alcoholic beverages are counterfeit and of low quality. These drinks can contain toxic substances that pose serious health risks, including poisoning, liver and kidney damage, and even death [35, 36]. To address this issue, it’s essential to combat the production and distribution of counterfeit alcohol through increased market surveillance, public education on the dangers, and stricter regulations [37].

Ilam province is one of the western provinces of Iran facing unique geographical and social conditions. The presence of deprived areas in some counties of this province can influence alcohol consumption patterns [20, 38, 39]. Furthermore, being bordering Iraq and close to Khuzestan and Kermanshah provinces can lead to illegal alcohol trade and consequently increase its consumption in this region [40]. The prevalence of alcohol consumption among students in the city of Ilam was estimated at 2.2% in 2014 [41]. Studies have focused on specific segments of society [22, 25] and do not represent the prevalence of alcohol consumption in the general population of Ilam city. Indeed, recent studies on alcohol consumption in Ilam province are limited, though evidence indicates that socioeconomic status, access to alcohol, and cultural changes all play a role. Many studies focus on specific groups, like students [41], leaving the general population unexamined. Moreover, while some research addresses psychological and social factors [3], the long-term effects on physical and mental health remain underexplored. There is also a need for more investigation into the economic and social impacts of alcohol consumption. To gain a comprehensive understanding of alcohol use patterns in Ilam province, broader studies are needed.

Conducting a cross-sectional study to estimate the prevalence of alcohol consumption in Ilam can demonstrate the impact and dynamics of alcohol consumption in society. Through detailed data analysis, it can help organize measures to reduce alcohol consumption and promote a healthy culture in the community. The lack of information and the need for up-to-date information for comprehensive planning in this area prompted us to conduct a study to estimate the age- and sex-standardized prevalence of alcohol consumption and its determinants in individuals over 15 years old in Ilam City in the year 2021–2022.

Methods

Design, location, and study population

This population-based cross-sectional study was conducted in the general population over 15 years old in the city of Ilam. The methodology of the present study was published elsewhere [19, 42] and is briefly explained here. Ilam, located in western Iran and bordering Iraq, has a population of approximately 200,000 [43]. (Fig. 1)

Fig. 1.

Location of Ilam city on Iran’s map

Sample size

Based on the results of the study by Nedjat [44], a prevalence of 33% for alcohol consumption, a type I error of 0.05, and a precision of 0.03 were considered to estimate the sample size. Ultimately, the sample size was estimated to be 931 individuals based on the following formula.

Considering a design effect of 1.5 and the sampling method, the sample size was estimated to be 1,400 individuals. The sampling method used was multi-stage stratified cluster sampling, where samples were selected using the proportion-to-size approach. In the first stage, the city of Ilam was divided into 10 comprehensive health centers, and each division was considered as a stratum and the population under the coverage of each area was determined. Then, based on the population of each area, the proportion of sample size to be selected from each area was determined. In the second stage, a cluster map of Ilam City was created based on the blocked map provided by the Statistical Centre of Iran, with each block being considered a cluster (supplement Fig. 1). Cluster sampling was used after determining the sample size in each area. A sample size of 20 individuals per cluster was considered, with clustered maps prepared for each area, and clusters were selected based on the sample size in each area. After identifying each cluster, the sampling team visited that cluster’s address, positioned themselves in the southwest corner (as each cluster has four corners, to select a corner, lottery method was used), and began sampling households in a clockwise direction until reaching the end of the sample size for each cluster. It’s important to note that household sampling was conducted using a convenience method. The first household in each cluster, located at the southwest corner, was designated as the starting point. After collecting data from the first household, the second household was selected. This process continued until the required number of households in each cluster was reached.

Eligibility criteria

All family members over the age of 15 were invited to participate. However, people not willing to participate in the study, people with cognitive diseases, and those who could not understand the questions correctly were excluded from the study.

Data collection and variables definition

At the beginning of the interview, the aims of the study were clarified to the invited people by samplers and if people who had more than 18 years old, were intent to participate, informed consent was obtained from participants. For participants who had not yet reached the legal age (18 years old in Iran), approval was obtained by a parent or guardian to participate in the research. The child was then asked whether they would like to participate or not, at which time the child can assent or dissent (refuse to participate). The assent process involved an ongoing, respectful conversation between interviewers and individuals under 18 years old. Interviewers ensured that each participant understood the research study and what participation entailed.

Then the data were collected by trained interviewers through face-to-face interviews. The questionnaire consisted of two sections. The first section included demographic information (age, gender, race, education, household size, occupation, and insurance coverage) and economic status (which included 15 questions about assets and an economic variable constructed using principle component analysis). The second section included a portion of a high-risk behavior questionnaire that had previously been validated (reported Cronbach’s alpha above 73% for all dimensions) [45]. Study variables included: lifetime alcohol use (referring to whether the individual has ever consumed alcohol at any point in their life; Yes/No), alcohol use in the past year (indicating whether the individual has consumed alcohol at least once in the past year; Yes/No), alcohol use in the past month (showing whether the individual has consumed alcohol at least once in the past month; Yes/No), and daily/almost daily alcohol use in the past month (referring to instances of daily or almost daily alcohol consumption in the past month; Yes/No) [46, 47].

Statistical analysis

Means with standard deviations (SD) and percentages were used for the description of quantitative and qualitative data. To estimate the age-sex-standardized prevalence of alcohol consumption, the population of the city of Ilam was prepared, and then the sample was weighted accordingly. Subsequently, the age-sex standardized prevalence of alcohol consumption with a 95% confidence interval (CI) was estimated. Initially, a simple logistic regression was conducted to calculate odds ratio (OR) and examine the relationship between the alcohol consumption with several determinants, including gender, race, marital status, education, job, economic status, cigarette smoking, hookah smoking and drug. Subsequently, a multiple logistic regression was employed to construct a full model and assess the simultaneous impact of study variables on the outcome. It is important to note that variables were included in the multiple logistic regression model based on a significance level of less than 0.2 [48]. Since one of the present study objectives was to compare the effect size of variables, the standardized coefficients were calculated to determine the most effective variable. In standardized coefficients, all variables with different scales were changed to a common scale; in other words, the scale effect was removed and the variables’ effect size were comparable. It should be noted that in all steps of analysis, missing values were imputed by performing multiple imputations and considering the Nearest Neighbors Imputation (NNI) approach. All analyses were conducted using Stata version 11 and R software with a significance level of 0.05 considered.

Results

Data for 1,431 participants were analyzed. The demographic and other characteristics of the participants can be seen in previous studies [19, 42]. The mean ± SD age of the study participants was 43.40 ± 15.51 years (age range: 15 to 92). Females accounted for 50.38% (95% CI: 47.76 to 53) of the participants. The race of the majority of participants was Kurdish (94.33%). About 61.28% (95% CI: 58.70 to 63.81) of the participants were married, while approximately 40.25% (95% CI: 37.69 to 42.84) worked as housekeepers. Age-sex standardized prevalence of alcohol consumption was estimated 4.05% (95% CI: 3.09 to 5.20).

Table 1 displays the prevalence of alcohol consumption based on gender. The results indicate that males had a higher prevalence of overall alcohol use (3.4%) compared to females (0.7%). The age-sex standardized prevalence of alcohol consumption throughout one’s lifetime, within the past year, within the past month, and on a daily or almost daily basis were estimated at 4.05% (95% CI: 3.09 to 5.20), 2.65 (95% CI: 1.88 to 3.62), 0.83 (95% CI: 0.43 to 1.46), and 0.13 (95% CI: 0.01 to 0.50) respectively.

Table 1.

Age-sex standardized prevalence of alcohol consumption in general population of Ilam based on gender

Alcohol consumption	N (%)		*Total% (95% CI)
	Male (N = 710)	Female (N = 721)
Lifetime use	48 (3.4%)	10 (0.7%)	4.05 (3.09 to 5.20)
Past year use	33 (2.3%)	5 (0.3%)	2.65 (1.88 to 3.62)
Past month use	9 (0.6%)	3 (0.2%)	0.83 (0.43 to 1.46)
Daily/almost daily use	1 (0.1%)	1 (0.1%)	0.13 (0.01 to 0.50)

*Age-sex standardized

Table 2 shows results of simple and multiple binary logistic regressions. In the results of the simple logistic regression model, only variables with p < 0.2 had the criterion for entry into the multiple regression model. As a results, variables such as gender, marital status, education, occupation, economic status, cigarette smoking, hookah use, and drug use met the entry criteria for the multiple model. Here, the results of the multiple logistic regression model are presented due to its more comprehensive nature. Results of multiple logistic regression model, in compare with people who had less than diploma education, the odds of alcohol consumption in people with diploma & associate degree were 4.07 (95% CI: 1.08 to 15.23) and in people who had more than bachelor degree were 7.13 (95% CI: 1.89 to 26.76). Compared to people with low economic status, the odds of alcohol consumption for middle and high economic status were 0.39 (95% CI: 0.16 to 0.94) and 0.62 (95% CI: 0.26 to 1.48); respectively. Result of multiple model showed that adjusted for other variables in model including gender, marital status, education, occupation, economic status, cigarette smoking (OR: 6.92; 95% CI: 2.94 to 16.29), hookah smoking (OR: 7.34; 95% CI: 3.09 to 17.47) and drug abuse (OR: 2.88; 95% CI: 1.38 to 5.99) had a positive association with alcohol consumption. The odds ratio for other variables was shown in the Table 2.

Table 2.

Associations between alcohol consumption and study factors in general population of Ilam based on logistic regression model

Variables		Alcohol consumption (Lifetime)
		alcohol consumption	Number (%)	Simple model		Multiple model		Standardized coefficient
				OR (95% CI)	P-value	OR (95% CI)	P-value
Gender	Male	Yes	48 (6.76)	Reference	---	Reference	---	NA
		No	662 (93.24)
	Female	Yes	10 (1.39)	0.19 (0.09 to 0.38)	< 0.001*	0.49 (0.20 to 1.20)	0.119
		No	711 (98.61)
Race	Other	Yes	3 (3.70)	Reference	---	NI		NA
		No	78 (96.30)
	Kurd	Yes	55 (4.07)	1.10 (0.33 to 3.60)	0.87
		No	1,295 (95.93)
Marital status	Married	Yes	30 (3.42)	Reference	---	Reference	---	NA
		No	847 (96.58)
	Single	Yes	26 (5.49)	1.63 (0.95 to 2.80)	0.072	1.55 (0.73 to 3.31)	0.251
		No	448 (94.51)
	Divorce /widow	Yes	2 (2.50)	0.72 (0.16 to 3.08)	0.662	1.34 (0.21 to 8.55)	0.750
		No	78 (97.50)
Education	< Diploma	Yes	5 (1.12)	Reference	---	Reference	---	0.703
		No	442 (98.88)
	Diploma & Associate Degree	Yes	17 (3.59)	3.28 (1.20 to 8.98)	0.020*	4.07 (1.08 to 15.23)	0.037*
		No	457 (96.41)
	≥ Bachelor	Yes	36 (7.06)	6.71 (2.61 to 17.26)	< 0.001*	7.13 (1.89 to 26.76)	0.004*
		No	474 (92.94)
Job	Student	Yes	4 (1.93)	Reference	---	Reference	---	NA
		No	203 (98.07)
	Employed	Yes	16 (7.24)	3.96 (0.01 to 1.30)	0.015*	1.48 (0.34 to 6.45)	0.597
		No	205 (92.76)
	self-employment	Yes	22 (8.09)	4.46 (0.07 to 1.51 )	0.007*	1.59 (0.41 to 6.08)	0.493
		No	250 (91.91)
	Retrieved	Yes	2 (1.29)	0.66 (0.63 to 0.11)	0.638	0.46 (0.06 to 3.46)	0.456
		No	153 (98.71)
	Housekeeper / unemployed	Yes	14 (2.43)	1.26 (0.68 to 0.41)	0.682	1.57 (0.41 to 6.04)	0.505
		No	562 (97.57)
Economic status	Low	Yes	35 (6.42)	Reference	---	Reference	---	-0.286
		No	510 (93.58)
	Middle	Yes	11 (4.47)	0.36 (0.18 to 0.73)	0.005*	0.39 (0.16 to 0.94)	0.037*
		No	435 (97.53)
	High	Yes	12 (5.73)	0.40 (0.20 to 0.79)	0.009*	0.62 (0.26 to 1.48)	0.290
		No	428 (97.27)
Cigarette smoking	No	Yes	13 (1.04)	Reference	---	Reference	---	0.588
		No	1,233 (98.96)
	Yes	Yes	45 (24.32)	30.48 (16.05 to 57.89)	< 0.001*	6.92 (2.94 to 16.29)	< 0.001*
		No	140 (75.68)
Hookah smoking	No	Yes	11 (0.88)	Reference	---	Reference	---	0.743
		No	1,246 (99.12)
	Yes	Yes	47 (27.01)	41.91 (21.20 to 82.85)	< 0.001*	7.34 (3.09 to 17.47)	< 0.001*
		No	127 (72.99)
drug	No	Yes	46 (3.27)	Reference	---	Reference	---	0.310
		No	1,362 (96.73)
	Yes	Yes	12 (52.17)	5.76 (2.92 to 11.38)	< 0.001*	2.88 (1.38 to 5.99)	0.005*
		No	11 (47.83)

NA: Not applicable; NI: Not included; OR: Odds ratio

Also, the values of standardized coefficients for variables showed that the hookah smoking (0.588), education (0.743) and being a smoker (0.743) were the most powerful determinants for alcohol consumption; respectively.

Discussion

This study aimed to determine the prevalence of alcohol consumption in the general population of Ilam city. According to the results of the current study, the age-sex standardized prevalence of alcohol consumption was 4.05%.

Different studies have estimated the prevalence of alcohol consumption differently, with some reporting higher and some lower estimates than the present study, as summarized in Table 3.

Table 3.

Comparison of prevalence of alcohol consumption in similar studies

Place		Author	Design	Year	Sample size	Age group	Prevalence%
Iran	six cities	Roshanfekr et al.[7]	Cross-sectional	2022	856	10–18	16.6
	Iran	Chegeni et al.[6]	Meta-analysis	2020	49,863	30>	13
	Iran	Rezaii et al.[28]	Cross-sectional	2016	29,068	18–70	8
	Tabriz	Naghizadeh et al.[21]	Cohort	2023	15,006	35–70	2.1
	Iran	Amin-Esmaeili et al.[20]	Cross-sectional	2017	7,840	15–60	7.5
	Iran	Moradinazar et al.[9]	Cross-sectional	2020	130,570	35>	12.37
	North of Iran	Pourmohammadi et al. [56]	Cross-sectional	2017	668	18–31	13.77
	East of Iran	Hosseinnataj et al.[45]	Case-series	2019	202	18–29	33
	Five cites	Mehrabi et al. [8]	Cross-sectional	2019	2,065	> 18	28
World	Ethiopia	Shibiru et al.[11]	Cross-sectional	2022	291	19 − 16	27.84
	Indian	Kumar et al.[10]	Cross-sectional	2013	946	> 10	9.4
	Ghana	Aboagye et al.[12]	Cross-sectional	2021	418	> 16	5.39
	Indian	Singh et al.[13]	Cross-sectional	2022	102,985	> 15	19
	China	Xu et al. .[32]	Cross-sectional	2010–2012	145,263	> 15	34

The prevalence of alcohol consumption in various studies conducted worldwide [6–14] was higher than in the present study, ranging from 9.04 to 39.5%. In comparison, Naghizadeh et al. studied 15,006 individuals aged 35 to 70 and found a 2.1% prevalence of alcohol consumption [21], which was reported lower than in the present study. Reasons for these inter-studies difference may be due to differences in age-gender distribution, the study population, differences in the definition and measurement tools of alcohol consumption, and cultural and social factors related to alcohol consumption [21].

Several studies showed that of alcohol consumption prevalence is different in different races [1, 29, 40]. However, in the present study, no relationship was found between race and alcohol consumption. Since the majority of the subjects studied were of Kurdish race (94%) and this variable did not have a high variance, the statistical power required to see the difference was not possible.

Several studies have shown differences between genders in the prevalence of alcohol consumption such as Kumar et al., who reported alcohol consumption prevalence in men as 16.1% and in women as 1.3% [10]. Wang et al. reported a significantly higher prevalence of alcohol consumption in men (57.5%) compared to women (36.2%) [14]. The higher prevalence of alcohol consumption in men compared to women was also observed in Shibiru et al. [11]. These findings were consistent with present study results. Gender-specific disparities in alcohol consumption, related behaviors, and consequences, including alcohol use disorders, are influenced by psycho-socio-cultural factors. These factors encompass perceived differences in traditional gender roles across various countries and generations [49, 50].

In many societies, alcohol consumption is accepted and often encouraged for men, while it can be viewed as distasteful or forbidden for women [51]. These social norms may lead men to drink more to adhere to traditional gender roles, viewing alcohol as part of their masculine identity and a means to demonstrate power and independence. Conversely, women may avoid drinking due to the conservative behaviors expected of them [52]. Gender schemas also influence how individuals cope with stress. Men might use alcohol as a coping mechanism, while women may seek alternatives that fit their roles [53]. Additionally, women often face greater social and legal consequences for drinking, which can result in lower consumption rates among them [54]. In Iran, for example, cultural factors make alcohol consumption less accepted for women than men, reflecting the significant impact of societal gender roles [55].

According to the present study findings, alcohol consumption increases with higher levels of education. Although this finding is consistent with Green et al. [57], it contradicts Norström et al.‘s findings [27]. Norström showed that there were significant differences between educational groups in alcohol consumption and alcohol-related harms, and the lower the level of education, the higher the prevalence of alcohol consumption and related harms [27]. It seems that individuals with lower levels of education have less awareness of the harmful effects of alcohol consumption, leading to increased consumption among them [27]. However, our finding was against of previous evidences. On the one side, evidence suggests that alcohol consumption among youth is increasing in Islamic societies. In the other side, population of Ilam differs significantly from other population in terms of cultural practices, regulations, population composition, traditions, and societal beliefs.

The present results revealed that higher economic status has an inverse relationship with alcohol consumption. In other words, individuals with average income levels consume more alcohol than those with lower incomes, which is consistent with other studies [24, 27, 58]. However, it should be noted that the relationship between economic status and the prevalence of alcohol consumption in different societies and cultures can be different and complex [24, 27, 58]. Allen et al. stated in their study that tobacco and alcohol consumption is more prevalent in lower socioeconomic groups compared to higher socioeconomic groups [59]. In contrast, Martin et al. with studying 18- to 24-year-old Unites State college students [60] and Gu et al. with studying Chinese adult [61] reported different results so that alcohol consumption prevalence was higher in high socio-economic groups. This controversy may be due to the fact that lifestyle and exposure to stressful events can influence substance use at times. It should be noted that even if individuals with higher economic status consumed more alcohol, individuals in lower economic groups experienced more negative consequences of alcohol consumption [60, 61].

Another study’s findings were that cigarette smoking, hookah smoking and drug use significantly increase the likelihood of alcohol consumption. The results of this study are consistent with other studies [14, 61–64]. Epidemiological studies of cigarette smoking and alcohol consumption have shown that more than 70% of alcohol users are cigarette smokers [61]. Additionally, cigarette smoking and drug use in individuals who consume alcohol is higher due to their increased tendency to experience synergistic effects [62, 63]. Also, alcohol consumption and stress increase the tendency to smoke in individuals [64]. The reason for this mechanism is still unknown, however several mechanisms may contribute. Alcohol consumption prior to cigarette smoking may nullify the satiating effects of smoking, motivating additional smoking behavior. Alternatively, nicotine may counteract the sedative effects of alcohol consumption and co-use may also be maintained by associative learning [63].

Although the research team tried to conduct the study flawlessly, this study has some limitations. Due to the cross-sectional nature of the study and the lack of temporality criteria, the observed relationships cannot be considered causal. Furthermore, since alcohol consumption was self-reported and subject to social desirability bias, there may be underreporting in the results of this study [20]. Nevertheless, the high sample size, use of trained questionnaires, and standard tools can be considered strengths of this research.

Conclusions

Based on the present study, the standardized prevalence of alcohol consumption in the general population was estimated at 4.05%. The prevalence was higher in men compared to women. Alcohol consumption was influenced by various variables including gender, education, economic status, cigarette smoking, drug use, and hookah smoking. However, the most influential variables were hookah smoking, education, and cigarette smoking. These findings highlight the need for a comprehensive approach to addressing alcohol consumption through education, awareness, and policy measures simultaneously. Additional research is needed to analyze trends in alcohol consumption over time and assess the effectiveness of interventions aimed at reducing alcohol consumption and its related harms in the population. Efforts should focus on targeted educational and awareness programs, especially among vulnerable populations, to reduce the prevalence of alcohol consumption.

Practical implications

The study’s findings revealed that out of every 1,000 people, 31 to 52 individuals had consumed alcohol at some point in their lives. Although this figure might seem low at first, it’s important to take into account the potential underreporting of alcohol consumption. This means that the actual number of people with alcohol-related issues in the studied population could be higher. The key factors associated with alcohol consumption included other high-risk behaviors such as cigarette smoking, illicit drug use, and hookah. Consequently, health policymakers should also address these behaviors when developing comprehensive plans. Given that education emerged as one of the most influential factors affecting alcohol consumption, implementing policies aimed at raising public awareness could be an effective strategy for reducing alcohol consumption. This will be executable by implementing interventions to raise public awareness, such as spreading information about the complications of alcohol through local or national social media, and news outlets, and distributing small books or pamphlets in communities. Furthermore, as mentioned in the limitations section, due to the constraints of a cross-sectional study in assessing causal effects, it is necessary to design large longitudinal studies to assess the causal association between determinants and alcohol consumption. It will be possible also to examine the trends in alcohol consumption in the future based on different variables and health policymakers will be able to develop a more effective plan to combat alcohol abuse.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Author contributions

R-P and M-B, D-A and K-M participated in designing the study, analyzing and interpreting data. Z-M, A-S and K-M collected the data and reviewed the literature. All authors prepared the manuscript and R-P and D-A worked on editing and finalizing the paper’s draft. All authors read and approved the manuscript.

Funding

No.

Data availability

The dataset supporting the conclusions of this article is available upon editor request to corresponding author (Reza Pakzad, Email: rezapakzad2010@yahoo.com).

Declarations

Ethics approval and consent to participate

This study adhered to the Helsinki Declaration and was approved by the Ethics Committee of Ilam University of Medical Sciences (IR.MEDILAM.REC.1401.031). All methods were carried out in accordance with relevant guidelines and regulations. Also, informed consent was obtained from all subjects. For people who had under the age of 16, informed consent to participate was obtained from the parents or legal guardians.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.