Alcohol consumption among Iranian population: STEPS survey, 2021

Alcohol consumption among Iranian population: STEPS survey, 2021 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Alcohol consumption among Iranian population: STEPS survey, 2021 Amirali Hajebi, Maryam Nasserinejad, Negar Rezaei, Sina Azadnajafabad, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3771284/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Jul, 2024 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Alcohol production and consumption have been prohibited in Iran for over four decades, leading to a typical underestimation of its consumption. This study aimed to assess the prevalence of alcohol consumption, its associated factors, and estimate per capita alcohol consumption among Iran's adult population. In this population-based survey, 27,874 adults from across Iran were selected using systematic proportional to size cluster sampling. Alcohol consumption was evaluated through a modified Persian version of the STEPS questionnaires from previous studies, applied over different timespans. Per capita consumption was calculated using the quantity-frequency method, expressed in liters of pure alcohol. Adjusted odds ratios were reported for associates of alcohol consumption concerning metabolic risk factors, sociodemographic elements, and lifestyle variables. The prevalence of lifetime alcohol consumption was 6.9% (95% CI: 6.5–7.2) in the adult population, with a notable sex difference (males: 13.7% [95% CI: 13-14.4]; females: 1.4% [95% CI: 1.1–1.6]). The 12-month prevalence was 3.8% (95% CI: 3.6–4.1). For individuals aged 18 and older, the per capita alcohol consumption in Iran was 0.12 liters. Factors such as being a lifetime smoker, younger, wealthier, and having 7–12 years of education were significantly linked to higher alcohol consumption. Significant associations were also observed between alcohol consumption and obesity, history of heart attacks, and physical injuries. The study revealed a complex relationship between alcohol consumption, behavioral risk factors, and metabolic profiles. Consequently, immediate preventive measures tailored to each factor's association with alcohol use are recommended. Health sciences/Medical research/Epidemiology Health sciences/Risk factors Health sciences/Health care/Public health Figures Figure 1 1. Introduction Globally, harmful use of alcohol is responsible for 3 million deaths every year which represents 5.3% of all deaths 1 . The recent Global Burden of Diseases (GBD) study identifies alcohol as the primary risk factor for the 25–49 age group regarding attributable burden 2 , 3 . Between 2010 and 2019, there was an annualized increase of 0.5% in alcohol use, contributing to a significant rise in the percentage of attributable Disability-Adjusted Life Years (DALYs) 2 , 4 . Alcohol per capita consumption (APC), the total amount of pure alcohol consumed by individuals 5 , has risen from 5.4 liters in 2005 to 6.2 liters in 2018 among individuals aged over 15 years worldwide 6 , 7 . Research indicates a link between alcohol consumption and various non-communicable diseases (NCDs), mental and behavioral disorders, and injuries, including road traffic incidents, drowning, poisoning and falls 8 , 9 . Additionally, the consumption of bootleg or adulterated alcohol can lead to methanol poisoning, causing hospitalizations and deaths 10 , 11 . The harmful use of alcohol also leads to significant social and economic losses to individuals and society 1 . In Iran, a Muslim-majority country in the Middle East, alcohol production, consumption, and trade are criminalized 12 , 13 . Also, there is a social stigma linked to alcohol consumption in this country 14 . These factors contribute to lower APC and prevalence of alcohol use in Iran compared to majority non-Muslim countries 11 . However, they have also delayed comprehensive scientific research and healthcare policy development 15 , 16 . Despite the alcohol ban, alcoholic beverages have the potential to be illicitly manufactured in residential settings and illegally transported into the country, subsequently being distributed through underground channels 17 . Consequently, there is no official data on the production or sales of alcoholic products 17 , 18 . To the best of our knowledge, few studies have measured Iran's APC or alcohol consumption prevalence 10 , 18 – 21 . However, the increasing trend of alcohol consumption 22 , alongside its association with various NCDs and mental disorders, necessitates a current and detailed report to formulate appropriate population-wide policies and action plans. This study aims to determine the prevalence of alcohol consumption among Iran's adult population, classified by demographics and socio-economic status, and estimate the APC to assess the pattern of alcohol use in 2021. Understanding these patterns is crucial for health authorities to combat the harmful use of alcohol and its extensive negative impacts. 2. Materials and method The World Health Organization (WHO) initiated the STEPwise Approach to NCD Risk Factor Surveillance (STEPS) in 2000, offering a standardized method for global data collection, processing, and dissemination 23 . STEPS is a large-scale population-based, sequential cross-sectional study that continuously monitors key risk factors for NCDs. In Iran, eight surveys have been conducted based on the WHO STEPS methodology 24 . The current study is part of the most recent STEPS, carried out in 2021 25 . The data collection phase comprised three steps: first, data were collected using the STEPS questionnaire through participant interviews; second, physical examinations were conducted; and third, laboratory assessments were performed on adults over 25 25 . 2.1 Study population The latest data come from the eighth round of the STEPS survey. A total of 28,520 individuals from urban and rural areas across all 31 provinces of Iran were selected using a multistage clustered probability design to create a nationally representative sample. Of these, 27,874 chose to participate in the first step, 27,745 in the second, and 18,119 in the third. The primary reason for non-response was unwillingness to participate. All participants were at least 18 years old and residents of Iran at the time of data collection. After obtaining written informed consent, trained in-home interviewers collected a broad range of information on sociodemographic characteristics, household assets, healthcare utilization, health behaviors, history of metabolic risk factors, and anthropometric measures. Data collection began in January 2020 and was partially completed by February 2020 when it was suspended due to the COVID-19 outbreak in Iran. It resumed approximately a year later with COVID-19 safety measures in place, and the remaining data were collected between February and April 2021. The protocol was explained comprehensively and with further details elsewhere 25 . 2.2 Alcohol consumption assessment For the alcohol consumption assessment part of the STEPS study, a Persian-translated version of earlier STEPS questionnaires, modified for the Iranian cultural and religious context, was used 25 . Alcohol consumption prevalence, a key variable of this study, was assessed over three timespans: lifetime, past 12 months, and past 30 days. Binge drinking was also measured over the past 12 months and 30 days, using the Bettering the Evaluation and Care of Health (BEACH) definition of consuming six or more standard drinks on one occasion 26 . In line with the STEPS protocol, we used a regular cup (approximately 250–300 cc) as the standard measure for beer and wine, and a smaller cup (about 50 cc) for hard liquors such as vodka, whiskey, tequila, cognac, rum, and their domestic equivalents. APC, another main variable, is defined as the total amount of alcohol consumed in liters of pure alcohol by the population over 15 years old in a calendar year 27 . As our study included individuals aged 18 and older, we reported the APC for the 18 + age group. Several methods exist to calculate APC 10 , 28 . The social stigma toward alcohol consumption in Muslim-majority countries and the low prevalence and frequency of alcohol use led to underestimation of methods such as yesterday and last week 29 , 30 . As a result, the method that we employed in this study is the Quantity-Frequency (QF) method which is one of the preferred methods to calculate APC in Muslim-majority countries with very low drinking levels 10 . QF is among the earliest methods to assess alcohol use and is most useful when information about occasional high and low drinking days is not required and time is limited 31 . We employed the below formula of QF method for calculating APC: $$Alcohol per capita consumption=F\times Q\times \alpha$$ In this formula, F represents the frequency of alcohol consumption, which we asked questions about in the past 12 months during this study, Q is the amount of alcohol consumed in a typical day of drinking and α is a constant number which refers to the amount of pure alcohol per each alcoholic drink. We used the Iranian Ministry of Health’s routinely used definition of a standard drink, which is 13 g of pure alcohol 10 . APC was calculated by multiplying the estimated number of drinking days in the past 12 months by the daily quantity of drinks and then, multiplying the result by 13 to calculate the total alcohol consumed annually in grams. 2.3 Definition of variables For socioeconomic stratification in this survey, the Wealth Index (WI) was computed based on data regarding household assets obtained from questionnaires. This index was then divided into five levels, ranging from the least wealthy (first quintile) to the most wealthy (fifth quintile). Education levels were recorded in four distinct categories: none, 1–6 years, 7–11 years, and 12 or more years. The living environment of the participants was classified as either urban or rural. Ages of the participants were grouped into seven brackets: 18–24, 25–34, 35–44, 45–54, 55–64, 65–70, and above 70. BMI was calculated using the evaluated height and weight for each individual entered the second step of the study. Obesity was defined as a Body Mass Index (BMI) of more than 30 according to references 32 . The cardiometabolic conditions and other diseases assessed in this study were identified based on participants' self-reports of having the condition or taking medication for its treatment, as outlined in the questions of the STEPS questionnaire tool. History of heart attacks variable was investigated via related questions in the questionnaire asking whether the individual had a history of heart attacks in his/her lifetime or not. Physical injuries variable was assessed via the same method and considered positive if the individual reports history of physical injury(s) during the past 12 months prior to the study. 2.4 Data analysis Data cleaning adhered to WHO STEPS guidelines 23 , and statistical analyses were performed with R software version 4.0.5 at a 0.05 significance level. Baseline characteristics were presented using means (standard deviation (SDs)) for continuous variables and numbers (percentages) for categorical variables. To investigate the association between sociodemographic characteristics and alcohol consumption and the association between alcohol consumption and the non-communicable diseases investigated in this study, we used multiple and univariate logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Initially, each variable was analyzed using a bivariate regression model. Subsequently, a multiple model was developed, incorporating multiple variables informed by the results of the bivariate analysis. Bivariate analyses were performed to estimate crude ORs, and all variables with p-value < 0.2 (including age, sex, wealth index, level of education and smoking, and conditions of diabetes, hypertension, hypercholesterolemia, history of heart attack(s), stroke, physical injuries, and obesity) entered the multiple model to calculate adjusted ORs. 2.5 Ethical considerations All eligible individuals were informed about the study's objectives and methods. Participation was voluntary, with written consent obtained from all participants. Ethical approval was granted by the ethics committee of Tehran University of Medical Sciences (IR.TUMS.NIHR.REC.1398.006). The funding source played no role in the study's design, data collection, analysis, interpretation, manuscript writing, or decision to submit the paper. 3. Results 3.1 Overview The study included 27,874 adults aged 18 and older (mean age (SD): 45.7 (0.1); 55.4% females). Among these participants, 43.6% had more than 12 years of education, and 75% were urban residents. 3.2 Alcohol consumption scale of Iran’s population The mean lifetime alcohol consumption prevalence was 6.9% (95% CI: 6.5–7.2) for the entire population, 1.4% (95% CI: 1.1–1.6) for females, and 13.7% (95% CI: 13-14.4) for males. Using the Quantity-Frequency (QF) method, the study calculated the Alcohol Per Capita Consumption (APC) as 0.120 liters of pure alcohol (95% CI: 0.081–0.159). The 12-month prevalence of alcohol consumption was 3.8% (95% CI: 3.6–4.1), with 0.9% for females (95% CI: 0.7-1) and 7.5% for males (95% CI: 7-8.1). In the past 30 days, 2.1% of participants (95% CI: 1.9–2.2) reported alcohol consumption, with 0.5% females (95% CI: 0.3–0.6) and 4% males (95% CI: 3.6–4.4). The overall prevalence of binge drinking in the past 12 months was 1.7% (95% CI: 1.5–1.8) (Table 1 ). Males were nearly four times more likely to consume alcohol than females (OR 3.8, 95% CI: 3-4.9) (Table 2 ). The highest alcohol consumption rates, including binge drinking, were observed in the 18–24 and 25–34 age groups, decreasing with age. In all age groups, males had higher prevalence rates than females (Table 1 ). Table 1 Alcohol consumption in Iran status and socio-demographic characteristics, based on Iran STEPS 2021 Survey. Alcohol Drinking Status Lifetime alcohol drinking (%) Past 12 months alcohol drinking (%) Past 30 days alcohol drinking (%) Past 12 months binge drinking (%) Past 30 days binge drinking (%) Variables Categories Sex Female 177 (1.4%) 108 (0.9%) 55 (0.5%) 27 (0.3%) 15 (0.1%) Male 1593 (13.7%) 869 (7.5%) 460 (4%) 372 (3.4%) 213 (1.9%) Age 18–24 years 219 (9.19%) 164 (7%) 86 (3.6%) 91 (4.3%) 43 (1.9%) 25–34 years 501 (10.2%) 326 (6.8%) 176 (3.8%) 148 (3.3%) 89 (2%) 35–44 years 440 (7.5%) 253 (4.4%) 135 (2.4%) 95 (1.6%) 59 (1%) 45–54 years 256 (5.1%) 116 (2.3%) 56 (1.1%) 32 (0.7%) 18 (0.4%) 55–64 years 196 (4.9%) 80 (2.1%) 43 (1.1%) 22 (0.6%) 12 (0.3%) 65–70 years 112 (4.6%) 29 (1.1%) 15 (0.5%) 9 (0.3%) 6 (0.2%) > 70 46 (5%) 9 (1.2%) 4 (0.5%) 2 (0.3%) 1 (0.1%) Residential status Rural 456 (6.6%) 247 (3.5%) 134 (1.9%) 92 (1.4%) 55 (0.8%) Urban 1314 (7%) 730 (3.9%) 381 (2.1%) 307 (1.8%) 173 (0.9%) Wealth index Poor 281 (5.6%) 125 (2.5%) 69 (1.3%) 48 (1%) 29 (0.5%) Second quintile 320 (6.2%) 165 (3.2%) 79 (1.4%) 73 (1.6%) 35 (0.7%) Third quintile 359 (7.4%) 195 (4.1%) 107 (2.3%) 84 (1.8%) 45 (1%) Forth quintile 360 (7.8%) 213 (4.6%) 107 (2.5%) 82 (1.9%) 45 (1%) Rich 388 (8.1%) 236 (5%) 131 (2.8%) 96 (2.2%) 62 (1.4%) Lifetime smoking No 1122 (4.7%) 615 (2.6%) 312 (1.4%) 235 (1.1%) 131 (0.6%) Yes 647 (27.6%) 361 (16%) 203 (8.9%) 164 (7.4%) 97 (4.2%) Total 1770 (6.9%) 977 (3.8%) 515 (2.1%) 399 (1.7%) 228 (1.2%) Table 2 Assessment of lifetime alcohol consumption associated factors using multiple logistic regression Lifetime alcohol consumption Variable Category OR (95% CI) Model a 1 P value OR (95% CI) Model b 2 P value Sex Female Ref - - - Male 11.56(9.74,13.71) < 0.001 3.84(2.99,4.94) < 0.001 Residential status Rural Ref - - - Urban 1.06(0.94,1.20) 0.32 - - Wealth index Poor ref - - - Second quintile 1.1(0.91,1.32) 0.32 1.07(0.85,1.35) 0.57 Third quintile 1.34(1.12,1.60) 0.001 1.26(1.01,1.57) 0.04 Forth quintile 1.41(1.19,1.69) < 0.001 1.34(1.07,1.67) 0.01 Rich 1.47(1.23,1.75) < 0.001 1.49(1.18,1.87) 0.001 Education Illiterate Ref - - - Less than 7 years of education 3.08(2.29,4.12) < 0.001 1.58(1.12,2.22) 0.01 7–12 years of education 6.33(4.76,8.41) < 0.001 2.23(1.58,3.15) < 0.001 More than 12 years of education 4.38(3.32,5.78) < 0.001 1.67(1.18,2.36) 0.01 Lifetime smoking No Ref Yes 7.65(6.80,8.62) < 0.001 4.17(3.58,4.85) < 0.001 1 Crude odds ratio 2 Adjusted odds ratio (all variables with p-value < 0.2 entered the model including age, sex, wealth index, level of education and smoking) 3.3 Associates of alcohol consumption Table 2 shows the crude and adjusted odds ratios for sex-categorized variables. Generally, the adjusted odds for lifetime alcohol consumption were significantly higher among males (OR = 3.84, 95% CI: 2.99–4.94), smokers (OR = 4.17, 95% CI: 3.58–4.85), the oldest compared to the youngest (OR = 0.98, 95% CI: 0.97–0.98), and the wealthiest compared to the poorest (OR = 1.49, 95% CI: 1.18–1.87) (Fig. 1 ). Individuals with 7–12 years of education had the highest odds of alcohol consumption (OR = 2.23, 95% CI: 1.58–3.15). Multivariable logistic regression revealed that individuals reporting lifetime alcohol consumption had significantly greater odds of obesity (OR = 1.23, 95% CI: 0.97–1.56), a history of heart attacks (OR = 2.04, 95% CI: 1.44–2.89), and physical injuries (OR = 1.88, 95% CI: 1.34–2.64). The study also found positive associations between lifetime alcohol consumption and certain metabolic diseases and risk factors, but negative associations with stroke and diabetes. However, these associations were not significant (Table 3 , Fig. 1 ). Table 3 Assessment of metabolic diseases and risk factors associated with alcohol consumption using multiple logistic regression Life time alcohol consumption Variable Category OR (95% CI) Model a 1 P value OR (95% CI) Model b 2 P value Diabetes No Ref - - - Yes 0.57(0.41,0.80) 0.001 0.80(0.57,1.11) 0.18 Hypertension No Ref - - - Yes 0.60(0.50,0.71) < 0.001 1.06(0.83,1.35) 0.64 Hypercholesterolemia No Ref - - Yes 0.58(0.43,0.80) 0.001 1.13(0.83,1.55) 0.44 History of heart attack(s) No Ref - - - Yes 0.81(0.59,1.11) 0.18 2.04(1.44,2.89) < 0.001 Stroke No Ref - - - Yes 0.31(0.10,0.98) 0.04 0.79(0.38,1.66) 0.54 Cancer No Ref - - - Yes 0.85(0.42,1.75) 0.67 - - Lung diseases No Ref - - - Yes 1.09(0.78,1.52) 0.61 - - Physical injuries No Ref - - - Yes 2.72(2.20,3.37) < 0.001 1.88(1.34,2.64) < 0.001 Obesity No Ref - - - Yes 0.68(0.57,0.82) < 0.001 1.23(0.97,1.56) 0.01 1 Crude odds ratio 2 Adjusted odds ratio (all variables with p-value < 0.2 entered the model including age, sex, wealth index, level of education and smoking, and conditions of diabetes, hypertension, hypercholesterolemia, history of heart attack(s), stroke, physical injuries, and obesity). 4. Discussion This study evaluated alcohol consumption prevalence in Iranians aged 18 and older. The findings indicate that approximately 3.9 million and 2.2 million individuals over 18 in Iran have consumed alcohol at least once in their lifetime and in the past 12 months, respectively. The lifetime and 12-month prevalence rates of alcohol consumption in our study are lower than the global average but higher than the figures estimated by the WHO for EMRO countries 6 . It's important to note that the WHO's estimates refer to populations aged over 15 years. Additionally, our study showed a lower lifetime prevalence of alcohol consumption than that reported in four Iranian provinces in 2015 17 . Part of this difference can be attributed to the setting of the studies. The 2015 study was a street-based study and the participants faced less stigma in disclosing facts about their alcohol consumption. Essentially the prohibition of alcohol consumption in Iran and other Muslim-majority countries usually leads to under-reporting of alcohol use 19 , 33 . Our study likely reflects this trend, suggesting that the actual prevalence may be higher than reported. Compared to other countries, the prevalence of binge drinking in the last month and last 12 months was notably lower in our study 34 – 36 . A higher prevalence of alcohol consumption was observed in male participants compared to females, aligning with both national 10 , 17 , 37 , and international studies 6 , 38 , 39 . This gender disparity in alcohol consumption could be attributed to cultural and religious norms, as women typically adhere more closely to cultural and religious principles that discourage alcohol use 39 . The rate of alcohol consumption in males over the past 12 months was 8.8 times higher than in females, mirroring the gender gap reported in Iran's National Mental Health Survey 19 . Interestingly, alcohol consumption patterns in North America and Europe have shifted in recent decades, with female patterns increasingly resembling those of males, particularly concerning harmful use 40 – 42 . The exact extent of this change remains unclear 43 . Consistent with other research, our study found that binge drinking was more prevalent among males 44 – 47 . Bing drinking has been traditionally more prevalent among the males, though the gap is narrowing due to rising alcohol consumption levels among females 48 , 49 . The findings of our study align closely with those from a recent meta-analysis on alcohol consumption in Iran 12 . This analysis reported a combined prevalence of lifetime alcohol consumption at 13.0% (95% CI: 11.0% − 16.0%). It also noted a pooled prevalence of 12.0% (95% CI: 7.0–18.0%) for alcohol consumption in the past 12 months within the general population, and a slightly higher prevalence of 15.0% (95% CI: 9.0–22.0%) among youth. Additionally, the study highlighted notable regional variations in alcohol consumption rates, which ranged broadly from as low as 0.03% to as high as 68.0%. Prevalence rates were observed to vary significantly by gender, with figures for males ranging from 0.3–66.6%, and for females from 0.2–21.0% 12 . This study indicates that the highest prevalence of alcohol consumption in the past month, past 12 months, and over a lifetime occurred in the 18–34 age group for both sexes. This trend is likely influenced by various developmental and cultural factors 50 . Young adults are prone to consuming larger quantities of alcohol, leading to more adverse effects, and individuals between 20 to 34 years old experience the highest mortality rates related to alcohol consumption 51 . The results also demonstrated that alcohol consumption prevalence is higher among cigarette smokers across all age groups. Correspondingly, higher instances of binge drinking were noted among smokers, aligning with research showing a link between tobacco and alcohol use 52 . The relationship between alcohol and tobacco use is complex and influenced by both social and pharmacological factors, especially as tobacco use prevalence is highest among young adults engaged in binge drinking 53 , 54 . Moreover, a greater prevalence of alcohol consumption was observed among urban residents and individuals with higher education levels, highlighting the impact of social factors, living conditions, and education on alcohol consumption in Iran. Studies within Iran have shown similar patterns, with higher alcohol consumption among high school and university students 55 – 57 . These findings are consistent with results from other countries 58 – 60 . Research on the geographical relationship with alcohol consumption presents mixed results; some studies report higher consumption in urban areas 61 , while others find increased consumption in rural settings 62 . Therefore, understanding the relationship between living status and alcohol consumption requires considering a range of demographic, social, and cultural factors 63 . In our study, individuals with a higher wealth index exhibited increased alcohol consumption, with the wealthiest group consuming 1.5 times more than those in the lowest wealth index category. Numerous studies have established a direct association between socio-economic status and alcohol consumption, yet an inverse relationship exists between harmful drinking patterns, such as binge drinking, and socio-economic status 64 – 69 . Research indicates that in societies where alcohol consumption is stigmatized due to legal and religious prohibitions, as well as criminalization, there is a tendency for alcohol users to underreport their usage. This underreporting is particularly pronounced when questions pertain to recent consumption (past day or week), while queries about the past month or year tend to yield more accurate results. In contrast, in countries without such prohibitions, questioning about last day or week alcohol consumption tends to be more reliable, effectively addressing recall bias and serving as a better tool for calculating APC 10 , 30 , 70 . Given the legal and social stigma associated with alcohol in Iran, our survey considered the most recent recall period as the last month. The Quantity-Frequency (QF) method was used for annual APC calculation, although it entails more recall bias than the "last week" method 71 . The survey results showed that Iran's APC (0.120L) is lower than the global (6.4L) and regional (0.6L) averages 6 . It's important to note that while these international figures typically pertain to individuals over 15 years old, our study focused on those over 18, which might contribute to some of the observed differences. Compared to the QF calculation by Amin-Esmaeili et al. in 2011, the APC reported in this study showed a 50% increase 10 . The results from the multiple logistic regression model in our study indicated a significant positive correlation between alcohol consumption and various non-communicable diseases and metabolic syndromes, including hypertension, hypercholesterolemia, heart attacks, obesity, and physical injuries. Interestingly, the data suggested a decrease in the risk of diabetes mellitus and stroke associated with alcohol consumption. Particularly noteworthy is the elevated and significant risk linked with heart attacks, obesity, and physical injuries. Various studies have explored the relationship between alcohol consumption and non-communicable diseases. Identified patterns include the J-shaped curve, illustrating a dose-response relationship between alcohol intake and the odds of metabolic syndrome 72 , and the U-shaped pattern, where heavy drinkers face a significantly higher risk, unlike low and moderate consumers 73 . An inverse relationship has also been reported, indicating that low to moderate alcohol use could correlate with a lower incidence of metabolic syndrome and positively affect waist circumference and fasting insulin levels 74 . While some studies suggest a linear relationship between alcohol consumption and metabolic syndrome 75 , 76 , others find no significant correlation 77 , 78 . The growing body of research underscoring the link between lifetime alcohol consumption and its detrimental effects, especially the risk of metabolic syndrome, highlights the urgent need for preventive measures against alcohol consumption 3 , 79 , 80 . This evidence is vital for shaping public health policies and strategies, particularly those addressing any level of alcohol consumption due to its potential adverse health impacts 3 . Despite the challenges posed by the COVID-19 pandemic, this study's data collection was conducted face-to-face, adhering to health guidelines and social distancing. This national study encompasses a large sample size from across the country. A key feature of this study is its alignment with the WHO's STEPS methodology, enabling comparisons with global studies. In response to the stigma surrounding alcohol consumption in Iran, interviewers were specifically trained to gather data discreetly and privately. Another strength of this study lies in its assessment of comorbidities associated with alcohol consumption. Conditions like hypercholesterolemia and diabetes were evaluated using both laboratory data and medical history, and participants' blood pressure was measured during their assessment. Future studies could focus on longitudinal analyses to better understand the causal relationships between alcohol consumption and non-communicable diseases, particularly in the context of cultural and legal restrictions. Research exploring the impact of COVID-19 on alcohol consumption patterns would also be valuable. Clinically, there is a need for targeted interventions and public health strategies that address the unique challenges of alcohol consumption in Iran, considering the social stigma and legal implications. This includes developing culturally sensitive prevention programs and educational campaigns, especially targeting high-risk groups such as young adults and urban residents. Further, integrating alcohol use assessment into routine clinical practice could enhance early detection and management of alcohol-related health issues. Finally, considering the low reporting rates in certain demographics, innovative data collection methods that ensure confidentiality and reduce social desirability bias are essential for more accurate prevalence estimates and effective policy-making. This study is subject to some limitations. Firstly, its cross-sectional design poses challenges in identifying potential reverse associations between alcohol consumption and assessed outcomes, as well as in establishing causality. As a household survey, it does not include individuals living in residential facilities, institutions with restricted access, or those who are homeless, where alcohol consumption prevalence might differ. Additionally, the reliance on self-reporting could lead to underreporting, particularly since alcohol consumption is illegal and socially stigmatized in Iran. This study focuses on individuals over 18 years old, which limits the comparability of the Alcohol Per Capita Consumption (APC) results with other national and international studies that often include those aged 15 and older. Furthermore, restricted access to recent alcohol consumption data (last week) made it impossible to employ the "last week" method alongside the Quantity-Frequency (QF) method. Consequently, calculating APC using a combination method was not feasible 10 . A key limitation of our study is the low prevalence of alcohol consumption in the Iranian population, potentially due to under-reporting or genuinely lower consumption levels. This led to smaller sample sizes for recent consumption periods (past 12 months and 30 days), limiting the power and reliability of our statistical analyses. The impact of COVID-19 on changes in alcohol consumption levels could be significant during the pandemic based on literature, but measuring this impact was beyond the scope of our study and it was another limitation of the current research. In this population-based study, we estimated the prevalence of alcohol consumption over multiple timespans, finding the highest rates among males and younger age groups. This underscores the need for targeted prevention strategies within these demographics in public health policies. The potential hazardous effects of even lifetime alcohol consumption call for appropriate preventive measures to address this public health concern. Moreover, focusing on harm reduction interventions among those with lower socioeconomic status is crucial to mitigate the adverse impacts of harmful alcohol use. Our findings also highlight a positive correlation between alcohol consumption and metabolic syndrome. To reduce the possible negative effects of alcohol on individuals' metabolic profiles, implementing preventive strategies against alcohol consumption, particularly its harmful patterns, is a critical priority. Declarations Acknowledgement The authors extend their heartfelt gratitude to the Deputy of Health and the Deputy of Research and Technology at the Ministry of Health and Medical Education, the National Institute for Health Research, the World Health Organization, and numerous scholars and experts in related fields. We also sincerely thank all participants and the scientific and executive partners from the medical universities who contributed to this project. Your collaboration and support have been invaluable to the success of this study. Authors’ Contribution Conceptualization: F.F., N.R., A.H.; Data Curation: M.N., E.G., M.Y., N.A.; Formal Analysis: M.N., E.G., M.Y., N.A.; Investigation: F.F. and all of co-authors; Methodology: F.F., A.H., E.G., N.R.; Project Administration: A.H., R.H., S.A., MM.R., E.F., Y.F., S.R., M.A., N.F.; Supervision: R.H., Y.F., S.D., A.K., E.F., A.M.; Validation: F.F., A.H., S.A., N.R.; Writing—Original Draft Preparation: A.H.; Writing—Review and Editing: S.A., MM.R., K.R., A.M., H.J.; Visualization: M.N., N.A.; All authors reviewed the manuscript, critically commented on the draft and provided their approval for the submission. Data Availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. 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Farzadfar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBAC9gbGByCasb2BAcICgwQ8WngOMBuAtfQcYGA2OECqFjaJA3hUIrQwMDN+rvhjJ9vDfvZZ9ce2bfYM7IcfMDzcg1cLs+QZnmTjHp50sxsH224nNvCkGTAkPMOtxV7+/QHJBgnmxP0MaWwgLUBf5AD9gseJIFt+NhjUJ/bwP2MrAGqxZ+B/Q1ALm2RDwuHEHok0NgagFsYGCcK2sFk2HDhu3CPxjFnizLnbiW0SzwwOEHLYzYY/1bI9/GmMHyrKbtvz8yc/fPgDjxZMwAbEJGkYBaNgFIyCUYAJAH6bTm3t6R7EAAAAAElFTkSuQmCC","orcid":"","institution":"Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Farshad","middleName":"","lastName":"Farzadfar","suffix":""}],"badges":[],"createdAt":"2023-12-18 10:14:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3771284/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3771284/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-66257-w","type":"published","date":"2024-07-22T16:15:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49102482,"identity":"09a7a618-84ca-460b-986d-1abeab8d2a3a","added_by":"auto","created_at":"2024-01-03 06:21:39","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":116702,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of lifetime alcohol consumption correlates and associated metabolic diseases and risk factors analyzed by bivariate regression.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3771284/v1/baae34a64b14fc015cadd45f.jpg"},{"id":61596248,"identity":"ede45171-973f-4089-9484-2a6fcf9c8fb1","added_by":"auto","created_at":"2024-08-01 17:25:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1112804,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3771284/v1/186c5860-1f46-43af-a66d-943af50916fb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Alcohol consumption among Iranian population: STEPS survey, 2021","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eGlobally, harmful use of alcohol is responsible for 3\u0026nbsp;million deaths every year which represents 5.3% of all deaths \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The recent Global Burden of Diseases (GBD) study identifies alcohol as the primary risk factor for the 25\u0026ndash;49 age group regarding attributable burden \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Between 2010 and 2019, there was an annualized increase of 0.5% in alcohol use, contributing to a significant rise in the percentage of attributable Disability-Adjusted Life Years (DALYs) \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Alcohol per capita consumption (APC), the total amount of pure alcohol consumed by individuals \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, has risen from 5.4 liters in 2005 to 6.2 liters in 2018 among individuals aged over 15 years worldwide \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Research indicates a link between alcohol consumption and various non-communicable diseases (NCDs), mental and behavioral disorders, and injuries, including road traffic incidents, drowning, poisoning and falls \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Additionally, the consumption of bootleg or adulterated alcohol can lead to methanol poisoning, causing hospitalizations and deaths \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The harmful use of alcohol also leads to significant social and economic losses to individuals and society \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn Iran, a Muslim-majority country in the Middle East, alcohol production, consumption, and trade are criminalized \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Also, there is a social stigma linked to alcohol consumption in this country \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. These factors contribute to lower APC and prevalence of alcohol use in Iran compared to majority non-Muslim countries \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. However, they have also delayed comprehensive scientific research and healthcare policy development \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Despite the alcohol ban, alcoholic beverages have the potential to be illicitly manufactured in residential settings and illegally transported into the country, subsequently being distributed through underground channels \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Consequently, there is no official data on the production or sales of alcoholic products \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, few studies have measured Iran's APC or alcohol consumption prevalence \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. However, the increasing trend of alcohol consumption \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, alongside its association with various NCDs and mental disorders, necessitates a current and detailed report to formulate appropriate population-wide policies and action plans. This study aims to determine the prevalence of alcohol consumption among Iran's adult population, classified by demographics and socio-economic status, and estimate the APC to assess the pattern of alcohol use in 2021. Understanding these patterns is crucial for health authorities to combat the harmful use of alcohol and its extensive negative impacts.\u003c/p\u003e"},{"header":"2. Materials and method","content":"\u003cp\u003eThe World Health Organization (WHO) initiated the STEPwise Approach to NCD Risk Factor Surveillance (STEPS) in 2000, offering a standardized method for global data collection, processing, and dissemination \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. STEPS is a large-scale population-based, sequential cross-sectional study that continuously monitors key risk factors for NCDs. In Iran, eight surveys have been conducted based on the WHO STEPS methodology \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The current study is part of the most recent STEPS, carried out in 2021 \u003csup\u003e25\u003c/sup\u003e. The data collection phase comprised three steps: first, data were collected using the STEPS questionnaire through participant interviews; second, physical examinations were conducted; and third, laboratory assessments were performed on adults over 25 \u003csup\u003e25\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study population\u003c/h2\u003e \u003cp\u003eThe latest data come from the eighth round of the STEPS survey. A total of 28,520 individuals from urban and rural areas across all 31 provinces of Iran were selected using a multistage clustered probability design to create a nationally representative sample. Of these, 27,874 chose to participate in the first step, 27,745 in the second, and 18,119 in the third. The primary reason for non-response was unwillingness to participate. All participants were at least 18 years old and residents of Iran at the time of data collection. After obtaining written informed consent, trained in-home interviewers collected a broad range of information on sociodemographic characteristics, household assets, healthcare utilization, health behaviors, history of metabolic risk factors, and anthropometric measures. Data collection began in January 2020 and was partially completed by February 2020 when it was suspended due to the COVID-19 outbreak in Iran. It resumed approximately a year later with COVID-19 safety measures in place, and the remaining data were collected between February and April 2021. The protocol was explained comprehensively and with further details elsewhere \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Alcohol consumption assessment\u003c/h2\u003e \u003cp\u003eFor the alcohol consumption assessment part of the STEPS study, a Persian-translated version of earlier STEPS questionnaires, modified for the Iranian cultural and religious context, was used \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Alcohol consumption prevalence, a key variable of this study, was assessed over three timespans: lifetime, past 12 months, and past 30 days. Binge drinking was also measured over the past 12 months and 30 days, using the Bettering the Evaluation and Care of Health (BEACH) definition of consuming six or more standard drinks on one occasion \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. In line with the STEPS protocol, we used a regular cup (approximately 250\u0026ndash;300 cc) as the standard measure for beer and wine, and a smaller cup (about 50 cc) for hard liquors such as vodka, whiskey, tequila, cognac, rum, and their domestic equivalents.\u003c/p\u003e \u003cp\u003eAPC, another main variable, is defined as the total amount of alcohol consumed in liters of pure alcohol by the population over 15 years old in a calendar year \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. As our study included individuals aged 18 and older, we reported the APC for the 18\u0026thinsp;+\u0026thinsp;age group. Several methods exist to calculate APC \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. The social stigma toward alcohol consumption in Muslim-majority countries and the low prevalence and frequency of alcohol use led to underestimation of methods such as yesterday and last week \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. As a result, the method that we employed in this study is the Quantity-Frequency (QF) method which is one of the preferred methods to calculate APC in Muslim-majority countries with very low drinking levels \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. QF is among the earliest methods to assess alcohol use and is most useful when information about occasional high and low drinking days is not required and time is limited \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. We employed the below formula of QF method for calculating APC:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$Alcohol per capita consumption=F\\times Q\\times \\alpha$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn this formula, F represents the frequency of alcohol consumption, which we asked questions about in the past 12 months during this study, Q is the amount of alcohol consumed in a typical day of drinking and α is a constant number which refers to the amount of pure alcohol per each alcoholic drink. We used the Iranian Ministry of Health\u0026rsquo;s routinely used definition of a standard drink, which is 13 g of pure alcohol \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. APC was calculated by multiplying the estimated number of drinking days in the past 12 months by the daily quantity of drinks and then, multiplying the result by 13 to calculate the total alcohol consumed annually in grams.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Definition of variables\u003c/h2\u003e \u003cp\u003eFor socioeconomic stratification in this survey, the Wealth Index (WI) was computed based on data regarding household assets obtained from questionnaires. This index was then divided into five levels, ranging from the least wealthy (first quintile) to the most wealthy (fifth quintile). Education levels were recorded in four distinct categories: none, 1\u0026ndash;6 years, 7\u0026ndash;11 years, and 12 or more years. The living environment of the participants was classified as either urban or rural. Ages of the participants were grouped into seven brackets: 18\u0026ndash;24, 25\u0026ndash;34, 35\u0026ndash;44, 45\u0026ndash;54, 55\u0026ndash;64, 65\u0026ndash;70, and above 70. BMI was calculated using the evaluated height and weight for each individual entered the second step of the study. Obesity was defined as a Body Mass Index (BMI) of more than 30 according to references \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe cardiometabolic conditions and other diseases assessed in this study were identified based on participants' self-reports of having the condition or taking medication for its treatment, as outlined in the questions of the STEPS questionnaire tool. History of heart attacks variable was investigated via related questions in the questionnaire asking whether the individual had a history of heart attacks in his/her lifetime or not. Physical injuries variable was assessed via the same method and considered positive if the individual reports history of physical injury(s) during the past 12 months prior to the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data analysis\u003c/h2\u003e \u003cp\u003eData cleaning adhered to WHO STEPS guidelines \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, and statistical analyses were performed with R software version 4.0.5 at a 0.05 significance level. Baseline characteristics were presented using means (standard deviation (SDs)) for continuous variables and numbers (percentages) for categorical variables. To investigate the association between sociodemographic characteristics and alcohol consumption and the association between alcohol consumption and the non-communicable diseases investigated in this study, we used multiple and univariate logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Initially, each variable was analyzed using a bivariate regression model. Subsequently, a multiple model was developed, incorporating multiple variables informed by the results of the bivariate analysis. Bivariate analyses were performed to estimate crude ORs, and all variables with p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.2 (including age, sex, wealth index, level of education and smoking, and conditions of diabetes, hypertension, hypercholesterolemia, history of heart attack(s), stroke, physical injuries, and obesity) entered the multiple model to calculate adjusted ORs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Ethical considerations\u003c/h2\u003e \u003cp\u003eAll eligible individuals were informed about the study's objectives and methods. Participation was voluntary, with written consent obtained from all participants. Ethical approval was granted by the ethics committee of Tehran University of Medical Sciences (IR.TUMS.NIHR.REC.1398.006). The funding source played no role in the study's design, data collection, analysis, interpretation, manuscript writing, or decision to submit the paper.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Overview\u003c/h2\u003e \u003cp\u003eThe study included 27,874 adults aged 18 and older (mean age (SD): 45.7 (0.1); 55.4% females). Among these participants, 43.6% had more than 12 years of education, and 75% were urban residents.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Alcohol consumption scale of Iran\u0026rsquo;s population\u003c/h2\u003e \u003cp\u003eThe mean lifetime alcohol consumption prevalence was 6.9% (95% CI: 6.5\u0026ndash;7.2) for the entire population, 1.4% (95% CI: 1.1\u0026ndash;1.6) for females, and 13.7% (95% CI: 13-14.4) for males. Using the Quantity-Frequency (QF) method, the study calculated the Alcohol Per Capita Consumption (APC) as 0.120 liters of pure alcohol (95% CI: 0.081\u0026ndash;0.159). The 12-month prevalence of alcohol consumption was 3.8% (95% CI: 3.6\u0026ndash;4.1), with 0.9% for females (95% CI: 0.7-1) and 7.5% for males (95% CI: 7-8.1). In the past 30 days, 2.1% of participants (95% CI: 1.9\u0026ndash;2.2) reported alcohol consumption, with 0.5% females (95% CI: 0.3\u0026ndash;0.6) and 4% males (95% CI: 3.6\u0026ndash;4.4). The overall prevalence of binge drinking in the past 12 months was 1.7% (95% CI: 1.5\u0026ndash;1.8) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Males were nearly four times more likely to consume alcohol than females (OR 3.8, 95% CI: 3-4.9) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The highest alcohol consumption rates, including binge drinking, were observed in the 18\u0026ndash;24 and 25\u0026ndash;34 age groups, decreasing with age. In all age groups, males had higher prevalence rates than females (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAlcohol consumption in Iran status and socio-demographic characteristics, based on Iran STEPS 2021 Survey.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e \u003cp\u003eAlcohol Drinking Status\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLifetime alcohol drinking (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ePast 12 months alcohol drinking (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePast 30 days alcohol drinking (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePast 12 months binge drinking (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePast 30 days binge drinking (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCategories\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e177 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e108 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1593 (13.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e869 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e460 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e372 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e213 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;24 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e219 (9.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e164 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e43 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e501 (10.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e326 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e176 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e148 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e89 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;44 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e440 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e253 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e135 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e59 (1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u0026ndash;54 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e256 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e116 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u0026ndash;64 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e196 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;70 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e112 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e46 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eResidential status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e456 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e247 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e134 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e92 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e55 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1314 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e730 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e381 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e307 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e173 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eWealth index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e281 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecond quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e320 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e165 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThird quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e359 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e195 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e107 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45 (1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForth quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e360 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e213 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e107 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45 (1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e388 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e236 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e131 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eLifetime smoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1122 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e615 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e312 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e235 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e131 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e647 (27.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e361 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e203 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e164 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e97 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1770 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e977 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e515 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e399 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e228 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssessment of lifetime alcohol consumption associated factors using multiple logistic regression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eLifetime alcohol consumption\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCategory\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eOR (95% CI) Model a\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eOR (95% CI) Model b\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.56(9.74,13.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.84(2.99,4.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eResidential status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06(0.94,1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eWealth index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eref\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecond quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1(0.91,1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.07(0.85,1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThird quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.34(1.12,1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.26(1.01,1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForth quintile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.41(1.19,1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.34(1.07,1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.47(1.23,1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.49(1.18,1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 7 years of education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.08(2.29,4.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.58(1.12,2.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;12 years of education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.33(4.76,8.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.23(1.58,3.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore than 12 years of education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.38(3.32,5.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.67(1.18,2.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eLifetime smoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.65(6.80,8.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.17(3.58,4.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Crude odds ratio\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Adjusted odds ratio (all variables with p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.2 entered the model including age, sex, wealth index, level of education and smoking)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Associates of alcohol consumption\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the crude and adjusted odds ratios for sex-categorized variables. Generally, the adjusted odds for lifetime alcohol consumption were significantly higher among males (OR\u0026thinsp;=\u0026thinsp;3.84, 95% CI: 2.99\u0026ndash;4.94), smokers (OR\u0026thinsp;=\u0026thinsp;4.17, 95% CI: 3.58\u0026ndash;4.85), the oldest compared to the youngest (OR\u0026thinsp;=\u0026thinsp;0.98, 95% CI: 0.97\u0026ndash;0.98), and the wealthiest compared to the poorest (OR\u0026thinsp;=\u0026thinsp;1.49, 95% CI: 1.18\u0026ndash;1.87) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Individuals with 7\u0026ndash;12 years of education had the highest odds of alcohol consumption (OR\u0026thinsp;=\u0026thinsp;2.23, 95% CI: 1.58\u0026ndash;3.15).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMultivariable logistic regression revealed that individuals reporting lifetime alcohol consumption had significantly greater odds of obesity (OR\u0026thinsp;=\u0026thinsp;1.23, 95% CI: 0.97\u0026ndash;1.56), a history of heart attacks (OR\u0026thinsp;=\u0026thinsp;2.04, 95% CI: 1.44\u0026ndash;2.89), and physical injuries (OR\u0026thinsp;=\u0026thinsp;1.88, 95% CI: 1.34\u0026ndash;2.64). The study also found positive associations between lifetime alcohol consumption and certain metabolic diseases and risk factors, but negative associations with stroke and diabetes. However, these associations were not significant (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssessment of metabolic diseases and risk factors associated with alcohol consumption using multiple logistic regression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eLife time alcohol consumption\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR (95% CI) Model a\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95% CI) Model b\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57(0.41,0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80(0.57,1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.60(0.50,0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.06(0.83,1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHypercholesterolemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.58(0.43,0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.13(0.83,1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHistory of heart attack(s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81(0.59,1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.04(1.44,2.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.31(0.10,0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79(0.38,1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85(0.42,1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLung diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.09(0.78,1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhysical injuries\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.72(2.20,3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.88(1.34,2.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68(0.57,0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.23(0.97,1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Crude odds ratio\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Adjusted odds ratio (all variables with p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.2 entered the model including age, sex, wealth index, level of education and smoking, and conditions of diabetes, hypertension, hypercholesterolemia, history of heart attack(s), stroke, physical injuries, and obesity).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study evaluated alcohol consumption prevalence in Iranians aged 18 and older. The findings indicate that approximately 3.9\u0026nbsp;million and 2.2\u0026nbsp;million individuals over 18 in Iran have consumed alcohol at least once in their lifetime and in the past 12 months, respectively.\u003c/p\u003e \u003cp\u003eThe lifetime and 12-month prevalence rates of alcohol consumption in our study are lower than the global average but higher than the figures estimated by the WHO for EMRO countries \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. It's important to note that the WHO's estimates refer to populations aged over 15 years. Additionally, our study showed a lower lifetime prevalence of alcohol consumption than that reported in four Iranian provinces in 2015 \u003csup\u003e17\u003c/sup\u003e. Part of this difference can be attributed to the setting of the studies. The 2015 study was a street-based study and the participants faced less stigma in disclosing facts about their alcohol consumption. Essentially the prohibition of alcohol consumption in Iran and other Muslim-majority countries usually leads to under-reporting of alcohol use \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Our study likely reflects this trend, suggesting that the actual prevalence may be higher than reported. Compared to other countries, the prevalence of binge drinking in the last month and last 12 months was notably lower in our study \u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA higher prevalence of alcohol consumption was observed in male participants compared to females, aligning with both national \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, and international studies \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. This gender disparity in alcohol consumption could be attributed to cultural and religious norms, as women typically adhere more closely to cultural and religious principles that discourage alcohol use \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. The rate of alcohol consumption in males over the past 12 months was 8.8 times higher than in females, mirroring the gender gap reported in Iran's National Mental Health Survey \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Interestingly, alcohol consumption patterns in North America and Europe have shifted in recent decades, with female patterns increasingly resembling those of males, particularly concerning harmful use \u003csup\u003e\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The exact extent of this change remains unclear \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Consistent with other research, our study found that binge drinking was more prevalent among males \u003csup\u003e\u003cspan additionalcitationids=\"CR45 CR46\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Bing drinking has been traditionally more prevalent among the males, though the gap is narrowing due to rising alcohol consumption levels among females \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe findings of our study align closely with those from a recent meta-analysis on alcohol consumption in Iran \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. This analysis reported a combined prevalence of lifetime alcohol consumption at 13.0% (95% CI: 11.0% \u0026minus;\u0026thinsp;16.0%). It also noted a pooled prevalence of 12.0% (95% CI: 7.0\u0026ndash;18.0%) for alcohol consumption in the past 12 months within the general population, and a slightly higher prevalence of 15.0% (95% CI: 9.0\u0026ndash;22.0%) among youth. Additionally, the study highlighted notable regional variations in alcohol consumption rates, which ranged broadly from as low as 0.03% to as high as 68.0%. Prevalence rates were observed to vary significantly by gender, with figures for males ranging from 0.3\u0026ndash;66.6%, and for females from 0.2\u0026ndash;21.0% \u003csup\u003e12\u003c/sup\u003e. This study indicates that the highest prevalence of alcohol consumption in the past month, past 12 months, and over a lifetime occurred in the 18\u0026ndash;34 age group for both sexes. This trend is likely influenced by various developmental and cultural factors \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Young adults are prone to consuming larger quantities of alcohol, leading to more adverse effects, and individuals between 20 to 34 years old experience the highest mortality rates related to alcohol consumption \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe results also demonstrated that alcohol consumption prevalence is higher among cigarette smokers across all age groups. Correspondingly, higher instances of binge drinking were noted among smokers, aligning with research showing a link between tobacco and alcohol use \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. The relationship between alcohol and tobacco use is complex and influenced by both social and pharmacological factors, especially as tobacco use prevalence is highest among young adults engaged in binge drinking \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMoreover, a greater prevalence of alcohol consumption was observed among urban residents and individuals with higher education levels, highlighting the impact of social factors, living conditions, and education on alcohol consumption in Iran. Studies within Iran have shown similar patterns, with higher alcohol consumption among high school and university students \u003csup\u003e\u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. These findings are consistent with results from other countries \u003csup\u003e\u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Research on the geographical relationship with alcohol consumption presents mixed results; some studies report higher consumption in urban areas \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e, while others find increased consumption in rural settings \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Therefore, understanding the relationship between living status and alcohol consumption requires considering a range of demographic, social, and cultural factors \u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn our study, individuals with a higher wealth index exhibited increased alcohol consumption, with the wealthiest group consuming 1.5 times more than those in the lowest wealth index category. Numerous studies have established a direct association between socio-economic status and alcohol consumption, yet an inverse relationship exists between harmful drinking patterns, such as binge drinking, and socio-economic status \u003csup\u003e\u003cspan additionalcitationids=\"CR65 CR66 CR67 CR68\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eResearch indicates that in societies where alcohol consumption is stigmatized due to legal and religious prohibitions, as well as criminalization, there is a tendency for alcohol users to underreport their usage. This underreporting is particularly pronounced when questions pertain to recent consumption (past day or week), while queries about the past month or year tend to yield more accurate results. In contrast, in countries without such prohibitions, questioning about last day or week alcohol consumption tends to be more reliable, effectively addressing recall bias and serving as a better tool for calculating APC \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. Given the legal and social stigma associated with alcohol in Iran, our survey considered the most recent recall period as the last month. The Quantity-Frequency (QF) method was used for annual APC calculation, although it entails more recall bias than the \"last week\" method \u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. The survey results showed that Iran's APC (0.120L) is lower than the global (6.4L) and regional (0.6L) averages \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. It's important to note that while these international figures typically pertain to individuals over 15 years old, our study focused on those over 18, which might contribute to some of the observed differences. Compared to the QF calculation by Amin-Esmaeili et al. in 2011, the APC reported in this study showed a 50% increase \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe results from the multiple logistic regression model in our study indicated a significant positive correlation between alcohol consumption and various non-communicable diseases and metabolic syndromes, including hypertension, hypercholesterolemia, heart attacks, obesity, and physical injuries. Interestingly, the data suggested a decrease in the risk of diabetes mellitus and stroke associated with alcohol consumption. Particularly noteworthy is the elevated and significant risk linked with heart attacks, obesity, and physical injuries. Various studies have explored the relationship between alcohol consumption and non-communicable diseases. Identified patterns include the J-shaped curve, illustrating a dose-response relationship between alcohol intake and the odds of metabolic syndrome \u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, and the U-shaped pattern, where heavy drinkers face a significantly higher risk, unlike low and moderate consumers \u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. An inverse relationship has also been reported, indicating that low to moderate alcohol use could correlate with a lower incidence of metabolic syndrome and positively affect waist circumference and fasting insulin levels \u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e. While some studies suggest a linear relationship between alcohol consumption and metabolic syndrome \u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e,\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e, others find no significant correlation \u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e,\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e. The growing body of research underscoring the link between lifetime alcohol consumption and its detrimental effects, especially the risk of metabolic syndrome, highlights the urgent need for preventive measures against alcohol consumption \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. This evidence is vital for shaping public health policies and strategies, particularly those addressing any level of alcohol consumption due to its potential adverse health impacts \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e Despite the challenges posed by the COVID-19 pandemic, this study's data collection was conducted face-to-face, adhering to health guidelines and social distancing. This national study encompasses a large sample size from across the country. A key feature of this study is its alignment with the WHO's STEPS methodology, enabling comparisons with global studies. In response to the stigma surrounding alcohol consumption in Iran, interviewers were specifically trained to gather data discreetly and privately. Another strength of this study lies in its assessment of comorbidities associated with alcohol consumption. Conditions like hypercholesterolemia and diabetes were evaluated using both laboratory data and medical history, and participants' blood pressure was measured during their assessment.\u003c/p\u003e \u003cp\u003eFuture studies could focus on longitudinal analyses to better understand the causal relationships between alcohol consumption and non-communicable diseases, particularly in the context of cultural and legal restrictions. Research exploring the impact of COVID-19 on alcohol consumption patterns would also be valuable. Clinically, there is a need for targeted interventions and public health strategies that address the unique challenges of alcohol consumption in Iran, considering the social stigma and legal implications. This includes developing culturally sensitive prevention programs and educational campaigns, especially targeting high-risk groups such as young adults and urban residents. Further, integrating alcohol use assessment into routine clinical practice could enhance early detection and management of alcohol-related health issues. Finally, considering the low reporting rates in certain demographics, innovative data collection methods that ensure confidentiality and reduce social desirability bias are essential for more accurate prevalence estimates and effective policy-making.\u003c/p\u003e \u003cp\u003eThis study is subject to some limitations. Firstly, its cross-sectional design poses challenges in identifying potential reverse associations between alcohol consumption and assessed outcomes, as well as in establishing causality. As a household survey, it does not include individuals living in residential facilities, institutions with restricted access, or those who are homeless, where alcohol consumption prevalence might differ. Additionally, the reliance on self-reporting could lead to underreporting, particularly since alcohol consumption is illegal and socially stigmatized in Iran. This study focuses on individuals over 18 years old, which limits the comparability of the Alcohol Per Capita Consumption (APC) results with other national and international studies that often include those aged 15 and older. Furthermore, restricted access to recent alcohol consumption data (last week) made it impossible to employ the \"last week\" method alongside the Quantity-Frequency (QF) method. Consequently, calculating APC using a combination method was not feasible \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. A key limitation of our study is the low prevalence of alcohol consumption in the Iranian population, potentially due to under-reporting or genuinely lower consumption levels. This led to smaller sample sizes for recent consumption periods (past 12 months and 30 days), limiting the power and reliability of our statistical analyses. The impact of COVID-19 on changes in alcohol consumption levels could be significant during the pandemic based on literature, but measuring this impact was beyond the scope of our study and it was another limitation of the current research.\u003c/p\u003e \u003cp\u003eIn this population-based study, we estimated the prevalence of alcohol consumption over multiple timespans, finding the highest rates among males and younger age groups. This underscores the need for targeted prevention strategies within these demographics in public health policies. The potential hazardous effects of even lifetime alcohol consumption call for appropriate preventive measures to address this public health concern. Moreover, focusing on harm reduction interventions among those with lower socioeconomic status is crucial to mitigate the adverse impacts of harmful alcohol use. Our findings also highlight a positive correlation between alcohol consumption and metabolic syndrome. To reduce the possible negative effects of alcohol on individuals' metabolic profiles, implementing preventive strategies against alcohol consumption, particularly its harmful patterns, is a critical priority.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors extend their heartfelt gratitude to the Deputy of Health and the Deputy of Research and Technology at the Ministry of Health and Medical Education, the National Institute for Health Research, the World Health Organization, and numerous scholars and experts in related fields. We also sincerely thank all participants and the scientific and executive partners from the medical universities who contributed to this project. Your collaboration and support have been invaluable to the success of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: F.F., N.R., A.H.; Data Curation: M.N., E.G., M.Y., N.A.; Formal Analysis: M.N., E.G., M.Y., N.A.; Investigation: F.F. and all of co-authors; Methodology: F.F., A.H., E.G., N.R.; Project Administration: A.H., R.H., S.A., MM.R., E.F., Y.F., S.R., M.A., N.F.; Supervision: R.H., Y.F., S.D., A.K., E.F., A.M.; Validation: F.F., A.H., S.A., N.R.; Writing\u0026mdash;Original Draft Preparation: A.H.; Writing\u0026mdash;Review and Editing: S.A., MM.R., K.R., A.M., H.J.; Visualization: M.N., N.A.; All authors reviewed the manuscript, critically commented on the draft and provided their approval for the submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization (WHO) \u003cem\u003eAlcohol\u003c/em\u003e, \u0026lt;https://www.who.int/news-room/fact-sheets/detail/alcohol\u0026gt; (2018).\u003c/li\u003e\n\u003cli\u003eMurray, C. 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The Western New York Health Study (WNYHS). \u003cem\u003eEur J Epidemiol\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 129-138, doi:10.1007/s10654-005-5457-y (2006).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3771284/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3771284/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlcohol production and consumption have been prohibited in Iran for over four decades, leading to a typical underestimation of its consumption. This study aimed to assess the prevalence of alcohol consumption, its associated factors, and estimate per capita alcohol consumption among Iran's adult population.\u003c/p\u003e \u003cp\u003eIn this population-based survey, 27,874 adults from across Iran were selected using systematic proportional to size cluster sampling. Alcohol consumption was evaluated through a modified Persian version of the STEPS questionnaires from previous studies, applied over different timespans. Per capita consumption was calculated using the quantity-frequency method, expressed in liters of pure alcohol. Adjusted odds ratios were reported for associates of alcohol consumption concerning metabolic risk factors, sociodemographic elements, and lifestyle variables.\u003c/p\u003e \u003cp\u003eThe prevalence of lifetime alcohol consumption was 6.9% (95% CI: 6.5\u0026ndash;7.2) in the adult population, with a notable sex difference (males: 13.7% [95% CI: 13-14.4]; females: 1.4% [95% CI: 1.1\u0026ndash;1.6]). The 12-month prevalence was 3.8% (95% CI: 3.6\u0026ndash;4.1). For individuals aged 18 and older, the per capita alcohol consumption in Iran was 0.12 liters. Factors such as being a lifetime smoker, younger, wealthier, and having 7\u0026ndash;12 years of education were significantly linked to higher alcohol consumption. Significant associations were also observed between alcohol consumption and obesity, history of heart attacks, and physical injuries.\u003c/p\u003e \u003cp\u003eThe study revealed a complex relationship between alcohol consumption, behavioral risk factors, and metabolic profiles. Consequently, immediate preventive measures tailored to each factor's association with alcohol use are recommended.\u003c/p\u003e","manuscriptTitle":"Alcohol consumption among Iranian population: STEPS survey, 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-03 06:21:35","doi":"10.21203/rs.3.rs-3771284/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-03-22T10:09:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-18T22:21:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9ea540cb-4e96-4b6d-908a-242ff3e712f0","date":"2024-02-24T14:45:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-01-17T19:26:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"14835b82-b5c3-4d43-9fad-b9c563ea5a67","date":"2024-01-07T11:13:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-05T10:26:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-12-30T17:31:31+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-12-30T17:24:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-12-30T17:19:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2023-12-18T10:05:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dff9d683-2373-4b26-ae7f-350ec0d39ee8","owner":[],"postedDate":"January 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":27879119,"name":"Health sciences/Medical research/Epidemiology"},{"id":27879120,"name":"Health sciences/Risk factors"},{"id":27879121,"name":"Health sciences/Health care/Public health"}],"tags":[],"updatedAt":"2024-08-01T17:07:12+00:00","versionOfRecord":{"articleIdentity":"rs-3771284","link":"https://doi.org/10.1038/s41598-024-66257-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-07-22 16:15:53","publishedOnDateReadable":"July 22nd, 2024"},"versionCreatedAt":"2024-01-03 06:21:35","video":"","vorDoi":"10.1038/s41598-024-66257-w","vorDoiUrl":"https://doi.org/10.1038/s41598-024-66257-w","workflowStages":[]},"version":"v1","identity":"rs-3771284","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3771284","identity":"rs-3771284","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}