Skip to main content

Socioeconomic and environmental factors associated with waterpipe tobacco smoking among Iranian adults: a PERSIAN cohort-based cross-sectional study



Waterpipe tobacco smoking (WTS) is associated with several deleterious health outcomes. We sought to estimate the prevalence of WTS and explore socioeconomic inequalities associated with this culturally-rooted tobacco smoking practice among Iranian adults.


A cross-sectional analysis was conducted among 20,460 adults (ages 18 and older) enrolled in the PERSIAN cohort study during 2020. Data were collected on socioeconomic status (SES), lifestyle, alcohol consumption, cigarette smoking, and several risk factors related to non-communicable diseases. The concentration curve and relative concentration index (RCI) were administered to assess and quantify the SES-based inequality in WTS.


Overall age-adjusted prevalence of past-month WTS was 5.1% (95%CI:4.6–5.8), with about 1% for women and 10.6 for men. Age-adjusted prevalence of WTS was higher among younger adults, men, cigarette smokers, obese adults, and those with higher SES. The RCI estimation showed that WTS is more popular among adults with high income and education. WTS was higher among younger adults, cigarette smokers, obese adults, and those with higher SES.


There is a clear socioeconomic inequality in WTS, with a higher prevalence among adults with higher income and education. The findings suggest the need for targeted interventions to address this inequality and reduce the prevalence of WTS among high-income communities.

Peer Review reports


Tobacco smoking causes more than 8 million worldwide deaths annually [1]. One contributor to this burden is waterpipe tobacco smoking (WTS), also known as nargile, shisha, hookah, or galyan. WTS is a centuries-old smoking practice rooted in Eastern Mediterranean culture. It gained popularity worldwide since the 1990s after the introduction of flavoured tobacco known as Muʽassel (Arabic: معسل, meaning 'honeyed') (Massal) [2,3,4]. A typical WTS session lasts about an hour, accompanied by friends in a café or lounge [5,6,7], and is now the second most common form of tobacco consumption in Iran and neighbouring Arab countries [6, 8]. During a WTS session (as illustrated in Fig. 1), charcoal-heated flavoured or non-flavoured tobacco passes through a water-filled glass base, which cools the smoke before delivering nicotine and other toxicants into the user's lungs [9,10,11,12]. The type of tobacco (flavoured or non-flavoured), configuration, size, and appearance of the device varies from region to region [13].

Fig. 1
figure 1

Schematic image of typical waterpipe tobacco smoking device, retrieved from Alqahtani et al., [14]

The combustion produced during WTS session puts the smokers at detrimental health risks such as lung and cardiovascular diseases and many other dire health consequences [15, 16]. Despite the well-documented harmful effects of WTS on human health, many smokers believe that WTS is not as harmful and addictive as cigarettes due to water filtration, enticing flavors, and intermittent use, which are the main reason for popularity of WTS worldwide [17, 18].

Iran is one of the countries where WTS has a historical origin, and in recent years, the pattern of WTS has changed, being a more popular method of tobacco use among young adults, with increasing trends in women [6, 19,20,21]. The prevalence of current (past 30 days) WTS among Iranian adults ranges from 17 to 28% in different regions of Iran. Waterpipe use prevalence in men is significantly more than women's (24.2% vs. 11.3%) [6]. Ineffective enforcement of regulations regarding WTS and inadequate supervision of tobacco production(import and export), as well as scarce control of WTS in hookah bars contribute significantly to the growing popularity of WTS in Iran [6]. Monitoring tobacco use at population level-especially in low- and middle-income nations like Iran is one of the main goals for the World Health Organization Framework on Tobacco Convention Treaty (WHO FTCT) [22, 23]. Therefore, understanding the current condition and main factors that contribute to the popularity of WTS in developing countries is one of the critical factors to decrease the prevalence of WTS and eliminate waterpipe-induced addiction and its related health risks [24].

To better monitor the trend of WTS in Iran and help design targeted prevention and control programs, in this study we aim to evaluate the prevalence of WTS and related socio-economic and environmental factors in a large sample of Iranian adults participated at baseline wave of Prospective Epidemiological Research Studies in IrAN (PERSIAN) cohort study.


Study setting and sample

The research for this cross-sectional study was carried out in Ardabil, a city located in the northwest of Iran that has a population of about 610,000 individuals [25]. The study draws on data collected from the PERSIAN cohort study, which was established to modify healthcare policies related to non-communicable diseases (NCDs) and involved a variety of sites across Iran. Among these sites, the Ardabil NCD (ArNCD) cohort study was one of 18 geographically distinct locations included in the PERSIAN cohort study. Further information on the sampling design and methodology can be found elsewhere [26].

The research involved individuals mostly belonging to Turk ethnicities. The PERSIAN cohort study's extensive protocol aimed to recruit participants for this study, resulting in 20,525 men and women aged 18 years and above residing in Ardabil, who participated in the baseline survey between May 2017 and February 2020. As defined in study protocol [26, 27], the alluded age range was chosen for three reasons to be eligible in participating PERSIAN cohort: i) individuals in this age group are more likely to have well-established behaviors and lifestyles, 2) they are active and energetic enough to participate in a study; and iii) they will, within a reasonable amount of time, incur the PERSIAN study’s primary outcomes of interest (ie. a number of deaths, by cause and incidence of major NCDs) (see Poustchi et al. 2017 [26] for more details). The present study only included individuals who were Iranian citizens and residing in Ardabil. Those with medical conditions such as deafness, blindness, palsy, mental disorders, intellectual disability, or acute psychiatric illnesses were excluded from the PERSIAN cohort. Trained interviewers conducted the cohort questionnaire. After accounting for missing data, the final sample size for this study was 20,460 individuals. Ethics approval for the current analysis was obtained from the ethics committees of the Ministry of Health and Medical Education in Iran, as well as from the medical universities of each study site, including Ardabil University of Medical Science.



The outcome variable of the study was defined as the current use of waterpipe smoking (WTS) in the past 30 days prior to the interview time [6]. Participants who reported using waterpipes in the past 30 days were considered current waterpipe smokers. The outcome variable was dichotomous, meaning it only had two categories: current and non-current waterpipe smokers. We did not include ex-smokers or never-smokers in our outcome variable definition..


Selected covariates included age (categorized from under 35 (18–35 years) to upper 65), sex (man/ woman), marital status (single/ married/divorced/ widow), education status (no formal education, primary, intermediate, secondary, or academic degree), BMI (underweight/ normal/ overweight/ obesity) as previously defined [28], cigarette smoking (Current smoker (those who smoked one or more cigarettes a day for at least a month or those who reported having quit smoking for less than one month)/ nonsmoker) and chronic underlying disease (hypertension and diabetes (yes/no). Data about the non-communicable diseases (Diabetes and Hypertension) was extracted based on the individuals’ self-declaration, clinical tests results, and requests to see their clinical records.

Wealth index

Wealth index (WI) was calculated as socioeconomic status (SES) of the participant based on their self-reported wealth, and it was divided into five quintiles (from 1st quintile as poorest to 5th quintile as richest groups). The WI is a composite index composed of key asset ownership variables; it is used as a proxy indicator of household household's cumulative living standard. To construct the wealth index, we need all the indicators that allow us to understand the level of wealth of the household. To create the WI, the Principal Component Analysis (PCA) was used. Filmer and Pritchett [29] popularized PCA for estimating wealth levels using asset indicators to replace income or consumption data. Following Filmer and Pritchett, many other studies, especially in economics and public policy, have implemented and recommended the use of PCA for estimating wealth effects [30, 31]. A PCA is run with all the selected variables. For constructing the wealth index, the principal component (first factor) presents the household’s wealth [32, 33]. The PCA is a multivariate statistical technique used to reduce the number of variables in a data set into a smaller number of ‘dimensions’. In mathematical terms, PCA creates uncorrelated indices or components from an initial set of n correlated variables, where each component is a linear weighted combination of the initial variables. For example, from a set of variables X1 through to Xn,

$${PC}_{1}={a}_{11}{X}_{1}+ {a}_{12}{X}_{2}+\dots +{a}_{1n}{X}_{n}$$
$${PC}_{m}={a}_{m1}{X}_{1}+ {a}_{m2}{X}_{2}+\dots +{a}_{mn}{X}_{n}$$

where amn represents the weight for the mi principal component and the ni variable [33].

To calculate the wealth index by using PCA in this study, assets (having freezer, washing machine, dishwasher, laptop or PC, and etc.) homeownership, number of books read per year, home area, number of trips abroad, number of domestic trip, having a car and its price was considered. All the yes/no variables recoded in binary variables (0 = no vs 1 = yes). The variables with more than one category recoded in improved ‘1’ or not improved ‘0’ (when possible). Recode in binary categories that clearly distinguish ‘wealthier’ from ‘poorer’. We include in the PCA all the variables (assets, housing etc.) that we think will be appropriate to explain the household's wealth.

Statistical analysis

Data were analyzed using Stata software, version 14.0.0 (Stata Corp, College Station, TX, USA). The results are presented as non-waterpipe smokers and current waterpipe smokers for the purpose of this analysis, separately. The categorical variables with corresponding 95% confidence intervals (95%CI) are presented as proportions. For the numerical variables, we calculated the means with the standard deviation (SD) and median with interquartile ranges. In order to achieve the crude and adjusted prevalence and their respective 95% CI, Poisson regression was used. Univariate and multivariable logistic regressions were fitted to our data accounting for demographic variables and chronic disease status. Crude and adjusted Odds Ratio (OR) and corresponding 95% CI were reported.

Relative Concentration Index (RCI) and Concentration Curve (CC) [34] examined SES differences in WTS among participants. The RCI was employed for quantifying and decomposing socioeconomic inequality in WTS among Ardabil adults. The concentration curve was used to calculate RCI, which diagrams the cumulative percentage of SES-ranked participants on the x-axis and the cumulative percentage of a health interest variable (i.e., WTS) on the y-axis. The RCI is equivalent to twice the area between the perfect equality line (45-degree line) and the concentration curve [35]. RCI values ranges from − 1 to + 1; with positive when the concentration curve lies below the line of perfect equality, and negative when this curve lies below the line. The RCI's positive (and negative) values indicate that the WTS concentrated more among the poorest (richest) [34]. The RCI was separated by \(\frac{1}{1-\mu }\) to normalization following Wagstaff [36]. For this calculation, μ is assumed to be the measure of WTS. The decomposition process was used to classify the key determinants of the reported inequities of WTS [37]. There is a relationship regarding the WTS and other factors, \({x}_{k}\) [38].

$$y=\alpha +\sum_{k}{\beta }_{k}{x}_{k}+\varepsilon$$

where \({x}_{k}\) describes the explanatory variables alluded to in the previous portion. The RCI for WTS has been decomposed [39]:

$$RC=\sum_{k}\left(\frac{{\beta }_{k}{\overline{x} }_{k}}{\mu }\right){RC}_{k}+\frac{{AC}_{\varepsilon }}{\mu }$$

where \(RC\) is the relative concentration index for WTS, \({\overline{x} }_{k}\) the mean of \({x}_{k}\) determinants, \({C}_{k}\) are the \(RC\) for explanatory variables, and \({x}_{k}\left(\frac{{\beta }_{k}{\overline{x} }_{k}}{\mu }\right){RC}_{k}\) is the elasticity of WTS in relation to the explanatory variable \({x}_{k}\). \(\sum_{k}\left(\frac{{\beta }_{k}{\overline{x} }_{k}}{\mu }\right){RC}_{k}\) presents the contribution of the explanatory factor \({x}_{k}\) to the\(RC\). The last term,\(\frac{{AC}_{\varepsilon }}{\mu }\), is the residual component.


Out of 20,460 participants, 45.8% were men, mostly 46–55 years (35.1%). The mean age of participants was 49.0 (95% CI: 48.92 to 49.2) years of the total participants, 16.1% were cigarette smokers, more than 42% were obese, and 20.8% and 11.7% had hypertension and diabetes, respectively.

The overall prevalence of WTS was 5.14% (95% CI: 4.85 to 5.45), with an overall age-adjusted prevalence of 5.12% (95% CI: 4.63 to 5.79). The prevalence among women was 0.72% (95% CI: 0.57 to 0.88), while among men, it was 10.64% (95% CI: 10.1 to 11.2). The prevalence of WTS was higher among adults who were married (5.5%), had primary school level education (5.69%), smokers (13.95%), had normal BMI(5.82%), and richest group (8.87%) (Table 1).

Table 1 Baseline characteristics and prevalence of WTS in ArNCD cohort study (n = 20,460)

As presented in Table 2, WTS prevalence decreased among older adults compared to younger adults. Men were more likely to be current waterpipe smokers compared to women (12.9, 95% Ci:10.10–16.49). Adults with primary education were 1.3-fold more likely to be waterpipe smokers than their no formal education counterparts. However, with the increase in the level of education, the relationship between education level and WTS yielded null results. Cigarette smokers were 74% more likely to be waterpipe smokers than those who were not cigarette smokers. The richest people were about 210% more likely to be waterpipe smokers than the poorest people.

Table 2 Association between explanatory variables and the prevalence of WTS (logistic regression model)

Table 3 illustrates the estimated concentration index (CI), where CI was 0.25 (95% CI: 0.23 to 0.27) for all participants. A positive CI value means WTS is at a higher rate among the richest group (Fig. 2). There was a positive value for CI for men (0.13;95% CI: 0.111 to 0.149) and women (0.163;95% CI: 0.102 to 0.224), in terms of WTS inequality, in both cases gender WTS were in favor of richest group. In addition, estimated inequality for WTS among education level was in favor of the richest group, with positive CI in all education levels. It was 0.150 for no formal education and 0.081 for the population with an academic degree. Figures 3 and 4 display the concentration curve (CC) for inequality in WTS among participants based on gender and educational level, respectively.

Table 3 Concentration index for WTS based on socioeconomic status, education level, and sex
Fig. 2
figure 2

Concentration curve (CC) prevalence of WTS among adults in ArNCD cohort, where the prevalence of WTS is pro-rich and unequally distributed. The CC of WTS is positive and pro-rich, which indicates the significant inequality in WTS is towards the rich group in the population

Fig. 3
figure 3

Concentration curve (CC) prevalence of WTS among adults in ArNCD cohort, separately for men and women. Among men, CC of WTS was positive and significantly pro-rich, but among women. No difference was observed between rich and poor among women in terms of WTS

Fig. 4
figure 4

Concentration curve (CC) prevalence of WTS among adults in ArNCD cohort stratified by education level. Distribution of WTS did not differ significantly between rich and poor groups among people with no education, primary and academic education level. There was however significant pro-rich inequality in WTS among those with intermediate and secondary level education


This large sample cross-sectional study from a developing country highlights a comprehensive picture of the WTS in the within the context of socioeconomic inequality, which is not fully addressed in previous studies. Socioeconomic disparities in WTS were found to be more pronounced among affluent adults with higher educational attainment compared to those who were poor and had no formal education. The overall age-adjusted prevalence of WTS was 5.12% and it was 12 times more common among men than women. The prevalence of current WTS among the study participants was lower than most studies in Iran (8.6%-43.8%), which is likely related to the target population since in most studies, young people over 18 years old were considered [8, 19, 40], but in our study, about adults over 35 years old were included in the study because of their SES stability. However, the influence of SES on smoking patterns among this age group and the impact of SES instability remains unclear [20, 41], despite several studies indicating a higher prevalence of WTS among individuals aged 18–24 years with university education. Therefore, understanding this gap in older adults can add necessary information to growing literature and benefit targeted WTS intervention cessation programs.

The most important finding of this study is that inequality in WTS that was more pronounced for pro-rich in Iran, where it is in contrast to cigarettes smoking that is more popular among the poorest group than the richest, as observed in the same cohort earlier [42]. Previous studies, using the same methodology, found inequality in expenditure on tobacco, primarily cigarettes (as a share of household budget) disproportionality concentrated among poorer households in Iran [43]. This discrepancy highlights the popularity of cigarettes among people with lower SES, which could be different from WTS that is historically popular among people with higher SES in Middle Eastern culture [44]. Although about a decade ago, an Iranian study showed a lower prevalence of WTS in the high SES group than low SES [20], it is crucial to monitor tobacco use prevalence with a large sample to develop effective measures to limit its popularity [45]. A few studies in Iran are not in line with our results, where Ghelichkhani et al. found that the prevalence of WTS was lower in the group with high SES than in the group with low SES, and the gap was significant between the two mentioned SES groups [46]. One possible reason for the difference between the results of the present study and Ghelichkhani et al. is that our study focused on Iranian adults aged over 35 years who had achieved relative SES stability. In contrast, Ghelichkhani et al. studied individuals aged 7 to 70 years, which may have diluted the impact of SES status on WTS. Relatedly, the preparation of WTS or gathering in groups of friends at hookah café requires time and may cost more for people from a low-income neighborhood, contrary to cigarettes that are more easily accessible and cheaper for this low SES group [47]. In contrast to the findings of the present study, a study of Iranian adults in 2010 suggested that income had no significant effect on hookah use [48]. It should be noted that SES conditions have changed in recent years, and WTS on its own is much more expensive than cigarette smoking in Iran. The median and interquartile range of the monthly cost of WTS in Iran was estimated to be about US$3 (about 90,000 IRR) and US$15 (about 4,500,000 IRR), respectively, which is almost the same as a pack of cigarettes [6]. Furthermore, the depreciation of the Iranian currency exacerbates this burden, making it increasingly challenging for individuals with lower socioeconomic status to access and enjoy the welfare-to-service benefits, especially when compared to their wealthier counterparts. This could be another important reason why the results of this study are not in line with some previous studies that were conducted during a time, when Rial (Iranian currency) was enjoying its high value and WTS may have been more affordable for lower SES as high SES. Finally, it should be noted that hookah often is offered in expensive and luxury cafes in Iran and is considered a kind of luxury entertainment [49].

Studies conducted beyond the Middle East [50] have found that young people of higher SES are particularly at risk for WTS, highlighting the differences in SES levels between WTS and cigarette smoking. Earlier studies from Pakistan have shown that the highest rates of WTS were observed among college students with higher SES [51]. Danaei etal. in a cross-sectional study showed that the rate of WTS in the age group 18 to 24 years was 4.9 times higher than that in the group 45 years and older [6], which is in line with other studies in Iran [52]. However, this study reported similar results that young men, highSES, and urban groups are associated positively with WTS. One possible cause of this problem could be a lack of healthy entertainment options for young people in Iran and neighboring countries.

Similar to cigarette smoking, gender differences were observed among waterpipe smokers. Our study showed that men smoke waterpipe about 12 times more than women in north-west of Iran. This finding is consistent with studies conducted in other parts of Iran, Vietnam, Egypt, USA, and Turkey [19, 42, 53, 54]. In contrast, three studies conducted in Hormozgan [55] and Bushehr [56] and Kuwait [57] showed a higher prevalence of WTS among women than men. These differences are logical, as women's WTS in the eastern mediterranean region is traditional and rooted in culture. The tendency to WTS is seen among women in many societies, especially Middle Eastern nations, as it is believed that WTS is less dangerous and less stigmatized than cigarette smoking. Also, in Iranian society, some cultural and religious factors prevent women from smoking cigarettes [49].

According to our findings, there is a correlation between education level and socioeconomic (SES) inequality in regard to WTS, with a higher prevalence of WTS observed among individuals with higher education levels. A study conducted in Iran by Rezaei and colleagues demonstrated that the concentration of tobacco use among low-income households was primarily influenced by wealth and education [43]. A study in the US revealed that individuals with higher education were more likely to smoke waterpipe, and people living outside of poverty were disproportionately more likely to smoke waterpipe compared to whites [58].

The prevalence of tobacco use in a society is a helpful indicator of estimating its harmful health effects. Due to the risk factor of smoking, especially WTS, for many non-communicable diseases, if the current situation continues and no special intervention is taken, If the current situation continues without any special intervention, the inequality in WTS is likely to contribute to an unequal burden of WTS-induced diseases. Hypertension and diabetes as risk factors of heart diseases are associated significantly with higher odds of WTS in this study. Islami et al. showed that WTS was significantly associated with heart disease prevalence [59].

The prevalence of WTS in this study was lower than in other studies [6, 60], although the older age range is one of the main limitations of this study (see limitations section). WTS seems to be increasing in Ardabil. This is not only worrying but also shows a great deal of interest in WTS, which could be due to misconceptions about the safety of WTS. Abdollahifard et al. found that the popularity of WTS increased during the last decade and will increase over the next half-decade [19]. Therefore, monitoring WTS and how SES can affect pattern of WTS is crucial for prevention and cessation programs.


A limitation of this study is that, given the study's cross-sectional nature, the causal relationship between WTS and findings should be interpreted with caution. In addition, data were collected as a self-report, which could lead to reporting/response bias, for which a valid Persian cohort questionnaire was used and interviews. The study population consists of participants over 35 years of age since PERSIAN cohort’s primary purposes are collecting data to better understand the trajectories of NCDs outcomes.In order to generalize the results to the entire population of Iran, more comprehensive studies are necessary to include ages above 15, especially young adults who encompass a large proportion of waterpipe tobacco smokers in Iran. The strength of this research is the large sample of 20,427 people in the Ardabil Persian Cohort. A standard PERSIAN cohort questionnaire compares the results with other study results from different sites of Iran and future multicenter prospective studies from different sites of PERSIAN cohort would add synergy to growing literature about SES and how it can change over time.


This study from a large sample of adults showed that rich people are more at risk of WTS than poor people, showing WTS as a pro-rich mode of smoking in the northwest of Iran. The index and concentration curve measures showed the existence of SES inequalities in WTS in the northwestern region of Iran. Waterpipe-specific prevention and interventions (e.g., high taxation and intensify monitoring of waterpipe supply centers) are needed to implement policies to reduce tobacco use among adults. Future similar studies are warranted to explore the SES inequlities in WTS among adults aged < 35, especially youths considering instability in their SES and matching it with parents or guardians SES.

Availability of data and materials

Data are available from the authors upon reasonable request to corresponding authors.



Ardabil Non-Communicable Diseases


Concentration Curve


Non-communicable diseases


Principal Component Analysis


Prospective Epidemiological Research Studies in IrAN


Relative Concentration Index


Socioeconomic Status


  1. World Health Organization W. WHO Report on the Global Tobacco Epidemic, 2021: Addressing new and emerging products. 2021.

  2. Akl EA, Jawad M, Lam WY, Obeid R, Irani J. Motives, beliefs and attitudes towards waterpipe tobacco smoking: a systematic review. Harm Reduct J. 2013;10(1):1–10.

    Article  Google Scholar 

  3. Rostami R, Kalan ME, Ghaffari HR, Saranjam B, Ward KD, Ghobadi H, et al. Characteristics and health risk assessment of heavy metals in indoor air of waterpipe cafés. Building and Environment. 2021;190.

  4. Naddafi K, Nabizadeh R, Rostami R, Ghaffari HR, Fazlzadeh M. Formaldehyde and acetaldehyde in the indoor air of waterpipe cafés: Measuring exposures and assessing health effects. Building and Environment. 2019;165.

  5. Hessami Z, Masjedi MR, Ghahremani R, Kazempour M, Emami H. Evaluation of the prevalence of waterpipe tobacco smoking and its related factors in Tehran, Islamic Republic of Iran. EMHJ-Eastern Mediterranean Health Journal. 2017;23(2):94–9.

    Article  Google Scholar 

  6. Danaei M, Jabbarinejad-Kermani A, Mohebbi E, Momeni M. Waterpipe tobacco smoking prevalence and associated factors in the southeast of Iran. Addict Health. 2017;9(2):72.

    PubMed  PubMed Central  Google Scholar 

  7. Masjedi MR, Taghizadeh F, Hamzehali S, et al. Air pollutants associated with smoking in indoor/outdoor of waterpipe cafés in Tehran, Iran: Concentrations, affecting factors and health risk assessment. Sci Rep. 2019;9(3110);1–22.

  8. Aziz-ur-Rahman Niazi NA, Shayan SO, Shafiq Ahmad Joya HO. Waterpipe Smoking among Herat University Students: Prevalence, Attitudes, and Associated Factors. Addict Health. 2020;12(4):235.

  9. Sterling KL, Mermelstein R. Examining hookah smoking among a cohort of adolescent ever smokers. Nicotine Tob Res. 2011;13(12):1202–9.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Ebrahimi Kalan M, Abazari M, Ben Taleb Z, Adham D, Abbasi A, Bursac Z, et al. Characteristics of flavored and non-flavored waterpipe tobacco users: a real-world setting study. Environ Sci Pollut Res. 2021;28(41):57629–39.

    Article  Google Scholar 

  11. Adham D, Kalan ME, Fazlzadeh M, Abbasi-Ghahramanloo A. Latent class analysis of initial nicotine dependence among adult waterpipe smokers. J Environ Health Sci Eng. 2021;19(2):1765–71.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Naddafi K, Nabizadeh R, Rostamy R, Ebrahimi Kalan M, Hassanvand MS, Fazlzadeh M. Indoor air quality in waterpipe cafés: exposure level to particulate matter. Environ Sci Pollut Res. 2019;26(26):26605–16.

    Article  CAS  Google Scholar 

  13. Maziak W, Ward KD, Soweid RA, Eissenberg T. Tobacco smoking using a waterpipe: a re-emerging strain in a global epidemic. Tob Control. 2004;13(4):327–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Alqahtani MM, Goodfellow LT, Zimmerman RD, Zavorsky GS. Waterpipe smoking in health-care students: prevalence, knowledge, attitudes, and motives. Respir Care. 2019;64(3):321–7.

    Article  PubMed  Google Scholar 

  15. Shakhatreh MAK, Khabour OF, Alzoubi KH, Masadeh MM, Hussein EI, Bshara GN. Alterations in oral microbial flora induced by waterpipe tobacco smoking. International journal of general medicine. 2018;11:47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Martinasek MP, Gibson-Young LM, Davis JN, McDermott RJ. Waterpipe tobacco smoking impact on public health: implications for policy. Risk management and healthcare policy. 2015;8:121.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Jawad M, Lee JT, Millett C. Waterpipe tobacco smoking prevalence and correlates in 25 Eastern Mediterranean and Eastern European countries: cross-sectional analysis of the Global Youth Tobacco Survey. Nicotine Tob Res. 2016;18(4):395–402.

    Article  PubMed  Google Scholar 

  18. Akl EA, Gunukula SK, Aleem S, Obeid R, Abou Jaoude P, Honeine R, et al. The prevalence of waterpipe tobacco smoking among the general and specific populations: a systematic review. BMC Public Health. 2011;11(1):1–12.

    Article  Google Scholar 

  19. Abdollahifard G, Vakili V, Danaei M, Askarian M, Romito L, Palenik CJ. Are The Predictors of Hookah Smoking Differ From Those of Cigarette Smoking? Report of a population-based study in Shiraz, Iran, 2010. Int J Prev Med. 2013;4(4):459–66.

    PubMed  PubMed Central  Google Scholar 

  20. Meysamie A, Ghaletaki R, Haghazali M, Asgari F, Rashidi A, Khalilzadeh O, et al. Pattern of tobacco use among the Iranian adult population: results of the national Survey of Risk Factors of Non-Communicable Diseases (SuRFNCD-2007). Tob Control. 2010;19(2):125–8.

    Article  PubMed  Google Scholar 

  21. Kalan ME, Taleb ZB. Waterpipe tobacco smoking: a reality or hidden iceberg for Iranian women. Health promotion perspectives. 2018;8(4):252.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Organization WH, Regulation WSGoTP. Advisory note: waterpipe tobacco smoking: health effects, research needs and recommended actions by regulators. 2015.

  23. World Health Organization W. An Overview of Global Regulatory Practices in Controlling Waterpipe Tobacco Use. WHO FCTC Secretariat’s Knowledge Hub on Waterpipe Tobacco Smoking under the grant from the Convention Secretariat, WHO FCTC; 2018.

  24. Jawad M, El Kadi L, Mugharbil S, Nakkash R. Waterpipe tobacco smoking legislation and policy enactment: a global analysis. Tob Control. 2015;24(Suppl 1):i60–5.

    Article  PubMed  Google Scholar 

  25. Statistical Center of Iran. Population and Household of the Country by Province and Sub-province Tehran, Iran: Statistical Center of Iran; 2017.

  26. Poustchi H, Eghtesad S, Kamangar F, Etemadi A, Keshtkar A-A, Hekmatdoost A, et al. Prospective Epidemiological Research Studies in Iran (the PERSIAN Cohort Study): Rationale, Objectives, and Design. Am J Epidemiol. 2017;187(4):647–55.

    Article  PubMed Central  Google Scholar 

  27. Zahirian Moghadam T, Pourfarzi F, Mohseni Rad H, Zandian H. Kidney stones among Iranian adults: Prevalence and socioeconomic inequality assessment in a cohort-based cross-sectional study. Health Science Reports. 2022;5(6): e877.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Lohse T, Rohrmann S, Bopp M, Faeh D. Heavy smoking is more strongly associated with general unhealthy lifestyle than obesity and underweight. PLoS ONE. 2016;11(2): e0148563.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Filmer D, Pritchett LH. Estimating wealth effects without expenditure data—or tears: an application to educational enrollments in states of India. Demography. 2001;38(1):115–32.

    CAS  PubMed  Google Scholar 

  30. Minujin A, Bang JH. Indicadores de inequidad social. Acerca del uso del" indice de bienes" para la distribucion de los hogares. Desarrollo económico. 2002:129–46.

  31. McKenzie DJ. Measuring inequality with asset indicators. J Popul Econ. 2005;18(2):229–60.

    Article  Google Scholar 

  32. Howe LD, Hargreaves JR, Huttly SRA. Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries. Emerg Themes Epidemiol. 2008;5(1):3.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan. 2006;21(6):459–68.

    Article  PubMed  Google Scholar 

  34. Wagstaff A, Paci P, Van Doorslaer E. On the measurement of inequalities in health. Soc Sci Med. 1991;33(5):545–57.

    Article  CAS  PubMed  Google Scholar 

  35. Pulok MH, van Gool K, Hajizadeh M, Allin S, Hall J. Measuring horizontal inequity in healthcare utilisation: A review of methodological developments and debates. Eur J Health Econ. 2020;21(2):171–80.

    Article  PubMed  Google Scholar 

  36. Wagstaff A. The concentration index of a binary outcome revisited. Health Econ. 2011;20:1155–60.

    Article  PubMed  Google Scholar 

  37. Wagstaff A, Doorslaer vE, Watanabe N. On decomposing the causes of health sector inequalities with an application to malnutrition inequalities in Vietnam: The World Bank; 2001.

  38. Sheiham A. Oral health, general health and quality of life. SciELO Public Health; 2005.

  39. Monteiro CN, Beenackers MA, Goldbaum M, de Azevedo Barros MB, Gianini RJ, Cesar CLG, et al. Socioeconomic inequalities in dental health services in Sao Paulo, Brazil, 2003–2008. BMC Health Serv Res. 2016;16(1):683.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Boskabady MH, Farhang L, Mahmoodinia M, Boskabady M, Heydari GR. Prevalence of water pipe smoking in the city of Mashhad (North East of Iran) and its effect on respiratory symptoms and pulmonary function tests. Lung India. 2014;31(3):237.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Smith JR, Edland SD, Novotny TE, Hofstetter CR, White MM, Lindsay SP, et al. Increasing hookah use in California. Am J Public Health. 2011;101(10):1876–9.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Moghadam TZ, Zandian H, Pourfarzi F, et al. Environmental and economics-related factors of smoking among Iranian adults aged 35–70: a PERSIAN cohort–based cross-sectional study. Environ Sci Pollut Res. 2021;28(28):45365–74.

  43. Rezaei S, Pulok MH, Ebrahimi M. Socioeconomic inequality in tobacco expenditure in Iran: a cross-sectional analysis at national and subnational levels. BMC Public Health. 2020;20(1):1031.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Sibai AM, Iskandarani M, Darzi A, Nakkash R, Saleh S, Fares S, et al. Cigarette smoking in a Middle Eastern country and its association with hospitalisation use: a nationwide cross-sectional study. BMJ open. 2016;6(4):e009881-e.

  45. Elkalmi RM, Elnaem MH, Elsayed TM, Salawi AA, Alkoudmani RM, Allela OQ. Disparity and compatibility, familiarity and perception among waterpipe tobacco smokers (Shisha) in Malaysia: A comparative study. Arch Pharm Pract. 2021;12(1):21–31.

    Article  Google Scholar 

  46. Ghelichkhani P, Yaseri M, Youseffard M, Baikpour M, Asady H, Oraii A, et al. The gap of cigarette and hookah smoking between socioeconomic groups in Iran: effect of inequalities on socioeconomic position. Arch Iran Med. 2018;21(9):418–24.

    PubMed  Google Scholar 

  47. Golestan YP, Ebrahimi Kalan M, Ben Taleb Z, Ward KD, Fazlzadeh M, Bahelah R, et al. The effect of price on cigarette consumption, distribution, and sale in Tehran: a qualitative study. BMC Public Health. 2021;21(1):1720.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Sarrafzadegan N, Toghianifar N, Roohafza H, Siadat Z, Mohammadifard N, O’Loughlin J. Lifestyle-related determinants of hookah and cigarette smoking in Iranian adults. J Community Health. 2010;35(1):36–42.

    Article  PubMed  Google Scholar 

  49. Makvandi Z, Mostafavi F, Bashirian S, Zamani-Alavijeh F, Kelishadi R. Sociocultural factors contributing to waterpipe tobacco smoking among adolescents and young adult women: a qualitative study in Iran. Int J Qual Stud Health Well Being. 2021;16(1):1857043.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Palamar JJ, Zhou S, Sherman S, Weitzman M. Hookah use among US high school seniors. Pediatrics. 2014;134(2):227–34.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Anjum Q, Ahmed F, Ashfaq T. Knowledge, attitude and perception of water pipe smoking (Shisha) among adolescents aged 14–19 years. J Pakistan Med Assoc. 2008;58(6):312.

    Google Scholar 

  52. Baheiraei A, Mirghafourvand M, Nedjat S, Mohammadi E, Charandabi SM-A. Prevalence of water pipe use and its correlates in Iranian women of reproductive age in Tehran: a population-based study. Med Principles Pract. 2012;21(4):340–4.

  53. Morton J, Song Y, Fouad H, El Awa F, Abou El Naga R, Zhao L, et al. Cross-country comparison of waterpipe use: nationally representative data from 13 low and middle-income countries from the Global Adult Tobacco Survey (GATS). Tobacco control. 2014;23(5):419–27.

  54. Rahman S, Chang L, Hadgu S, Salinas-Miranda AA, Corvin J. Peer reviewed: Prevalence, Knowledge, and practices of hookah smoking among university students, Florida, 2012. Preventing chronic disease. 2014;11.

  55. Ghanbarnejad A, Aghamolaei T, Ghafari HR, Daryafti H. Hookah smoking and associated factors in rural region of Hormozgan. Iran: Zahedan J Res Med Sci; 2010.

    Google Scholar 

  56. Yousefi F, Darabi H, Nabipour I, Assadi M, Vahdat K, Kardeh E, et al. Prevalence of tobacco smoking in Bushehr Province: Comparison of two phases of the Persian Gulf healthy heart study. Ismj. 2014;17(3):487–95.

    Google Scholar 

  57. Maziak W, Taleb ZB, Bahelah R, Islam F, Jaber R, Auf R, et al. The global epidemiology of waterpipe smoking. Tob Control. 2015;24 Suppl 1(Suppl 1):i3-i12.

  58. Assari S, Chalian H, Bazargan M. Social Determinants of Hookah Smoking in the United States. J Ment Health Clin Psychol. 2020;4(1):21–7.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Islami F, Pourshams A, Vedanthan R, Poustchi H, Kamangar F, Golozar A, et al. Smoking water-pipe, chewing nass and prevalence of heart disease: a cross-sectional analysis of baseline data from the Golestan Cohort Study. Iran Heart. 2013;99(4):272.

    Article  PubMed  Google Scholar 

  60. Jawad M, Charide R, Waziry R, Darzi A, Ballout RA, Akl EA. The prevalence and trends of waterpipe tobacco smoking: A systematic review. PLoS ONE. 2018;13(2): e0192191.

    Article  PubMed  PubMed Central  Google Scholar 

Download references


We would like to thank managers and staffs of the central office of the PERSIAN Cohort Study, for helping us to conduct this study.


This project was financially supported by National Institute for Medical Research Development (NIMAD: 962249). In addition, a part of this work was funded by the Ardabil University of Medical Sciences (ARUMS). The funders had no role in study design, data analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations



TZM, HZ and FP contributed with the research idea, study design, performing the study, and writing the manuscript. TZM and HZ designed the chart and graph and analysis of data; and MF and MEK helped with study design and data collection. HZ, MEK and MF critically revised the manuscript for important intellectual content. All authors approved the final manuscript and agreed to be accountable for all aspects of the work.

Corresponding authors

Correspondence to Hamed Zandian or Farhad Pourfarzi.

Ethics declarations

Ethics approval and consent to participate

This study was approved by Ethical Committee of Research of ARUMS with reference number (IR.ARUMS.REC.1401.117). All methods were carried out in accordance with relevant guidelines and regulations (Declaration of Helsinki) and informed consent was obtained from all participants based on PERSIAN cohort protocol.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moghadam, T.Z., Zandian, H., Fazlzadeh, M. et al. Socioeconomic and environmental factors associated with waterpipe tobacco smoking among Iranian adults: a PERSIAN cohort-based cross-sectional study. BMC Public Health 23, 1295 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: