Clustering of chronic disease risk factors with tobacco smoking habits among adults in the work place in Sousse, Tunisia
Hmad Sonia, Maatoug Jihene, Harrabi Imed, Ghammem Rim, Belkacem Mylene, Saadi Mounir, Amimi Souad, Knani Khaoula, Al’Absi Mustafa, Lando Harry, Mrizak Najib, Ghannem Hassen
The Pan African Medical Journal. 2016;24:220. doi:10.11604/pamj.2016.24.220.7163

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Clustering of chronic disease risk factors with tobacco smoking habits among adults in the work place in Sousse, Tunisia

Cite this: The Pan African Medical Journal. 2016;24:220. doi:10.11604/pamj.2016.24.220.7163

Received: 26/05/2015 - Accepted: 12/05/2016 - Published: 12/07/2016

Key words: Tobacco use, work places, risk factors, tobacco use, adults, chronic diseases

© Hmad Sonia et al. The Pan African Medical Journal - ISSN 1937-8688. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Available online at: http://www.panafrican-med-journal.com/content/article/24/220/full

Corresponding author: Ghammem Rim, Department of Epidemiology, University Hospital Farhat Hached, Sousse, Tunisia (ghammam.rim2013@gmail.com)


Clustering of chronic disease risk factors with tobacco smoking habits among adults in the work place in Sousse, Tunisia

Hmad Sonia1, Maatoug Jihene1, Harrabi Imed1, Ghammem Rim1,&, Belkacem Mylene1, Saadi Mounir2, Amimi Souad2, Knani Khaoula2, Al’Absi Mustafa3, Lando Harry4, Mrizak Najib5, Ghannem Hassen1

 

1Department of Epidemiology, University Hospital Farhat Hached, Sousse, Tunisia, 2Group of Occupational Medicine, Sousse, Tunisia, 3University of Minnesota Medical School, USA, 4Department of Epidemiology & Community Health, University of Minnesota, USA, 5Department of Occupational Medicine, University Hospital Farhat Hached, Sousse, Tunisia

 

 

&Corresponding author
Ghammem Rim, Department of Epidemiology, University Hospital Farhat Hached, Sousse, Tunisia

 

 

Abstract

Introduction: the aim of our study was to explore the major non-communicable risk factors (unhealthy diet, sedentarily, alcohol consumption) of smokers and nonsmokers in workplaces.

 

Methods: a cross-sectional study was derived from an initial assessment in workplaces which was part of a community-based intervention to prevent chronic disease risk factors conducted in 2009 in the region of Sousse, Tunisia. The surveyed subjects were employees in six factories spread across three delegations in the region. Overall, 1770 of 2250 employees participated in the assessment. In this study, the clustering of non-communicalbe diseases risk factors with smoking habits was made only for male employees including in this study 1099 among 2250. Data were collected at worksites by a questionnaire, via interview or self-report .The main items assessed socio-demographics characteristics, smoking status, eating habits, level of physical activity and alcohol use of the participants.

 

Results: the percentage of male smokers was 54.0%(n=594). Their average age of daily smoking initiation was 19.22 (±4.24 years). The percentage of male smokers consuming 5 fruits and vegetables per day was significantly lower than nonsmokers (57.2% vs 63.5%, p=0.04). The proportion of male smokers consuming alcohol was about three times that of nonsmokers (16.5% vs 5.8%, p=0.001). The proportion of male employees who agree with anti-smoking laws in work places was higher for nonsmokers than for smokers.

 

Conclusion: a strong association existed between smoking and risky lifestyles factors in the work place. Such findings are potentially useful in directing intervention efforts regarding smoking cessation in occupational settings.

 

 

Introduction    Down

Tobacco use is a major health concern in the modern world [1, 2]. Based on recent estimates, nearly 20% of the world’s adult population smokes cigarettes. Tobacco use kills approximately 5.2 million people worldwide each year, a figure expected to increase to more than 8 million a year by 2030 [3, 4]. Likewise, current data indicate that Tunisia has one of the highest rates of adult male tobacco use in the Eastern Mediterranean region with a prevalence of 52.7% [5]. Furthermore, a growing occupational disparity in smoking prevalence represents a crucial challenge for worksite tobacco control initiatives [6].

 

Previous studies have reported that smoking is associated with various psychosocial and demographic factors including social status, education, age, employment and marital status [2, 7]. Some studies suggest that smoking acts both as a causal factor and as a marker of an unhealthy lifestyle [8, 9]. Moreover, the clustering of multiple risk factors provides support for multiple-behavior interventions as opposed to single-behavior interventions [10]. To date, the occurrence of smoking and other non communicable disease risk factors has not been fully investigated, particularly among workers in Tunisia. The clustering of lifestyle factors (primarily unhealthy diet, lack of physical activity, alcohol consumption) with smoking therefore needs further research. As such this study provides useful data concerning smoking patterns among adults in the work place in the region.

 

 

Methods Up    Down

Study design: this is a cross-sectional study which represents a part of an assessment of the prevalence of chronic disease risk factors in workplaces. This assessment was part of a community-based intervention to prevent chronic disease risk factors carried out in 2009 in the region of Sousse, Tunisia.

 

Population: the pre-assessment of the community-based intervention took place in the manufacturing sector in six factories spread across three delegations of the region of Sousse. All employees in these six factories were included. Overall, 1770 from 2250 employees participated at the initial assessment. However, as we already know that women seemed often to underreport their smoking status due to social issues, which might distort the clustering of risk factors with smoking habits, we have chosen in the current study, to focus only on male employees. The number of male employees among the 2250 was 1099. They were all included in this study.

 

Data collection: socio-demographic characteristics and lifestyle data have been collected by a pre-tested questionnaire in Arabic: the managerial staff responded to a self administrated questionnaire, while workers were interviewed by a medical doctor. Socio-demographic characteristics measured included age, sex, marital status, educational level and profession. Lifestyle items were composed of smoking status, daily cigarette consumption, eating habits, physical activity and alcohol consumption. Concerning smoking habits, the participants were asked if they smoked any kind of tobacco (cigarettes, cigar, pipe or water-pipe). “Smokers” were the participants who responded yes to this question. BMI was determined as the body weight in kilograms divided by squared height in meters (kg/m2). Obesity was defined as a BMI ≥30 kg/m2. Analysis: Statistical analysis was performed using the SPSS 10.0 software. Data were presented as frequencies, means and standard deviations. The chi-square test was used to compare current smokers and never smokers for the categorical variables. The t-test was used to compare the means and standard deviation (SD) of quantitative data. For both tests, the level of significance was 0.05.

 

 

Results Up    Down

The mean age of male employees was 33.8±8.59 years. The percentage of male smokers was 54.0 % (n=594). The average age of initiation of daily smoking was 19.22 (±4.24 years). Their mean daily consumption of cigarettes was 16.4±9.37. As indicated in Table 1, a higher percentage of male employees with a primary level of education reported smoking than did employees with university level of education (63.3% vs 49.1%, p =0.007). The proportion of smokers was also significantly higher among single employees than among married employees (61.1% vs 53.4%, p=0.002). The proportion of smokers among male workers (58 %) was higher than that among male managerial staff (46.6%), but this difference was not statistically significant (p=0.39).

 

Male smokers and nonsmokers differed significantly in lifestyle habits (Table 2). The percentage of male smokers consuming 5 fruits and vegetables per day was significantly lower than male nonsmokers (57.2% vs 63.5%, p=0.04). The percentage of male smokers avoiding foods that are too fat or too sweet or too salty was also significantly lower than nonsmokers male (41.9% vs 53.9%, p=0.001). The percentage of smokers adding salt to meals was significantly higher than nonsmokers with 29.3% vs 21.2%, p=0.003. Moreover, the percentage of male smokers consuming alcohol was about three times the percentage of non smokers male consumers (16.5% vs 5.8%, p=0.001). Concerning physical activity, we found a significant difference between male smokers and male nonsmokers, who tried to reduce time setting outside work (25.7% vs 33.7%, p=0.005). Only 31.0% of male smokers and 36.4% of male nonsmokers (p=0.06) used to practice physical activity 30 minutes or more per day, 5 days per week. However, as might be expected, the rate of obesity (defined as BMI≥30kg/m2) was significantly higher among male nonsmokers than male smokers (19.4% vs 14.2%, p=0.02)

 

Table 3 presents the proportion of male employees who agree with anti-smoking laws in work places. Although nonsmokers were more likely to agree, there was substantial agreement among smokers as well (respectively 87.6% vs 73.0%, p=0.001). However, the proportion of male workers who reported that their company encourages them to prevent or stop smoking was similar for both smokers and nonsmokers (25.1% vs 23.2%, p=0.47).

 

 

Discussion Up    Down

Aiming for more investigation on the clustering of risk factors with smoking habits, we have analyzed data from a cross sectional survey conducted in the work place. The results highlighted the important magnitude of tobacco use in work places and demonstrated a strong association between smoking and risky lifestyles, such as unhealthy diet, alcohol consumption and lack of physical activity.

 

The reported prevalence of smoking was 54% among male employees and this is relatively consistent with previous Tunisian statistics. A study carried out in the region of Ariana found prevalence smoking of 55% in men [11]. Another study conducted in the Tunisian Sahel reported a percentage of 66% of men who are smokers [12]. Worldwide, the prevalence of smoking is much higher in men than in women [13, 14] and the pattern is similar in the Mediterranean region where the proportion of men who smoke ranges from 20% in Islamic Republic of Iran to 63% in Turkey [15].

 

The average age of initiating daily smoking found among male employees (19.2 years) was similar to another Tunisian survey [15]. Though, Lando et al [16] have found 17.7 years the mean age of initiation in a study involving 2120 working adults, they noted that those who initiate smoking at an early age may be at higher risk for poor dietary practices, reduced physical activity, greater alcohol consumption, and a variety of other risky health practices [16]. Our results revealed mean daily consumption of 16.4±9.37 cigarettes among male workers and this is quite similar to Lando’s et al results with 16.7±9.2 [16]. Smoking and educational level seem to be strongly associated [2]. Many studies have demonstrated that smoking is more prevalent in less educated people [2, 15, 17]. However, significant international variations in educational gradients and smoking may exist. Similar findings were documented in our study. In fact, primary level education was more frequent among smoking employees than among nonsmokers. Employees with university level education were less likely to smoke. Thus, the prevalence of smoking and educational level were inversely related.

 

Smoking prevalence depends on social class and occupation [18]. In western countries, tobacco use is more frequent in the lower socioeconomic classes [2]. In Tunisia, Fakhfakh et al [15], have reported this fact in an epidemiological study including 1334 adults where smoking among manual workers were 54.4%. As to our results, we have found that lower grade male employees (workers) were likely to be current smokers (58.3%) but not significantly different from higher grade male employees (managerial staff) being smokers (46.6%). Similarly a Japanese study [2] has obtained similar findings and attested that lower income generally promotes smoking with the strongest influence in the 25-39 years population group.

 

Regarding lifestyle habits, our results indicated that several variables were associated with smoking status. Indeed, male smoking employees appeared to have a less healthy diet, as the percentage of smokers consuming 5 fruits and vegetables per day was significantly lower than nonsmokers in our studied population. This has been widely demonstrated in the literature. Smokers compared with never-smokers have been shown to eat less cereal [19], less vegetables and fruits, and eat more fat [19- 21]. Furthermore, smokers have been shown to have a higher energy intake [8]. Philips et al [21] have demonstrated from a cross-sectional household health survey that smoking status was inversely associated with intake of vitamins A and C, dietary fiber, folate, and iron among women, whereas differences were smaller and not significant among men. Women who smoked consumed fewer servings of fruits and vegetables than nonsmokers, but this trend was not noted in men. In a Japanese study involving 2310 workers, comparing the lifestyle of smokers with non-smokers, smokers had worse health practices than nonsmokers with regard to eating breakfast and nutritional balance [22].

 

On the other hand, in most populations, smokers weigh less than do nonsmokers [23, 24]. Adult smokers weigh, on average, 4-5 kg less than nonsmokers and are less likely to be overweight or obese [25]. In Finnish men, the relation between smoking and BMI was reported to change from an inverse association to a positive one in the late 1980s [24]. Results have demonstrated that smoking employees are significantly less obese compared with non-smoking employees.

 

However, according to Thompson et al [23], weight differences between smokers and nonsmokers are more likely to be due to differences in diet than in exercise.

 

Certainly, smoking and physical activity are largely incongruent behaviors. Considerable interest currently exists in how physical activity indirectly influences health by acting through other behaviors, such as smoking [26]. The association between cigarette smoking and poor physical functioning has been demonstrated in the published literature [2]. Woodward et al. [27] reported that smokers had lower physical activity than non- smokers [22]. Hu et al [2] have demonstrated that civil servants who did not engage in regular moderate physical activities (more than twice per week) are 1.4 times more likely to be active smokers. In a similar Italian study among civil servants, the percentage of sedentary subjects was found to be particularly high among smokers (67%) versus nonsmokers (59%) [28]. Our results show that the percentages of smokers who practice recommended levels of physical activity (30 minutes or more per day, 5 days per week) were non-significantly lower than the percentages of nonsmokers who met this standard. Whereas, the percentages of smokers and non-smokers, who tried to reduce time setting outside work were significantly different. These findings appear relatively controversial to other studies. In fact, in a review of the literature, Blair et al, noted that smoking may be inversely associated with leisure-time activity and that occupational physical activity is positively associated with the smoking habit, although this is likely due to confounding by socioeconomic status [26]. However, they documented several problems encountered in reviewing research on exercise and physical activity. First, there are no consistent definitions of these terms used by different authors. Also, assessments of exercise and physical activity have been crude and imprecise; therefore, much misclassification occurs in studies of exercise behavior and, in turn, this may obscure the relationships between exercise or physical fitness and other behaviors [26].

 

Strong association between smoking behavior and alcohol consumption was demonstrated in this study. A strong positive relationship between alcohol and tobacco smoking previously has been reported [2, 29, 30]. A cross-sectional study carried out among 4521 male Japanese workers demonstrated that subjects who consumed the lowest amount of alcohol had the lower prevalence of smoking [29]. An epidemiological analysis of alcohol consumption in the USA [30] revealed that among young adults, the prevalence of recent concurrent alcohol and tobacco use was approximately 35 to 45 percent.

 

Other interesting results of this study are those that have implications for smoking intervention programs. In fact, the primary objective of workplace smoking restrictions and bans may be to reduce environmental tobacco smoke in the workplace. However, several studies have shown that restrictions and bans also lead to a decrease in the prevalence of smoking and the number of cigarettes smoked daily among workers [31]. Workers’ attitudes regarding the implementation of an anti-smoking law at worksites therefore need to be addressed. Research suggests that both nonsmokers and smokers at work prefer a smoking policy to be in place [32]. Our results were in accord with this as the majority of non-smoking and smoking workers support anti-smoking policies. Pearson D et al [33] have reported in a study involving hospitality workers that more than half of all workers supported local bans on smoking in restaurants, in bars, and on a statewide basis. They preferred to work in smoke-free settings and a majority supported bans on smoking in the workplace [33]. On the other hand, providing prevention programs for tobacco cessation in workplaces would be more effective. Sherriff NS et al [34] reported that employees were knowledgeable about the negative health impacts of smoking, but showed limited awareness of smoking cessation services and aids available. Our findings are in accord as the proportions of both smokers and nonsmokers who were knowledgeable about their companies’ encouragement of prevention and smoking cessation were quite limited.

 

It’s important to address the limitations of this study, which are mainly associated with the design factors. Indeed, it may be difficult to generalize the findings to different settings and populations as the studied population wasn’t randomly selected. A second limitation is self-reported smoking status (without objective measures). The validity of self-reporting in determining the rate of smoking remains often questioned. Moreover, we haven’t assessed the clustering of risk factors among women as our study may have underestimated the rate of female smoking, (there may have been under-reporting in spite of assurances to participants about the confidentiality of the data).

 

Finally, health monitoring at the workplaces could contribute to a better awareness of these risky lifestyle factors, independently of workers’ socioeconomic level. Regular data collection on tobacco use should be thenceforth disaggregated by sex. This will permit identification of trends and health effects on men and women and also will illuminate the impact of gender on smoking initiation, types of tobacco used, and depth and frequency of inhalation. The research tools of estimating smoking prevalence, such as self-reporting, must be improved, as women may be more reluctant to report accurately due to greater social disapproval of female smoking in our society [35].

 

 

Conclusion Up    Down

Our study suggests the importance of considering differences in lifestyle risk factors in relation to smoking status to improve lifestyle practices among workers. Further investigation should be conducted in order to focus on an effective strategy for smoking cessation in these groups. These are very important issues for occupational health in Tunisia.

What is known about this topic

  • Tunisia has one of the highest rates of adult tobacco use in the Mediterranean region;
  • The disparity in smoking prevalence in workplaces;
  • Workplaces could be an interesting setting to assess and intervene on unhealthy life styles.

What this study adds

  • The important prevalence of tobacco use at workplaces mainly among men;
  • The strong association between smoking and risky life styles factors;
  • The importance of preventing all risk factors in association with tobacco use to be more effective.

 

 

Competing interests Up    Down

The authors declare no competing interest.

 

 

Authors’ contributions Up    Down

Hassen Ghannem contributed to the design of the study research protocol. Sonia Hmad, Mylene Belgacem Rim Ghammem, Khawla Knani, Mounir saadi, Souad Amimi and Najib Mrizak participated in the collection and data entry. Imed Harrabi, Hmad Sonia and Jihene Maatoug analyzed and interpreted the results. Jihene Maatoug and Sonia Hmad wrote the article. Hassen Ghannem, Mostafa Alabsi and Harry Lando participated in the final approval of the manuuscript. All the authors have read and approved the final manuscript.

 

 

Acknowledgments Up    Down

The data collection and analysis was supported by a grant from United Health Group. The manuscript writing and reviews were supported by award n°R56TW009265 from the Fogarty International Center of the National Institutes of Health.

 

 

Tables Up    Down

Table 1: socio-demographic characteristics of male workers according to their smoking status

Table 2: lifestyles habits of male workers according to their smoking status

Table 3: male workers’ attitudes concerning smoking in work places according to their smoking status

 

 

References Up    Down

  1. Glynn T, Seffrin JR, Brawley OW, Grey N, Ross H. The globalization of tobacco use: 21 challenges for the 21st Century. CA Cancer J Clin. 2010;60(1):50-61. PubMed | Google Scholar

  2. Hu L, Sekine M, Gaina A, Nasermoaddeli A, Kagamimori S. Association of smoking behavior and socio-demographic factors, work, lifestyle and mental health of japaneese civil sevants. J Occup Health. 2007 Nov;49(6):443-52. PubMed | Google Scholar

  3. The tobacco atlas. http://www.tobaccoatlas.org/products/cigarette_consumption/text/.Accessed on May 26 2015. PubMed | Google Scholar

  4. The tobacco atlas. http://www.tobaccoatlas.org/products/male_tobacco_use/males_smoke/. Accessed on May 26 2015. PubMed | Google Scholar

  5. WHO. Gender and Tobacco in the Eastern Mediterranean Region. http://applications.emro.who.int/dsaf/libcat/LibCat_26pdf. Accessed on May 26 2015. Google Scholar

  6. Sorensen G. Worksite tobacco control programs: the role of occupational health. Respiration Physiology. 2001 Oct;128(1):89-102. PubMed | Google Scholar

  7. Adel Khattab A, Javaid A, Iraqi G, Alzaabi A, Ben Kheder A, Koniski M-L et al. Smoking habits in the Middle East and North Africa: Results of the BREATHE study. Respiratory Medicine. 2012;106(S2):S16-S24. PubMed | Google Scholar

  8. Oshaug A, Bj0nnes Ch, Bugge Kh, Trygg Ku. Tobacco smoking, an independent determinant for unhealthy diet? A cross-sectional study of Norwegian workers on platforms in the North Sea. Eur J Pub Heal. 1996;3(6):196-202. PubMed | Google Scholar

  9. Castelll WP. Diet, smoking, and alcohol: Influence on coronary heart disease risk. Am J Kidney Dis. 1990;16(4):41-6. PubMed | Google Scholar

  10. Poortinga W. The prevalence of clustering of four major lifestyle risk factors in an English adult population. Prev Med. 2007;44(2):124-8. PubMed | Google Scholar

  11. Ben Romdhane H. Les cardiopathies ischémiques, l’épidémie et ses determinants,Vol 1, Les facteurs de risque: Résultats d’une étude épidémiologique auprès de 5771 adultes tunisiens. [Ischaemic heart diseases, the epidemic and its determinants, Vol 1, Risk factors: results of an epidemiological study on 5771 Tunisian adults.] Tunis: Institut National de Sante Publique; 2001. Google Scholar

  12. Ghannem H, Limam K, Ben Abdelaziz A, Hadj Fredj A, Marzouki M. Facteurs de risque des maladies cardio-vasculaires dans une communauté semi-urbaine du Sahel Tunisien. Rev Epidemiol Sante Publique. 1992;40(2):108-12. PubMed | Google Scholar

  13. Grunberg NE, Winders SE, Wewers ME. Gender differences in tobacco use. Health psychology. 1991;10(2):143-53. PubMed | Google Scholar

  14. Sánchez-Chaparro MA, Román-García J, Calvo-Bonacho E, Gómez-Larios T, Fernández-Meseguer A, Sáinz-Gutiérrez JC et al. Prevalence of Cardiovascular Risk Factors in the Spanish Working Population. Rev Esp Cardiol. 2006;59(5):421-30. PubMed | Google Scholar

  15. Fakfakh R, Hsairi M, Maalej M, Achour N, Nacef T. Tobacco use in Tunisia: behaviour and awareness. Bull World Health Organ. 2002;80(5):350-6. PubMed | Google Scholar

  16. Lando HA, Thai DT, Murray DM, Robinson LA, Jeffery RW, Sherwood NE et al. Age of Initiation, Smoking Patterns, and Risk in a Population of Working Adults. Prev Med. 1999 Dec;29(6 Pt 1):590-8. PubMed | Google Scholar

  17. Cavelaars AEJM, Kunst AE, Geurts JJM, Crialesi R, Grotvedt L, Helmert U et al. Educational differencies in smoking= international comparaison. BMJ. 2000 Apr 22;320(7242):1102-7. PubMed | Google Scholar

  18. Albertsen K, Hannerz H, Borg V, Burr H. The effect of work environment and heavy smoking on the social inequalities in smoking cessation. Public Health. 2003 Nov;117(6):383-8. PubMed | Google Scholar

  19. Morabia A, Wynder EL. Dietary habits of smokers, people who never smoked, and exsmokers. Am J din Nutr. 1990 Nov;52(5):933-7. PubMed | Google Scholar

  20. Hebert JR, Kabat GC. Differences in dietary Intake associated with smoking status. Eur J din Nutr. 1990 Mar;44(3):185-93. PubMed | Google Scholar

  21. McPhillips JB, Eaton C, Gans KM et al. Dietary differences in smokers and nonsmokers from two southeastern New England communities. J Am Diet Assoc. 1994 Mar;94(3):287-92. PubMed | Google Scholar

  22. Nakayama K, Yamaguchi K, Maruyama S, Morimoto K. Association of smoking with other lifestyle factors and mental health status of Japanese factory workers. Environ Health Prev Med. 1997;2(1):11-5. PubMed | Google Scholar

  23. Thompson DH, Warburton DM. Lifestyle differences between' smokers, Ex-smokers and non-smokers, and implications for their health. Psychol Healrh. 1992; 7:311- 21. Google Scholar

  24. Lahti-Koski M, Pietinen P, Heliövaara M, Vartiainen E. Associations of body mass index and obesity with physical activity, food choices, alcohol intake, and smoking in the 1982–1997 FINRISK Studies. Am J Clin Nutr. 2002 May;75(5):809-17. PubMed | Google Scholar

  25. Audrain-McGovern J, Benowitz NL. Cigarette Smoking, Nicotine, and Body Weight. Clin Pharmacol Ther. 2011 July;90(1):164-168. PubMed | Google Scholar

  26. Blair SN, Jacobs DR, Powell KE. Relationships between exercise or physical activity and other health behaviors. Public Health Rep. 1985;100(2):172-180. PubMed | Google Scholar

  27. Woodward M, Bolton-Smith C, Tunstall-Pedoe H. Deficient health knowledge, diet, and other lifesyles in smokers: Is a multifactorial approach required? Prev Med. 1994 May;23(3):354-61. PubMed | Google Scholar

  28. Bottoni A, Cannella C, Del BV. Lifestyle and dietary differences in smokers and nonsmokers from an Italian employee population. Public Health. 1997;111(3):161-4. PubMed | Google Scholar

  29. Saito I, Okamura T, Fukuhara S, Tanaka T, Suzukamo Y, Okayama A. A cross-sectional study of alcohol drinking and health-related quality of life among male workers in Japan. J Occup Health. 2005 Nov;47(6):496-503. PubMed | Google Scholar

  30. Anthony JC, Echeagaray-Wagner F. Epidemiologic Analysis of Alcohol and Tobacco Use. Alcohol Res Health. 2000;24(4):201-8. PubMed | Google Scholar

  31. Farrelly MC, Evans WN, Sfekas AS. The impact of workplace smoking bans: results from a national survey. Tob Control. 1999 Autumn;8(3):272-7. PubMed | Google Scholar

  32. Parry O, Platt S, Thomson C. Out of sight, out of mind: workplace smoking bans and the relocation of smoking at work. Health Promotion International. 2000;15(2):125-133. PubMed | Google Scholar

  33. Pearson D, Angulo A, Bourcier E, Freeman E, Valdez R. Hospitality Workers' attitudes and exposure to secondhand smoke, hazardous chemicals, and working conditions. Public Health Rep. 2007;122(5):670-678. PubMed | Google Scholar

  34. Sherriff NS, Colemanb L. Understanding the needs of smokers who work as routine and manual workers on building sites: Results from a qualitative study on workplace smoking cessation. Public health. 2013 Feb;127(2):125-33. PubMed | Google Scholar

  35. Sarraf-Zagedan N, Boshtam M, Shahrokhi S, Naderi GA, Asgary S, Shahparian M et al. Tobacco use among Iranian men, women and adolescents. Eur J Public Health 2004;14(1):76-78. Google Scholar

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


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