Five-Year Trends of Second-Hand Smoke Exposure in Greece: A Comparison Between Complete,Partial,and Prelegislation Levels

Abstract

Background:

Our aim was to assess second-hand smoke (SHS) exposure in hospitality venues after the smoke-free legislation implemented in September 2010 in Greece and to compare with when a partial ban was in place and in 2006 when no ban was in place.

Methods:

Hospitality venues were prospectively assessed for their indoor concentrations of particulate matter (PM_2.5) during the partial ban phase (n=149) and the complete ban phase (n=120, 80% followed up), while overall and matched by venue comparisons were also performed (no ban vs. partial ban vs. complete ban). Comparisons with previously collected data in 2006 when no ban was in place also was performed.

Results:

Indoor air levels of PM_2.5 attributable to SHS dropped following the transition from a partial to a complete ban by 34% (137 μg/m³ vs. 90 μg/m³, p=0.003). This drop was larger in bars (from 195 μg/m³ to 121 μg/m³), than in cafes (124 μg/m³ vs. 87 μg/m³) or restaurants (42 μg/m³ vs. 39 μg/m³). PM_2.5 concentrations between 2006 (no ban) and the partial ban of 2010 were also found to decrease by 94 μg/m³; however, among matched venues, the levels of indoor air pollution were not found to change significantly (218 μg/m³ vs. 178 μg/m³, p=0.58). Comparing the 2010 complete ban results (n=120) with previously collected data from 2006 when no ban was in place (n=43), overall PM_2.5 concentrations were found to fall from 268 μg/m³ to 89 μg/m³, while a matched analysis found a significant reduction in PM_2.5 concentrations (249 μg/m³ vs. 46 μg/m³, p=0.011).

Conclusion:

The complete ban of smoking in hospitality venues in Greece led to a reduction in SHS exposure, in comparison to when the partial ban or no ban was in place; however, exposure to SHS was not eliminated indicating the need for stronger enforcement.

Introduction

Second-hand smoke (SHS) is a cause of cancer and other health problems. It contains thousands of chemicals, 200 of which are classified as toxic substances, and a substantial number are carcinogens.^(1,2) Exposure to SHS can lead to cardiovascular disease, cancer, chronic obstructive pulmonary disease, and has been associated with lung function.⁽³⁾ An additional constituent of SHS is particulate matter (PM_2.5), which is commonly used as a proxy for SHS exposure in air monitoring studies, and is routinely used as an index of impact of a smoke-free legislation.^(4–6)

Given the deleterious effects of acute and chronic exposure to SHS and public support for smoke-free legislation, many countries have moved to ban smoking in public places. These bans result in substantial gains in occupational and public health such as reductions in respiratory symptoms among bar workers and in the incidence of asthma and coronary heart disease among children and adults, respectively.^(7–9) On May 31, 2010, Greece announced the adoption of a comprehensive ban on smoking in public places (two-phased), the first of which came into force on September 1, 2010. Within this first phase, smoking indoors in all hospitality venues under 300 m² was prohibited (cafes, bars, restaurants), which included covered outdoor areas. The law was met with skepticism by the media due in part to the fact that previous partial laws adopted in 2009 (based on the “Spanish model”) were not entirely enforced and relatively ignored by the public.^(10,11)

The aim of the Hellenic Air Monitoring Study was to compare the levels of exposure to SHS within the hospitality industry in Greece after the implementation of the smoke-free legislation in cafes, bars, and restaurants and to compare the measurements with previous data collected during May 2010 (when a partial ban was in place) and in 2006 (when no ban was in place).

Methods

The Hellenic Air Monitoring Study

The Hellenic Air Monitoring Study is a national longitudinal cohort of hospitality venues within five regions of Greece, within which indoor air pollution attributable to SHS is assessed at six month intervals (waves). We sampled five urban areas in Greece: Athens and Heraklion in Southern Greece, Thessaloniki and Serres in Northern Greece, and Larissa in Central Greece. As we were unable to obtain a comprehensive list of hospitality venues in each city, we used a convenience sample of 150 venues (30 from each area) based on ease of access and popularity. We completed Wave 1 in March–May 2010 (during the partial ban) and Wave 2 from October–December 2010 (1 month after the enactment of the complete smoking ban). Out of the 150 venues assessed in Wave 1, we discarded one due to incomplete data leaving a total of 149 venues. In Wave 2, we successfully assessed 120 of the same venues, an 80% follow up rate. The number of missing venues (n=29) was due to the exclusion of betting parlors (n=2) and Internet cafes (n=5) from the follow-up, lost data on the data logger (n=7), and venues that were open in Wave 1 but closed during Wave 2 (n=15). In addition to the above two waves assessed in this study, we compared our measurements with data collected in 2006 (Wave 0) when no ban was in place (n=43 hospitality venues). Thus we were able to compare the PM_2.5 concentrations by type of legislation (no ban in 2006 vs. a partial ban in 2010 vs. a complete ban in 2010).⁽⁴⁾

Air monitoring methodology

We performed measurements using the TSI Sidepack AM510 according to standardized methodology for monitoring indoor air pollution attributable to SHS (Calibration factor 0.32, flow rate 1.7 L/min) that has been used previously to assess indoor PM_2.5 attributable to SHS in numerous studies.^(4,6,12) Field researchers were trained together during which a number of pilot venues were simultaneously assessed for descriptive characteristics and PM_2.5 concentrations. During the field work, sampling was discreet to avoid altering the employees and patrons normal behavior. We collected data on the number of cigarettes smoked, the number of people, air volume, and other factors that might affect the data (e.g., candles or cooking in area). The researchers also noted open windows and doors or sliding walls, which are common in the Greek hospitality industry due to the mild Mediterranean climate.⁽¹⁰⁾ So as to assure that limited weather differences between Wave 1 and Wave 2, the average temperature of the months in each wave were taken into account. According to the Hellenic National Meteorological Service (EMY), the average temperatures of March–April–May 2010 (15.4°C, 17.6°C, 21.5°C) were almost the same as the average temperatures of December–November–October 2010 (15.9°C, 18.9°C, 21.7°C).

Statistical analysis—Data management

We programmed the data logger to record at 1-min intervals, that is, averages of the previous 60 individual second measurements. During data management, we discarded the first and last 1-min measurements. We subtracted outdoor levels of PM_2.5 from the indoor levels to calculate indoor levels of PM_2.5 attributable to SHS. Outdoor levels were collected by assessing for 3 min the outdoor PM2.5 concentrations, further away from the venue (50 m) and away from any source of SHS. We then averaged the minute-logged measurements noted between entering and exiting each venue. The average outdoor PM_2.5 concentrations were 12 μg/m³, with a range between 5 μg/m³ and 25 μg/m³.

We classified venues as: (1) cafes, bars, or restaurants based on the basic service provided (coffee, alcohol, or food); (2) oen/closed based on the existence of open windows or sliding glass walls; (3) day of week (weekday: Monday to Friday vs. weekend: Saturday and Sunday); and (4) time of day (daytime: before 8 p.m. vs. nighttime after 8 p.m.).

Given the nonparametric distribution of the PM_2.5 levels, we performed Wilcoxon signed-ranked tests during the comparisons between legislations. We presented the results as means (SD) and ranges. We performed Spearman's ρ correlations to assess the relationship between smoker density (cigarettes per 100 m³ of venue volume) and indoor PM_2.5 concentrations. We performed a linear regression analysis for Waves 1 and 2 to quantify the factors influencing indoor PM_2.5 levels attributable to SHS. The variables included in the regression analysis were based on the level of statistical significance in the univariate analysis, which excluded the day of the week (nonstatistically significant). Furthermore, in the regression analysis, the “Café vs. restaurant” and “Bar vs. restaurant” acted as dummy variables in absence of each other. Beta coefficients and their 95% confidence intervals (β, 95% CI) are provided. We performed the statistical analysis using the statistical package PASW 18.0.

Results

Initially, in order to verify the validity of indoor PM_2.5 as a marker of SHS exposure, we correlated indoor PM_2.5 concentrations attributable to SHS with the smoker density within the venues among both Wave 1 venues (Spearman's ρ=0.614, p<0.001) and Wave 2 venues (Spearman's ρ=0.713, p<0.001).

Indoor SHS concentrations before and after the complete ban

Table 1 depicts the average PM_2.5 concentrations by city and venue type during the partial (Wave 1) and the complete smoking ban (Wave 2). According to our measurements and among matched pairs (n=120), indoor air pollution attributable to SHS dropped after the implementation of smoke-free legislation by 34% (from 137 μg/m³ to 90 μg/m³, p=0.003). This reduction was larger in bars (from 195 μg/m³ to 121 μg/m³, p=0.014) than in cafes (from 124 μg/m³ to 87 μg/m³, p=0.051) or restaurants (from 42 μg/m³ to 39 μg/m³, p=0.85). Among the venues that did go completely smoke free, and had a smoker density of 0 during the postban assessment, indoor PM_2.5 levels attributable to SHS dropped by 82%. Figure 1 shows the distribution of PM_2.5 concentrations in Wave 1 and Wave 2, by venue type. SHS exposure in open and closed air venues dropped following the implementation of the smoking ban from 129 μg/m³ to 51 μg/m³ and from 278 μg/m³ to 98 μg/m³, respectively (Table 2). We must note that in Wave 2 the majority of the venues had closed doors and windows (n=104), in comparison to the number of venues in Wave 1 (n=48), with only Heraklion and Athens in Wave 2 to have venues with open doors and windows (61 and 51%, respectively).

FIG. 1.

PM_2.5 levels attributable to SHS in bars, cafes, and restaurants in Greece during the partial (Wave 1) and complete (Wave 2) smoke-free legislation in Greece, 2010.

Table 1.

PM_2.5 Attributable to SHS in Matched Venues, by Venue Type and Sampling Site During the Partial (Wave 1) and Complete (Wave 2) Smoke-Free Legislation in Greece, 2010

		Wave 1 Preban (partial ban)			Wave 2 Postban (comprehensive ban)
	N	Mean (SD) in μg/m ³	Min–Max in μg/m ³	N	Mean (SD) in μg/m ³	Min–Max in μg/m ³	p-value^a
Total	120	137 (149)	1–735	120	90 (92)	0–373	0.003
by venue type
Bars	42	195 (169)	14–658	42	121 (13)	0–373	0.014
Café	56	124 (136)	3–735	56	86 (82)	0–286	0.051
Restaurants	16	42 (54)	1–179	16	38 (80)	1–330	0.847
By sampling site
Athens	13	320 (154)	106–560	13	100 (113)	0–324	<0.001
Heraklion	25	173 (209)	1–735	25	57 (61)	2–240	0.004
Thessaloniki	30	103 (101)	3–368	30	111 (99)	6–373	0.694
Serres	27	74 (65)	3–261	27	74 (73)	1–257	0.979
Larissa	25	116 (106)	3–410	25	109 (106)	2–372	0.823

p-Values based on Wilcoxon signed-ranked tests.

Table 2.

PM_2.5 Attributable to SHS by Descriptive Characteristics of the Entire Sample of Venues Assessed During the Partial (Wave 1) and Complete (Wave 2) Smoke-Free Legislation in Greece, 2010

		Wave 1 Preban ^a (partial ban)			Wave 2 postban ^a (comprehensive ban)
	N	Mean (SD) in μg/m³	Min–Max in μg/m³	N	Mean (SD) in μg/m³	Min–Max in μg/m³
Descriptive characteristics
Open air venues	98	129 (136)	1–735	40	51 (61)	0–324
Closed air venues	48	278 (379)	3–2480	104	98 (96)	0–373
Sampled during the day	45	92 (89)	3–380	60	60 (66)	0–233
Sampled during the night	104	210 (288)	1–2480	86	102 (100)	0–373
Sampled Monday–Friday	56	150 (166)	3–897	74	90 (100)	0–373
Sampled Saturday–Sunday	93	189 (291)	1–2480	72	79 (78)	0–324
Smoke-free venues
Yes	8	6 (4)	1–14	120	84 (90)	0–373
No	141	184 (255)	3–2480	0	n/a	n/a

Sample sizes are different as a direct comparison of characteristics within recruited versus followed up venues was performed.

Comparisons of indoor SHS concentrations by type of legislation

Using data from a previous survey, we compared PM_2.5 concentrations in 2006 (Wave 0, when no ban was in place, n=43), with those measured in 2010 during Wave 1 (partial ban, n=120) and Wave 2 (complete ban, n=120). Overall PM_2.5 concentrations attributable to SHS within hospitality venues in Greece over the past 5 years have fallen from 268 μg/m³ in 2006, to 174 μg/m³ in Wave 1 and down to 89 μg/m³ in Wave 2, a 67% decrease. These results indicate a reduction in indoor levels of PM_2.5 attributable to SHS during both the transition from no ban to a partial ban, and from a partial ban to a complete ban; however, these concentrations may not be directly comparable due to a different population sample. It is interesting to note that among the three types of venues assessed we noted the greatest reduction among restaurants within which PM_2.5 concentrations fell from 273 μg/m³ in 2006 to 39 μg/m³ in 2010 (postban), an 85% reduction in SHS exposure. In regard to the average smoker density throughout Greece (cigarettes per 100 m³) it was found to reduce from 2.5 per 100 m³ in 2006 to 1.93 during the partial ban and 1.31 in the complete, but not enforced, ban. So as to possibly assess enforcement we also assessed the change in smoker density by city, which was found to decrease. The largest drop in smoker density was found in Athens (3.0 preban to 1.6 postban), while smoker density also reduced in Larissa (2.1 to 1.7), in Serres (1.6 to 1.0), and in Thessaloniki (1.7 to 1.3). In Heraklion, smoker density was not found to change (1.1 preban vs. 1.0 postban).

So as to verify the above-noted reductions, and to evaluate the transition in legislation with the use of a cohort study design, matching pairs of venues were identified and their PM_2.5 concentrations were compared and thus a longitudinal approach was also used. According to this sensitivity analysis, PM_2.5 concentrations between 2006 (Wave 0, no ban) and Wave 1 of 2010 (partial ban) in 10 matching venues, were not found to change significantly (218 μg/m³ vs. 178 μg/m³, p=0.58). On the other hand, PM_2.5 concentrations measured in 2006 (Wave 0, no ban) vs. Wave 2 of 2010 (complete ban) in nine matching venues, were found to reduce significantly (249 μg/m³ vs. 46 μg/m³, p=0.011).

Factors influencing indoor SHS concentrations pre- and postban

To further assess the factors contributing to indoor PM_2.5 concentrations before and after the smoking ban, we applied linear regression models. As Table 3 demonstrates, the strongest functional determinant of the concentrations of indoor air pollution attributable to SHS was the existence of open doors and windows, which would increase indoor air ventilation, and which we found to be related to a lower SHS concentrations when open (β=147.5 μg/m³ preban and 47.9 μg/m³ postban). Although the existence of open doors and/or windows did reduce, it did not eliminate SHS exposure. We found that venue type was related to indoor air pollution, with cafes (β=33.7 μg/m³ preban and 24.7μg/m³ postban), and bars (β=86.6 μg/m³ preban and 45.0 μg/m³ postban), being more heavily polluted than restaurants. Moreover, in both pre- and postmeasurements the average number of smokers per 100 m³ in the venue was also a significant determinant of indoor air pollution attributable to SHS (β=53.5 μg/m³ preban and β=20.2 μg/m³ postban).

Table 3.

Factors Found to Increase Indoor PM_2.5 Levels Attributable to SHS (in μg/m³) During the Partial (Wave 1) and Complete (Wave 2) Smoke-Free Legislation in Greece, 2010

Wave 1 Preban ^a	β coefficient ^a	(95% CI of the β)
Closed versus open venue	147.5	(70.0 to 224.9)
Average smoker density	53.5	(31.3 to 75.8)
Day versus night sampling	46.5	(−39.5 to 132.6)
Bar versus restaurant	86.6	(−20.4 to 2193.7)
Cafe versus restaurant	33.7	(−71.4 to 138.8)
Wave 2 postban^a
Closed versus open venue	47.9	(18.8 to 77.1)
Average smoker density	20.2	(11.7 to 28.6)
Day versus night sampling	20.1	(−6.7 to 47.0)
Bar versus restaurant	45.0	(6.45 to 83.6)
Cafe versus restaurant	24.7	(−11.9 to 61.3)

Linear regression analysis controlling for all factors in the table, the inclusion of criteria was based on a p<0.1 in the univariate analysis.

Discussion

Main findings

We found that the implementation of the Greek smoke-free legislation in bars cafes and restaurants in September 2010 resulted in a 34% reduction in indoor PM_2.5 concentrations attributable to SHS in comparison to previous, partial ban levels. However, a reduction in indoor exposure to SHS was also noted during the transition from a “no-ban” status to a partial-ban status as indicated by the reduction in smoker density. Comparing the PM_2.5 concentrations among venues assessed in 2010 (complete ban) with those assessed in 2006 (no ban), we found an average 67% decrease in indoor PM_2.5 levels attributable to SHS occurred in Greece over the past 5 years, although comparisons of paired observations indicated an even greater (−85%) reduction in PM_2.5 concentrations.⁽⁴⁾

Previous research and occupational health implications

The noted reduction could possibly be attributable to population support. Research among the Greek population has indicated that nonsmokers before the ban stated to be more likely to support the adoption of a complete smoke-free legislation either by voicing discontent to the identified smoker or employee or by notifying officials.⁽¹³⁾ The success of the current smoke-free legislation in Greece is comparable to the effectiveness of the implementation of smoke-free legislation in other countries. After the implementation of the ban in Norway, total PM_2.5 concentrations in bars and restaurants fell from 262 to 77 μg/m³, and a similar reduction was reported in Scotland (246 μg/m³ to 20 μg/m³).^(14,15) In Israel, after the implementation of partial smoke-free legislation, albeit poorly enforced, indoor PM_2.5 concentrations within Jerusalem and Tel Aviv were reduced from 245 μg/m³ to 161 μg/m³.⁽¹²⁾ According to Valente et al.⁽⁵⁾ the application of a smoking ban in the Italian hospitality industry led to a considerable reduction in the exposure to SHS within these venues. Preban levels of 119 μg/m³ fell to 38 μg/m³ postban, associated with a concomitant reduction in urinary cotinine levels of employees. Previous research in Athens had noted elevated cotinine concentrations among nonsmoking bar workers in greater Athens prior to the smoke-free legislation (during the partial ban), and identified a strong association between indoor PM_2.5 concentrations and urinary cotinine levels. These associations imply that our observed 34% reduction in PM_2.5 concentrations after the smoke-free legislation would lead to a reduction in employee cotinine levels, and lower risk of disease.^(16,17) The implementation of a complete smoke-free legislation has been shown to alleviate respiratory and sensory symptoms of bar workers, while also shown to lead to a reduction in concentrations of tobacco-specific carcinogens.^(7,18) The benefits of smoke-free legislation are not limited to the occupational workforce. Reducing SHS smoke exposures reduces the impact of cardiovascular disease, stroke, and asthma, and further denormalizes smoking—a key point in sustaining a reduction in tobacco use.^{(7–9,19–21)}

Despite the complete indoor ban, a number of smoke-free venues in Greece had slightly elevated indoor PM_2.5 levels attributable to SHS due to smoking in adjacent outdoor areas. Researchers have noted this phenomenon before and classified it as SHS drift. Doors and windows facing these outdoor smoking areas can be a source of SHS. Legislative action is needed to regulate smoking in such areas so as to eliminate exposure of patrons and employees to SHS.^(22,23) Furthermore, it is of interest to note that the reductions were noted to be higher in Athens and in Heraklion, two cities in southern Greece, in comparison to the participating cities in North-Central Greece. Such differences we attribute to the different climate between these cities in Wave 2, as doors and windows were open in more venues in southern Greece. However, these differences could also be due to enforcement; however, no such data was available and smoker density was comparable in the postban measurements by city. Further research is needed to investigate into the above.

Strengths and limitations

Repeated measurements in the same venues before and after the implementation of the smoke-free legislation allow us to confidently interpret the reduction in PM_2.5 concentrations attributable to SHS (partial ban vs. complete ban). The methods are routinely used to assess indoor air pollution attributable to SHS, and thus our national results are directly comparable to the results of studies in other countries or regions. Although the 5-year trends in SHS concentrations are of interest, we must note that these studies (2006 survey vs. 2010) are not entirely comparable as the sample size is not the same (43 vs. 120 venues). Only nine matching pairs were identified during this period (2006–2010). However, the associations identified overall and through these matched pairs were in all cases strong and statistically significant. Within the context of our study we used PM_2.5 concentrations as an indicator of SHS exposure. Other methods of assessing exposure to SHS such as worker cotinine levels, airborne nicotine sampling, can also be used and additional research in Greece is being performed to assess these markers of exposure.

Conclusions

The observed reduction in indoor SHS exposure within the hospitality industry in Greece after the transition to a partial ban and from a partial ban to a complete ban is a positive step toward protecting occupational and public health, whereas the 67% reduction in PM_2.5 attributable to SHS when comparing the no-ban to the postban periods are even more promising findings. This reduction exists despite the elasticity of the enforcement mechanisms and in the absence of a comprehensive media campaign. Strict enforcement of the law supported by a mass media campaign of that could lead to an even greater reduction in SHS concentrations in the hospitality industry with substantial benefits to the population of Greece.

Footnotes

Acknowledgments

Funding was provided by the George D. Behrakis Foundation through the HEART project (Hellenic Action for Research Against Tobacco). We would like to dedicate this research in memory of Dr. Markos Minas.

Author Contributions

N.A., C.N., V.D., M.M., E.P., G.G., K.I.G., P.P., A.A., and C.L. performed the data collection, separate city data cleansing and helped draft the manuscript. M.B. and E.P. participated also in data cleansing and analysis, whereas C.V. conceived the idea and had the main role in study design, data interpretation, and manuscript preparation. P.B., M.B., G.C., and D.D. participated in study design, data interpretation, and manuscript preparation, whereas all authors read and approved the final manuscript. C.I.V., P.P., K.G., and P.B. are also members of the national steering committee on tobacco control, of the Ministry of Health and Social Solidarity, Athens, Greece.

Author Disclosure Statement

The authors declare that no conflicting financial interests exist.

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