INTRODUCTION

Second-hand tobacco smoke is one of the most widespread air pollutants in indoor environments¹. Exposure to it has been linked to several health outcomes, including respiratory asthma, infections of the lower respiratory tract, otitis media and sudden infant death syndrome, as well as ischaemic heart disease and lung cancer in adults¹. The World Health Organization (WHO) Framework Convention on Tobacco Control (FCTC), an international health treaty, promotes smoke-free environments to achieve effective protection from the hazards of secondhand tobacco smoke. Article 8 of the FCTC calls upon Parties to implement measures for protection from exposure to tobacco smoke in public places, including but not limited to indoor workplaces, public transportation, indoor public places, and other public places². Guidelines for the implementation of Article 8 have been developed further to assist countries in the adoption and implementation of smoke-free measures, as well as in identifying the key elements of their smoke-free legislation³.

Ratification of the WHO FCTC is associated with the accelerated implementation of key demand-reduction measures, including smoke-free laws^4,5, with evidence of significant dose-respondent decreases in smoking prevalence and highest-level implementation of these measures⁶. Since 2004, many countries have adopted complete national smoking bans in public places, which has resulted in benefits to both non-smokers (less second-hand smoke exposure) and smokers (tend to smoke less, have greater cessation success, and experience more confidence in their ability to quit)7. However, only 16% of the world’s population is covered by comprehensive smoke-free laws⁷. Furthermore, these policies at the national level have only been adopted within the public domain and do not usually apply to private settings, such as homes and cars, where exposure to second-hand tobacco smoke is still common^8,9. Nevertheless, some studies indicate that smoke-free legislation has had unexpected effects in promoting private smoke-free settings^10,11. It has been hypothesised that public policies affect a variety of psychosocial and behavioural variables¹². We hypothesise that the implementation of robust smoke-free legislation in public places will lead to the subsequent cessation of smoking in public places; this will in a second stage lead to changes in psychological mediators (e.g. awareness of the health effects of second-hand tobacco smoke) and in a third stage to behavioural changes, such as the establishment of voluntary tobacco-free policies in private settings.

Little is known on the extent to which smokers implement smoke-free bans within their own private settings. Thus, the objective of this study was to assess existing smoking rules and their correlates in smokers’ private settings, such as homes and cars, in six European countries.

METHODS

RESULTS

Smoking rules at home

Among all smokers across the six countries, 26.5% reported a total smoking ban in their home, with Hungary having the highest prevalence (35.5%) and Spain the lowest (13.1%); see Figure 1 and Supplementary Table 1. On the other hand, 28.8% of smokers across the six countries had no-smoking rules in their homes, varying from 20.2% in Romania to 45.6% in Spain. Overall, the prevalence of a total smoking ban in homes was similar in both sexes, but was significantly lower among participants aged 55 years or older and among those with lower educational level (Table 1). The prevalence of a total smoking ban in homes was higher among smokers with a non-smoker partner and among those with more children. Forty-two per cent of smokers who had children less than one year of age had a total smoking ban in their homes, varying from 11.4% in Spain to 56.6% in Romania (Supplementary Table 2). Additionally, there was a higher prevalence of total smoking bans among homes of smokers who reported to smoke less, were least nicotine dependent, and who had ever attempted to quit smoking (Table 1). Information for each EU MS is provided in the Supplementary Table 2.

Table 1

Prevalence of smoking rules in smokers’ homes, according to sociodemographic and smoking characteristics, 2016

	Overall		Total ban		Partial ban		No rules
	n	%a	n	%b	n	%b	n	%b	pc
Overall	5967	100.0	1686	26.5	2661	44.7	1620	28.8	<0.001
Sex									<0.001
Men	3155	57.4	910	26.7	1328	42.6	917	30.7
Women	2812	42.6	776	26.4	1333	47.6	703	26.0
Age (years)									<0.001
18−24	507	10.1	161	28.8	188	36.8	158	34.4
25−39	1757	31.5	553	29.6	782	45.3	422	25.1
40−54	1992	34.1	534	25.7	957	46.5	501	27.8
≥ 55	1711	24.4	438	22.9	734	44.8	539	32.3
Educational level									<0.001
Low	2207	37.7	563	23.5	951	42.6	693	33.9
Intermediate	3074	51.4	909	28.2	1382	45.3	783	26.5
High	652	10.9	206	29.7	311	48.9	135	21.4
Smoker partner									<0.001
Yes	2242	58.9	569	24.6	1088	47.9	585	27.5
No	1629	41.1	614	35.9	737	45.8	278	18.3
Children									<0.001
Yes	1958	33.6	702	34.6	929	47.2	327	18.2
No	4001	66.4	982	22.5	1729	43.5	1290	34.0
Number of children									<0.001
0	4001	66.4	982	22.5	1729	43.5	1290	34.0
1	1000	17.1	352	34.3	493	49.5	155	16.2
2	709	12.1	280	37.8	314	43.4	115	18.8
≥3	249	4.4	70	27.6	122	48.3	57	24.1
Children’s age (years)d
<1	140	7.9	59	42.0	65	47.4	16	10.6	0.041
1−5	731	38.6	287	37.4	319	44.1	125	18.5	0.149
6−12	1029	53.2	360	32.9	505	48.9	164	18.2	0.247
13−17	760	37.4	255	33.1	356	46.0	149	20.9	0.119
Cigarettes smoked per day									<0.001
≤ 10	2063	33.2	764	35.9	892	43.2	407	20.9
11−20	3059	52.8	771	23.5	1405	45.7	883	30.8
21−30	523	8.9	97	16.9	224	45.2	202	37.9
>30	314	5.1	51	14.3	138	44.2	125	41.5
Nicotine dependence									<0.001
Low	2341	40.0	802	33.5	1021	43.7	518	22.8
Medium	2799	51.1	680	22.3	1277	45.4	842	32.3
High	516	9.0	74	13.0	222	44.0	220	43.0
Attempts to quit smoking									<0.001
Yes	3223	53.4	990	29.0	1439	45.3	794	25.7
No	2741	46.6	695	23.6	1221	44.1	825	32.3

a Weighted percentages per column.

b Weighted percentages per row.

c χ² test.

d Multiple response.

Table 2

Comparison of smoking rules (partial ban vs total ban; no rules vs total ban) in smokers’ homes, according to independent variables, 2016

	Partial ban vs Total ban			No rules vs Total ban
	PR	95% CI	pa	PR	95% CI	pa
Country
Germany	1	-		1	-
Greece	1.23	1.07−1.42	0.005	1.68	1.29−2.19	<0.001
Hungary	0.94	0.80−1.10	0.417	1.12	0.85−1.47	0.422
Poland	0.99	0.85−1.15	0.883	1.33	1.04−1.71	0.026
Romania	1.07	0.92−1.24	0.394	1.27	0.97−1.65	0.082
Spain	1.40	1.23−1.60	<0.001	2.38	1.89−2.98	<0.001
Sex
Men	1	-		1	-
Women	1.09	1.04−1.15	0.001	1.12	1.02−1.22	0.014
Age (years)
18−24	1.04	0.87−1.24	0.692	1.15	0.90−1.47	0.259
25−39	1.04	0.94−1.15	0.445	1.01	0.88−1.15	0.898
40−54	1.04	0.95−1.14	0.356	0.96	0.85−1.09	0.558
≥55	1	-		1	-
Educational level
Low	1.05	0.94−1.18	0.370	1.51	1.20−1.90	0.001
Intermediate	1.00	0.90−1.12	0.995	1.21	0.97−1.51	0.097
High	1	-		1	-
Smoker partner
Yes	1.18	1.10−1.27	<0.001	1.49	1.33−1.68	<0.001
No	1	-		1	-
Children
Yes	1	-		1	-
No	1.19	1.10−1.29	<0.001	1.64	1.44 −1.86	<0.001
Cigarettes smoked per day
≤10	1	-		1	-
11−20	1.22	1.12−1.34	<0.001	1.41	1.20−1.64	<0.001
21−30	1.22	1.06−1.42	0.007	1.52	1.22−1.90	<0.001
>30	1.18	0.94−1.48	0.147	1.53	1.10−2.14	0.013
Nicotine dependence
Low	1	-		1	-
Medium	1.03	0.94−1.13	0.486	1.17	1.01−1.36	0.038
High	1.15	0.96−1.39	0.128	1.33	1.01−1.76	0.044
Attempts to quit smoking
Yes	1	-		1	-
No	1.06	0.99−1.13	0.090	1.18	1.06 −1.31	0.002

Prevalence ratios (PR) are derived from Poisson regression models, adjusted for all independent variables.

a χ² test.

Figure 1

Prevalence of smoking rules in smokers’ homes and cars with children, 2016

We further assessed the association of smoking rules in homes (partial vs total ban; no rules vs total ban) with different independent variables, where prevalence ratios >1 indicate less smoking rules in homes (Table 2). Compared to smokers from Germany, the countries where smokers were more likely to have a partial smoking ban or no-smoking rules in their homes were Spain (PR=1.40, 95% CI: 1.23-1.60 for partial vs total smoking ban; PR=2.38, 95% CI: 1.89-2.98 for no-smoking rules vs total smoking ban) and Greece (PR=1.23, 95% CI: 1.07-1.42 for partial vs total smoking ban; PR=1.68, 95% CI: 1.29-2.19 for no-smoking rules vs total smoking ban). The variables significantly associated with not having smoking rules in homes were: female, low educational level, partner who smokes, no children, more CPD, more nicotine dependent, and never attempted to quit smoking (Table 2).

DISCUSSION

More than a quarter of smokers surveyed across six EU MS reported having a total smoking ban in their homes; a similar proportion of smokers had no smoking rules. Prevalence of total smoking ban in homes varied across countries, from 13.1% in Spain to 35.5% in Hungary. These findings are consistent with data from other studies conducted in European countries within the ITC Project^17-20 that indicated cross-country differences in the prevalence of smoke-free homes, varying from 13% in Scotland in 2007 to 38.2% in Germany in 2009. The later studies also indicated an increased prevalence of smoke-free homes in European countries over two survey waves^17-20.

A different situation was found in cars when children were present where 61% of smokers had a total smoking ban and only 16% had no rules, with less heterogeneity observed across countries, varying from 51.8% in Greece to 67.7% in Germany. Data from other ITC studies conducted between 2007 and 2008 in France, Germany and the Netherlands indicated generally lower support for smoking bans in cars when children are present (41%, 48%, 64%, respectively)²¹, probably due to the time that has elapsed between these ITC studies and ours. In a brief review that included eight studies examining attitudes of adult smokers to smoking restrictions in cars with children²², the authors found that support for such regulations generally increased with time, for example, from 63%, 45% and 51% of surveyed smokers in New South Wales (Australia) in 1994, 2000 and 2004, respectively, to 96% in New Zealand in 2007-2008 and 87% in South Australia (Australia) in 2008²².

It is noteworthy to mention some differences observed in the prevalence of partial smoking rules and no-smoking rules in homes. For example, we observed that the higher the educational level, the higher the prevalence of partial bans in homes and the lower the prevalence of no rules. Also, the trend in the prevalence of the different rules differed by sex, age group, educational level and having children. The prevalence of no-smoking rules among participants who had children was almost half the prevalence of no-smoking rules among those who did not have children; conversely, the prevalence of partial bans was slightly higher among those who had children. In cars, such differences in prevalence are not remarkable, but we still observed some by educational level in a similar way to what we observed in homes. By CPD, the more the CPD smoked the more the prevalence of partial smoking rules and no-smoking rules; but the increase is two-fold for partial rules, whereas it is three-fold for no rules.

In our study, some of the factors that seem to affect smokers’ support for smoke-free regulations in these private settings are: having higher educational level, having children, and having a non-smoker partner. Age seems to have a different effect on the support for smoking regulation in these settings; higher support for smoke-free homes was observed in younger people and higher support for smoke-free cars in older people. Our data also showed that a total smoking ban in homes and cars was more likely among smokers with higher educational level, as shown by others^23,24. This possibly indicates that the adoption of voluntary smoke-free rules among smokers follows diffusion of innovations theory (early adopters are those from more advantaged socioeconomic groups)²⁵. Although having children is taken into account in deciding to have both partial and total smoking bans in both settings, we observed that this factor was more important for total smoking bans. This finding has potential implications for the encouragement of smokers with partial smoking bans to move towards total smoking bans in their homes and cars. In addition, having a non-smoker partner was also associated with smoking bans in homes and cars, indicating the importance of social support in encouraging smoke-free environments in private settings. The social system is crucial for the diffusion of smoking bans, because decisions are made not only at the individual but also at the collective and societal level²⁵, thus highlighting the importance of the interaction between the individual and the environment²⁶.

The results show, however, that some improvements are needed to protect non-smokers from second-hand smoke exposure in private settings, especially vulnerable members of the population, such as children. It has been proven that partial smoking does not effectively protect non-smokers from second-hand tobacco smoke due to leaking smoke^27-29; furthermore, smoking in this context is still being promoted as a social norm. Furthermore, our findings demonstrate differences among smokers across the six EU MS in the attempt to implement smoking bans in private settings. Cross-country variation might reflect the level of denormalization of smoking in each country. Furthermore, differences may be related to the implementation status of smoke-free legislation, namely Article 8 of the FCTC, within each EU MS. While smoke-free legislation generally does not have wide jurisdiction over private settings, several studies have demonstrated the positive impact of smoke-free legislation on these unregulated places^10,11,30-33. Comprehensive population-level policies may increase the prevalence of smoke-free environments in private settings^33,34 by promoting awareness of the harmful effects of second-hand smoke exposure and the beneficial effects of reducing such exposure. Among the EU MS participating in our study, Germany and Poland are the countries were the least proportion of the population is protected by smoke-free laws regulating public places (national regulation is absent in Germany, while Poland has few public places where smoking is prohibited by national law)³⁵. When examining the prevalence of total or partial smoking bans by country, no clear pattern in relation to smoke-free environment legislation was observed; therefore, further longitudinal analyses are necessary to better explain the effects of smoke-free regulations and voluntary smoking bans in private settings. Also, studies should take into account the degree to which public regulations are enforced (overall and by country) and its relationship to other issues, such as social conditions that may affect smoking bans in private settings.

Disentangling the relationship and causal pathway between the awareness of second-hand smoke risks, the country-level climate of smoking denormalization, the degree of implementation of smoke-free legislation, and the individual opting for smoke-free homes and cars, are challenging issues that warrant further research. A comprehensive understanding of the factors associated with the voluntary implementation of smoke-free rules in private settings and the mechanism of impact on the population, can contribute to enhancing and tailoring interventions.

This study has some limitations. First, this is a survey conducted among smokers; thus, some information bias on smoking rules is possible due to social desirability and the general antismoking climate, with country variations across EU-MS. These results, therefore, cannot be generalised to all populations, such as non-smokers. Voluntary smoke-free rules in homes and cars are, however, more frequent among non-smokers^36-40. Second, survey questions on smoking rules in cars were asked specifically when children were present in the car, indicating that smoking may still occur in the absence of minors in the car. Third, the cross-sectional nature of the analysis precludes any inference about cause-effect relationships between the variables studied. Fourth, the use of self-reported information may introduce a source of bias that can affect the validity of our results. Nevertheless, self-reporting of smoking bans has been shown to have moderate to high correlation with measures of airborne nicotine, with excellent specificity and positive predictive values²⁹. Also, the use of questionnaires is extensive in population studies, because it allows reaching many people at low cost.

On the other hand, the study has many strengths, including a large sample size, the representativeness of the samples of smokers in each country, and the use of a common questionnaire, derived from the expansive ITC Project¹⁴. Moreover, the use of six EU MS with diverse geographical and sociodemographic characteristics provided variability in the implementation extent of smoke-free rules in private settings. These EU MS have different smoking prevalence and different stages of the tobacco epidemic (all of them at advanced stages, III or IV of the tobacco epidemic model)⁴¹. In addition, these countries share some legislation, such as the EU Tobacco Products Directive, whilst maintaining their own legislation. This study provides a baseline assessment for analysis of prospective data in successive waves of the EUREST-PLUS cohort study that will allow trends to be examined. The current analysis will further facilitate evaluation of changes in voluntary smoke-free rules in private settings, and other smoking-related variables, as a result of changes in legislation.

CONCLUSIONS

This study found that a quarter of smokers have a voluntary smoking ban at home and almost two-thirds for cars in the presence of children. These figures, however, are far from satisfactory and highlight the need to promote public policies and interventions aimed at increasing the number of smoke-free homes and cars.