Abstract

Background

Smokers' knowledge of the risks of second-hand smoke (SHS) and the role this plays in implementing behaviours to reduce the SHS exposure of others have not been thoroughly explored. Mass media health promotion is used to promote behaviour change partly by providing information on the consequences of behaviour. In England, between 2003 and 2006, frequent mass media campaigns highlighted the toxicity of SHS.

Objectives

To examine peoples' knowledge of SHS-related illnesses in England over time, identify the determinants of good knowledge and to assess its importance in predicting SHS-protective behaviours.

Methods

Statistical analysis of repeat cross-sectional data (1996–2008) from the Omnibus Survey to explore the trends and determinants of knowledge of SHS-related illnesses and the determinants of SHS-protective behaviours.

Results

Only 40% of smokers had ‘good’ knowledge of SHS-related illnesses compared with 65% of never smokers. Knowledge increased markedly when frequent SHS-related mass media campaigns (2003–06) ran, compared with earlier years (1996–2002). Smokers with better knowledge were more likely to have smoke-free homes [odds ratio (OR): 1.10, 1.04–1.16] and abstain from smoking in a room with children (OR: 1.11, 1.09–1.14).

Conclusions

The low levels of knowledge of some SHS-related conditions, especially among smokers, and the relationship between knowledge and SHS-protective behaviours, suggest that greater efforts to educate smokers about the risks associated with SHS are worthwhile.

Introduction

Knowledge acquisition is an important step in the process of health behaviour change.1–7 Nevertheless, the relationship between knowledge and behaviour change is complex. There is often a discrepancy between one's beliefs and behaviours known as cognitive dissonance. Dissonance theory proposes that in order to achieve consonance, either the belief or the behaviour must be changed.8,9 Although some smokers change their smoking behaviour by quitting or reducing their smoking,10 other evidence suggests that many smokers choose to understate the scientific evidence or adduce anecdotal evidence to counter risks publicized in the media instead.11,12

There is no safe level of exposure to SHS.13,14 People's knowledge of the impacts of SHS and the role this might play in smoking practices have not been thoroughly explored. It may be the case that smokers' concerns about harming others is a motivating factor in quit attempts.15 Furthermore, for those smokers who are unable or unwilling to quit, concerns about the dangers and decreased social acceptability of smoking may influence smokers to take measures to protect others from their smoke.16 In Queensland, Australia, researchers found that smokers immediately indicated that they would avoid exposing both adults and children to their SHS after they were informed of the risks of SHS to non-smokers.17 Qualitative work in Scotland indicated that concerns about the possible health risks were cited as the main reason for both total and partial smoking restrictions at home.18 Similarly, in the USA, strong belief in the danger that SHS posed to children's health was associated with home smoking bans amongst smokers.19 It may be the case that smokers' unrealistic optimism about their own risk of illness is juxtaposed by their concern about the impact of their smoking on others.20 Indeed, a phenomenon known as the ‘third person effect’ suggests that people often discount the personal effects of harmful environments and at the same time recognize the risks to others.21 However, results from a small-scale US study on children with asthma showed that although many parents were aware that their smoking exacerbated the symptoms of their children's asthma, only 33% of these smokers reported having a smoke-free home.22 Similarly, a UK study found that 85% of parents from smoking households believed that smoking affects children's health, yet only 30% prohibited smoking in the house. However, 65% of these parents did report other measures that they believed protected against SHS exposure, e.g. opening a window or not smoking in the same room with a child.23 Recent qualitative UK research has suggested that smokers are confused about the specific impacts of SHS and are displaying classic cognitive dissonance behaviours, as well as employing the aforementioned protective smoking practices. The authors conclude that mass media campaigns could be used to give information on the ineffectuality of these behaviours in order to reduce ‘half-way’ measures.24

The Health Bill enacting smoke-free legislation (SFL) in England was passed in February 2006 and SFL was implemented on 1 July 2007. Awareness of the dangers and concerns about the impact of SHS might have been expected to be particularly salient during the build-up to SFL. In 2003, debate surrounding the issue of smoke free started in earnest and was highly publicized in the media as a result. In the same year, a government-funded TV, press and billboard campaign on the effect of SHS on children, titled ‘If you smoke, I smoke’ was launched. Anti-SHS mass media campaigns frequently ran between December 2003 and April 2007.25 Thereafter, government-funded campaigns focused on compliance with SFL. Action for Smoking and Health (ASH) monitored their personal media coverage and noted it was at its highest between March 2004 and February 2006, with stories mentioning ASH England reaching an average audience of 4.5 million people a week.25

Evidence suggests that media coverage of debates over smoke-free policies and SHS mass media health promotion campaigns help disseminate the implicit message that SHS exposure is unacceptable.26 Furthermore, increased awareness of the issue, including knowledge of the dangers of SHS, may influence subsequent knowledge and smoking behaviours.

In England, recent evidence shows that 79% of children whose parents smoke are still exposed to SHS at home.27 In the absence of definitive evidence of what works in terms of increasing the prevalence of smoke-free homes,28 it is worth exploring the factors that may be influential in achieving reduced SHS exposure in children. This paper aims to quantitatively explore levels of and trends in knowledge of the health impacts of SHS exposure in England, the predictors of knowledge and, in turn, to assess whether knowledge is associated with SHS-protective behaviours.

Methods

Data

The Omnibus Survey (OS) is a monthly survey conducted using a multistage design by the Office of National Statistics to produce a nationally representative sample of adults living in private households in Great Britain, with one interviewee per household.29 A smoking module was conducted in October and November every year, apart from 1998. Data from 2007 onwards were therefore collected post-SFL. A sampling error compromised the 2008 survey results, and therefore the 2008 survey was repeated in February and March 2009. For simplicity, we refer to these data as the 2008 data. The smoking module was discontinued in 2009. Between 1996 and 2004, ∼1800 adults were interviewed each month; ∼1200 were interviewed since 2005. Response rates from 1996 to 2008 ranged from 61 to 70% of the eligible sample.

Outcome measures

Knowledge

Respondents were asked 10 questions about their knowledge of SHS-related illnesses, 5 about illnesses in children and 5 in adults. ‘Do you think that living with someone who smokes does, or does not, increase a child's risk of: asthma/ear infection/cot death/chest infections/other infections?’ and ‘Do you think that breathing in someone else's smoke increases the risk of a non-smoker getting: asthma/lung cancer/heart disease/bronchitis/coughs & colds?’ Response options are ‘increases risk’ or ‘does not increase risk’ of each illness.

SHS-protective behaviour

Since 2006, the OS asked ‘all’ respondents to describe their home smoking policy: smoking is not allowed at all, smoking is allowed in some rooms or at some times, smoking is allowed everywhere or don't know. In our analyses, a smoke-free home describes a household where smoking is not allowed at all.

Since 1997, ‘smokers only’ have been asked about their smoking behaviour when in a room with a non-smoking adult and a child; whether they smoke the same number of cigarettes as usual, smoke fewer, do not smoke at all or other. Smokers are asked regardless of whether they report a smoke-free home as it does not only refer to smoking within their own home.

Analyses

We examined the levels of and trends (1996–2008) in knowledge of SHS-related illnesses before creating a composite knowledge score by giving one point for every correctly identified illness. As knowledge of respiratory illnesses is relatively common1 and many of the questions asked were about respiratory illnesses, a total score of 8–10 was taken to indicate good knowledge.

To determine the predictors of good knowledge and SHS-protective behaviours, the data were analysed using univariate and multivariate logistic regression, with adjustments made for the OS complex sampling design. A weighting factor was applied to correct for unequal probability of selection.

The predictor variables included were age group, gender, smoking status, social class, number of cars owned, number of adults in the household and age of youngest child. To evaluate changes over time and to crudely assess whether mass media campaigns have impacted on knowledge or SHS-protective behaviour, three time periods were created, 1996–2002 (pre-SHS-media campaigns), 2003–06 (during SHS-media campaigns) and 2007–08 (post-SFL). Although one campaign on the impacts of SHS ran between March and April 2007, from then until July 2007 the campaigns focused on explaining compliance with legislation. No SHS-mass media campaigns were run in 2008.

The predictive ability of each model was assessed using predicted probabilities to compute the receiver operating characteristic. A value of 1 represents perfect predictive fit, whereas 0.5 means the model is synonymous with a random guess.30 An area under the curve (AUC) value of 0.7 is representative of a good fit.31

The SHS-protective behaviour analyses included knowledge of SHS-related illnesses and attitudes towards restrictions in three public places. A composite score of 0–3 was created for agreement with smoking restrictions in pubs, restaurants and workplaces.

Results

The sample distribution for gender and age for each annual sample are consistent with national population estimates.32 A total sample of 32 630 respondents was obtained across the 12-year period (Table 1). Approximately 50% of respondents had never smoked, 27% were ex-smokers and 24% were current smokers (17% light and 7% heavy smokers). Examining annual smoking prevalence rates showed that, in line with other national surveys,33 smoking prevalence decreased from 28% in 1996 to 21% in 2007.

Table 1

Characteristics of the OS England sample by year (1996–2008); proportion of respondents in each socio-demographic subgroup (%)

Socio-demographics 1996 1997 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008a Total 
Gender 
 Male 49 46 46 49 43 46 46 46 45 46 47 45 15 101 (46) 
 Female 51 54 54 51 57 54 54 54 55 54 53 55 17 529 (54) 
Age group (years) 
 16–24 12 13 13 12 13 12 14 12 11 12 11 4008 (12) 
 25–44 38 36 37 35 35 34 34 35 36 34 33 31 11 450 (35) 
 45–64 32 33 31 32 31 33 32 33 32 34 35 36 10 585 (32) 
 65+ 18 18 19 22 21 20 20 20 21 20 20 24 6587 (20) 
Smoking status 
 All smokers 28 25 26 25 23 25 23 22 22 24 21 19 7924 (24) 
 Light (0–20/day) 19 17 18 17 16 17 16 16 16 18 15 2244 (7) 
 Heavy (20+/day) 14 5680 (17) 
 Ex 26 28 28 28 26 26 26 28 26 27 27 36 8917 (27) 
 Never 46 47 46 47 51 49 51 50 51 49 52 55 15 721 (48) 
Social class 
 Professional and managerial 32 30 34 34 33 32 34 33 32 31 34 36 10 547 (32) 
 Skilled non-manual and manual 41 42 39 38 42 42 39 41 42 41 39 40 13 260 (41) 
 Part skilled and unskilled 23 23 23 21 20 19 19 19 19 19 19 16 6357 (20) 
 Never worked/unclassifiedb 2465 (8) 
Total sample 3202 3174 3003 2881 3032 3316 3050 3095 2097 2013 1956 1812 32 630 
Socio-demographics 1996 1997 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008a Total 
Gender 
 Male 49 46 46 49 43 46 46 46 45 46 47 45 15 101 (46) 
 Female 51 54 54 51 57 54 54 54 55 54 53 55 17 529 (54) 
Age group (years) 
 16–24 12 13 13 12 13 12 14 12 11 12 11 4008 (12) 
 25–44 38 36 37 35 35 34 34 35 36 34 33 31 11 450 (35) 
 45–64 32 33 31 32 31 33 32 33 32 34 35 36 10 585 (32) 
 65+ 18 18 19 22 21 20 20 20 21 20 20 24 6587 (20) 
Smoking status 
 All smokers 28 25 26 25 23 25 23 22 22 24 21 19 7924 (24) 
 Light (0–20/day) 19 17 18 17 16 17 16 16 16 18 15 2244 (7) 
 Heavy (20+/day) 14 5680 (17) 
 Ex 26 28 28 28 26 26 26 28 26 27 27 36 8917 (27) 
 Never 46 47 46 47 51 49 51 50 51 49 52 55 15 721 (48) 
Social class 
 Professional and managerial 32 30 34 34 33 32 34 33 32 31 34 36 10 547 (32) 
 Skilled non-manual and manual 41 42 39 38 42 42 39 41 42 41 39 40 13 260 (41) 
 Part skilled and unskilled 23 23 23 21 20 19 19 19 19 19 19 16 6357 (20) 
 Never worked/unclassifiedb 2465 (8) 
Total sample 3202 3174 3003 2881 3032 3316 3050 3095 2097 2013 1956 1812 32 630 

Not all variable classifications will add up to the sample totals due to the missing data for those variables.

aThe 2008 data were collected in February and March 2009 due to a sampling error in October and November 2008.

bNot included in the final sample.

Levels of and trends in knowledge of SHS-related illnesses

Overall, more than 80% of respondents knew that SHS causes respiratory illnesses (Fig. 1a) but fewer were aware of the role of SHS in cot death (55%) and other infections (64%) in children and the links to coronary heart disease (71%) and coughs and colds in adults (68%). Knowledge of childhood ear infections was particularly poor (33%). There was a small increase in this knowledge between 1996 and 2008 for cot death (6%), ear infection (7%) and coronary heart disease (6%). Using the composite score, it was clear that knowledge increased from 1996 (Fig. 1b). The most marked increase was between 2003 and 2004 from 56% (54.4–57.0%) to 62% (60.3–63.7%). The highest level of knowledge was reached in 2006 (64%) but this fell significantly to 59% in 2007, and remained constant in 2008.

Fig. 1

(a) Trends in respondents' knowledge of illnesses linked to SHS (1996–2008). *The 2008 data were collected in February and March 2009 due to a sampling error in October and November 2008. (b) Trends in the percentage of respondents with good knowledge of the illnesses caused by SHS.

Fig. 1

(a) Trends in respondents' knowledge of illnesses linked to SHS (1996–2008). *The 2008 data were collected in February and March 2009 due to a sampling error in October and November 2008. (b) Trends in the percentage of respondents with good knowledge of the illnesses caused by SHS.

A higher proportion of never smokers had good knowledge (65%, 64.0–65.5%) compared with ex- (59%, 58.1–60.1%), light (46%, 44.6–47.2%) and heavy (34%, 31.9–35.8%) smokers (Table 2). Unfortunately, the trend data for each subgroup are not reliable due to sample size limitations.

Table 2

Logistic regression predicting ‘good’ knowledge (1996–2008)

Predictor variables n Good knowledge (%) Univariate
 
Multivariate
 
   OR 95% CI OR 95% CI 
Gender 
 Female 16 721 59 1.00  1.00  
 Male 13 641 56 0.87 0.83–0.92 0.90 0.86–0.95 
Age (years) 
 45–64 9721 57 1.00  1.00  
 16–24 1936 57 1.03 0.94–1.13 1.05 0.94–1.18 
 25–44 11 035 62 1.27 1.20–1.35 1.20 1.12–1.29 
 65+ 7670 52 0.82 0.77–0.88 0.77 0.72–0.83 
Social class 
 Skilled manual and non-manual 13 237 57 1.00  1.00  
 Managerial and professional 10 583 61 1.21 1.15–1.28 1.09 1.03–1.16 
 Part skilled and unskilled 6542 53 0.86 0.80–0.92 0.93 0.87–1.00 
Number of cars 
 1 13 754 57 1.00    
 0 7117 52 0.80 0.75–0.85 0.96 0.89–1.03 
 2+ 9491 61 1.17 1.12–1.24 1.03 0.96–1.09 
Smoking status 
 Never 13 937 65 1.00  1.00  
 Ex 8811 59 0.79 0.75–0.84 0.86 0.81–0.92 
 Light 5375 46 0.46 0.43–0.49 0.45 0.42–0.48 
 Heavy 2239 34 0.28 0.25–0.31 0.28 0.25–0.31 
Adults in household 
 2 16 323 59 1.00  1.00  
 1 9804 54 0.80 0.76–0.84 0.96 0.91–1.03 
 3+ 4235 57 0.90 0.84–0.96 0.89 0.83–0.96 
Child in the household 
 No child <16 21 930 55 1.00  1.00  
 <16 years 8432 63 1.39 1.32–1.47 1.24 1.16–1.33 
Year 
 2003–06 9392 56 1.00  1.00  
 1996–2002 17 510 60 0.83 0.79–0.88 0.85 0.80–0.90 
 2007–08a 3460 59 0.95 0.88–1.03 0.92 0.84–1.01 
Predictor variables n Good knowledge (%) Univariate
 
Multivariate
 
   OR 95% CI OR 95% CI 
Gender 
 Female 16 721 59 1.00  1.00  
 Male 13 641 56 0.87 0.83–0.92 0.90 0.86–0.95 
Age (years) 
 45–64 9721 57 1.00  1.00  
 16–24 1936 57 1.03 0.94–1.13 1.05 0.94–1.18 
 25–44 11 035 62 1.27 1.20–1.35 1.20 1.12–1.29 
 65+ 7670 52 0.82 0.77–0.88 0.77 0.72–0.83 
Social class 
 Skilled manual and non-manual 13 237 57 1.00  1.00  
 Managerial and professional 10 583 61 1.21 1.15–1.28 1.09 1.03–1.16 
 Part skilled and unskilled 6542 53 0.86 0.80–0.92 0.93 0.87–1.00 
Number of cars 
 1 13 754 57 1.00    
 0 7117 52 0.80 0.75–0.85 0.96 0.89–1.03 
 2+ 9491 61 1.17 1.12–1.24 1.03 0.96–1.09 
Smoking status 
 Never 13 937 65 1.00  1.00  
 Ex 8811 59 0.79 0.75–0.84 0.86 0.81–0.92 
 Light 5375 46 0.46 0.43–0.49 0.45 0.42–0.48 
 Heavy 2239 34 0.28 0.25–0.31 0.28 0.25–0.31 
Adults in household 
 2 16 323 59 1.00  1.00  
 1 9804 54 0.80 0.76–0.84 0.96 0.91–1.03 
 3+ 4235 57 0.90 0.84–0.96 0.89 0.83–0.96 
Child in the household 
 No child <16 21 930 55 1.00  1.00  
 <16 years 8432 63 1.39 1.32–1.47 1.24 1.16–1.33 
Year 
 2003–06 9392 56 1.00  1.00  
 1996–2002 17 510 60 0.83 0.79–0.88 0.85 0.80–0.90 
 2007–08a 3460 59 0.95 0.88–1.03 0.92 0.84–1.01 

For every consecutive increase in the predictor variable ‘year’, the OR represents the increase in odds of the outcome occurring. For all categorical variables, the OR describes a multiplicative change in the outcome compared with the reference category.

aThe 2008 data were collected in February and March 2009 due to a sampling error in October and November 2008.

Predictors of good knowledge

Adjusted multivariate logistic regression found age, gender, social class, smoking status, number of adults in the household, having a child under 16 in the household and time period, all independently predicted knowledge (Table 2). Odds of good knowledge were highest for 25- to 44-year-olds (OR: 1.20, 95% CI: 1.12–1.29) compared with 45- to 64-year-olds and for those of managerial and professional occupations (OR: 1.09, 1.03–1.16) compared with those of skilled occupation. Heavy (odds 0.28, 0.25–0.31), light (OR: 0.45, 0.42–0.48) and ex-smokers (OR: 0.86, 0.81–0.92) were all less likely to have good knowledge than never smokers. The presence of children in the household increased the odds of good knowledge (OR: 1.24, 1.16–1.33) compared with households with no children, whereas those living in households with three or more adults had lower odds (0.89, 0.83–0.96) compared with households with two adults. Odds of good knowledge were lower in 1996–2002 compared with 2003–06 (Odds 0.85, 0.80–0.90). There was no significant difference in the odds of good knowledge between 2007 and 2008 and between 2003 and 2006. The AUC value testing the predictive ability of the model was 0.63, P< 0.05, suggesting that the model was unable to fully explain all the variation in knowledge.

SHS-protective behaviours

In 2008, the percentage of respondents with smoke-free homes was 72% (69.4–73.6%); this was an 11% absolute increase since 2006. Amongst smokers, there was a smaller increase from 27% (22.6–30.4%) to 30% (25.0–34.7%) during the same period. In 2008, smoking abstinence was higher when in a room with a child (67%) than that with an adult (49%).

Knowledge and SHS-protective behaviours

The prevalence of smoke-free homes and smoking abstinence varied markedly with respondents' level of knowledge of SHS-related illnesses (Table 3).

Table 3

Relationship between knowledge of SHS-related illnesses and SHS-protective behaviours

Number of illnesses correctly identified Percentage respondents (95% confidence intervals)
 
 Smoke-free home (2006–08)
 
Smoking abstinence (1997–2008) with
 
 All Smokers only A child Non-smoking adult 
0–5 39 (35.7–41.5) 16 (12.8–19.9) 56 (54.2–58.1) 42 (40.5–44.4) 
6–7 65 (62.5–68.0) 33 (27.4–38.7) 72 (69.3–73.8) 49 (46.3–51.3) 
8–10 75 (73.9–76.7) 35 (30.9–38.7) 74 (72.8–76.0) 54 (52.5–56.0) 
Total 66 (65.1–67.6) 28 (25.8–30.8) 67 (62.2–68.4) 49 (47.7–50.0) 
Number of illnesses correctly identified Percentage respondents (95% confidence intervals)
 
 Smoke-free home (2006–08)
 
Smoking abstinence (1997–2008) with
 
 All Smokers only A child Non-smoking adult 
0–5 39 (35.7–41.5) 16 (12.8–19.9) 56 (54.2–58.1) 42 (40.5–44.4) 
6–7 65 (62.5–68.0) 33 (27.4–38.7) 72 (69.3–73.8) 49 (46.3–51.3) 
8–10 75 (73.9–76.7) 35 (30.9–38.7) 74 (72.8–76.0) 54 (52.5–56.0) 
Total 66 (65.1–67.6) 28 (25.8–30.8) 67 (62.2–68.4) 49 (47.7–50.0) 

Of those respondents who knew of 0–5 SHS-related illnesses, only 39% (35.7–41.5%) had smoke-free homes, whereas 75% (73.9–76.7%) of those with knowledge of 8–10 illnesses did. Similarly, amongst smokers, only 16% (12.8–19.9%) with knowledge of 0–5 illnesses had smoke-free homes compared with 35% (30.9–38.7%) of smokers with good knowledge.

Smoking abstinence in a room with a child for those with knowledge of 0–5 SHS-related illnesses was 56% (54.2–58.1%), while for those who were aware of 8–10 illnesses it was 74% (72.8–76.0%). Although abstinence was less prevalent when in a room with a non-smoking adult, better knowledge was associated with an increased proportion of abstinent smokers, 54% (52.5–56.0%) of those with knowledge of 8–10 illnesses compared with 42% (40.5–44.4%) of those who knew about only 0–5 illnesses.

Predictors of smoke-free homes: the population as a whole

Adjusted multivariate analysis found that knowledge of SHS-related illnesses predicted smoke-free homes with odds increasing by 18% (14–21%) for every unit increase in knowledge (Table 4). There was a significant increase in the prevalence of smoke-free homes between 2006 and 2007 (OR: 1.30, 1.09–1.56) and between 2006 and 2008 (OR: 1.58, 1.31–1.90). Respondents with part skilled or unskilled occupations and those with no car had poorer odds of having a smoke-free home (OR: 0.70, 0.57–0.86 and OR: 0.64, 0.53–0.78, respectively) compared with those of skilled occupation and those with one car. Heavy (OR: 0.09, 0.06–0.13), light (OR: 0.18, 0.14–0.22) and ex-smokers (OR: 0.81, 0.68–0.97) all had lower odds of a smoke-free home than never smokers. Those with a child under the age of 5 had much greater odds of a smoke-free home (OR: 2.33, 1.71–3.19) than those with no children under 16 years residing. Respondents' odds of a smoke-free home increased with each additional public place in which they agreed smoking restrictions were necessary (OR: 1.78, 1.61–1.97). The AUC was 0.82, P< 0.05, indicating that the model was a good fit of the data.

Table 4

Logistic regression predicting smoke-free home incidence for all respondents and smokers only (2006–2008)

Predictors All respondents
 
Smokers only
 
 n Smoke free (%) Univariate OR Multivariate OR n Smoke free (%) Univariate OR Multivariate OR 
Sex         
 Female 2388 67 1.00 1.00 599 32 1.00  
 Male 2842 65 0.92 (0.82–1.04) 1.06 (0.91–1.24) 565 24 1.47 (1.19–1.94) 1.39 (1.00–1.93) 
Age group (years) 
 45–64 1872 66 1.00 1.00 396 25 1.00 1.00 
 16–24 264 59 0.74 (0.59–0.93) 0.95 (0.65–1.38) 106 36 1.64 (1.06–2.55) 0.97 (0.52–1.79) 
 25–44 1739 69 1.17 (1.01–1.35) 1.08 (0.88–1.33) 477 31 1.33 (0.96–1.83) 0.77 (0.51–1.16) 
 65+ 1416 66 1.01 (0.86–1.17) 1.09 (0.90–1.33) 185 16 0.59 (0.35–0.98) 0.74 (0.41–1.35) 
Social class 
 Skilled manual and non-manual 2346 66 1.00 1.00 567 29 1.00 1.00 
 Managerial and professional 1911 73 1.44 (1.25–1.66) 0.98 (0.83–1.17) 290 33 1.23 (0.88–1.73) 0.96 (0.66–1.41) 
 Part skilled and unskilled 1034 55 0.63 (0.53–0.74) 0.70 (0.57–0.86) 307 21 0.67 (0.46–0.99) 0.79 (0.51–1.21) 
Number of cars 
 1 2361 65 1.00  513 28 1.00 1.00 
 0 1129 50 0.53 (0.46–0.62) 0.64 (0.53–0.78) 359 14 0.43 (0.29–0.62) 0.47 (0.30–0.75) 
 2+ 1801 74 1.49 (1.29–1.71) 1.17 (0.97–1.40) 292 40 1.74 (1.27–2.39) 1.46 (1.00–2.13) 
Smoking status 
 Never 2444 79 1.00 1.00 — —   
 Ex 1683 73 0.72 (0.62–0.84) 0.81 (0.68–0.97) — —   
 Light 846 33 0.13 (0.11–0.16) 0.18 (0.14–0.22) 846 33 1.00 1.00 
 Heavy 318 15 0.04 (0.03–0.06) 0.09 (0.06–0.13) 318 15 0.34 (0.23–0.49) 0.47 (0.31–0.72) 
Number of adults 
 2 2842 69 1.00 1.00 509 31 1.00 1.00 
 1 1745 58 0.61 (0.54–0.69) 1.04 (0.88–1.23) 475 16 0.42 (0.31–0.56) 0.75 (0.51–1.10) 
 3+ 704 66 0.85 (0.72–1.00) 1.07 (0.85–1.35) 180 33 1.10 (0.78–1.54) 1.07 (0.69–1.67) 
Age of youngest child (years) 
 No child <16 3982 64 1.00 1.00 813 24 1.00 1.00 
 0–4 597 77 1.85 (1.50–2.29) 2.33 (1.71–3.19) 154 42 2.36 (1.62–3.43) 2.96 (1.77–4.96) 
 5–10 392 66 1.09 (0.87–1.35) 1.17 (0.87–1.58) 115 29 1.29 (0.81–2.06) 1.34 (0.77–2.33) 
 11–15 320 71 1.34 (1.04–1.71) 1.42 (1.03–1.97) 82 41 2.18 (1.35–3.52) 1.54 (0.94–2.52) 
Year 
 2006 1833 61 1.00 1.00 444 27 1.00 1.00 
 2007 1785 67 1.26 (1.09–1.45) 1.30 (1.09–1.56) 393 29 1.14 (0.82–1.57) 1.19 (0.82–1.71) 
 2008a 1673 72 1.58 (1.36–1.83) 1.58 (1.31–1.90) 327 30 1.18 (0.83–1.66) 1.22 (0.81–1.83) 
Knowledge of SHS illnesses   1.29 (1.26–1.32) 1.18 (1.14–1.21)   1.16 (1.11–1.22) 1.10 (1.04–1.16) 
Agreement with restrictions   2.75 (2.52–2.99) 1.78 (1.61–1.97)   1.87 (1.60–2.19) 1.64 (1.35–1.97) 
Predictors All respondents
 
Smokers only
 
 n Smoke free (%) Univariate OR Multivariate OR n Smoke free (%) Univariate OR Multivariate OR 
Sex         
 Female 2388 67 1.00 1.00 599 32 1.00  
 Male 2842 65 0.92 (0.82–1.04) 1.06 (0.91–1.24) 565 24 1.47 (1.19–1.94) 1.39 (1.00–1.93) 
Age group (years) 
 45–64 1872 66 1.00 1.00 396 25 1.00 1.00 
 16–24 264 59 0.74 (0.59–0.93) 0.95 (0.65–1.38) 106 36 1.64 (1.06–2.55) 0.97 (0.52–1.79) 
 25–44 1739 69 1.17 (1.01–1.35) 1.08 (0.88–1.33) 477 31 1.33 (0.96–1.83) 0.77 (0.51–1.16) 
 65+ 1416 66 1.01 (0.86–1.17) 1.09 (0.90–1.33) 185 16 0.59 (0.35–0.98) 0.74 (0.41–1.35) 
Social class 
 Skilled manual and non-manual 2346 66 1.00 1.00 567 29 1.00 1.00 
 Managerial and professional 1911 73 1.44 (1.25–1.66) 0.98 (0.83–1.17) 290 33 1.23 (0.88–1.73) 0.96 (0.66–1.41) 
 Part skilled and unskilled 1034 55 0.63 (0.53–0.74) 0.70 (0.57–0.86) 307 21 0.67 (0.46–0.99) 0.79 (0.51–1.21) 
Number of cars 
 1 2361 65 1.00  513 28 1.00 1.00 
 0 1129 50 0.53 (0.46–0.62) 0.64 (0.53–0.78) 359 14 0.43 (0.29–0.62) 0.47 (0.30–0.75) 
 2+ 1801 74 1.49 (1.29–1.71) 1.17 (0.97–1.40) 292 40 1.74 (1.27–2.39) 1.46 (1.00–2.13) 
Smoking status 
 Never 2444 79 1.00 1.00 — —   
 Ex 1683 73 0.72 (0.62–0.84) 0.81 (0.68–0.97) — —   
 Light 846 33 0.13 (0.11–0.16) 0.18 (0.14–0.22) 846 33 1.00 1.00 
 Heavy 318 15 0.04 (0.03–0.06) 0.09 (0.06–0.13) 318 15 0.34 (0.23–0.49) 0.47 (0.31–0.72) 
Number of adults 
 2 2842 69 1.00 1.00 509 31 1.00 1.00 
 1 1745 58 0.61 (0.54–0.69) 1.04 (0.88–1.23) 475 16 0.42 (0.31–0.56) 0.75 (0.51–1.10) 
 3+ 704 66 0.85 (0.72–1.00) 1.07 (0.85–1.35) 180 33 1.10 (0.78–1.54) 1.07 (0.69–1.67) 
Age of youngest child (years) 
 No child <16 3982 64 1.00 1.00 813 24 1.00 1.00 
 0–4 597 77 1.85 (1.50–2.29) 2.33 (1.71–3.19) 154 42 2.36 (1.62–3.43) 2.96 (1.77–4.96) 
 5–10 392 66 1.09 (0.87–1.35) 1.17 (0.87–1.58) 115 29 1.29 (0.81–2.06) 1.34 (0.77–2.33) 
 11–15 320 71 1.34 (1.04–1.71) 1.42 (1.03–1.97) 82 41 2.18 (1.35–3.52) 1.54 (0.94–2.52) 
Year 
 2006 1833 61 1.00 1.00 444 27 1.00 1.00 
 2007 1785 67 1.26 (1.09–1.45) 1.30 (1.09–1.56) 393 29 1.14 (0.82–1.57) 1.19 (0.82–1.71) 
 2008a 1673 72 1.58 (1.36–1.83) 1.58 (1.31–1.90) 327 30 1.18 (0.83–1.66) 1.22 (0.81–1.83) 
Knowledge of SHS illnesses   1.29 (1.26–1.32) 1.18 (1.14–1.21)   1.16 (1.11–1.22) 1.10 (1.04–1.16) 
Agreement with restrictions   2.75 (2.52–2.99) 1.78 (1.61–1.97)   1.87 (1.60–2.19) 1.64 (1.35–1.97) 

The continuous predictors, knowledge and agreement with restrictions in public places produce a multiplier that describes the ORs of the outcome occurring for each unit increase in the predictor variable. For all categorical variables, the OR describes a multiplicative change compared with the reference category.

aThe 2008 data were collected in February and March 2009 due to a sampling error in October and November 2008.

Predictors of smoke-free homes: smokers only

Odds of a smoke-free home increased by 10% (4–16%) with every unit increase in knowledge. Smokers' odds also increased with agreement with restrictions in each additional public place. Heavy smokers had lower odds of having a smoke-free home (OR: 0.47, 0.31–0.72) compared with light smokers, as did those with no car (OR: 0.47, 0.30–0.75) compared with those with a car. Smokers with a child under 5 years had greater odds of a smoke-free home (OR: 2.96, 1.77–4.96). The AUC (0.74, P< 0.05) indicated that the model was a good fit.

Smokers' abstinence in a room with children and non-smoking adults: smokers only

The odds of abstinence when in a room with children increased by 11% (9–14%) for each unit increase in composite knowledge score and the odds of abstinence when in a room with a non-smoking adult by 6% (4–8%; Table 5). Additionally, the odds of abstinence were greater for each additional public place that smokers added to their list. Heavy smokers, compared with light smokers, respondents with a part skilled or unskilled occupation, compared with those of skilled occupation, and those with no car, compared with those with a car, were less likely to abstain, whilst those with two or more cars and those of managerial or professional occupation were more likely to. However, for the latter group, this relationship was only significant when in a room with a child (OR: 1.52, 1.29–1.78). Older smokers had greater odds of abstinence in both contexts than younger smokers. Having children 0–10 years old in the household predicted abstinence when in a room with non-smoking adults and having children aged 5–15 years predicted abstinence when in a room with children. Interestingly, having infants (0–4 years) in the household was significantly associated with being less likely to abstain in a room with children. The number of adults residing and gender were not significant predictors of abstinence when in a room with a child. However, compared with women, men were less likely to abstain when in a room with other non-smoking adults (OR: 0.88, 0.79–0.99). Compared with the period 2003–06, the odds of abstinence in a room with a child were lower in 1996–2002 (OR: 0.85, 0.74–0.97) but higher in 2007–08 (OR: 1.77, 1.40–2.24). However, abstinence in a room with adults was not significantly higher in this final period. The model for abstinence with children was a good fit of the data (AUC = 0.71, P< 0.05), whilst the model for abstinence with adults was not so good (AUC = 0.67, P< 0.05).

Table 5

Logistic regression predicting smoking abstinence when in a room with a child or a non-smoking adult (smokers only, 1997–2008)

Predictors Abstain when in a room with
 
 A child
 
A non-smoking adult
 
 n Abstain (%) Univariate OR Multivariate OR n Abstain (%) Univariate OR Multivariate OR 
Sex 
 Female 3618 68 1.00 1.00 3619 51 1.00 1.00 
 Male 3071 67 0.97 (0.87–1.08) 0.93 (0.82–1.05) 3082 47 0.84 (0.77–0.93) 0.88 (0.79–0.99) 
Age group (years) 
 45–64 2099 65 1.00 1.00 2105 53 1.00 1.00 
 16–24 671 70 1.23 (1.02–1.48) 0.95 (0.76–1.19) 672 39 0.59 (0.49–0.70) 0.42 (0.34–0.53) 
 25–44 3049 67 1.08 (0.95–1.22) 0.97 (0.83–1.14) 3050 48 0.83 (0.74–0.93) 0.59 (0.51–0.69) 
 65+ 870 71 1.32 (1.10–1.59) 1.38 (1.12–1.69) 874 57 1.18 (1.00–1.40) 1.25 (1.04–1.50) 
Social class 
 Skilled manual and non-manual 3108 67 1.00 1.00 3116 49 1.00 1.00 
 Managerial and professional 1677 77 1.64 (1.42–1.90) 1.52 (1.29–1.78) 1678 54 1.21 (1.06–1.38) 1.07 (0.93–1.22) 
 Part skilled and unskilled 1904 60 0.74 (0.65–0.84) 0.82 (0.72–0.95) 1907 45 0.83 (0.73–0.94) 0.88 (0.77–1.01) 
Number of cars         
 1 2962 68 1.00 1.00 2965 50 1.00 1.00 
 0 2084 61 0.73 (0.65–0.83) 0.79 (0.68–0.92) 2093 42 0.71 (0.63–0.80) 0.80 (0.69–0.92) 
 2+ 1643 73 1.26 (1.10–1.45) 1.17 (1.00–1.37) 1643 53 1.11 (0.98–1.26) 1.15 (1.00–1.33) 
Smoking status         
 Light 4754 74 1.00 1.00 4760 54 1.00 1.00 
 Heavy 1935 51 0.37 (0.33–0.42) 0.44 (0.38–0.50) 1941 36 0.47 (0.42–0.53) 0.50 (0.44–0.57) 
Number of adults 
 2 3137 67 1.00 1.00 3140 50 1.00 1.00 
 1 2554 65 0.90 (0.81–1.00) 0.99 (0.86–1.13) 2562 48 0.90 (0.81–0.99) 1.05 (0.93–1.19) 
 3+ 998 69 1.08 (0.93–1.25) 1.04 (0.88–1.24) 999 47 0.88 (0.77–1.01) 1.01 (0.86–1.18) 
Age of youngest child (years) 
 No child <16 4437 70 1.00 1.00 4448 48 1.00 1.00 
 0–4 991 68 0.90 (0.78–1.05) 0.89 (0.73–1.07) 991 49 1.04 (0.90–1.19) 1.27 (1.07–1.51) 
 5–10 764 57 0.57 (0.48–0.67) 0.52 (0.43–0.64) 765 52 1.17 (1.00–1.38) 1.36 (1.12–1.65) 
 11–15 497 60 0.66 (0.54–0.80) 0.61 (0.49–0.77) 497 48 0.99 (0.81–1.20) 1.11 (0.89–1.38) 
Year 
 2003–06 2231 69 1.00 1.00 2232 47 1.00 1.00 
 1996–2002 3741 64 0.78 (0.69–0.88) 0.85 (0.74–0.97) 3751 50 1.13 (1.01–1.26) 1.27 (1.12–1.43) 
 2007–08a 717 78 1.55 (1.26–1.91) 1.77 (1.40–2.24) 718 50 1.11 (0.93–1.33) 1.15 (0.95–1.40) 
Knowledge of SHS illnesses   1.14 (1.12–1.16) 1.11 (1.09–1.14)   1.08 (1.06–1.09) 1.06 (1.04–1.08) 
Agreement with restrictions   1.55 (1.46–1.63) 1.35 (1.27–1.44)   1.44 (1.36–1.51) 1.31 (1.23–1.39) 
Predictors Abstain when in a room with
 
 A child
 
A non-smoking adult
 
 n Abstain (%) Univariate OR Multivariate OR n Abstain (%) Univariate OR Multivariate OR 
Sex 
 Female 3618 68 1.00 1.00 3619 51 1.00 1.00 
 Male 3071 67 0.97 (0.87–1.08) 0.93 (0.82–1.05) 3082 47 0.84 (0.77–0.93) 0.88 (0.79–0.99) 
Age group (years) 
 45–64 2099 65 1.00 1.00 2105 53 1.00 1.00 
 16–24 671 70 1.23 (1.02–1.48) 0.95 (0.76–1.19) 672 39 0.59 (0.49–0.70) 0.42 (0.34–0.53) 
 25–44 3049 67 1.08 (0.95–1.22) 0.97 (0.83–1.14) 3050 48 0.83 (0.74–0.93) 0.59 (0.51–0.69) 
 65+ 870 71 1.32 (1.10–1.59) 1.38 (1.12–1.69) 874 57 1.18 (1.00–1.40) 1.25 (1.04–1.50) 
Social class 
 Skilled manual and non-manual 3108 67 1.00 1.00 3116 49 1.00 1.00 
 Managerial and professional 1677 77 1.64 (1.42–1.90) 1.52 (1.29–1.78) 1678 54 1.21 (1.06–1.38) 1.07 (0.93–1.22) 
 Part skilled and unskilled 1904 60 0.74 (0.65–0.84) 0.82 (0.72–0.95) 1907 45 0.83 (0.73–0.94) 0.88 (0.77–1.01) 
Number of cars         
 1 2962 68 1.00 1.00 2965 50 1.00 1.00 
 0 2084 61 0.73 (0.65–0.83) 0.79 (0.68–0.92) 2093 42 0.71 (0.63–0.80) 0.80 (0.69–0.92) 
 2+ 1643 73 1.26 (1.10–1.45) 1.17 (1.00–1.37) 1643 53 1.11 (0.98–1.26) 1.15 (1.00–1.33) 
Smoking status         
 Light 4754 74 1.00 1.00 4760 54 1.00 1.00 
 Heavy 1935 51 0.37 (0.33–0.42) 0.44 (0.38–0.50) 1941 36 0.47 (0.42–0.53) 0.50 (0.44–0.57) 
Number of adults 
 2 3137 67 1.00 1.00 3140 50 1.00 1.00 
 1 2554 65 0.90 (0.81–1.00) 0.99 (0.86–1.13) 2562 48 0.90 (0.81–0.99) 1.05 (0.93–1.19) 
 3+ 998 69 1.08 (0.93–1.25) 1.04 (0.88–1.24) 999 47 0.88 (0.77–1.01) 1.01 (0.86–1.18) 
Age of youngest child (years) 
 No child <16 4437 70 1.00 1.00 4448 48 1.00 1.00 
 0–4 991 68 0.90 (0.78–1.05) 0.89 (0.73–1.07) 991 49 1.04 (0.90–1.19) 1.27 (1.07–1.51) 
 5–10 764 57 0.57 (0.48–0.67) 0.52 (0.43–0.64) 765 52 1.17 (1.00–1.38) 1.36 (1.12–1.65) 
 11–15 497 60 0.66 (0.54–0.80) 0.61 (0.49–0.77) 497 48 0.99 (0.81–1.20) 1.11 (0.89–1.38) 
Year 
 2003–06 2231 69 1.00 1.00 2232 47 1.00 1.00 
 1996–2002 3741 64 0.78 (0.69–0.88) 0.85 (0.74–0.97) 3751 50 1.13 (1.01–1.26) 1.27 (1.12–1.43) 
 2007–08a 717 78 1.55 (1.26–1.91) 1.77 (1.40–2.24) 718 50 1.11 (0.93–1.33) 1.15 (0.95–1.40) 
Knowledge of SHS illnesses   1.14 (1.12–1.16) 1.11 (1.09–1.14)   1.08 (1.06–1.09) 1.06 (1.04–1.08) 
Agreement with restrictions   1.55 (1.46–1.63) 1.35 (1.27–1.44)   1.44 (1.36–1.51) 1.31 (1.23–1.39) 

The continuous predictors, knowledge and agreement with restrictions in public places produce a multiplier that describes the ORs of the outcome occurring for each unit increase in the predictor variable. For all categorical variables, the OR describes a multiplicative change compared with the reference category.

aThe 2008 data were collected in February and March 2009 due to a sampling error in October and November 2008.

Discussion

Main findings of this study

To our knowledge, this quantitative study is the first in England to assess the trends in, and determinants of, knowledge of the specific illnesses related to SHS and to explore the relationship between knowledge and the implementation of SHS-protective behaviours such as smoke-free homes and smoking abstinence around others. Our findings show that respondents know SHS increases the risk of respiratory illnesses but are less aware of non-respiratory diseases. A quarter of the population were unaware that SHS exposure can cause heart disease in adults, whilst only a third knew SHS could cause ear infection in children and 55% cot death. Awareness has improved over the last decade, yet levels of knowledge remain low for these conditions.

‘Good knowledge’ (correct identification of an association between SHS and at least 8 of the 10 SHS-related illnesses) was most prevalent amongst never smokers (65%), falling to 34% among those smoking over 20 per day. In addition to being a non-smoker, having a child in the household, being aged 25–44 years, female and of higher social class were all predictive of good knowledge.

Our multivariate analysis suggests that knowledge was highest during the period of frequent SHS-related mass media campaigns (2003–06) and that post-SFL there was no further increase in knowledge. This coincided with the end of SHS-related mass media campaigns which in 2007 ran from March to April only.34 To our knowledge, there have been no further national, government-funded mass media campaigns that have focused specifically on SHS between May 2007 and March 2009—the last data collection point of this study. Campaigns in late 2007 and 2008/09 focused on smoking cessation34 and since April 2010 there have been no mass media campaigns at all.35

Knowledge was associated with smoke-free homes and abstinence from smoking when in a room with others even once potential confounders had been adjusted for. The odds of smokers having a smoke-free home increased by 9% with each unit increase in knowledge. Similarly, with each additional unit increase in knowledge, the odds of smoking abstinence increased by 11% when with children and 6% when with adults. Although our findings are cross sectional in nature, they do support earlier findings of a relationship between knowledge and smoking-related behaviour.18,19,24,36

Knowledge did not increase in 2007–08 but smoking abstinence with children did, as did smoke-free homes amongst non-smokers. There was no increase in abstinence around adults or smoke-free homes amongst smokers in 2007–08 compared with 2003–06. Whilst it is unknown why abstinence increased with children when knowledge concurrently decreased, it may be the case that smoking parents are subject to social desirability bias which may lead them to either falsely report abstinence or truly abstain when in a room with a child but not go as far to implement a smoke-free home. What is clear from this study is that more smokers with good knowledge have a smoke-free home compared with those with poor knowledge, 35 versus 16%, respectively (Table 3).

What is already known on this topic

Our findings are consistent with qualitative studies which suggest a relationship between knowledge of the dangers of SHS and SHS-protective behaviour.16,24,36 In California, smokers who believed that SHS was harmful were five times more likely to report living in a smoke-free home16 and in Tasmania, a mass media campaign highlighting the link between SHS and cot death successfully reduced child SHS exposure.36

As outlined above, to reduce experiences of cognitive dissonance, it is not uncommon for people to revise their beliefs to complement their behaviour.9 A qualitative study in England showed smoking mothers who smoked at home used risk-minimizing beliefs to justify their behaviour.37 Increasing knowledge of the impacts of SHS is required to challenge cognitive dissonance-based rationalizations that smokers make to justify their smoking behaviour and to encourage them to change their behaviour rather than their beliefs.24,38,39 Given that our results show that good knowledge was not more likely in 2007–08 compared with 2003–06, there is a case for further education campaigns in order to increase knowledge. This knowledge should be framed so that it combats functional and risk-minimizing beliefs and provides practical advice on how to protect children from SHS. Research investigating the impact of mass media campaigns on SHS-related knowledge and subsequent behaviour is also warranted.

Although we recognize that knowledge alone is unlikely to be sufficient to bring about behaviour change, given that knowledge acquisition is an important step in the process of behaviour change and that without knowledge, behaviour change is unlikely,1,6,7,39 the low levels of knowledge revealed in our study are cause for concern. This concern is further heightened by our findings of the significant link between knowledge and protective behaviours and that 52% of children with smoking parents in England still live in homes where smoking occurs.40

What this study adds

This study quantifies levels of knowledge by population subgroups and provides quantitative evidence that the knowledge of SHS-related illnesses is predictive of keeping a smoke-free home and abstaining from smoking in the presence of children and non-smoking adults. This link between knowledge and behaviour and its concurrence with topical mass media campaigns has potential implications for policy and practice. Given the lack of evidence for what really works in terms of producing smoke-free homes,41,42 and that little has hitherto been known about the levels of national SHS knowledge in England, our findings suggest a role for including knowledge in the development of future interventions and supports the recent call for further mass media campaigns to highlight the dangers of SHS24,41 in combination with information on the ineffectuality of some ‘protective’ measures and how smoke-free homes can be achieved.

Limitations of this study

Our data are cross sectional; it would be useful to examine the relationship between knowledge and SHS-protective behaviours using longitudinal data but such data were not available. Our logistic regression model for ‘good’ knowledge could have been a better fit, suggesting that there may be other important predictors of knowledge that we have not included in our analyses.

Due to the nature of self-reported data, we cannot rule out the possibility of social desirability bias amongst parents which leads them to report smoke-free homes and smoking abstinence in a room with a child as they wish to be seen as a considerate smoker, neither can we deny that this bias may have increased over time. However, cotinine measures have been used to verify self-reported prevalence of smoke-free homes in previous studies.27,40 Furthermore, some smokers may have a different view of ‘smoke free’ than others. A study with smoking mothers found a discrepancy whereby some women describe their homes as non-smoking whilst also reporting that they smoke in an open doorway, believing that this still constitutes a non-smoking home.43

Finally, it was not possible to discern whether respondents had a suitable outdoor space to smoke. One of the reported barriers to smoking outdoors is lack of appropriate space;44 future work needs to encompass the impact of such barriers.

Funding

This work was supported by the Policy Research Programme of the Department of Health (PR-SF-0707-10004). A.G. is supported by a Health Foundation Clinician Scientist Fellowship. A.G. is also a member of the UK Centre for Tobacco Control Studies (UKCTCS), a centre for public excellence which is funded by the British Heart Foundation, Cancer Research UK, the Economic and Social Research Council, the Medical Research Council and the National Institute of Health Research. This funding is gratefully acknowledged.

Acknowledgements

This is an independent report and the views expressed are not necessarily those of the department.

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