BACKGROUND AND OBJECTIVE: Worldwide, roughly 40% of children are exposed to the damaging and sometimes deadly effects of tobacco smoke. Interventions aimed at reducing child tobacco smoke exposure (TSE) have shown mixed results. The objective of this study was to perform a systematic review and meta-analysis to quantify effects of interventions aimed at decreasing child TSE.
METHODS: Data sources included Medline, PubMed, Web of Science, PsycNet, and Embase. Controlled trials that included parents of young children were selected. Two reviewers extracted TSE data, as assessed by parentally-reported exposure or protection (PREP) and biomarkers. Risk ratios and differences were calculated by using the DerSimonian and Laird random-effects model. Exploratory subgroup analyses were performed.
RESULTS: Thirty studies were included. Improvements were observed from baseline to follow-up for parentally-reported and biomarker data in most intervention and control groups. Interventions demonstrated evidence of small benefit to intervention participants at follow-up (PREP: 17 studies, n = 6820, relative risk 1.12, confidence interval [CI] 1.07 to 1.18], P < .0001). Seven percent more children were protected in intervention groups relative to control groups. Intervention parents smoked fewer cigarettes around children at follow-up than did control parents (P = .03). Biomarkers (13 studies, n = 2601) at follow-up suggested lower child exposure among intervention participants (RD −0.05, CI −0.13 to 0.03, P = .20).
CONCLUSIONS: Interventions to prevent child TSE are moderately beneficial at the individual level. Widespread child TSE suggests potential for significant population impact. More research is needed to improve intervention effectiveness and child TSE measurement.
- CCR —
- cotinine/creatinine ratio
- CI —
- confidence interval
- CT —
- controlled trial
- PREP —
- parentally reported exposure or protection
- RCT —
- randomized controlled trial
- RD —
- relative difference
- RR —
- relative risk
- SHS —
- secondhand smoke
- THS —
- thirdhand smoke
- TSE —
- tobacco smoke exposure
Exposure to tobacco smoke, which causes serious disease and shortens life,1 is a leading public health issue worldwide.2 Children are especially susceptible to toxicity from secondhand smoke (SHS) because of their size and developmental stage,1 with increased risk of sudden infant death syndrome, middle ear disease, more severe asthma, pneumonia, and lowered lung function, as well as school absenteeism and days of restricted activity.1,3 Detrimental health effects of SHS exposure persist into adulthood,4 with children of smoking parents at greater risk for tobacco use.5 Worldwide, 40% of children are exposed to SHS.6 The importance of protecting children from SHS is recognized by the World Health Organization,7 the Environmental Ministers of the G8,8 and US Healthy People 2020.9
Thirdhand smoke (THS) is defined as “residual tobacco smoke contamination that remains after the cigarette is extinguished.”10 Particulate matter from cigarette smoke may settle on home surfaces, and be released into the air over a period of months. Young children may be exposed to THS from contact with their parents’ clothing, from furniture or carpets, or from upholstery in cars or homes.11 Harm attributed in the past to SHS exposure may have included harm due to THS exposure. The term “tobacco smoke exposure (TSE)” is used in this article to denote a combination of SHS and THS exposure.
Children, particularly young children, spend much of their time in the home. Although there have been sporadic initiatives regarding regulation of smoking in homes, private cars, and the open air public spaces that children tend to frequent, regulation of the home environment is generally rare.12 Hence, reliable protection remains an elusive goal.
In the past few decades, researchers have explored means to convince families and caretakers to voluntarily protect children from TSE. Some have focused on getting parents to quit smoking to protect their children. However, the impact of such programs has been limited. First, some smokers are unwilling to quit or to participate in smoking-cessation programs. Second, most parents do not quit even within the context of controlled trials aimed at promoting cessation to benefit the children.13,14 Even among those who do quit, many may return to smoking.15 Further, smoking cessation of 1 smoker in the home does not fully control exposure when other family members, child caretakers, and/or friends continue to smoke in the home or when with the child. Thus, cessation interventions, although important, are not successful for most families in which smoking occurs, and are not sufficient to fully protect children from multiple sources of exposure.
Some researchers have focused on getting parents to protect their children by moving their smoking and others’ smoking behaviors away from the home, car, or child. In particular, smoke-free homes and smoke-free cars have been emphasized. Tools used to effect change have included cognitive behavioral approaches, motivational interviewing, self-help materials, individual counseling, and biofeedback. Previous reviews have, for the most part, used narrative synthesis.5,16–19 No meta-analyses have been performed to quantify and test the effects of the interventions on decreasing child exposure.
In this article, we present meta-analyses of original studies evaluating interventions aimed at protecting children from TSE. The key outcome variables were (1) parentally reported child exposure or protection (PREP), and (2) biomarkers of child exposure. We performed exploratory subgroup analyses in an attempt to identify “active ingredients” of effective interventions.
Data Sources and Search Strategy
We conducted a number of literature searches, and were familiar with the literature from previous research. We report here on our final search, which was a targeted search performed with the aid of a librarian specializing in medical databases (Ruth Suhami). We searched Medline (Ovid), PubMed, PsycINFO, Web of Science, and Embase for articles published through the beginning of October 2013. We created the search strategy in Medline and then adapted it to all other databases, according to each database’s vocabulary and syntax. We used both index terms and keyword searches, as follows:
Medline: We used the following MESH terms: Tobacco Smoke Pollution OR (Parents AND “Tobacco Use Cessation”).
Embase: We used the following EMTREE terms: second hand smoke OR passive smoking OR (smoking cessation AND parents).
PsycINFO: We used the Index Term “Passive Smoking”.
All databases: We searched for the following keywords: second-hand smoke OR passive smoking OR environmental tobacco smoke OR involuntary smoking OR Tobacco smoke exposure (with all variations of spellings and endings).
We limited all searches to the age groups of newborn/infant/child.
We used a randomized controlled trial (RCT) filter for the search, requiring each article to be a randomized controlled trial or a controlled clinical trial. We excluded the following publication types: case-control study, cross-sectional study, meta-analysis, systematic review, protocol, observational study, and guideline.
In cases in which data on relevant outcomes were collected but required information was missing, we attempted to contact study authors for data. We received additional information from authors of 15 studies.20–34
Data were independently extracted by at least 2 of 3 reviewers (LJR, VM, MBN), and then compared. Differences were resolved through discussion.
We assessed study design, blinding of observers, percent follow-up, fidelity to treatment (eg, how many participants received the intervention), and whether the control group received an active intervention.
To be included, the studies had to meet the following criteria:
Study design: RCT using a cluster or individual-level randomization scheme, quasi-randomized RCT, or controlled trial (CT).
Participants: Parents (mother, father, or both parents) of children between the ages of 0 and 6 years. Trials that included children older than 6 years were acceptable only if children 6 years old or younger were also included.
Types of interventions: Any type of intervention that had as one of its aims helping parents decrease TSE of their children.
Length of observation period: Minimum 1 month from start of intervention. In studies reporting different follow-up times, we used the longest available period.
We descriptively examined changes in outcome variables for each study, by intervention group.
We used meta-analyses to compare between intervention groups for each outcome. For parentally reported outcomes, we examined (1) values at follow-up, and (2) change from study beginning to end. For biomarkers and parentally reported numbers of cigarettes smoked around the children, we did not have sufficient data on change, and so compared values at follow-up.
Parentally-reported exposure or protection (PREP)
PREP included home smoking bans, changes in smoking location to protect child, smoking around the child, moving the child away from others’ smoking, being in action/maintenance phase of child TSE protection, and exposure of the child. We examined (1) values of PREP at the end of the study, and (2) changes in values of PREP from beginning to end of the study.
Parentally reported number of cigarettes smoked around the child. Because measurement differed from study to study (number of cigarettes per day, week, or month), we standardized each value by dividing by a pooled SD.35
Biomarkers of tobacco smoke exposure: measured levels of cotinine or nicotine in urine, blood, saliva, or hair. Because the measurement differed from study to study (raw values, logged values, geometric means, cotinine/creatinine ratios [CCRs]), we standardized each value by using a pooled SD.35
We extracted and categorized the following variables:
Child-related subgroups: Child age at recruitment, child cohort.
Intervention-related subgroups: Recruitment setting, intervention setting, provider, intervention intensity, length of observation, intervention components: biochemical feedback, counseling, phone support, self-help materials, cessation medication use, air cleaner.
Study quality–related subgroups: Study design, blinding of observers, follow-up of participants, fidelity to treatment, provision of active intervention to the control group during the study period.
Statistical analyses and meta-analyses were performed by using RevMan 5.2.7 (Cochrane Collaboration, Copenhagen). We used the DerSimonian and Laird random-effects method with 95% CIs to pool results.36 We chose to use the random-effects method because we assumed that different intervention conditions would be associated with different effects, and we were interested in getting an average of the true effects from the population of intervention studies (as opposed to an estimate of a single population effect, as would be the case were we to use the fixed-effects method).35
For the biomarker analysis and parentally reported number of cigarettes to which the child was exposed, we standardized each value by using a pooled SD from the study, and present risk differences (RDs). For PREP, we present relative risks (RRs) and RDs. Estimates are presented with 2-sided 95% CIs. The pooled RRs and RDs were estimated with weights based on the inverse variance method and adjusted for the random-effects assumption.35
We performed meta-analyses on the following outcomes: (1) PREP at study end, (2) change in PREP from baseline to end, (3) number of cigarettes smoked around child at study end, and (4) biomarkers at the end of the study.
Heterogeneity and Publication Bias
We used the I2 statistic to investigate statistical heterogeneity. This describes the percentage of the variability in effect estimates that is due to heterogeneity rather than sampling error (due to chance).37 Existence of publication bias was assessed via visual examination of funnel plots.35
Exploratory Subgroup Analyses
We performed exploratory analyses for PREP using the following subgroups: intervention intensity, counseling, biochemical feedback, fidelity to protocol, and control group intervention.
Description of Studies
Our targeted, systematic search produced 386 articles. We were aware of 4 additional articles that did not appear in the search, bringing the total to 390. Two records were duplicates and we could not find any information on 2 records. We scanned titles of a total of 386 articles. Most articles (n = 276) were excluded on the basis of title, and another 35 were excluded after reading the abstract. Seventy-five full-text articles were read. Forty-five studies were excluded for the following reasons: no relevant outcomes, 18 studies38–55; the trial did not include a control group, 7 studies56–62; the interventions were not aimed at parents of young children, 3 studies63–65; the reporting period was <1 month, 2 studies66,67; data necessary for analysis were missing, 10 studies68–77; the paper was a review article, 1 study78; the article was a protocol, 2 studies79,80; the article was a follow-up of a previous study, 1 study81; there was no true control group (eg, 2 active interventions were compared), 1 study82.
Interventions included the following components: self-help materials, 20 studies,23,25,26,28,29,33,83–95,97; face-to-face counseling, 26 studies20–26,28–34,84–92,95–97; telephone counseling, 13 studies21–25,31,33,83–85,90,93,96; free nicotine replacement therapy to help parents quit smoking, 1 study25; biochemical feedback, 4 studies31,32,92,93; and air cleaners, 2 studies20,27.
In 11 studies, up to 1 session (either face-to-face or on the phone) was given26,27,30,83,86,87,89,92,94,95,97; in 18 of the studies >1 session was given.20–25,28,29,31–33,84,85,88,90,91,93,96 One study did not report the number of sessions.34
Control Group Intervention
In 9 of the studies, the control group participants received some sort of intervention that was specific to trial participants related to smoking, cessation, or risk to children from smoking.24,26,28,83,86,91,92,94,95 In 7 studies, control groups received asthma education that may or may not have referred to TSE, or reported the provision of very brief advice to control group participants as part of usual care.20,23,29–32,96 In 14 studies, the control participants received usual care, had contact for measurement only, or received an unrelated control group intervention.21,22,25,27,33,34,84,85,87–90,93,97
Of the 13 studies presenting biomarker information at follow-up, 9 presented urinary cotinine or urinary CCR20,23–25,31–33,93,96; 2 presented salivary cotinine22,26; 1 presented serum cotinine27; and 1 presented hair nicotine and cotinine.21
Seventeen studies reported blinding of observers20,22–27,30,31,33,34,83,84,88,89,95,97; 1 study reported nonblinding of observers91; and the remaining 12 studies did not report on blinding.21,28,29,32,85–87,90,92–94,96
Seven studies reported high fidelity, with at least 80% of participants receiving the full intervention23,24,27,84,88,93,96; 6 studies had moderate fidelity, with 50% to 79% of participants receiving the intervention25,29–33; and the remaining 17 studies did not report fidelity.20–22,26,28,34,83,85–87,89–92,94,95,97
Parentally Reported Outcomes
PREP at baseline, follow-up, and/or change in PREP are presented for 23 studies in Table 3. PREP improved in 86.4% (19/22) of intervention groups and 90.9% (20/22) of control groups. We were unable to describe change in 1 study that presented only data at follow-up.83
PREP at follow-up.
Seventeen studies (n = 6820),20,23,28–32,83–86,88,90–94 were included in the analysis of PREP at follow-up (Fig 2A). Benefit was apparent in 88.2% (15/17) of studies, with 29.4% (5/17) showing a statistically significant advantage to the intervention group. Risk ratios from individual studies ranged from 0.97 to 2.05, with an overall RR of 1.12 (CI 1.07 to 1.18], P < .0001), showing a small but statistically significant benefit to the intervention group. The RD was 0.07 (CI 0.05 to 0.09, P < .0001), indicating a benefit to 7% of the intervention families.
2. Seven studies (n = 1639) were included in the analysis of change in PREP from baseline to follow-up (Fig 2B).21,26,86,87,89,95,97 Benefit was suggested in 71.4% (5/7) of studies, with 42.9% (3/7) reaching statistical significance. The overall risk ratio showed moderate, but not statistically significant, benefit of the interventions (RR 1.44, CI 0.90 to 2.29], P = .13).
3. Eight studies (n = 908) were included in the analysis of number of cigarettes to which the children were exposed (Table 4, Fig 2C). For all 7 studies that had available data at baseline and follow-up, the numbers of cigarettes smoked around children decreased from baseline to follow-up in both the intervention and control groups. At study end, positive effect of the intervention was indicated in 75% (6/8) of studies,20,21,24,25,27,96 with 2 studies showing statistically significant improvement in the intervention group.24,25 RDs ranged from −0.81 to 0.20. The overall RD was −0.24 (CI −0.46 to −0.03, P = .03), showing a statistically significant difference between intervention and control groups at study end.
Table 5 presents changes in biomarkers from baseline to follow-up. Levels of biomarkers decreased, on average, in 11 of the 13 intervention groups20–26,31–33,93 and in 10 of the 13 control groups.20,22,23,25–27,31–33,93
Thirteen studies (n = 2601) (Fig 2D) were included in the analysis of biomarker assessment of child exposure at follow-up.20–27,31–33,93,96 A positive effect of the intervention was found in 61.5% (8/13) of the studies,20–22,24,25,26,31,32 with 1 study24 showing a statistically significant advantage to the intervention group. RDs for the individual studies ranged from −0.52 to 0.20. Overall, the RD was −0.05 (CI −0.13 to 0.03, P = .20), demonstrating a trend toward benefit without statistical significance.
Funnel plots for the 4 meta-analyses are found in Fig 3. The funnel plots for the PREP and biomarker analyses show indication of publication bias.
Heterogeneity of Results
The test for heterogeneity was not significant for the PREP at end of study analysis (I2 = 23%, P = .18) or for the biomarker end point (I2 = 0%, P = .57), indicating that the results were homogeneous in those analyses. Heterogeneity was present in the PREP – change analysis (I2 = 87%, P < .0001) and the analysis of number of cigarettes (I2 = 62%, P = .01)
Exploratory Subgroup Analyses on PREP
The exploratory analyses (see Table 6) included 3 to 14 studies each, with RRs ranging from 1.07 to 1.27. Most subgroups showed significant, albeit small, benefit to the interventions.
Interventions aimed at aiding parents to protect their children from TSE showed small benefits when assessed by parental report at study follow-up (RR 1.12, CI 1.07 to 1.18, P < .0001; RD 0.07, CI 0.05 to 0.09, P < .0001). Although the direction of the effect was beneficial, biomarkers at study follow-up did not show evidence of an intervention effect (RD −0.05, CI −0.13 to 0.03, P = .20)
Our results add to previous knowledge, which was primarily obtained from narrative reviews. Emmons et al16 found significant reductions in parentally reported exposure in 40% (2/5) of studies, but did not find significant differences in objective biochemical measures. Wewers and Uno,19 in their 2002 narrative review of 4 clinical interventions, found small improvements in exposure associated with clinical interventions, without statistical confirmation. Gehrman et al’s 2003 review17 with 19 studies found a small effect size (0.34, range −0.14 to 1.04)98 due to interventions, again without statistical confirmation. Klerman’s 2004 review18 reported benefit in 2 of 3 trials using biochemical measures, and 3 of 3 trials using parental reports of the number of cigarettes smoked in the home. Cochrane reviewers in 2008,5(p3) by using a narrative approach to summarize 36 studies, concluded that “effectiveness has not been clearly demonstrated.” We attribute our more definitive findings to the use of formal meta-analysis: benefits include the ability to detect and quantify small benefits of interventions.35
The Cochrane review noted “limited support for more intensive counselling interventions for parents in such contexts [eg, child health settings].”5 Our exploratory analyses, by contrast, found small benefit to both intensive (RR 1.12, CI 1.07 to 1.18, P < .0001) and less-intensive (RR 1.18, CI 1.02 to 1.35, P = .02) interventions. The lower-intensity interventions included in this review used a range of self-help materials, including innovative approaches, such as comic books, story books, videos, and air cleaners.
Observed Benefits Among Control Group Participants
One of the most interesting findings of this review was the consistent suggestion of benefit to control group participants. Many authors of included studies21,25,26,86,95,96 remarked on this in their articles; 90.9% (20/22) of control groups in the PREP analysis, and 76.9% (10/13) of control groups in the biomarker analysis, showed trends toward improvements from baseline to the end of the study.
There are a number of plausible explanations, the most obvious of which is the effect of monitoring. Hovell et al25 estimated that monitoring alone was responsible for about two-thirds of the decline in exposure among trial participants. Trial enrollment may be a factor: Wahlgren et al81 found improvements in child TSE protection after recruitment but before the intervention took place. Secular trends may also be of importance: cigarette smoking is declining in the United States99 and Western Europe,100 smoke-free regulation is increasing across the globe,2 and the prevalence of smoke-free homes among smokers has been shown to increase with regulation against smoking in public places.101 Another possible explanation is that trials that provide active, usually weakened, interventions to control group participants, a common technique,102 are less likely to show true benefits of interventions. However, our subgroup analyses did not support this hypothesis.
Comparisons of Parentally Reported and Biomarker End Points
Whereas statistically significant intervention effects on parentally reported end points (both in PREP at study end, and number of cigarettes smoked around child) were found in this study, statistically significant intervention effects were not demonstrated for biomarkers, although a trend was found toward benefit (RD −0.05, CI −0.13 to 0.03], P = .20). This may be due to several factors. First, it may be related to the number of trials and participants included in the respective meta-analyses. The analysis involving parental report had more power to detect true differences because it included more trials and a greater number of participants. Second, it may be that parental reports are unreliable: parents may tend to incorrectly estimate exposure because they deny exposure or are unaware of it. This leads to 2 problems: first, it is more difficult to detect true differences if measurement is inexact,103 and, second, if intervention group participants underreported exposure to a greater degree than did control group participants, it would lead to overestimation of intervention benefit. An additional possibility is that biomarkers, although considered the gold standard for evaluation of child exposure,1 may not be sufficiently sensitive to detect small changes in exposure levels. Matt et al104 found that precisely estimating exposure over a period of 4 to 13 months could require up to 12 urine samples. Wilson et al32 found that “single, intermittent urine samples provide a relatively crude index of both typical and maximal exposure.”p.1718 Inexact measurement lowers the probability of detecting true intervention effects.103 Finally, it is possible that biomarkers and parental reports measure different quantities, particularly as urinary cotinine reflects short-term exposure. This is supported by the mixed correlations reported in studies of parentally reported and biochemically measured child TSE: Hovell et al105 found correlations of between 0.22 and 0.75, and a more recent study106 found correlations ranging from 0.02 to 0.80. Any of these reasons, or a combination, may have contributed to the different findings in biochemically measured versus parentally reported child TSE.
Benefits of interventions to help parents protect children from TSE are real, but small on an individual level.
At a population level, such benefits could have significant public health impact.
Benefit was observed both for more-intensive and less-intensive interventions.
Trends toward improvements during the trial period were observed in most control groups, for both biochemical and parentally reported end points, indicating either an effect of trial participation or of monitoring.
Monitoring of TSE, either by parental report or biochemical means, holds promise as a simple but powerful measure to reduce exposure. Feedback of an individual child's levels may be essential particularly in comparison with children of nonsmoking families. Such monitoring could, in principle, be conducted at regular health visits. This needs further investigation.
At best, the interventions showed only small benefits at the individual level. It is essential to identify powerful intervention strategies that are acceptable to the families with young children where smoking occurs, and could be implemented with high fidelity to protocol. It is possible that immediate, sensitive feedback from biomarkers for child TSE, or immediate feedback on home or car air nicotine, or THS, could be helpful. This requires advances in immediate biomarker measurement, with pricing that would enable widespread implementation.
Strengths and Limitations
To the best of our knowledge, this is the first review to quantify and rigorously test the effects of interventions aimed at protecting young children from TSE. Strengths of this review include the targeted search, the strong methodology of included studies, testing of intervention effects, effect size estimates, and subgroup analyses.
Our research has several limitations. First, we were unable to incorporate baseline values of biomarkers into the meta-analyses of biomarkers and number of cigarettes smoked around the child because of missing information about individual-level changes. We were able to incorporate baseline information into the analysis of PREP, but only for a minority of the studies. Although all but 1 of the included trials were randomized, and randomization tends to produce groups that are equal in measured and unmeasured characteristics, this may not hold true for any specific trial, and is less likely to hold in small studies.103
The subgroup analyses of PREP did not provide information on advantages of specific intervention components, perhaps because of the homogeneity of included studies, and small observed effect sizes.
Interventions aimed at parents to reduce TSE in children provide small benefits when assessed by parental reports, although significant differences between intervention and control groups at study follow-up times were not found for biomarkers. Trends toward improvements during the study period were seen in most of both control and intervention groups. Because of the widespread scale of TSE among young children and the difficulties inherent in convincing all family members to quit smoking, substantial gains are possible by reducing exposure. Original research is needed to develop more effective programs for reducing child TSE, to accurately measure child exposure, and to understand how to efficiently disseminate effective interventions.
We thank Ms. Ruth Suhami for her assistance with the systematic review of the literature. We also thank the individuals who provided unpublished data and/or provided additional information on published studies for use in this systematic review.
- Accepted January 10, 2014.
- Address correspondence to Laura J. Rosen, PhD, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, POB 39040, Ramat Aviv, Israel 69978. E-mail:
Dr Rosen conceptualized and designed the study, oversaw all aspects of the research, performed the systematic review of the literature, extracted data from the original studies, contributed to the statistical analysis, wrote sections of the manuscript, and edited the entire manuscript; Ms Myers contributed to systematically reviewing the literature, extracted data from the original articles, contributed to the data analysis, and contributed to the writing of the manuscript; Dr Hovell contributed to the design of the meta-analysis and interpretation of the data and edited the manuscript for scientific content; Dr Zucker assisted with various statistical issues in the analysis of the manuscript and edited the manuscript; Ms Ben Noach contributed to the design of the study, the systematic review of the literature, data extraction, data analysis, data interpretation, and writing of the manuscript; and all authors approved the final version of the manuscript.
FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.
FUNDING: Supported by the Flight Attendants' Medical Research Institute Award 072086_YCSA.
POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.
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