Reducing Children
’
s Exposure to Secondhand Smoke
at Home: A Randomized Trial
WHAT’S KNOWN ON THIS SUBJECT: The World Health Organization estimates that∼700 million children breathe tobacco smoke polluted air, particularly at home. Educational strategies either directly or indirectly targeting household decision-makers through other family members are effective in reducing children’s exposure in private homes.
WHAT THIS STUDY ADDS: Intensive intervention was effective in decreasing children’s personal exposure to secondhand smoke (SHS), educating mothers about SHS, and promoting smoking restrictions at home. However, superiority over minimal intervention to decrease children’s personal exposure to SHS was not statistically significant.
abstract
OBJECTIVE:To develop and test an intervention to reduce children’s exposure to secondhand smoke (SHS) at homes in Yerevan, Armenia.
METHODS:A single-blind, randomized trial in 250 households with 2- to 6-year-old children tested an intensive intervention (counseling sessions, distribution of tailored educational brochures, demonstration of home air pollution, and 2 follow-up counseling telephone calls) against minimal intervention (distribution of standard leaflets). At baseline and 4-month follow-up, researchers conducted biomonitoring (children’s hair) and surveys. The study used pairedt tests, McNemar’s test, and linear and logistic regression analyses.
RESULTS: After adjusting for baseline hair nicotine concentration, child’s age and gender, the follow-up geometric mean (GM) of hair nicotine concentration in the intervention group was 17% lower than in the control group (P = .239). The GM of hair nicotine in the intervention group significantly decreased from 0.30 ng/mg to 0.23 ng/mg (P= .024), unlike in the control group. The follow-up survey revealed an increased proportion of households with smoking restrictions and decreased exposure of children to SHS in both groups. The adjusted odds of children’s less-than-daily exposure to SHS at follow-up was 1.87 times higher in the intervention group than in the control group (P= .077). The GM of mothers’knowledge scores at follow-up was 10% higher in the intervention group than in the control group (P= .006).
CONCLUSIONS:Intensive intervention is effective in decreasing child-ren’s exposure to SHS through educating mothers and promoting smoking restrictions at home. However, superiority over minimal in-tervention to decrease children’s exposure was not statistically sig-nificant.Pediatrics2013;132:1071–1080
AUTHORS:Arusyak Harutyunyan, MD, MPH,aNarine
Movsisyan, MD, MPH,aVarduhi Petrosyan, MS, PhD,aDiana
Petrosyan, MD, MPH,aand Frances Stillman, EdD, EdMb
aCollege of Health Sciences, American University of Armenia,
Yerevan, Armenia; andbInstitute for Global Tobacco Control,
Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
KEY WORDS
children, nicotine, personalized feedback, randomized controlled trial, secondhand smoke
ABBREVIATIONS
GM—geometric mean OR—odds ratio PM—particulate matter SHS—secondhand smoke
Dr Harutyunyan contributed to the study design, coordinated the data collection, performed data analysis, conceptualized the scope of the paper, and drafted the manuscript; Dr Movsisyan, Dr Stillman, and Dr V. Petrosyan contributed to the study concept and design, accuracy and completeness of data analysis, interpretation of the results, and revision of the manuscript for important intellectual content; and Dr D. Petrosyan contributed to the study design, data collection, and interpretation of the results. All authors approved thefinal version of the manuscript.
This trial has been registered at www.clinicaltrials.gov (identifier NCT01630356).
www.pediatrics.org/cgi/doi/10.1542/peds.2012-2351 doi:10.1542/peds.2012-2351
Accepted for publication Sep 3, 2013
Address correspondence to Arusyak Harutyunyan, MD, MPH, Baghramyan 40, Yerevan, Armenia. E-mail: aharutyunyan@aua.am PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275). Copyright © 2013 by the American Academy of Pediatrics
FINANCIAL DISCLOSURE:The authors have indicated they have nofinancial relationships relevant to this article to disclose.
FUNDING:Funded by FAMRI (Flight Attendant Medical Research Institute) Center of Excellence in Translational Research at Johns Hopkins University.
Secondhand smoke (SHS), a complex mixture of gases and particles that contains many carcinogenic and toxic compounds,1,2 results from tobacco
smoking indoors. The US Environmen-tal Protection Agency has classified tobacco smoke as a known human carcinogen, with no safe level of expo-sure.3 The scientific evidence is clear
that SHS exposure causes diseases in adults and children. Children’s ex-posure is involuntary and primarily occurs through adults smoking in pla-ces where children live and play.
Given that.1 billion adults worldwide smoke, the World Health Organization estimates that ∼700 million, or al-most one-half of the world’s children, breathe air polluted by tobacco smoke, particularly at home.4 In children,
SHS exposure leads to reduced birth weight, lower respiratory tract ill-nesses, chronic respiratory symptoms, middle ear disease, and reduced lung function.5The large number of children
exposed to SHS suggests a substantial public health threat worldwide.
Armenia has high rates of tobacco use (63.0% of men; 2.0% of women), with the majority of households (82.2%) having at least 1 smoker.6,7Approximately 70.0% of
households do not have any restrictions on smoking.8
The World Health Organization recom-mends legislation and education to pro-tect children from SHS exposure.9
However, legislation is of limited value in reducing exposure in private homes, and educational strategies, including educa-tion about the risks to children from SHS exposure and steps to eliminate expo-sure, are suggested to be more effective in these settings. Educational programs must strategically target household decision-makers, either directly or in-directly through other family members.4
Randomized studies of culturally ap-propriate tobacco-related interventions, particularly SHS reduction inter-ventions, are rare. Although certain generic approaches may be effective, many agree that an intervention ap-proach that takes into consideration cultural attitudes, norms, expectations, and values would be more likely to in-crease acceptance and adoption of the program and improve its effectiveness.10
The goal of the current study was to test the hypothesis that an intervention which uses motivational interviewing along with immediate feedback and follow-up counseling telephone calls
would be effective in educating house-hold members about the health hazards of smoking and SHS exposure and re-ducing children’s exposure to SHS in households in Armenia.
METHODS
Study Design
The study was a randomized controlled trial with 2 arms (intervention and con-trol groups) conducted from May 2010 to November 2010 (Fig 1). A pilot study of 10 households preceded the clinical trial to test the recruitment strategy, study protocols, and instruments and tofi nal-ize intervention strategies.
Study Population
The sample population included house-holds with a nonsmoking mother and at least 1 child 2 to 6 years of age residing with at least 1 daily smoker. The study targeted homes with young children for whom the major source of exposure to tobacco smoke was smoking by parents or other household members.4 The
ex-clusion criteria were mother’s pregnancy and residency outside of Yerevan.
The study team recruited the house-holds through pediatrician’s offices in
FIGURE 1
polyclinics (primary health care facili-ties) by using multistage random sam-pling. First, the study team randomly selected 10 polyclinics from the list of 19 providing services to the population of Yerevan, the capital city of the Republic of Armenia. At each polyclinic, the study team selected 5 pediatrician offices (those that were open at the time of the study) and randomly selected medical records of children aged 2 to 6 years. The study team recruited 5 eligible households from each pediatrician.
Interviewers telephoned each house-hold selected to check for eligibility, provide information about the study and its procedures, and arrange the
first home visit upon oral consent. The 250 households recruited were assigned random numbers from 1 to 250; house-holds with odd numbers were included in the intervention group (intensive in-tervention) and those with even num-bers were included in the control group (minimal intervention). Study partic-ipants were unaware of their assign-ment status.
Data Collection
Trained interviewers made 2 baseline visits (1 week apart) and two 4-month follow-up household visits to conduct measurements, surveys, and the tervention (Fig 1). Measurements in-cluded hair samples from children to assess changes in nicotine concentra-tion over time; this biomarker is a val-idated method to quantify personal uptake of nicotine.11,12Given that each
centimeter of hair reflects∼1 month of exposure to SHS, a small sample of hair (∼30–50 strands, 2–3 cm) was cut near the hair root from the back of the scalp where there is the most uniform growth pattern between individuals; this method minimizes the variability of the results.12
Surveys were conducted among non-smoking mothers and 1 of the daily smokers in each household. The first choice was the father, if he was a daily
smoker. If the father did not smoke, the counseling was conducted with 1 of the household smokers who spent more time with the child at home. The interviewer-administered question-naire required∼15 minutes to complete and covered demographic information, knowledge about health hazards of SHS, and household smoking-related practi-ces. The instrument was adapted from the Global Adult Tobacco Survey: Core Questionnaire With Optional Questions.13
The study team translated the question-naire into Armenian and pretested it during the pilot phase.
Intervention
The intervention included an in-person counseling session with the nonsmoking mother and at least 1 daily smoker in each household, with distribution of a tailored educational brochure and demonstra-tion of measurement of indoor particu-late matter (PM2.5) (at second baseline
visit); it also included 2 follow-up coun-seling telephone calls 1 and 2 months after the initial session. The intervention was based on the motivational inter-viewing technique, which is a directive, client-centered counseling technique for eliciting behavior change that has been shown to be effective in smoking cessation and SHS reduction inter-ventions.14–16 The control group
re-ceived only a brief educational leaflet on the hazards of SHS developed by the US Environmental Protection Agency.17
In-person Counseling Session
The study team provided counseling on eliminating child exposure to tobacco smoke to at least 1 daily smoker and to the mother in the household. The counseling session emphasized the following issues: (1) importance of a healthy environment at home; (2) health dangers of smoking and expo-sure to SHS; (3) why and how to quit smoking; and (4) how to keep home air smoke-free. At the end of the 40-minute
counseling session, each family re-ceived a tailored and culturally adjusted educational brochure developed by the study team.
Demonstration of PM2.5 Pollution
The study team measured the PM2.5in the
air by using the TSI AM 510 Aerosol SidePak18to compare the quality of
in-door air with outin-door air and demon-strate the effect of smoking on indoor air quality in the intervention households. After completing the PM2.5measurement,
the interventionist immediately down-loaded the data to a laptop to visualize the results through graphical presentation of the PM2.5 fluctuations for immediate
feedback (Fig 2). Feedback, as part of an intervention, has been extensively used in health promotion, particularly for addic-tive behavior change.19 Demonstration
of the indoor PM2.5pollution was a
risk-based personalized feedback requiring less effort from participants to make the information personally relevant.
Follow-up Counseling Telephone Calls
Interventionists made 2 follow-up coun-seling telephone calls to nonsmoking mothers at 1 and 2 months after the in-person counseling session. These calls aimed at: (1) assessing the progress in meeting the goals set earlier; (2) coun-seling on barriers to change; and (3) encouraging study participants to main-tain progress made or to set new goals. These calls also provided an opportunity to ask questions or clarify issues.
Sample Size Calculation
The sample size calculation was based on data from an earlier study.20Using the
power.21Adjusting for 10% potential
re-fusal to provide hair samples and 40% potential losses to follow-up, the study estimated the sample size to be equal to 250.
Data Analysis
The data were analyzed by using Stata version 10 (Stata Corp, College Station, TX). The study team compared the baseline and follow-up measurements in both groups by using pairedttests for comparison of continuous measures and McNemar’s test for paired pro-portions. The primary outcome variable was child’s hair nicotine concentra-tion. Self-reported household smoking restrictions, frequency of smoking in the presence of the child, and participants’ knowledge scores were the secondary outcomes. We assessed the respon-dents’ knowledge by asking whether smoking or SHS caused a list of health conditions, with 1 point for each correct answer. The knowledge score was cal-culated as the sum of all scores on the knowledge questions.
Time-weighted average of hair nicotine was assayed at the Exposure Assess-ment Facility at Johns Hopkins Bloom-berg School of Public Health.20 The
skewed hair nicotine concentration data were log-transformed for statis-tical analysis. In addition, to compare hair nicotine concentrations at base-line and follow-up, we estimated the geometric mean (GM) and 95% confi -dence intervals of the hair nicotine concentrations.
The study team also compared the change in the outcome variables from baseline to follow-up between the in-tervention and control groups by using multiple logistic and linear regression models. The follow-up measurements were considered as dependent varia-bles, baseline measurements and other potential confounders as independent variables, and the intervention as the main dichotomous independent vari-able of interest.
The study used an intention-to-treat approach during statistical analyses to avoid the drop-out effect by imputing
all the missing follow-up data with their baseline values.22
Ethical Considerations
The institutional review boards of Johns Hopkins Bloomberg School of Public Health and American University of Arme-nia approved the study.
RESULTS
Participants’Recruitment and Retention
More than one-half of the contacted households (58.2%) were not eligible for participation, 30.3% refused to participate (most of them refused be-fore the eligibility criteria screening), and 0.7% agreed but were not available for baseline data collection. Overall, 250 households were enrolled in the study, and 250 mothers and 230 smokers participated in the baseline survey. At baseline, 173 households agreed to provide hair samples from their child (83 intervention, 90 control). Of 244 households eligible for the follow-up
FIGURE 2
measurement, 224 completed the study (110 intervention, 114 control) (Fig 3). Among them, 137 households (67 in-tervention, 70 control) provided their child’s hair samples at follow-up, and the remaining were treated by using an intention-to-treat approach. Comparison of sociodemographic characteristics be-tween those who completed the study and those who dropped out did not reveal any significant differences.
Participants’Characteristics
The mean 6 SD age of nonsmoking mothers was 30.0 6 5.2 years. Almost one-half (53.6%) were employed, and more than one-third (36.3%) had gradu-ated with a university degree. The mean age of smokers was 38.2611.4 years, and the overwhelming majority (81%) were the children’s fathers. Approxi-mately 31.3% of smokers had a university degree, and 72.1% were employed over the past 12 months. The mean age of children was 4.061.2 years, and 49.1% were girls. Demographic characteristics of participants were similar in the in-tervention and control groups (Table 1).
Children’s Hair Nicotine Concentration
Table 2 presents the summary of the hair nicotine concentrations at base-line and follow-up. The GM of hair nic-otine levels of control group children at baseline and follow-up was 0.29 ng/mg and 0.27 ng/mg, respectively (P= .613). For the intervention group, GM de-creased from 0.30 ng/mg to 0.23 ng/ mg, and this 23.3% decrease was sta-tistically significant (P= .024).
Multiple linear regression analysis demonstrated that after adjusting for the baseline hair nicotine concentra-tion, child’s age, and child’s gender, the follow-up GM of hair nicotine concen-tration was 17% lower in the in-tervention group compared with the control group (P= .239) (Table 3).
Smoking Practices in Households
At baseline, there were 1.560.8 smok-ers in each household smoking a mean of 25.5 6 11.5 cigarettes per day. Smoking was allowed in all households, with some restrictions in approximately one-half of homes. According to moth-ers, 5 (4.5%) intervention households and 6 (5.4%) control households com-pletely banned indoor smoking at follow-up. In addition, 5 (4.5%) smokers in the intervention group and 1 (0.9%) in the control group have reportedly stopped smoking at follow-up.
Table 4 presents the proportion of households with smoking restrictions at baseline and follow-up. Based on mothers’report, the odds of having any smoking restriction at follow-up was statistically significantly higher than at baseline in both the intervention (odds ratio [OR]: 4.67) and control (OR: 3.14) households. According to the smokers, the increase in the proportion of households with smoking restrictions at follow-up was statistically significant only in the intervention group (OR: 2.62). At follow-up, mothers and smokers in both groups reported statistically sig-nificantly less exposure of children to SHS (Table 5).
Multiple logistic regression analysis found that, based on mothers’report, at follow-up the adjusted odds of child’s less-than-daily exposure to SHS was marginally significantly higher in the intervention group compared with the control group (OR: 1.87,P= .077) (Table 6).
Knowledge About Hazards of Smoking and SHS
Paired analysis of knowledge scores revealed that the knowledge of in-tervention and control group partic-ipants increased significantly from baseline to follow-up. The mothers’ mean knowledge score increased from 9.5 to 11.3 in the intervention group and from 9.8 to 10.5 in the control group.
Among smokers, it increased from 7.1 to 8.6 and 7.1 to 7.9, respectively. Linear regression analysis suggests that the GM of the mothers’knowledge score at follow-up was 10% higher in the in-tervention group compared with control group, after controlling for baseline knowledge score (P= .006).
DISCUSSION
Protecting children from SHS exposure at homes is a complex and sensitive issue and has many social and political implications; hence, it is difficult to monitor and regulate people’s behavior at home.23There is a large disparity
between male and female smoking rates in Armenia, which poses an addi-tional unique challenge for protecting young children from tobacco smoke in similar societies. This study was thefirst clinical trial in Armenia designed to de-velop and test a culturally appropriate intervention to encourage implementa-tion of smoke-free homes and reduce children’s exposure to SHS.
The results of this trial suggest that adjusted follow-up GM of hair nicotine concentration in the intervention group was 17% lower compared with the control group. However, this difference was not statistically significant, which could be due to insufficient power, as fewer numbers of families provided hair samples at follow-up. The com-parison of children’s hair nicotine concentration at baseline and follow-up revealed statistically significant decreases only in the intervention group.
however, improvement of the mothers’ knowledge score was statistically significantly higher in the intervention group only.
Some of the observed changes in both groups might have been prompted by participation in the study, focusing on children’s exposure to SHS at
homes.24 Moreover, other
research-ers have also reported difficulties in detecting the true difference be-tween groups when the control
group receives a low-intensity in-tervention.25
The current study evaluated the effec-tiveness of an intervention package that included PM2.5measurement at home
to demonstrate the effect of smoking on indoor air quality in the intervention households. PM2.5 measurement does
not require laboratory analysis as do passive air and hair nicotine mea-surements, and it allows an immediate personalized feedback to household members. Several other studies that provided feedback to parents, such as
levels of air nicotine in the home or biochemical markers of SHS exposure as part of the intervention, were effec-tive in SHS reduction and smoking ces-sation.19,26A pilot study by Wilson et al26
provided information to 54 participants about PM2.5 levels in their homes and
suggested that personalized data could make the concept of SHS dangers more real to participants than if they had merely heard or read about it.
A number of studies have investigated methods to reduce children’s SHS exposure by targeting parental smoking
behavior change or smoking cessation. Some of them demonstrated success through decreased children’s SHS exposure measured according to self-reported parental smoking,27–30
reduced levels of air nicotine con-centrations,15,28,30 or reduced urine
cotinine assays.10,27–29 The current
study used participants’self-reported and biochemical (hair nicotine) mea-sures for outcome analysis. Hair nico-tine concentrations provide better information on long-term SHS expo-sure than biomarker meaexpo-sures in urine, saliva, or serum because of the shorter half-life of the latter bio-markers.12 Studies investigating the
correlation between self-reported and objective measures demonstrated that self-reported exposure to SHS may be both a valid and reliable measure to characterize SHS exposure.28,31,32
Adams et al33suggested that parallel
biological or environmental measure-ments and anonymity of the survey enhance the accuracy of self-reported measurements. We targeted both non-smoking mothers and non-smoking family members of the household (mainly children’s fathers) to increase the likelihood of smoking behavior change in the household, considering that the majority of households in Armenia (75%) make joint decisions regarding health-seeking behavior.6
TABLE 1 Baseline Demographic Characteristics of Respondentsa
Characteristic Mothers Household Smokers
Intervention Group (n= 125) Control Group (n= 124) Intervention Group (n= 118) Control Group (n= 112) Age, mean6SD, y 30.465.2 29.765.2 38.2610.6 38.2612.3 Education
Secondary/less than secondary school 45 (36.0) 53 (43.1) 56 (47.5) 69 (61.6) 2-year college 30 (24.0) 30 (24.4) 18 (15.3) 15 (13.4) University/postgraduate degree 50 (38.4) 40 (32.5) 44 (37.3) 28 (25.0) Employed 66 (52.8) 67 (54.5) 87 (73.7) 79 (70.5) Male gender, child 61 (49.2) 69 (55.2) — — Relationship to the child
Mother 125 (100) 124 (100) — — Father — — 79 (81.4) 71 (79.8) Grandfather — — 11 (11.3) 12 (13.5) Grandmother — — 5 (5.2) 3 (3.4)
Uncle — — 2 (2.1) 3 (3.4)
Unless otherwise noted, values are given asn(%).
aNo statistically significant differences between the intervention and control groups (P..05).
TABLE 2 Hair Nicotine Concentration (Nanogram/Milligram) According to Intervention and Control Groups
Variable Intervention Group Control Group
Baseline (n= 83) Follow-up (n= 83) Pa Baseline (n= 90) Follow-up (n= 90) Pa
Mean (95% CI) 0.54 (0.42–0.67) 0.40 (0.30–0.50) .024 0.71 (0.48–0.98) 0.51 (0.38–0.65) .613 Median (IQR) 0.30 (0.14–0.87) 0.27 (0.11–0.52) 0.30 (0.12–0.68) 0.30 (0.11–0.65) GM (95% CI) 0.30 (0.23–0.39) 0.23 (0.18–0.29) 0.29 (0.22–0.39) 0.27 (0.21–0.35)
CI, confidence interval; IQR, interquartile range.
aPairedttest using log-transformed data.
TABLE 3 Multiple Linear Regression Model for Children’s Follow-up Hair Nicotine Concentration
Variable Ratio of GM 95% CI P
Group
Control 1.00 — —
Intervention 0.83 0.61–1.14 .238 Child’s age, y 0.94 0.83–1.08 .396 Baseline hair nicotine concentration, ng/mg 1.57 1.39–1.77 ,.001 Child’s gender
Male 1.00 — —
Female 1.04 0.76–1.42 .825
This study was a single-blind trial: the participants did not know whether they were assigned to the intervention or control group; they were also blinded to the study hypothesis and details of the intervention and control group proce-dures, which minimized the possibility of differential reporting regarding the outcome variables.34,35
Seasonal variations were shown to affect the level of indoor SHS exposure in earlier studies.23 The current study conducted
measurements in late spring and early autumn (with similar weather conditions) to adjust for seasonalfluctuations in in-door smoking behavior; therefore, we had to limit the follow-up period to 4 months. However, this limited time in-terval does not allow for evaluation of longer-term effects of the intervention.
This intervention was not designed to achieve smoking cessation; however, a few smokers did quit. Several studies have shown that strategies which target
SHS reduction may indirectly lead to smoking cessation.10,23,28,36 The
meta-analysis of published controlled trials found that interventions targeting chil-dren had tangible potential for modifi -cation of parental behavior, including parental smoking cessation rate.37
Thefindings of this study emphasize the importance of motivational interview-ing and providinterview-ing immediate person-alized feedback for addictive behavior change. They could be relevant not only for Armenia but other countries, par-ticularly former Soviet Republics with similar rates of smoking and high ex-posure to SHS, and for other countries with large disparities in male/female smoking rates. This intervention can be tested in other settings. In Armenia, pediatricians and pediatric nurses are required to make 2 home visits to newborns. Moreover, monthly well-check visits to primary health care clinics are covered by the state for infants aged ,1 year. Such a system
TABLE 4 Smoking Restrictions Before and After the Intervention
Respondent Group Follow-up Baseline,n(%) ORa(95% CI) Any Restriction No Restriction
Mother Intervention Any restriction 45 (36.0) 28 (22.4) 4.67 (1.89–13.78) No restriction 6 (4.8) 46 (36.8)
Control Any restriction 55 (44.4) 22 (17.7) 3.14 (1.30–8.71) No restriction 7 (5.6) 40 (32.3)
Smoker Intervention Any restriction 61 (50.8) 21 (17.8) 2.62 (1.12–6.85) No restriction 8 (6.8) 28 (23.7)
Control Any restriction 59 (53.2) 18 (16.2) 2.25 (0.93–5.98) No restriction 8 (7.2) 26 (23.4)
CI, confidence interval.
aMcNemar’s test for matched pairs.
TABLE 5 Children’s Exposure to SHS Before and After the Intervention
Respondent Group Follow-up Baseline,n(%) ORa(95% CI) Less Than Daily Daily
Mother Intervention Less than daily 4 (3.2) 25 (20.0) 51 (3.08–860.92)b Daily 0 (0) 96 (76.8)
Control Less than daily 4 (3.2) 15 (12.2) 31 (1.83–519.26)b Daily 0 (0) 104 (84.6)
Smoker Intervention Less than daily 6 (5.1) 17 (14.5) 8.50 (2.02–75.85) Daily 2 (1.7) 92 (78.6)
Control Less than daily 8 (7.1) 12 (10.7) 6.0 (1.34–55.20) Daily 2 (1.8) 90 (80.4)
CI, confidence interval.
aMcNemar’s test for matched pairs. bCalculated by adding 0.5 to each cell.
TABLE 6 Unadjusted and Adjusted ORs for Comparing Intervention and Control Groups According to Household Smoking Restrictions and Children’s Exposure to SHS
Variable Mother Smoker
ORa(95% CI) Adjusted ORb,c(95% CI)a ORa(95% CI) Adjusted ORb,c(95% CI)a Household smoking restrictions
No restriction 1.00 (Ref) 1.00 (Ref) 1.00 (Ref) 1.00 (Ref) Any restriction 1.06 (0.58–1.94) 1.10 (0.59–2.05) 1.13 (0.59–2.16) 1.29 (0.66–2.53) Children’s exposure SHS
Daily 1.00 (Ref) 1.00 (Ref) 1.00 (Ref) 1.00 (Ref) Less than daily 1.73 (0.88–3.42) 1.87 (0.93–3.74) 1.29 (0.61–2.73) 1.54 (0.70–3.39)
CI, confidence interval.
aUnivariate logistic regression analysis. bMultiple logistic regression analysis.
would allow for developing and testing a pediatric practice-based modifi ca-tion of our model to reduce children’s exposure to SHS at homes.
CONCLUSIONS
This study demonstrated that in-person counseling, along with provision of im-mediate personalized feedback and
follow-up counseling telephone calls, was effective in decreasing children’s personal exposure to SHS. In addition, it more ef-fectively educated nonsmoking mothers about the health hazards of SHS and promoted smoking restrictions at home than providing an educational leaflet alone. The superiority of intensive intervention over the minimal intervention was not statistically significant; there is
a need for a cost-effectiveness evaluation to justify implementation of the intensive intervention or to test its effectiveness in other settings.
ACKNOWLEDGMENTS
The authors thank Marie Diener-West for her thorough review of the analysis and valuable comments; they also thank the participants of the study.
REFERENCES
1. US Department of Health and Human Services.The Health Consequences of In-voluntary Exposure to Tobacco Smoke: A Report of the Surgeon General. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention, Coordinating Center for Health Promotion, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2006
2. Jenkins RA, Guerin MR, Tompkins BA. The chemistry of environmental tobacco smoke: composition and measurement. Washington DC; Lewis Publishers 2000
3. US Environmental Protection Agency. Re-spiratory Health Effects of Passive Smok-ing: Lung Cancers and Other Disorders. Washington, DC: Office of Research and Development, Office of Health and Environ-mental Assessment; 1992
4. World Health Organization.Tobacco Free Ini-tiative. International Consultation on Envi-ronmental Tobacco Smoke (ETS) and Child Health. Consultation Report. Geneva, Switzerland: World Health Organization; 1999 5. US Department of Health and Human Services.Children and Secondhand Smoke Exposure. Excerpts from The Health Con-sequences of Involuntary Exposure to To-bacco Smoke: A Report of the Surgeon General, Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Co-ordinating Center for Health Promotion, National Center for Chronic Disease Pre-vention and Health Promotion, Office on Smoking and Health, 2007
6. National Statistical Service [Armenia], Ministry of Health [Armenia], and ICF In-ternational. 2012. Armenia Demographic and Health Survey 2010. Calverton, Maryland: National Statistical Service, Ministry of Health, and ICF International
7. Gyurjyan G, Bazarchyan A. Report on the results of the national survey on the drug,
alcohol and smoking prevalence among the general population of Armenia 2005. Available at: www.ichd.org/download.php? f=352&fc=Drug_Survey_eng.pdf. Accessed July 2012
8. Movsisyan N, Sahakyan K, Petrosyan V. Household smoking rules in Armenia. In: Abstracts from 14 th World Conference on Tobacco or Health (WCTOH), March 2009, Mumbai, India. Indian J Cancer. 2010;47: 109–210
9. World Health Organization. Policies to re-duce exposure to environmental tobacco smoke. Report on a WHO Working Group Meeting. Lisbon, Portugal; May 29–30, 2000 10. Hovell MF, Meltzer SB, Wahlgren DR, et al. Asthma management and environmental tobacco smoke exposure reduction in Latino children: a controlled trial. Pediat-rics. 2002;110(5):946–956
11. Marbury MC, Hammond SK, Haley NJ. Mea-suring exposure to environmental tobacco smoke in studies of acute health effects.Am J Epidemiol. 1993;137(10):1089–1097 12. Al-Delaimy WK. Hair as a biomarker for
exposure to tobacco smoke. Tob Control. 2002;11(3):176–182
13. Global Adult Tobacco Survey Collaborative Group. Global Adult Tobacco Survey (GATS): Core Questionnaire with Optional Ques-tions, Version 2.0. Atlanta, GA: Centers for Disease Control and Prevention, 2010
14. Curry SJ, Ludman EJ, Graham E, Stout J, Grothaus L, Lozano P. Pediatric-based smoking cessation intervention for low-income women: a randomized trial.Arch Pediatr Adolesc Med. 2003;157(3):295–302
15. Emmons KM, Hammond SK, Fava JL, Velicer WF, Evans JL, Monroe AD. A randomized trial to reduce passive smoke exposure in low-income households with young children. Pediatrics. 2001;108(1):18–24
16. Rubak S, Sandbaek A, Lauritzen T, Christensen B. Motivational interviewing: a systematic
review and meta-analysis.Br J Gen Pract. 2005;55(513):305–312
17. US Environmental Protection Agency. Sec-ondhand tobacco smoke and the health of your family. Available at: http://wwwepa-gov/smokefree/pdfs/trifold_brochurepdf. Accessed July 1, 2012
18. Model AM510 SIDEPAKTM Personal Aerosol Monitor. User guide. Available at: http:// tobaccofreeair.org/downloads/1980456b% 20SidePak%20manual.pdf. Accessed July 1, 2012
19. DiClemente CC, Marinilli AS, Singh M, Bellino LE. The role of feedback in the process of health behavior change.Am J Health Behav. 2001;25(3):217–227 20. Wipfli H, Avila-Tang E, Navas-Acien A, et al;
Famri Homes Study Investigators. Second-hand smoke exposure among women and children: evidence from 31 countries.Am J Public Health. 2008;98(4):672–679 21. Fleiss JL.Statistical Methods for Retes and
Proportions. 2nd ed. John Wiley; New York; 1981
22. Heritier SR, Gebski VJ, Keech AC. Inclusion of patients in clinical trial analysis: the intention-to-treat principle. Med J Aust. 2003;179(8):438–440
23. Gehrman CA, Hovell MF. Protecting children from environmental tobacco smoke (ETS) exposure: a critical review. Nicotine Tob Res. 2003;5(3):289–301
24. Conway TL, Woodruff SI, Edwards CC, Hovell MF, Klein J. Intervention to reduce envi-ronmental tobacco smoke exposure in La-tino children: null effects on hair biomarkers and parent reports. Tob Con-trol. 2004;13(1):90–92
25. Klerman L. Protecting children: reducing their environmental tobacco smoke expo-sure. Nicotine Tob Res. 2004;6(suppl 2): S239–S253
smoke in the home: a feasibility study. Tob Control. 2013;22(5):e8
27. Greenberg RA, Strecher VJ, Bauman KE, et al. Evaluation of a home-based in-tervention program to reduce infant pas-sive smoking and lower respiratory illness. J Behav Med. 1994;17(3):273–290 28. Hovell MF, Meltzer SB, Zakarian JM, et al.
Reduction of environmental tobacco smoke exposure among asthmatic children: a con-trolled trial.Chest. 1994;106(2):440–446 29. Hovell MF, Zakarian JM, Matt GE, Hofstetter
CR, Bernert JT, Pirkle J. Effect of counsel-ling mothers on their children’s exposure to environmental tobacco smoke: rando-mised controlled trial.BMJ. 2000;321(7257): 337–342
30. Wahlgren DR, Hovell MF, Meltzer SB, Hofstetter CR, Zakarian JM. Reduction of
environmental tobacco smoke exposure in asthmatic children. A 2-year follow-up. Chest. 1997;111(1):81–88
31. Chiu HT, Isaac Wu HD, Kuo HW. The re-lationship between self-reported tobacco exposure and cotinines in urine and blood for pregnant women. Sci Total Environ. 2008;406(1–2):331–336
32. Matt GE, Wahlgren DR, Hovell MF, et al. Measuring environmental tobacco smoke exposure in infants and young children through urine cotinine and memory-based parental reports: empirical findings and discussion.Tob Control. 1999;8(3):282–289 33. Adams J, Parkinson L, Sanson-Fisher RW,
Walsh RA. Enhancing self-report of adoles-cent smoking: the effects of bogus pipeline and anonymity.Addict Behav. 2008;33(10): 1291–1296
34. Schulz KF, Grimes DA. Blinding in rando-mised trials: hiding who got what.Lancet. 2002;359(9307):696–700
35. Friedberg JP, Lipsitz SR, Natarajan S. Chal-lenges and recommendations for blinding in behavioral interventions illustrated us-ing a case study of a behavioral in-tervention to lower blood pressure.Patient Educ Couns. 2010;78(1):5–11
36. McIntosh NA, Clark NM, Howatt WF. Re-ducing tobacco smoke in the environment of the child with asthma: a cotinine-assisted, minimal-contact intervention. J Asthma. 1994;31(6):453–462
37. Rosen LJ, Noach MB, Winickoff JP, Hovell MF. Parental smoking cessation to protect young children: a systematic review and meta-analysis. Pediatrics. 2012;129(1):141– 152
CIRCADIAN RESET WHILE RESTING UNDER THE STARS:The internal clocks that
govern our sleep-wake cycle are heavily influenced by artificial light exposure. Increasingly exposed to artificial light deep into the evening hours, many have pushed bedtime back, only to still wake up groggy even after eight hours of sleep. For those of us who wish we could be more in tune with a natural sleep cycle, a week outdoors may be all we need to put us back on track.
As reported by the BBC (Science & Environment: August 1, 2013), researchers investigating the effect of artificial light on sleep-wake cycles found an associ-ation between increased natural light exposure and changes in study partic-ipants’ circadian rhythms. Eight participants’ self-selected sleeping patterns were observed after one week in their typically electrically-lit environments and then again following one week of camping in Colorado where the only light came from the sun and a campfire. Melatonin, a hormone closely linked to circadian modulation and sleep onset was measured in participant salivary samples. Generally, melatonin rises just before sleep and decreases through the night until awakening. During the camping portion of the study, participants were exposed, on average, to four times the light exposure experienced in their electrically-lit environment.
While in their typical artificially-lighted environment, melatonin elevations rose two hours before going to sleep, usually at midnight or so, and remained elevated even after awakening, suggesting that they were out of sync with their natural rhythm. However, after one week of camping, melatonin levels rose two hours earlier (around 9-10 pm), with elevations occurring nearer to the time of sunset. Melatonin levels fell early in the morning about the time of participants’natural awakening and close to sunrise. No significant changes in sleep duration or efficiency occurred when the environment was changed.
While this study is small, it indicates that exposure to artificial light potentially acts as a strong, though easily changed, external cue. If future research solidifies the relationship between natural light, sleep-wake cycles, and melatonin, spending more time outside seems like a great way to tune our biologic clock.
DOI: 10.1542/peds.2012-2351 originally published online November 4, 2013;
2013;132;1071
Pediatrics
Frances Stillman
Arusyak Harutyunyan, Narine Movsisyan, Varduhi Petrosyan, Diana Petrosyan and
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DOI: 10.1542/peds.2012-2351 originally published online November 4, 2013;
2013;132;1071
Pediatrics
Frances Stillman
Arusyak Harutyunyan, Narine Movsisyan, Varduhi Petrosyan, Diana Petrosyan and
Trial
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