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Attitudes and experiences with secondhand smoke and smoke-free policies among subsidised and market-rate multiunit housing residents living in six diverse communities in the USA
  1. Andrea S Gentzke1,2,
  2. Andrew Hyland1,
  3. Marc Kiviniemi3,
  4. Mark J Travers1
  1. 1 Department of Health Behavior, Roswell Park Cancer Institute, Buffalo, New York, USA
  2. 2 Department of Epidemiology and Environmental Health, State University of New York at Buffalo, Buffalo, New York, USA
  3. 3 Department of Community Health and Health Behavior, State University of New York at Buffalo, Buffalo, New York, USA
  1. Correspondence to Dr Andrea S Gentzke, Department of Health Behavior, Roswell Park Cancer Institute, Elm & Carlton Streets, Buffalo, NY 14263, USA ; aslicht01{at}gmail.com

Abstract

Background Given that higher smoking rates persist among lower socioeconomic populations, multiunit housing (MUH) environments may result in higher secondhand smoke (SHS) exposures among subsidised MUH residents. This cross-sectional assessment compares experiences with SHS and smoke-free policies among subsidised and market-rate MUH residents living in six US communities.

Methods MUH residents (n=1565) were surveyed regarding their smoke-free rules (home and building), SHS exposures and preferences towards smoke-free policies. Binary logistic regression identified predictors of each outcome, focusing on differences by subsidised housing status (subsidised vs market rate).

Results Among residents enforcing smoke-free home rules (76%, overall), 50% reported SHS incursions into their unit. Only 23% reported living in a smoke-free building; 56% of those living in smoking-allowable buildings reported preferences towards smoke-free building policies. Among market-rate housing residents, smoke-free home (OR=4.18) and building (OR=2.26) rules were significantly higher when children were present. Smoke-free building rules reduced the odds of SHS incursions among market-rate housing residents (OR=0.50), but no association was observed among subsidised housing residents. Non-smoking subsidised housing residents exhibited stronger preferences for smoke-free policies compared with those in market-rate housing.

Discussion Smoke-free home rules may not protect MUH residents from SHS exposures, particularly in subsidised MUH. Although strong preferences towards smoke-free policies were present overall, subsidised MUH residents may have fewer alternative smoke-free housing options available. Therefore, all publicly funded housing should be smoke free to protect these vulnerable populations. However, continued efforts to encourage privately owned MUH operators to adopt smoke-free policies are also necessary.

  • Secondhand Smoke
  • Multiunit Housing
  • Policy
  • Smoke-free
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What this paper adds

  • Secondhand smoke (SHS) can move throughout a multiunit housing (MUH) building, entering into spaces where tobacco smoking is otherwise prohibited. Although clean indoor air legislation has contributed to reductions in SHS exposure over time, the magnitude of this decline has been smaller for lower socioeconomic groups.

  • To date, most of the MUH literature has focused on the attitudes and experiences with SHS and smoke-free policies among subsidised or market-rate housing residents, exclusively. The current study, however, compares the experiences with SHS and smoke-free policies between these MUH populations.

  • Results show that market-rate housing residents had significantly higher odds of protection from SHS through smoke-free home and building rules, particularly when children were present in the home, while no association was observed for either outcome among subsidised housing residents. Non-smoking subsidised housing residents exhibited stronger preferences for smoke-free building policies, but may have fewer opportunities to seek out smoke-free living environments, providing support for mandated smoke-free policies in all subsidised housing.

Introduction

The US Surgeon General has extensively documented the harmful health effects of secondhand smoke (SHS) exposure, concluding that there is no safe level of exposure to SHS.1 Smoke-free air legislation has contributed to reductions in SHS exposures among US adults and children, but gaps in protection remain particularly in private settings such as homes and vehicles.1 2 Although the prevalence of US households with voluntary smoke-free home rules has increased considerably over the last two decades,2 3 this space still represents a major source of SHS exposure in both children and adults.1 4–6 Despite efforts to reduce SHS exposure in public places, about one-third of US adults and approximately 32 million children remain involuntarily exposed to SHS.3 7 These gaps in protection are not randomly distributed in the population, as disparities in SHS exposures are also observed by socioeconomic status (SES).8 Over the last two decades, the magnitude of the decline in SHS exposures has been smaller for lower SES populations, widening the gap between low-income and high-income groups for SHS exposures.7

Multiunit housing (MUH) environments may perpetuate these disparities. Over 79 million individuals, or about 25% of the US population, currently reside in MUH,9 though a greater proportion of MUH residents live below the poverty line and identify as racial or ethnic minorities compared with the US population overall.9–11 Air circulation patterns inside MUH can facilitate the migration of tobacco smoke through shared hallways and ventilation systems, potentially entering into units and areas where smoking is otherwise restricted.5 12–15 Therefore, despite having a similar prevalence of smoke-free homes rules as the US population overall,3 it is estimated that 27.6–28.9 million MUH residents are exposed to SHS in their home.9 Given the socioeconomic disparities in MUH residency9–11 and in the prevalence of smoking,8 MUH environments may put vulnerable populations, including children, the elderly and those who are disabled, at an increased risk of health complications due to SHS exposures.

Due to differences in resident populations, attitudes and experiences with SHS and preferences towards smoke-free policies may vary between residents of subsidised (public and affordable) and market-rate MUH. However, literature to date has primarily focused on either subsidised,16–19 or market-rate housing residents,20 21 exclusively, or has not distinguished the study population according to subsidised housing status.22–25 The purpose of this paper is to describe and compare the experiences and preferences towards SHS exposures and smoke-free housing policies among both subsidised and market-rate MUH residents living in six diverse communities throughout the USA.

Methods

This paper describes the baseline data analysis of a longitudinal community-based educational intervention study aimed at increasing the adoption of smoke-free MUH policies. This study was initiated in three community pairs across the USA: Bismarck (BM) and Grand Forks (GF), North Dakota; Fort Collins (FC) and Pueblo (PB), Colorado; and Charleston (CH) and Columbia (CO), South Carolina. These communities were selected with the assistance of Americans for Nonsmokers’ Rights (Berkley, California, USA) based on their size and the availability of an existing group of public health practitioners present in each community that were familiar with issues related to SHS but who were not actively engaged in smoke-free MUH activities at the time of selection. All communities selected were protected by comprehensive smoke-free air legislation in public places either at the state (ND and CO) or local (SC) level.

Data were collected between August and December 2012 via telephone. Individuals aged 18 and older who resided in MUH (apartment, duplex, double/multifamily home, condominium or townhouse) and lived in each specified community were eligible for this study. Data collection was initiated using random digit dial (RDD) of landline (n=18 000) and cell phone (n=60 000) numbers. The sampling frame was restricted to the zip codes that represented each community. Commercially available lists of renters in each community were also included in the sampling frame. The renter lists (n=3) were called consecutively following the exclusion of duplicate records in the previous RDD and listed samples. Calling on these samples (RDD and listed) were completed until samples were exhausted. Figure 1 provides the number of completed interviews, response rates (RDD) and participation rates (lists) for each data source. The response rate for the RDD component was 32.1% (combined cell and landline), calculated using the American Association for Public Opinion Research (AAPOR) Response Rate 3 calculator.26 The participation rates for the listed samples ranged from 7.5% to 12.1% after exclusion of ineligible records. In households with more than one adult, a random selection process determined who was interviewed. The survey took approximately 25 min to complete. All MUH residents who completed the survey were mailed a check for $10. All study procedures were approved by the Institutional Review Board at Roswell Park Cancer Institute.

Figure 1

Completed interviews, response rates and participation rates by data source. AAPOR RR3 accounts for ineligible records within the denominator and estimates how many cases of unknown eligibility are likely to be actually eligible.26 Participation rates were calculated for the listed samples; all records of unknown eligibility were assumed to be eligible and are included in the denominator for these calculations.

AAPOR RR3, American Association of Public Opinion Research, Response Rate calculator 3.

Measures

  1. Enforcing a voluntary smoke-free home rule was defined as a response of ‘No’ to the question: ‘Do you allow smoking inside your residence?’.

  2. Experiencing an SHS incursion into the unit was defined as a response of ‘Everyday’, ‘A few times a week’, ‘A few times a month’ or ‘Rarely’ to the question: ‘In the past 12 months, how often has tobacco smoke entered your unit from somewhere else in or around your building? (vs ‘Never’)’. Analyses of SHS incursions are restricted to respondents who enforced voluntary smoke-free home rules (n=1259).

  3. Two questions were combined to determine the rules about smoking inside the building:

  4. Any rules about smoking in the building were defined as a response of ‘Yes’ to the question: ‘Regardless of whether you personally have set rules about smoking in your home, has your landlord or property manager set any rules regarding smoking on your property?’.

  5. Among respondents with ‘any rules’ in their building, living in a smoke-free building was defined as a response of ‘prohibited inside all areas of the building, including living units’ to the question: ‘Regarding these rules about smoking in the building, which of the following most accurately describes the official smoking policy in your building?’ (vs ‘prohibited in shared areas, but allowed inside living units’).

  6. Preferences towards smoke-free building policies were defined as an answer of ‘Yes’ to the question: ‘Would you prefer to have a policy in your building that prohibits smoking in all indoor areas, including individual residential units and common indoor areas?’ Analyses of preferences are restricted to MUH residents who live in smoking-allowable buildings (n=1061).

Predictors of interest

The primary predictors of interest were the respondent’s subsidised housing status and smoking status.

Subsidised housing residents were defined by an answer of ‘yes’ to the question ‘Do you currently live in public, affordable or subsidized housing or participate in a voucher or low-income housing program?’ Those responding ‘no’ were defined as market-rate housing residents. Responses of ‘don’t know’ or ‘refused’ were excluded (n=38).

Two questions determined the respondent’s smoking status (current smoker vs current non-smoker): (1) ‘Have you smoked at least 100 cigarettes in your lifetime?’ and, if yes, (2) ‘Do you now smoke cigarettes every day, some days, or not at all?’. Those answering ‘yes’ to question (1) and either ‘some days’ or ‘every day' to question (2) were defined as current smokers. Current non-smokers included both never smokers (‘no’ to question (1)) and former smokers (‘yes’ to question (1) and ‘not at all’ to question (2)).

Covariates

Other covariates included age (18–24 years, 25–64 years and 65+ years), sex (male and female), race/ethnicity (white, non-Hispanic, black, non-Hispanic, Hispanic, other or missing), education (<high school, high school graduate/General Educational Development (GED), some college, college graduate or graduate school), presence of 1+ children under the age of 18 in the home (no and yes), sample type (RDD and targeted lists) and knowledge of SHS (continuous, number of questions answered correctly, range: 0–10). Type of MUH was dichotomised as ‘apartment’ versus ‘other’ MUH (duplex, double/multifamily home, townhouse or condominium), given the differences in building structure and ownership status associated with these types of MUH.

Data analysis

Data were analysed using IBM SPSS V.21. Univariate and bivariate analyses are stratified by community and subsidised housing status. Significance testing for univariate analyses was calculated using the χ2 test; p values <0.05 were considered statistically significant.

Binary logistic regression within generalised linear mixed modelling (GLMM) assessed sociodemographic predictors of each outcome of interest overall and according to subsidised housing status (market rate, subsidised) while accounting for community clustering. Missing data in outcomes or predictor variables were excluded from analyses. Statistical tests for multiplicative interaction between subsidised housing status and smoking status were completed to assess whether non-smokers residing in subsidised housing experienced more SHS incursions into their living unit compared with non-smokers residing in market-rate housing.

Weighting procedures

Given the demographic diversity in the communities included in this study, community-specific poststratification weights were developed from Public Use Microdata Areas (PUMAs)27 as opposed to national or state-representative data sources to allow for the comparison of data between communities. PUMAs provide population-level demographic characteristics for geographically concise areas. For each community, PUMA person data were obtained for individuals aged 18 and over who resided in MUH. The frequency distributions for age, sex and race/ethnicity of the PUMA data in each community were used to construct poststratification weights. The weights were normalised to the unweighted sample size and were applied to the data for all univariate and bivariate analyses assessing differences by community. In lieu of applying weights to the multivariate analyses (GLMM), the covariates used in the construction of the weights (age, sex and race/ethnicity) were included in the models as independent variables.

Results

Across all communities, 1565 interviews were obtained. Weighted demographic characteristics of MUH residents overall and stratified by community are reported in table 1. The proportion of current smokers ranged from 23% (GF) to 34% (CO). Between 20% (FC) and 39% (PB) of residents lived in subsidised housing and over half of residents in four communities (PB, CO, BM and GF) had annual household incomes below $30 000. Racial and ethnic characteristics varied by community but were consistent between community pairs.

Table 1

Sociodemographic characteristics of 1565 MUH residents in six communities across the USA, 2012

Voluntary smoke-free home rules

The prevalence of each outcome stratified by community and subsidised housing status is reported in table 2. Voluntary smoke-free home rules were reported by 76% of all respondents, ranging from 64% (CH) to 95% (FC) by community. Only 10% of respondents allowed smoking inside their unit without any restrictions (range: 1.3% (FC) to 15% (CO)). A significantly higher proportion of market-rate housing residents enforced voluntary smoke-free home rules compared with subsidised housing residents overall (82% vs 69%, p<0.001) and within each community.

Table 2

Prevalence of voluntary smoke-free home rules, SHS incursions, rules about smoking in the building and preferences for smoke-free policies among MUH residents living in six communities across the USA: overall and stratified by public/affordable housing versus market-rate housing

In multivariate modelling overall, non-smokers were significantly more likely to report enforcing smoke-free home rules compared with current smokers (OR=14.73, 95% CI: 10.25 to 21.17; table 3). Residents of subsidised housing were about 30% less likely to enforce smoke-free home rules, though this was marginally non-significant (OR=0.70, 95% CI: 0.49 to 1.002; table 3).

Table 3

Demographic predictors of MUH residents reporting each outcome of interest in six communities across the USA

In analyses restricted to market-rate housing residents, those with children in the home were 4 times more likely to enforce voluntary smoke-free home policies (OR=4.18, 95% CI:1.99 to 8.79) compared with those without children. Among subsidised housing residents, higher odds of smoke-free home rules were observed for women (OR=2.18, 95% CI: 1.19 to 3.98) and those with a college education (OR=3.58, 95% CI: 1.18 to 10.87).

Rules about smoking in the building

Twenty-three percent (23.4%) of all respondents reported living in a smoke-free building, but most (67.3%) reported having no rules about smoking inside the building where they lived (table 2). Smoke-free building rules ranged from 6.4% (CO) to >40% (BM, GF) in community stratified analyses. Overall, smoke-free building policies were more common among residents of market-rate housing compared with those in subsidised housing though differences were noted in community-stratified analyses.

In multivariable modelling, no differences in smoke-free building policies were observed according to subsidised housing status (table 3). Overall, non-smokers were nearly twice as likely to live in a smoke-free building compared with current smokers (OR=1.94, 95% CI: 1.32 to 2.84; table 3), and similar associations were observed in analyses stratified by subsidised housing status (table 4). Market-rate housing residents with children in the home were twice as likely to live in a smoke-free building (OR=2.26, 95% CI: 1.38 to 3.76; table 4). Non-apartment style MUH residents were significantly less likely to reside in a smoke-free building, but this association persisted only among market-rate housing residents in stratified analyses (OR=0.35 (95% CI: 0.25 to 0.51; table 4).

Table 4

Demographic predictors of MUH residents reporting each outcome in six communities across the US: stratified by subsidised housing status*

SHS incursions

Approximately 50% of residents who enforce smoke-free home rules reported experiencing an SHS incursion into their unit from somewhere else in or around the building, ranging from 34% (CH) to over 75% (FC) in community-stratified analyses (table 2).

In multivariable modelling, no main effects of SHS incursions were observed according to smoking status or subsidised housing status (table 3). However, there is suggestive evidence (p=0.18) of an interaction between smoking and subsidised housing status on experiencing SHS incursions, in which non-smokers residing in subsidised housing had increased odds of reporting SHS incursions (OR=1.8, 95% CI: 0.8 to 4.5; not shown) compared with non-smokers residing in market-rate housing. Overall, higher odds of experiencing SHS incursions into the unit were observed among Hispanic respondents (OR=1.79, 95% CI: 1.04 to 3.09) and women (OR=1.47, 95% CI: 1.10 to 1.95). Residents of non-apartment style MUH buildings (OR=0.72, 95% CI: 0.54 to 0.96) and older individuals (65+; OR=0.46, 95% CI: 0.22 to 0.93) were both less likely to report incursions (table 3).

Respondents who lived in a smoke-free building had significantly reduced odds of reporting SHS incursions into their unit compared with those who lived in a smoke-permitted building (OR=0.59, 95% CI: 0.44 to 0.80; table 3). Although market-rate housing residents also experienced reduced odds of SHS exposure due to smoke-free building policies (OR=0.50, 95% CI: 0.35 to 0.71, table 4), there was no difference in SHS incursions according to smoke-free building status among residents of subsidised housing.

Preferences for smoke-free building policies

Over half (56%) of respondents who reside in smoking-allowable buildings reported they would prefer to have a policy in their building that prohibited smoking in all areas (range: 45% (PB) to 68% (GF); table 2). Preferences for smoke-free policies did not differ according to subsidised housing status overall, but community-specific differences were observed (table 2). Over 90% of residents already living in a smoke-free building reported preferences towards smoke-free building policies (data not shown).

In multivariable adjusted analyses, non-smokers were significantly more likely to report preferences towards smoke-free building policies overall (OR=5.80, 95% CI: 3.99 to 8.45; table 3) and in analyses stratified by subsidised housing (table 4). Those with children in the home were about 70% more likely to prefer a smoke-free building policy (OR=1.68, 95% CI: 1.05 to 2.68; table 3). In analyses restricted to market-rate housing, non-apartment style MUH residents were 40% less likely to prefer a smoke-free building policy (OR=0.58, 95% CI: 0.40 to 0.84; table 4) compared with apartment dwellers.

Discussion

Despite enforcing smoke-free home rules, half of MUH residents reported experiencing SHS incursions into their personal living space, indicating that personal smoke-free home rules do not confer full protection from SHS exposures in smoking-allowable MUH buildings.12–15 Although the majority of residents reported they would prefer to have a policy inside their building that prohibited smoking in all location, only about 25% actually lived in a building with a policy. Although multiple factors may play a role in choosing MUH, such as price, location and available amenities, this suggests there is a disconnect between preferences and availability of smoke-free living environments across the range of factors that are considered important in making housing decisions. Despite variation in smoke-free building rules and external influences of community-level tobacco control policies, preferences towards smoke-free policies were generally consistent across communities and with previously reported estimates.24 25

Higher smoking rates and SHS exposures persist among populations with lower socioeconomic indicators.7 8 This study found evidence to suggest that non-smokers living in subsidised housing may have higher SHS exposures in their homes compared with non-smokers living in market-rate housing. Furthermore, the relationship between smoking status and preferences towards smoke-free policies was stronger among residents of subsidised housing, suggesting that in addition to the greater need for smoke-free policies in subsidised housing, there may also be higher demand for smoke-free policies in this environment.

The clean indoor air legislation in Colorado and North Dakota prohibits smoking in commonly used areas of MUH buildings.28 29 However, a sizeable proportion of residents in these states reported that smoking was allowed ‘anywhere, or at any time’ inside their building. These findings suggest there is a lack of enforcement of these regulations and that there is a need to educate residents and building operators about these MUH-specific smoking restrictions.

The extent of state-level or community-level tobacco control policies may influence perceptions towards SHS exposures in the home environment. For example, residents living in states without comprehensive clean indoor air legislation, such as South Carolina, may become desensitised to tobacco smoke exposures occurring inside their homes due to more frequent exposures in public places. In the current study, South Carolina MUH residents reported the fewest SHS incursions into their units, despite having the lowest prevalence of smoke-free building policy coverage. Although community-level clean indoor air policies were present in both Charleston and Columbia, South Carolina, this discrepancy in SHS exposures in the home may have been influenced by the lack of a comprehensive smoke-free air policy at the state level.30

Among residents of market-rate housing, non-smokers and those with children in the home were more likely to reside in a smoke-free building, suggesting that specific populations may be seeking out smoke-free living environments. However, financial constraints and housing availability may limit the ability of subsidised housing residents to seek out smoke-free housing. In this study, market-rate housing residents were also more likely to enforce voluntary smoke-free home rules when children were present in the home, whereas no association was observed among residents of subsidised housing. Therefore, in addition to SHS exposures from in or around the building, children living in subsidised housing may also experience SHS exposures originating from active smoking inside their unit. Moreover, the accumulation of tobacco smoke pollution inside these units and buildings may contribute to thirdhand smoke exposures,31 placing children and other vulnerable populations at increased risk of health effects from these pollutants.

In late 2015, the US Department of Housing and Urban Development (HUD) proposed a rule prohibiting the use of lit tobacco products inside all public housing authority (PHA) buildings.32 According to this rule, finalised in December 2016 and effective as of February 2017, all PHAs must implement a smoke-free policy no later than 18 months from the effective date, banning the use of all prohibited tobacco products (cigarettes, cigars, pipes and waterpipes/hookahs) inside PHA living units, indoor common areas, administrative offices and buildings, and will extend to outdoor areas up to 25 feet (7.62 meters) from PHA buildings and offices.33 However, the majority of MUH residents would not be directly affected by the HUD rule, including approximately 5 million residents participating in Section 8 or other voucher programmes as well as the remaining 72 million residents living in market-rate housing.34 Although socioeconomic disparities in protection from SHS exposures underscore the importance of continued work to encourage or mandate subsidised and public housing providers to implement smoke-free building policies, efforts are also needed to promote policy adoption among market-rate housing operators.

Results of this study suggest that individuals residing in non-apartment style MUH, such as duplexes, townhouses or condominiums, may have different experiences with SHS in their homes due to varying building structures and ownership that could influence their attitudes towards smoke-free building policies. Residents of non-apartment style MUH reported fewer SHS incursions, lower preferences towards smoke-free building policies and fewer smoke-free building rules compared with apartment-style MUH. A higher proportion of residents living in townhouses or condominiums may own their units compared with apartment-style MUH residents, which may affect attitudes regarding individuals’ rights to smoke inside these personal living spaces. In addition, it may be comparatively more difficult to adopt smoke-free policies in these MUH environments because modifications to existing rules may require approvals by homeowners’ association and resident advisory boards.35 Public health personnel need to be aware of these important differences when working with non-traditional MUH communities to effectively encourage smoke-free policy adoption.

This study is not without limitations. First, as this study was confined to six US communities, the results may not be generalisable to other populations, particularly in regions not represented in this study. Second, because MUH residents are a difficult segment of the population to reach using population-based sampling methods (RDD), it was necessary to introduce targeted renter lists to increase the efficiency of data collection. Respondents identified using the targeted lists tended to be older, have lower annual household incomes and reside in subsidised housing compared with the RDD respondents. Moreover, the low participation rates obtained from these listed samples may suggest a selection bias in participation, although no information on non-responders from these samples is available to refute these concerns. To compensate for the fact that the respondents identified from these samples may not be representative of the population of MUH residents residing in each community, post-stratification survey weights were introduced to compensate for the particularly low participation among men, younger respondents and certain racial and ethnic groups in this survey. Although low, our RDD response rate (32%) was similar to that calculated for a national RDD survey of MUH residents.24 However, these issues with sample identification and potential selection biases in participation in telephone-based surveys points towards a need to adopt dual-method or non-population based data collection procedures to identify MUH populations in the future, such as the utilisation of targeted lists, address-based sampling procedures (including door-to-door surveys)23 or the integration of Internet panels.25 Third, our outcomes are based on self-report. MUH residents may overestimate the rules about smoking inside their building,21 or there may be interindividual differences in the ability to detect SHS exposures occurring inside one’s home. Moreover, the language used to assess voluntary smoke-free home rules did not elaborate on what constituted ‘smoking’. Therefore, the rules regarding the use of combustible and non-combustible products as well as electronic cigarettes inside the home may be left open to interpretation by individual respondents. Finally, because the self-reported assessment of SHS incursions was assessed over the previous 12 months, respondents living in their residence for less than 1 year (9.4% of sample) may have reported on experiences not related to their current living situation. However, our findings were largely consistent between community pairs, suggesting that any differences would be consistent in larger geographic regions (ie, at the state level). In addition, the main goal of this study overall is to assess changes over time within respondents, so any misclassification from this baseline survey is likely to continue through follow-up.

Conclusions

Voluntary enforcement of smoke-free home rules does not adequately protect MUH residents from SHS exposures inside their homes, particularly in subsidised MUH environments. Strong preferences for smoke-free policies were observed among all MUH residents, although subsidised housing residents may have fewer housing options available to seek out alternative smoke-free living environments. Due to these disparities, all publically funded housing should be required to implement smoke-free building policies in order to protect these vulnerable populations. However, efforts to encourage privately owned MUH buildings to adopt smoke-free policies should also continue.

References

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Footnotes

  • Contributors All authors were involved in the conceptualisation of this manuscript. ASG conducted the statistical analyses and completed the initial draft of the manuscript. All authors contributed to the interpretation of results and approved the final submitted and revised versions of this manuscript.

  • Funding This project was funded by R01CA151953 (NCI; Travers, Roswell Park Cancer Institute) and R25CA113951 (NCI; Freudenheim, State University of New York at Buffalo).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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