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Suzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CAInstitute for Addiction Science, University of Southern California, Los Angeles, CA
Department of Medicine, Division of Pulmonary Critical Care and Global Health, Virginia Commonwealth University, Richmond, VADepartment of Surgery, Global Health, Virginia Commonwealth University, Richmond, VA
Department of Psychiatry and Behavioral Sciences, Eastern Virginia Medical School, Norfolk, VAHealthcare Analytics and Delivery Science Institute, Eastern Virginia Medical School, Norfolk, VA
Corresponding Author: Andrew D. Plunk, PhD, Division of Community Health and Research, Eastern Virginia Medical School, 855 W Brambleton Ave, Norfolk, VA 23510, Phone: 757-446-6016; Fax: 757-446-8408
To better understand the inequitable impact of the pandemic by examining associations between stay-at-home orders and indoor smoking in public housing, measured by ambient particulate matter (PM2.5), a marker for secondhand smoke (SHS).
Methods
PM2.5 was measured in six public housing buildings in Norfolk, VA from 2018 – 2022. Multi-level regression was used to compare the seven-week period of the Virginia stay-at-home order in 2020 with that period in other years.
Results
Indoor PM2.5 was 10.29 μg/m3 higher in 2020 (95% CI [8.51, 12.07]) relative to the same period in 2019, a 72% increase. While PM2.5 improved in 2021 and 2022, it remained elevated relative to 2019.
Conclusions
Stay-at-home orders likely led to increased indoor SHS in public housing. In light of evidence linking air pollutants, including SHS, with COVID-19, these results also provide further evidence of the disproportionate impact of the pandemic on socioeconomically disadvantaged communities. This consequence of the pandemic response is unlikely to be isolated and calls for a critical examination of the COVID-19 experience to avoid similar policy failures in future public health crises.
Introduction
Public housing residents, compared to the general public, are more likely to smoke and nonsmoking residents are disproportionately exposed to chronic secondhand smoke (SHS), contributing to persistent health disparities.1 In response, the U.S. Department of Housing and Urban Development (HUD) adopted a federal rule in 2018 requiring Public Housing Authorities (PHAs) to ban smoking in all indoor areas of public housing, and within 25ft of PHA buildings.2 PHA officials have reported challenges implementing the rule, including ensuring resident adherence,3 which may deter the potential health impacts of the rule, particularly on reducing health disparities.4,5 The situation has broader implications for preventive interventions in challenged communities with limited autonomy, including homeless shelters and correctional facilities, where policy effectiveness is undermined by a lack of buy-in and low adherence.
The COVID-19 pandemic has further complicated implementation of the smoke-free housing rule. In the first quarter of 2020, many states issued extended stay-at-home orders in response to the pandemic. These orders have been linked to overall increases in cigarette smoking. For example, in an analysis of U.S. tax data, Asare et al. found that cigarette sales increased by 14% during the pandemic, relative to pre-COVID-19 trends.6
Consideration of cigarette smoking and SHS is important because they are significant risk factors for several major respiratory diseases including COPD, interstitial lung disease, and asthma that are also linked to poorer COVID-19 outcomes. Furthermore, current smoking and SHS exposure have been independently linked to higher COVID-19 mortality.7 On a population level, several studies have also shown a link between COVID-19 and outdoor air pollution.8–10 Particulate matter at the 2.5 micron threshold (PM2.5), a common measure of air pollution also used as a marker of SHS, has been implicated as a potential carrier of SARS-CoV-2, the virus that causes COVID-19.11
This study examined variation in ambient indoor PM2.5 in public housing communities subject to COVID-19 stay-at-home orders. The modeling procedure compared the period of the Virginia order to the same time-period two-years prior and post the stay-at-home order. The implications of stay-at-home orders for health outcomes in vulnerable communities that often have limited control over what happens to them—such as public housing—warranted further study. This assessment has the potential to reduce disparities by suggesting actionable targets of intervention.
Methods
Indoor air quality was monitored in common areas of six multi-unit PHA buildings in Norfolk, VA from 2018 - 2022. The mid-rise apartment buildings were the same across all years and ranged between 47 and 114 units (M = 87 units). Monitor placement maximized comparability between buildings (e.g., not in the direct path of HVAC airflow and similar distance from nearby vents). All common areas were interior spaces large enough for residents to congregate. Lobbies or other exits were not used due to the influx of outside air and monitor placement remained constant over the entire period. PM2.5 measurements were taken hourly using SidePak AM520 aerosol monitors (TSI, Inc., St. Paul, MN) with a flow rate of 1.7 L/min. A calibration factor of 0.32 was applied to yield measurements appropriate for SHS particles, as used in previous work.4 PM2.5 data, expressed as μg/m3, were downloaded twice weekly. The monitors were also cleaned and zero-calibrated on this schedule.
Using linear mixed modeling, average daily PM2.5 during the period spanning March 23rd to May 9th, 2020—the period of the VA stay-at-home order—was compared for the years 2018, 2019, 2020, 2021, and 2022. Seasonality was accounted for by limiting comparisons to the same period across years. Random site and day effects were modelled using the equation:
Version 4.1.0 of R was used for analysis.
Results
Mean indoor PM2.5 ranged from 1.83 – 108.41 μg/m3 across the six sites. Mean PM2.5 in 2018—before indoor smoking was prohibited—was 17.27 μg/m3 (Figure 1). Following the introduction of the ban in 2019, mean PM2.5 decreased to 14.33 μg/m3, but peaked in 2020 (24.52 μg/m3). PM2.5 decreased in 2021 (22.68 μg/m3) and 2022 (22.14 μg/m3), but not to levels observed before the pandemic. Analysis suggests the stay-at-home order was associated with 72% higher ambient indoor SHS relative to the same period in 2019, corresponding to a PM2.5 increase of 10.29 μg/m3 (95% CI [8.51, 12.07]; see the Appendix for the full model). While indoor air quality did improve in 2021 and 2022 after the stay-at-home order was lifted, PM2.5 remained 56.8% and 55.1% higher in 2021 and 2022, respectively, relative to 2019.
FigureMean daily indoor PM2.5 for the period of the 2020 Virginia stay-at-home order, March 23rd through May 9th, for the years 2018 – 2022.
Mean PM2.5 measured in the common areas of six Norfolk, VA mid-rise public housing buildings is shown.
The 2020 stay-at-home order was associated with increased ambient indoor SHS, and, by inference, SHS exposure among public housing residents. This is of particular concern because public housing residents entered the pandemic with a higher burden of smoking-related disease.12,13 While public housing residents have a multitude of other risk factors for poor health outcomes, this finding may contribute to understanding the increased burden and disparate COVID-19 outcomes observed in other studies of socioeconomically disadvantaged localities.14 For example, increased indoor smoking could have offset potential health benefits related to decreased exposure to outdoor pollution associated with COVID-19 stay-at-home orders and other pandemic-related restrictions.15
This study has limitations. PM2.5 is a non-specific marker of combustion. However, PM2.5 was shown to be a valid measure of tobacco smoke in earlier work conducted in the same locations.4 While it is unclear whether these findings are generalizable, there is evidence of low adherence with public housing smoke-free policies prior to the pandemic in multiple settings4,5 and the poorly coordinated COVID-19 pandemic response likely exacerbated factors already contributing to the failure of these policies to live up to their promise of protecting residents from harms associated with SHS. Extreme consequences—eviction, which could mean homelessness for this population—coupled with inconsistent enforcement had already undermined residents’ perceived legitimacy of the policies. Active, sustained, and meaningful resident engagement likely was the sole path forward. Unfortunately, the pandemic created additional barriers to policy enforcement (e.g., property managers working offsite).
With adequate resources and careful planning, HUD and local housing authorities could have supported public-housing residents with adherence to smoke-free rules or smoking cessation assistance during the stay-at-home phase of the COVID-19 pandemic. However, these efforts likely would have meant starting from a deficit, limited by the lack of trust and buy-in needed to engage residents to determine how best to support them. Further, while the reasons for persistently elevated levels of SHS exposure are not clear, these findings call for ongoing investigation and coordinated future interventions to prevent widening of the health disparities experienced by public housing residents and other socioeconomically marginalized groups.
Ensuring equitable responses to future public health crises will require a critical examination of the COVID-19 experience for marginalized groups. These findings suggest a crucial lesson: failing to understand how the deficiencies of the COVID-19 response were driven by, and even reinforced, pre-pandemic disparities will impede efforts to equitably respond to future public health crises. It is naïve to think this unintended consequence of COVID-19 is an isolated phenomenon. To do better in the future, policymakers must anticipate how emergency measures have the potential to cause harm in the presence of existing inequity. Authentic engagement of marginalized communities put in place before the next public health emergency is a necessary first step in this process.
Acknowledgements
Members of the Housing Collaborative Community Advisory Board contributed substantively to this project. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Dr. Choi's effort was supported by the Division of Intramural Research, National Institute on Minority Health and Health Disparities. Comments and opinions expressed in this article belong to the authors and do not necessarily reflect those of the US government, Department of Health and Human Service, National Institutes of Health, and National Institute on Minority Health and Health Disparities.
This research was financially supported by the National Cancer Institute (NCI) and the National Institute on Drug Abuse of the National Institutes of Health under the award numbers R37CA245716 (ADP, AP, BES, RAG, SG, VWR) and R01DA042195 (RAG). The work was also financially supported by the Department of Housing and Urban Development (VWR). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders.
No financial disclosures were reported by the authors of this paper.
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CRediT authorship contribution statement
Sarah Gehlert: Conceptualization, Writing – review & editing. Vaughan W. Rees: Conceptualization, Methodology, Writing – review & editing. Kelvin Choi: Conceptualization, Writing – review & editing. Peter D. Jackson: Writing – review & editing. Brynn E. Sheehan: Writing – review & editing. Richard A. Grucza: Methodology, Writing – review & editing. Amy Paulson: Writing – review & editing. Andrew D. Plunk: Data curation, Methodology, Writing – original draft.
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