IMPORTANCE Secondhand smoke (SHS) exposure is associated with many health conditions in children and adults. Millions of individuals in the US are currently exposed to SHS in their homes. OBJECTIVE To investigate whether a federal ban on smoking in public housing settings was associated with a decrease in indoor SHS levels in New York City public housing developments 12 months after the policy's implementation. DESIGN, SETTING, AND PARTICIPANTS This cohort study tracked indoor air quality longitudinally from April 2018 to September 2019 and used difference-indifferences analysis to examine SHS exposure before vs after implementation of the 2018 federal smoke-free housing (SFH) policy in 10 New York City Housing Authority (NYCHA) buildings vs 11 matched low-income buildings not subject to the SFH policy (ie, Section 8 buildings).

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In 2018, the U.S. Department of Housing and Urban Development required public housing authorities to implement a smoke-free housing (SFH) policy that included individual apartments. We analyzed the policy implementation process in the New York City Public Housing Authority (NYCHA). From June–November 2019, we conducted 9 focus groups with 64 NYCHA residents (smokers and nonsmokers), 8 key informant interviews with NYCHA staff and resident association leaders, and repeated surveys with a cohort of 130 nonsmoking households pre- and 12-month post policy. One year post policy implementation, participants reported widespread smoking violations and multi-level factors impeding policy implementation. These included the shared belief among residents and staff that the policy overreached by “telling people what to do in their own apartments”. This hindered compliance and enforcement efforts. Inconsistent enforcement of illegal marijuana use, staff smoking violations, and a lack of accountability for other pressing housing issues created the perception that smokers were being unfairly targeted, as did the lack of smoking cessation resources. Resident support for the policy remained unchanged but satisfaction with enforcement declined (60.1% vs. 48.8%, p = 0.047). We identified multilevel contextual factors that are influencing SFH policy implementation. Findings can inform the design of strategies to optimize policy implementation.

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Introduction:The percentage of adults in the United States reporting current marijuana use has more than doubled, from 4% to 9% between 2002 and 2018, suggesting that exposure to secondhand marijuana smoke (SHMS) has probably increased. Few studies have characterized the extent to which residents experience SHMS, particularly those living in multi-unit housing. It remains unknown how recently implemented smoke-free housing policies (SFH) targeting cigarette smoke in public housing authorities (PHAs) will affect SHMS exposure.Objective: To characterize prevalence of self-reported SHMS exposure among residents living in two different subsidized housing settings prior to SFH policy implementation in PHAs: New York City Housing Authority (NYCHA) buildings and private sector buildings where most residents receive Section 8 subsidy vouchers (herein 'Section 8' buildings).

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Previous studies have explored using calibrated low-cost particulate matter (PM) sensors, but important research gaps remain regarding long-term performance and reliability. Evaluate longitudinal performance of low-cost particle sensors by measuring sensor performance changes over 2 years of use. 51 low-cost particle sensors (Airbeam 1 N = 29; Airbeam 2 N = 22) were calibrated four times over a 2-year timeframe between 2019 and 2021. Cigarette smoke-specific calibration curves for Airbeam 1 and 2 PM sensors were created by directly comparing simultaneous 1-min readings of a Thermo Scientific Personal DataRAM PDR-1500 unit with a 2.5 µm inlet. Inter-sensor variability in calibration coefficient was high, particularly in Airbeam 1 sensors at study initiation. Calibration coefficients for both sensor types trended downwards over time to < 1 at final calibration timepoint [Airbeam 1 Mean (SD) = 0.87 (0.20); Airbeam 2 Mean (SD) = 0.96 (0.27)]. We lost more Airbeam 1 sensors (N = 27 out of 56, failure rate 48.2%) than Airbeam 2 (N = 2 out of 24, failure rate 8.3%) due to electronics, battery, or data output issues. Evidence suggests degradation over time might depend more on particle sensor type, rather than individual usage. Repeated calibrations of low-cost particle sensors may increase confidence in reported PM levels in longitudinal indoor air pollution studies.

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