Developing a peer-led intervention to promote COVID-19 testing in low-income housing settings.

Background: The Housing Collaborative project at Eastern Virginia Medical School has developed a method of adapting public health guidance from public housing communities, which face tremendous health challenges in cardiometabolic health, cancer, and other major health conditions. In this paper, we describe how academic and community partners in the Housing Collaborative came together to do this work with a focus on COVID-19 testing in the context of the emerging pandemic. Methods: The academic team used virtual community engagement methods to interact with the Housing Collaborative Community Advisory Board (HCCAB) and a separate cohort of research participants (N = 102) recruited into a study of distrust in COVID-19 guidance. We conducted a series of 44 focus group interviews with participants on related topics. Results from these interviews were discussed with the HCCAB. We used the collaborative intervention planning framework to inform adaptation of public health guidance on COVID-19 testing delivered in low-income housing settings by including all relevant perspectives. Results: Participants reported several important barriers to COVID-19 testing related to distrust in the tests and those administering them. Distrust in housing authorities and how they might misuse positive test results seemed to further undermine decision making about COVID-19 testing. Pain associated with testing was also a concern. To address these concerns, a peer-led testing intervention was proposed by the Housing Collaborative. A second round of focus group interviews was then conducted, in which participants reported their approval of the proposed intervention. Conclusion: Although the COVID-19 pandemic was not our initial focus, we were able to identify a number of barriers to COVID-19 testing in low-income housing settings that can be addressed with adapted public health guidance. We struck a balance between community input and scientific rigor and obtained high quality, honest feedback to inform evidence-based recommendations to guide decisions about health.

COVID-19 Stay-At-Home Orders and Secondhand Smoke in Public Housing.

INTRODUCTION: This study aimed to better understand the inequitable impact of the pandemic by examining the associations between stay-at-home orders and indoor smoking in public housing, measured by ambient particulate matter at the 2.5-micron threshold, a marker for secondhand smoke. METHODS: Particulate matter at the 2.5-micron threshold was measured in 6 public-housing buildings in Norfolk, VA from 2018 to 2022. Multilevel regression was used to compare the 7-week period of the Virginia stay-at-home order in 2020 with that period in other years. RESULTS: Indoor particulate matter at the 2.5-micron threshold was 10.29 µg/m3 higher in 2020 (95% CI=8.51, 12.07) than in the same period in 2019, a 72% increase. Although particulate matter at the 2.5-micron threshold improved in 2021 and 2022, it remained elevated relative to the level in 2019. CONCLUSIONS: Stay-at-home orders likely led to increased indoor secondhand smoke in public housing. In light of evidence linking air pollutants, including secondhand smoke, 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.

Virtual engagement of under-resourced communities: Lessons learned during the COVID-19 pandemic for creating crisis-resistant research infrastructure.

The COVID-19 pandemic led to an increased need to conduct research and community engagement using digital methods. Unfortunately, the shift away from in-person research activities can make it difficult to engage and recruit participants from under-resourced communities that lack adequate digital infrastructure. At the beginning of the pandemic, our team recognized that imminent lockdowns would significantly disrupt ongoing engagement with low-income housing resident community partners and that we would ultimately bear responsibility if that occurred. This manuscript outlines the development of methods designed to create capacity for virtual engagement with a community advisory board that were subsequently applied to a longitudinal mixed-methods study. We describe how our experience engaging low-income housing residents during the height of the pandemic influenced the approach and offer guidelines useful for engaging under-resourced communities regardless of setting. Of these, a strong commitment to providing technology, unlimited data connectivity, and basic digital literacy training/technical support is most important. While each of these is essential and failure in any one area will reduce overall effectiveness of the effort, providing adequate technical support while maintaining ongoing relationships with community members is the most important and resource-intensive.

A Qualitative Study of Unfairness and Distrust in Smoke-free Housing.

Objectives: Whereas smoke-free housing (SFH) has the potential to protect residents from tobacco smoke, evidence suggests that SFH could lead to increased indoor smoking. In this study, we examine how perceptions of a residential smoking ban could be related to non-compliance. Methods: We conducted 8 focus group interviews of low-income housing residents living in Norfolk, Virginia (N=53). Interviews were semi-structured and based on a list of guided questions related to SFH compliance, developed in partnership with a standing community advisory board comprised of low-income housing residents. Results: Several themes emerged, including pervasive non-compliance, perceived unfairness and shame, barriers to compliance, and distrust of the housing authority. Smokers reported behavior primarily motivated by punishment avoidance, rather than out of any perceived obligation to comply with the ban. Conclusions: Results led us to consider Procedural Justice Theory as a conceptual framework, in which compliance is directly related to perceptions about the legitimacy of a rule or authority. When compliance is low due to a lack of perceived legitimacy, SFH should be adapted to promote changes in smoking behavior. We offer specific theory-supported adaptations to SFH focused on trust-building and improving perceived fairness.

Development of a Risk Behavior Diagnosis Scale for E-cigarette Use.

Objectives: Adolescent use of electronic cigarettes has risen dramatically, prompting concerns about the health effects. There is need for brief measures to assess adolescents' perceived threat and efficacy related to e-cigarette use and cessation. A 12-item Likert-type scale was modeled after the Risk Behavior Diagnosis Scale and designed to assess threat (ie, severity and susceptibility of threat) and efficacy (ie, self-efficacy and response efficacy) as they relate to e-cigarette use. Methods: The scale was administered online to a developmental sample of 674 adolescents to examine internal consistency and factor structure. Participants (52.1% female, M age = 14.6) were representative of the surrounding community (60% non-Hispanic white; 27% non-Hispanic black; 8% Hispanic). Results: Factor analysis and Velicer's minimum average partial test revealed 2 factors (as expected), which explained 68% of the variance. Analyses revealed strong internal consistency, with Cronbach's alpha of .93 overall and alphas of .92 and .87 for threat and efficacy subscales, respectively. The measure also exhibited good convergent and discriminant validity with other constructs. Conclusions: The measure demonstrates strong preliminary reliability and validity for a developmental sample of adolescents.

Association of Racial Disparity of Cannabis Possession Arrests Among Adults and Youths With Statewide Cannabis Decriminalization and Legalization.

Importance: Despite calls for cannabis decriminalization and legalization, research investigating the association of policy with arrest rates and racial disparities is scarce. Objectives: To examine racial differences in cannabis arrest rates among adults and youths after statewide decriminalization, legalization, and no policy changes. Design Setting and Participants: This case-control study used race-based arrest data from the Uniform Crime Reporting Program and Surveillance, Epidemiology, and End Results county-level population data from January 2000 through December 2019. Data were analyzed in July 2021. Event-study analyses based on the arrest rates from 43 US states were conducted to compare preimplementation and postimplementation differences in arrest rates for states with decriminalization, legalization, and no policy changes. Exposures: Nine states implemented legalization, 8 implemented decriminalization, and 26 had no policy change. Main Outcomes and Measures: Outcome measures were cannabis arrest rates for Black and White adults and youths per year and by state, while controlling for several covariates. Results: Rates were reported per 100 000. When comparing absolute differences in arrests from January to December 2008 (before policy changes) to January to December 2019, legalization was associated with 561 and 195 fewer arrests and decriminalization with 448.6 and 117.1 fewer arrests for Black and White adults, respectively. States without a policy change saw reductions of 47.5 and 33.0 arrests for Black and White adults, respectively. Among youth, legalization was associated with 131.1 and 131.2 fewer arrests and decriminalization with 156.1 and 124.7 fewer arrests for Black and White youths, respectively. Among states without a policy change, arrests reduced by 35 and 52.4 for Black and White youths, respectively. Plotted trends of the arrest ratios from January 2000 through December 2019 suggests racial disparities remained over time. Event-study analyses suggest that decriminalization was associated with an arrest rate reduction for Black and White adults and youths. The timing of reductions suggests differential policy effects. Arrest disparities increased in states that did not have a cannabis policy change. Conclusions and Relevance: In this case-control study of states with and without cannabis decriminalization and legalization policies, increased arrest rate disparities in states without either policy highlight the need for targeted interventions to address racial injustice.

Increases in Secondhand Smoke After Going Smoke-Free: An Assessment of the Impact of a Mandated Smoke-Free Housing Policy.

OBJECTIVE: The 12-month impact of federally mandated smoke-free housing (SFH) policy adoption (July 2018) was assessed using two markers of ambient secondhand smoke (SHS): airborne nicotine and particulate matter at the 2.5-micrometer threshold (PM2.5). METHODS: We measured markers of SHS in Norfolk, VA from December 2017 to December 2018 in six federally subsidized multi-unit public housing buildings. Multi-level regression was used to model the following comparisons: (1) the month immediately before SFH implementation versus the month immediately after, and (2) December 2017 versus December 2018. RESULTS: There was a 27% reduction in indoor PM2.5 and a 32% reduction in airborne nicotine in the first month after SFH adoption, compared to the month prior to adoption. However, there was a 33% increase in PM2.5 and a 25% increase in airborne nicotine after 12 months. CONCLUSIONS: US Department of Housing and Urban Development (HUD)-mandated SFH can reduce SHS in multi-unit housing. However, SFH could also plausibly increase indoor smoking. Policy approaches adopted by individual properties or housing authorities-for example, property-wide bans versus allowing designated smoking areas-could be driving this potential unintended consequence. IMPLICATIONS: Successful implementation of SFH by public housing authorities in response to the HUD rule requires ongoing attention to implementation strategies. In this sense, SFH likely differs from other policies that might be seen as less intrusive. Long-term success of SFH will depend on careful policy implementation, including plans to educate and support housing authority staff, inform and engage residents, and build effective partnerships with community agencies.

Longitudinal Analysis of Associations Between Reasons for Electronic Cigarette Use and Change in Smoking Status Among Adults in the Population Assessment of Tobacco and Health Study.

INTRODUCTION: Electronic cigarette (ECIG) use and changes in cigarette smoking status may be influenced by self-reported reasons for using ECIGs. METHODS: We analyzed adult current and former cigarette smokers who were also current or former ECIG users at wave 1 (n = 3044) using wave 1 and wave 2 Population Assessment of Tobacco and Health Study data (2013-2015). Prevalence of reporting 13 reasons for ECIG use at wave 1 was examined and weighted logistic regressions were conducted predicting smoking status changes from wave 1 to wave 2. RESULTS: Reasons for ECIG use ranged from 18.1% (people in the media or public figures use them) to 82.5% (they might be less harmful to people around me than cigarettes). From wave 1 to wave 2, 27.2% of former smokers (n = 249) became current smokers and 11.6% of current smokers (n = 246) became former smokers. Among wave 1 former smokers, using ECIGs because of the availability of flavors (AOR = 0.57, 95% CI = 0.39-0.85) or because they don't smell (AOR = 0.64, 95% CI = 0.42-0.97) was associated with lower odds of relapse to smoking, but using ECIGs because using them helps people quit smoking (AOR = 1.55, 95% CI = 1.01-2.38) was associated with greater odds of relapse. Among wave 1 current smokers, using ECIGs because they can be used where smoking is not allowed (AOR = 0.56, 95% CI = 0.38-0.85) was associated with reduced odds of quitting cigarettes. CONCLUSIONS: Some reasons for ECIG use are associated with changes in self-reported smoking status. Researchers should examine ECIG user characteristics when assessing associations between ECIG use and smoking status transitions. IMPLICATIONS: Given that certain reasons for ECIG use, such as using ECIGs in locations are where smoking is not allowed, may inhibit smoking reduction, policies may be developed to prevent ECIG use in locations where smoking is banned. In addition, because certain reasons for ECIG use may aid in relapse prevention, such as availability of desired flavors, efforts should be made to identify ECIG device characteristics that are appealing to smokers but not youth or nontobacco users. These results provide support for future research on reasons for ECIG use to inform regulatory policies.

Youth and Adult Arrests for Cannabis Possession After Decriminalization and Legalization of Cannabis.

IMPORTANCE: Civil liberty advocates typically support legalization of cannabis, which targets adult use, rather than decriminalization, which can affect both adults and youths. However, it is unknown how arrests of youths for cannabis possession change when adult use of cannabis is legalized. OBJECTIVE: To model changes in arrest rates of adults and youths after decriminalization and legalization of cannabis. DESIGN, SETTING, AND PARTICIPANTS: This quasi-experimental study used the publicly available Uniform Crime Reporting Program Data: Arrests by Age, Sex, and Race administrative data set to examine arrest rates in 38 states from January 1, 2000, to December 31, 2016. Adult (age, ≥18 years) and youth (age, <18 years) arrests for possession of cannabis were examined. States were excluded if they did not report complete arrest data or if a policy was implemented that reduced penalties for possession of cannabis but fell short of decriminalization. Fixed-effects regression was used in an extended difference-in-differences framework. The analyses in their final form were conducted between January 17 and February 28, 2019. EXPOSURE: Living in a state with a cannabis decriminalization policy (ie, making the penalty for cannabis possession similar to the small fine for a traffic violation) or legalization policy (ie, creating a legal supply of cannabis along with the removal of penalties for possession of a small amount of cannabis for recreational use). MAIN OUTCOME AND MEASURES: State cannabis possession arrest rate per 100 000 population. RESULTS: Data from 38 states were examined, including 4 states with cannabis legalization policies and 7 states with cannabis decriminalization policies. The adult arrest rate decreased by 131.28 (95% CI, 106.23-154.21) per 100 000 population after the implementation of decriminalization and 168.50 (95% CI, 158.64-229.65) per 100 000 population after the implementation of legalization. The arrest rate for youths decreased by 60 (95% CI, 42-75) per 100 000 population after decriminalization but did not significantly change after legalization in a state (7 per 100 000 population; 95% CI, -15 to 30). CONCLUSIONS AND RELEVANCE: Legalization, as implemented through 2016, did not appear to reduce arrests for cannabis possession among youths, despite having benefited adults. The study's findings suggest that decriminalization reduces youth arrests in most cases, but these findings also suggest that any benefit for youths could be lost when adult use has also been legalized. To address this problem, it appears that state decriminalization policies should take the additional step to explicitly describe when youths can be arrested for possession of small amounts of cannabis.

Cannabis decriminalization: A study of recent policy change in five U.S. states.

BACKGROUND: A number of public health professional organizations support the decriminalization of cannabis due to adverse effects of cannabis-related arrests and legal consequences, particularly on youth. We sought to examine the associations between cannabis decriminalization and both arrests and youth cannabis use in five states that passed decriminalization measures between the years 2008 and 2014: Massachusetts (decriminalized in 2008), Connecticut (2011), Rhode Island (2013), Vermont (2013), and Maryland (2014). METHODS: Data on cannabis possession arrests were obtained from federal crime statistics; data on cannabis use were obtained from state Youth Risk Behavior Survey (YRBS) surveys, years 2007-2015. Using a "difference in difference" regression framework, we contrasted trends in decriminalization states with those from states that did not adopt major policy changes during the observation period. RESULTS: Decriminalization was associated with a 75% reduction in the rate of drug-related arrests for youth (95% CI: 44%, 89%) with similar effects observed for adult arrests. Decriminalization was not associated with any increase in the past-30 day prevalence of cannabis use overall (relative change=-0.2%; 95% CI: -4.5%, 4.3%) or in any of the individual decriminalization states. CONCLUSIONS: Decriminalization of cannabis in Massachusetts, Connecticut, Rhode Island, Vermont, and Maryland resulted in large decreases in cannabis possession arrests for both youth and adults, suggesting that the policy change had its intended consequence. Our analysis did not find any increase in the prevalence of youth cannabis use during the observation period.

Patterns of youth tobacco and polytobacco usage: The shift to alternative tobacco products.

BACKGROUND: Despite significant declines in youth cigarette smoking, overall tobacco usage remains over 20% as non-cigarette tobacco product usage is increasingly common and polytobacco use (using 1+ tobacco product) remains steady. OBJECTIVES: The present study was designed to identify patterns of youth tobacco use and examine associations with sociodemographic characteristics and tobacco dependence. METHODS: The current analysis uses Latent Class Analysis (LCA) to examine the 6,958 tobacco users (n = 2,738 female) in the National Youth Tobacco Survey (2012 and 2013). We used as indicators past month use of tobacco products (cigarettes, cigars, smokeless tobacco, e-cigarettes, hookah, snus, pipes, bidis, and kreteks) and regressed resulting classes on sociodemographic characteristics and tobacco dependence. RESULTS: Nine classes emerged: cigarette smokers (33.4% of sample, also included small probabilities for use of cigars and e-cigarettes), cigar smokers (16.8%, nearly exclusive), smokeless tobacco users (12.3%, also included small probabilities for cigarettes, cigars, snus), hookah smokers (11.8%), tobacco smokers/chewers (10.7%, variety of primarily traditional tobacco products), tobacco/hookah smokers (7.2%), tobacco/snus/e-cig users (3.3%), e-cigarette users (2.9%,), and polytobacco users (1.7%, high probabilities for all products). Compared to cigarette smokers, tobacco/hookah smokers and hookah smokers were more likely to report Hispanic ethnicity. Polytobacco users were more likely to report dependence (AOR:2.77, 95% CI:[1.49-5.18]), whereas e-cigarette users were less likely (AOR:0.49, 95% CI:[0.24-0.97]). CONCLUSION: Findings are consistent with other research demonstrating shifts in adolescent tobacco product usage towards non-cigarette tobacco products. Continuous monitoring of these patterns is needed to help predict if this shift will ultimately result in improved public health.

The impact of adolescent exposure to medical marijuana laws on high school completion, college enrollment and college degree completion.

BACKGROUND: There is concern that medical marijuana laws (MMLs) could negatively affect adolescents. To better understand these policies, we assess how adolescent exposure to MMLs is related to educational attainment. METHODS: Data from the 2000 Census and 2001-2014 American Community Surveys were restricted to individuals who were of high school age (14-18) between 1990 and 2012 (n=5,483,715). MML exposure was coded as: (i) a dichotomous "any MML" indicator, and (ii) number of years of high school age exposure. We used logistic regression to model whether MMLs affected: (a) completing high school by age 19; (b) beginning college, irrespective of completion; and (c) obtaining any degree after beginning college. A similar dataset based on the Youth Risk Behavior Survey (YRBS) was also constructed for confirmatory analyses assessing marijuana use. RESULTS: MMLs were associated with a 0.40 percentage point increase in the probability of not earning a high school diploma or GED after completing the 12th grade (from 3.99% to 4.39%). High school MML exposure was also associated with a 1.84 and 0.85 percentage point increase in the probability of college non-enrollment and degree non-completion, respectively (from 31.12% to 32.96% and 45.30% to 46.15%, respectively). Years of MML exposure exhibited a consistent dose response relationship for all outcomes. MMLs were also associated with 0.85 percentage point increase in daily marijuana use among 12th graders (up from 1.26%). CONCLUSIONS: Medical marijuana law exposure between age 14 to 18 likely has a delayed effect on use and education that persists over time.

The Impact of the Minimum Legal Drinking Age on Alcohol-Related Chronic Disease Mortality.

BACKGROUND: The minimum legal drinking age (MLDA) of 21 has been associated with a number of benefits compared to lower MLDAs, including long-term effects, such as reduced risk for alcoholism in adulthood. However, no studies have examined whether MLDA during young adulthood is associated with mortality later in life. We examined whether individuals exposed to permissive MLDA (<21) had higher risk of death from alcohol-related chronic disease compared to those exposed to the 21 MLDA. Because prior work suggests that MLDA affects college students differently, we also conducted conditional analyses based on ever having attended college. METHODS: Data from the 1990 through 2010 U.S. Multiple Cause-of-Death files were combined with data on the living population and analyzed. We included individuals who turned 18 during the years 1967 to 1990, the period during which MLDA varied across states. We examined records on death from several alcohol-related chronic diseases, employing a quasi-experimental approach to control for unobserved state characteristics and stable time trends. RESULTS: Individuals who reported any college attendance did not exhibit significant associations between MLDA and mortality for the causes of death we examined. However, permissive MLDA for those who never attended college was associated with 6% higher odds for death from alcoholic liver disease, 8% higher odds for other liver disease, and 7% higher odds for lip/oral/pharynx cancers (odds ratio [OR] = 1.06, 95% confidence interval [CI] [1.02, 1.10]; OR = 1.08, 95% CI [1.03, 1.13]; OR = 1.07, 95% CI [1.03, 1.12], respectively). CONCLUSIONS: The 21 MLDA likely protects against risk of death from alcohol-related chronic disease across the lifespan, at least for those who did not attend college. This is consistent with other work that shows that the long-term association between MLDA and alcohol-related outcomes is specific to those who did not attend college.

Declining Prevalence of Marijuana Use Disorders Among Adolescents in the United States, 2002 to 2013.

OBJECTIVE: Little is known about recent trends in marijuana use disorders among adolescents in the United States. We analyzed trends in the past-year prevalence of DSM-IV marijuana use disorders among adolescents, both overall and conditioned on past-year marijuana use. Potential explanatory factors for trends in prevalence were explored. METHOD: We assembled data from the adolescent samples of the 2002 to 2013 administrations of the National Survey on Drug Use and Health (N = 216,852; aged 12-17 years). The main outcome measures were odds ratios describing the average annual change in prevalence and conditional prevalence of marijuana use disorders, estimated from models of marijuana use disorder as a function of year. Post hoc analyses incorporated measures of potentially explanatory risk and protective factors into the trend analyses. RESULTS: A decline in the past-year prevalence of marijuana use disorders was observed (odds ratio = 0.976 per year; 95% CI = 0.968, 0.984; p < .001). This was due to both a net decline in past-year prevalence of use and a decline in the conditional prevalence of marijuana use disorders. The trend in marijuana use disorders was accounted for by a decrease in the rate of conduct problems among adolescents (e.g., fighting, stealing). CONCLUSION: Past-year prevalence of marijuana use disorders among US adolescents declined by an estimated 24% over the 2002 to 2013 period. The decline may be related to trends toward lower rates of conduct problems. Identification of factors responsible for the reduction in conduct problems could inform interventions targeting both conduct problems and marijuana use disorders.

Did the 18 Drinking Age Promote High School Dropout? Implications for Current Policy.

OBJECTIVE: Disagreement exists over whether permissive minimum legal drinking age (MLDA) laws affected underage adolescents (e.g., those age 17 years with the MLDA of 18). We used MLDA changes during the 1970s and 1980s as a natural experiment to investigate how underage exposure to permissive MLDA affected high school dropout. METHOD: MLDA exposure was added to two data sets: (a) the 5% public use microdata samples of the 1990 and 2000 censuses (n = 3,671,075), and (b) a combined data set based on the 1991-1992 National Longitudinal Alcohol Epidemiological Survey (NLAES) and the 2001-2002 National Epidemiological Survey on Alcohol and Related Conditions (NESARC; n = 16,331). We used logistic regression to model different thresholds of MLDA on high school dropout. We also estimated models conditioned on demographic variables and familial risk of developing alcohol problems. RESULTS: Only the MLDA of 18 predicted high school dropout. Exposure was associated with 4% and 13% higher odds of high school dropout for the census and NLAES/NESARC samples, respectively. We noted greater impact on women (5%-18%), Blacks (5%-19%), and Hispanics (6%). Self-report of parental alcohol problems was associated with 40% higher odds, which equals a 4.14-point increase in dropout rate for that population. CONCLUSIONS: The MLDA of 18 likely had a large impact on high school dropout rates, suggesting that the presence of legal-aged peers in a high school setting increased access to alcohol for younger students. Our results also suggest that policy can promote less dangerous drinking behavior even when familial risk of alcohol use disorders is high.

A reexamination of medical marijuana policies in relation to suicide risk.

OBJECTIVES: Previous research has suggested that medical marijuana policies lead to reductions in suicide rates. In this study, we further investigate the association between these policies and within-state changes in suicide risk. METHODS: Data on suicide deaths (n=662,993) from the National Vital Statistics System Multiple Cause of Death files were combined with living population data. Fixed-effects regression methods were employed to control for state differences in suicide rates and national and state secular trends. Analyses extended prior research that suggested a protective effect of medical marijuana policies by incorporating newer data and additional covariates. RESULTS: After adjustment for race/ethnicity, tobacco control policies, and other covariates, we found no association between medical marijuana policy and suicide risk in the population ages 15 and older (OR=1.000; 95% CI: 0.956, 1.045; p=0.98), among men overall (OR=0.996; 95% CI: 0.951, 1.043; p=0.87) or for any other age-by-sex groups. CONCLUSION: We find no statistically significant association between medical marijuana policy and suicide risk. These results contradict prior analyses which did not control for race/ethnicity and certain state characteristics such as tobacco control policies. Failure to control for these factors in future analyses would likely bias estimates of the associations between medical marijuana policy and health outcomes.