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Purpose: To (1) assess whether residential rurality/urbanicity was associated with the prevalence of 30‐ or 90‐day long COVID, and (2) evaluate whether differences in long COVID risk factors might explain this potential disparity. Methods: We used data from the Michigan COVID‐19 Recovery Surveillance Study, a population‐based probability sample of adults with COVID‐19 (n = 4,937). We measured residential rurality/urbanicity using dichotomized Rural‐Urban Commuting Area codes (metropolitan, nonmetropolitan). We considered outcomes of 30‐day long COVID (illness duration ≥30 days) and 90‐day long COVID (illness duration ≥90 days). Using Poisson regression, we estimated unadjusted prevalence ratios (PRs) to compare 30‐ and 90‐day long COVID between metropolitan and nonmetropolitan respondents. Then, we adjusted our model to account for differences between groups in long COVID risk factors (age, sex, acute COVID‐19 severity, vaccination status, race and ethnicity, socioeconomic status, health care access, SARS‐CoV‐2 variant, and pre‐existing conditions). We estimated associations for the full study period (Jan 1, 2020‐May 31, 2022), the pre‐vaccine era (before April 5, 2021), and the vaccine era (after April 5, 2021). Findings: Compared to metropolitan adults, the prevalence of 30‐day long COVID was 15% higher (PR = 1.15 [95% CI: 1.03, 1.29]), and the prevalence of 90‐day long COVID was 27% higher (PR = 1.27 [95% CI: 1.09, 1.49]) among nonmetropolitan adults. Adjusting for long COVID risk factors did not reduce disparity estimates in the pre‐vaccine era but halved estimates in the vaccine era. Conclusions: Our findings provide evidence of a rural‐urban disparity in long COVID and suggest that the factors contributing to this disparity changed over time as the sociopolitical context of the pandemic evolved and COVID‐19 vaccines were introduced. [ABSTRACT FROM AUTHOR]

Objectives: Fragmented industry and occupation surveillance data throughout the COVID‐19 pandemic has left public health practitioners and organizations with an insufficient understanding of high‐risk worker groups and the role of work in SARS‐CoV‐2 transmission. Methods: We drew sequential probability samples of noninstitutionalized adults (18+) in the Michigan Disease Surveillance System with COVID‐19 onset before November 16, 2020 (N = 237,468). Among the 6000 selected, 1839 completed a survey between June 23, 2020, and April 23, 2021. We compared in‐person work status, source of self‐reported SARS‐CoV‐2 exposure, and availability of adequate personal protective equipment (PPE) by industry and occupation using weighted descriptive statistics and Rao‐Scott χ2 tests. We identified industries with a disproportionate share of COVID‐19 infections by comparing our sample with the total share of employment by industry in Michigan using 2020 data from the US Bureau of Labor Statistics. Results: Employed respondents (n = 1244) were predominantly female (53.1%), aged 44 and under (54.4%), and non‐Hispanic White (64.0%). 30.4% of all employed respondents reported work as the source of their SARS‐CoV‐2 exposure and 78.8% were in‐person workers. Work‐related exposure was prevalent in Nursing and Residential Care Facilities (65.2%); Justice, Public Order, and Safety Activities (63.3%); and Food Manufacturing (57.5%). By occupation, work‐related exposure was highest among Protective Services (57.9%), Healthcare Support (56.5%), and Healthcare Practitioners (51.9%). Food Manufacturing; Nursing and Residential Care; and Justice, Public Order, and Safety Activities were most likely to report having adequate PPE "never" or "rarely" (36.4%, 27.9%, and 26.7%, respectively). Conclusions: Workplaces were a key source of self‐reported SARS‐CoV‐2 exposure among employed Michigan residents during the first year of the pandemic. To prevent transmission, there is an urgent need in public health surveillance for the collection of industry and occupation data of people infected with COVID‐19, as well as for future airborne infectious diseases for which we have little understanding of risk factors. [ABSTRACT FROM AUTHOR]

Background and Aims: Tobacco control policies may differentially impact smoking initiation among socio-demographic groups. We measured longitudinal associations between exposure to smoke-free laws in grade 12 (modal age 18 years) and patterns of smoking initiation in the United States. Design: Prospective longitudinal analysis. Setting and Participants: We used data on US young adults sampled at modal age 18 years from the Monitoring the Future Survey. Baseline data were collected between 2000 and 2017, with the last year of follow-up in 2018. The sample number varied by outcome and time-point, ranging from 7314 to 17 702. Measurements: Smoke-free law coverage in work-places and hospitality venues (restaurants/bars) was measured as the percentage of the county population covered by each type of law. We examined associations with any past 30-day smoking initiation and daily smoking initiation at modal ages 19/20, 21/22 and 23/24, using Poisson regression and calculating average marginal effects. We explored effect modification by sex, race/ethnicity and parental education by testing the significance of interaction terms. Findings: Work-place law coverage at modal age 18 was associated with a lower probability of daily smoking initiation at modal ages 21/22 [-2.4 percentage points (p.p.); 95% confidence interval (CI) = -3.9, -0.9] and 23/24 (-2.0 p.p.; 95% CI = -3.9, -0.2). Hospitality law coverage was associated with a lower probability of daily smoking initiation at modal ages 19/20 (-1.6 p.p.; 95% CI = -2.8, -0.4), 21/22 (-2.3 p.p.; 95% CI = -3.7, -0.9) and 23/24 (-1.8 p.p.; 95% CI = -3.6, -0.0). Findings were inconclusive with regard to associations with any past 30-day smoking initiation and with regard to effect modification, after adjusting for multiple testing. Conclusions: Exposure to smoke-free laws at age 18 appears to be prospectively associated with reduced daily smoking initiation 1-6 years later. [ABSTRACT FROM AUTHOR]