Introduction Asian Americans suffer high rates of smoking and tobacco-related deaths, varying by ethnic group. Trends of cigarette and alternative tobacco product use among Asian Americans, specifically considering ethnic group, sex, and nativity, are infrequently reported. Methods Using National Health Interview Survey (NHIS) data from 2006–2018 and the 2016–2018 alternative tobacco supplement (e-cigarettes, cigars, smokeless tobacco, pipes), we explored cigarette and alternative tobacco product use by Asian ethnic group (Asian Indian ( n = 4373), Chinese ( n = 4736), Filipino ( n = 4912)) in comparison to non-Hispanic Whites (NHWs ( n = 275,025)), adjusting for socioeconomic and demographic factors. Results Among 289,046 adults, 12% of Filipinos were current smokers, twice the prevalence in Asian Indians and Chinese ( p < 0.001). The male–female gender difference was fivefold for Chinese (10.3% vs. 2.2%; p < 0.001), eightfold for Asian Indians (8.7% vs. 1.1%; p < 0.001), and twofold for Filipinos (16.8% vs. 9.0%). Moreover, 16.3% of US-born and 10.3% of foreign-born Filipinos were current smokers. Odds of ever using e-cigarettes, cigars, smokeless tobacco, and pipes in comparison to NHWs were lowest for Chinese (ORs 0.6, 0.5, 0.2, and 0.5). Discussion Filipinos had the highest current smoking rates of Asian ethnic groups. Though more Asian men were current smokers, the high rate of current smoking among Filipinas is concerning. More US-born Filipinos were current smokers than foreign-born, despite rates typically decreasing for US-born Asians. Investigating cultural factors contributing to less frequent use of tobacco products, such as alternative tobacco products among Chinese, may aid campaigns in curbing tobacco usage. Supplementary Information The online version contains supplementary material available at 10.1007/s40615-021-01024-5.

Introduction COVID-19 continues to impact vulnerable populations disproportionally. Identifying modifiable risk factors could lead to targeted interventions to reduce infections. The purpose of this study is to identify risk factors for testing positive for SARS-CoV-2. Methods Using electronic health records collected from a large ambulatory care system in northern and central California, the study identified patients who had a test for SARS-CoV-2 between 2/20/2020 and 3/31/2021. The adjusted effect of active and passive smoking and other risk factors on the probability of testing positive for SARS-CoV-2 were estimated using multivariable logistic regression. Analyses were conducted in 2021. Results Of 556 690 eligible patients in our sample, 70 564 (12.7%) patients tested positive for SARS-CoV-2. Younger age, being male, racial/ethnic minorities, and having mild major comorbidities were significantly associated with a positive SARS-CoV-2 test. Current smokers (adjusted OR: 0.69, 95% CI: 0.66-0.73) and former smokers (adjusted OR: 0.92, 95% CI: 0.89-0.95) were less likely than nonsmokers to be lab-confirmed positive, but no statistically significant differences were found when comparing passive smokers with non-smokers. The patients with missing smoking status (25.7%) were more likely to be members of vulnerable populations with major comorbidities (adjusted OR ranges from severe: 2.52, 95% CI = 2.36-2.69 to mild: 3.28, 95% CI = 3.09-3.48), lower income (adjusted OR: 0.85, 95% CI: 0.85-0.86), aged 80 years or older (adjusted OR: 1.11, 95% CI: 1.07-1.16), have less access to primary care (adjusted OR: 0.07, 95% CI: 0.07-0.07), and identify as racial ethnic minorities (adjusted OR ranges from Hispanic: 1.61, 95% CI = 1.56-1.65 to Non-Hispanic Black: 2.60, 95% CI = 2.5-2.69). Conclusions Our findings suggest that the odds of testing positive for SARS-CoV-2 were significantly lower in smokers compared to nonsmokers. Other risk factors include missing data on smoking status, being under 18, being male, being a racial/ethnic minority, and having mild major comorbidities. Since those with missing data on smoking status were more likely to be members of vulnerable populations with higher smoking rates, the risk of testing positive for SARS-CoV-2 among smokers may have been underestimated due to missing data on smoking status. Future studies should investigate the risk of severe outcomes among active and passive smokers, the role that exposure to tobacco smoke constitutes among nonsmokers, the role of comorbidities in COVID-19 disease course, and health disparities experienced by disadvantaged groups.

Background Lung cancer has been the leading cause of American deaths from cancer. Although Medicare started covering lung cancer screening (LCS) with low-dose computed tomography (LDCT) in 2015, the uptake of LDCT-LCS remains low. This study examines the changes in adherence to provider referrals for LDCT-LCS and the factors at patient, provider, and health system levels that influence the completion rate of LDCT-LCS orders before and during the COVID-19 pandemic.Methods Our study examined electronic health record data (December 2013 - December 2020) from a large, community-based clinical healthcare delivery system in California. We plotted monthly trends in the frequency of LDCT-LCS orders and completion rate and compared the annual LDCT-LCS completion rate between LCS-eligible and LCS-ineligible groups. We then explored multilevel factors associated with the completion of LDCT-LCS orders using hierarchical generalized linear models.Results There was an increase in LDCT-LCS orders (N = 12,469) from 2013 to 2019, followed by a sharp decline in March 2020 due to the onset of the COVID-19 pandemic. Thereafter, LDCT-LCS orders slowly increased again in June 2020. The completion rate of LDCT-LCS increased from 0% in December 2013 to approximately 70% in 2018–2019 but declined to 50–60% in 2020 during the pandemic. Ineligible patients had lower completion rates of LDCT-LCS. Patients who were new to the healthcare system, Black, received the LDCT-LCS order in the first few years after Medicare coverage (2016 or 2017), during the pandemic, had major comorbidities, and smoked less than 30 pack-years were less likely to complete an order. Patients were more likely to complete LDCT-LCS orders if they were younger, received the LDCT-LCS order from a physician (vs. nonphysician provider), from family medicine or other specialties (vs. internal medicine), or saw a provider with more experience in LDCT-LCS.Conclusions The beginning of the COVID-19 pandemic largely decreased the volume of LDCT-LCS orders, but rates have since been slowing recovering. Future interventions to improve lung cancer screening should consider doing more targeted outreach to new patients and Black patients as well as providing additional education to nonphysician practitioners and those providers with lower rates of LDCT-LCS referral orders.