59 research outputs found

    Psychological Health and Smoking in Young Adulthood

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    Introduction: Young adulthood is a critical time for the emergence of risk behaviors including smoking. Psychological health is associated with smoking, but studies rarely track both over time. We used longitudinal data to assess whether average patterns of psychological health influenced average patterns of smoking and whether short-term fluctuations in psychological health influenced fluctuations in smoking. Method: Young adults aged 18–30 from the Panel Study of Income Dynamics were followed from 2007 to 2013, and mean trajectories of smoking were modeled. Psychological health variables included ever having a mental health diagnosis and time-varying distress. Results: In regression models, individuals with poorer psychological health (higher distress or a diagnosis) were more likely to be smokers and to smoke greater number of cigarettes. The association of diagnosis with number of cigarettes smoked increased with age. Conclusions: Smoking-related interventions should target individuals with poorer psychological health, even if they have no formal mental health diagnosis

    Sociodemographic Disparities in Tobacco Retailer Density in the United States, 2000-2017

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    Introduction: Studies find differences in tobacco retailer density according to neighborhood sociodemographic characteristics, raising issues of social justice, but not all research is consistent. Aims and Methods: This study examined associations between tobacco retailer density and neighborhood sociodemographic characteristics in the United States at four timepoints (2000, 2007, 2012, and 2017) and investigated if associations remained stable over time. Data on tobacco retailers came from the National Establishment Time-Series Database. Adjusted log-linear models examined the relationship between retailer density and census tract sociodemographic characteristics (% non-Hispanic Black [Black], % Hispanic, % vacant housing units, median household income), controlling for percentage of youth, urbanicity, and US region. To examine whether the relationship between density and sociodemographic characteristics changed over time, additional models were estimated with interaction terms between each sociodemographic characteristic and year. Results: Tobacco retailer density ranged from 1.22 to 1.44 retailers/1000 persons from 2000 to 2017. There were significant, positive relationships between tobacco retailer density and the percentage of Black (standardized exp(b) = 1.05 [95% CI: 1.04% to 1.07%]) and Hispanic (standardized exp(b) = 1.06 [95% CI: 1.05% to 1.08%]) residents and the percentage of vacant housing units (standardized exp(b) =1.08 [95% CI: 1.07% to 1.10%]) in a census tract. Retailer density was negatively associated with income (standardized exp(b) = 0.84 [95% CI: 0.82% to 0.86%]). From 2000 to 2017, the relationship between retailer density and income and vacant housing units became weaker. Conclusions: Despite the weakening of some associations, there are sociodemographic disparities in tobacco retailer density from 2000 to 2017, which research has shown may contribute to inequities in smoking. Implications: This study examines associations between tobacco retailer density and neighborhood sociodemographic characteristics in the United States at four timepoints from 2000 to 2017. Although some associations weakened, there are sociodemographic disparities in tobacco retailer density over the study period. Research suggests that sociodemographic disparities in retailer density may contribute to inequities in smoking. Findings from this study may help identify which communities should be prioritized for policy intervention and regulation

    Urban-rural differences in tobacco product availability in food retailers, United States, 2017

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    Purpose: Tobacco use prevalence is higher in rural compared to urban settings, possibly due to differences in tobacco availability, including the option to purchase food and other essential items in stores that do not sell tobacco (tobacco-free food retailers). The goal of this research is to determine whether tobacco-free food retailer availability varies by urbanicity/rurality. Methods: Using the 2017 National Establishment Time-Series database, we identified food retailers across all census tracts containing food retailers in the United States (n = 66,053). We used multivariable logistic and linear regression models to test whether tobacco-free food retailer availability varied across 4-levels of census tract urbanicity/rurality (urban, suburban, large town, and small town/rural) for 2 outcomes: (1) the presence of at least 1 tobacco-free food retailer and (2) the percent of all food retailers that were tobacco-free. Findings: Compared to urban core census tracts, suburban census tracts had a lower odds (aOR = 0.77, 95% CI = 0.73, 0.81) of having at least 1 tobacco-free food retailer, while small town/rural census tracts had greater odds (aOR = 1.23, 95% CI = 1.15, 1.32). Suburban census tracts (B = –2.29, P <.001) and large town census tracts (B = –1.90, P <.001) also had a lower percentage of tobacco-free food retailers compared to urban census tracts. Conclusions: Compared to urban cores, tobacco-free food retailers were less prevalent in suburban and large town areas, though similarly or slightly more available in rural areas. Future research should assess whether these differences depend on varying store types

    Associations of County Tobacco Retailer Availability With U.S. Adult Smoking Behaviors, 2014–2015

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    Introduction: Greater availability of tobacco product retailers in an area may be associated with smoking behaviors, and the majority of people who smoke purchase their cigarettes at gas stations and convenience stores. This cross-sectional study investigates the associations of overall tobacco retailer density and gas/convenience density with adult smoking behaviors. Methods: This study built a list of tobacco retailers in 2014 and calculated the county-level number of retailers per 1,000 people. Individual-level smoking behavior data were drawn from the 2014–2015 Tobacco Use Supplement for a sample of adults (n=88,850) residing in metropolitan counties across the U.S. General estimating equation models were fit to investigate the associations between retailer density and cigarette smoking behaviors (smoking status, quit attempt, quit length). Analyses were conducted in 2020. Results: A greater number of tobacco retailers (AOR=1.63, 95% CI=1.35, 1.96) and gas stations and convenience stores (AOR=3.29, 95% CI=2.39, 4.52) per 1,000 people were each associated with a higher odds of a respondent smoking every day than the odds of a respondent not smoking. In addition, both measures were associated with a higher odds of a respondent being an every-day than being a some-day smoker. Associations for gas/convenience density were similar in models that additionally controlled for other tobacco retailers (excluding gas/convenience). Study results did not support associations between retailer density and cessation. Conclusions: Tobacco retailer density, especially gas/convenience density, is correlated with daily smoking, the most harmful tobacco use behavior. Calculating tobacco retailer density using gas/convenience stores may be a feasible proxy for overall tobacco retailer density

    Associations of tobacco retailer availability with chronic obstructive pulmonary disease related hospital outcomes, United States, 2014

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    There are associations between tobacco retailer density and smoking behaviors, but little is known about whether places with more tobacco retailers have more smoking-related health problems. Using cross-sectional data from 2014, we investigated the relationships between tobacco retailer density and chronic obstructive pulmonary disease (COPD) related outcomes in a sample of 1510 counties across the United States. Higher retailer density was associated with a 19% (IRR, 1.19; 95% CI, 1.12–1.27) higher COPD-related hospital discharge rate and 30% (IRR, 1.30; 95% CI 1.21–1.39) higher total COPD-related hospital costs per population. The tobacco retailer environment may be an important target for reducing smoking-related health burdens and costs

    Sociodemographic inequities in tobacco retailer density: Do neighboring places matter?

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    We apply a spatial perspective to measure the extent to which the 2018 U.S. racial, ethnic, and socioeconomic composition of census tracts were each associated with tobacco retailer density within a tract and in its neighboring tracts (n = 71,409). A 10-percentage point increase in the Black population was associated with 0.07 (p < 0.05) more retailers per square mile within a focal tract and 0.35 (p < 0.001) more retailers per square mile in its neighbors on average. A greater percent of Hispanic/Latino residents was associated with more retailers per square mile, both within a focal tract (b = 0.95, p < 0.001) and in its neighbors 0.39 (p < 0.001). Inverse associations were observed for percent white. We also observed inequities by socioeconomic status. The overall magnitude of inequities may be underestimated if the spatial dependence between focal tracts and their neighbors are not taken into consideration. Policymakers should prioritize interconnected geographic areas experiencing high racialized and socioeconomic segregation when designing and implementing policies to reduce retail tobacco product availability

    Neighborhood Inequities in Tobacco Retailer Density and the Presence of Tobacco-Selling Pharmacies and Tobacco Shops

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    Studies document inequitable tobacco retailer density by neighborhood sociodemographics, but these findings may not be robust to different density measures. Policies to reduce density may be less equitable depending on how the presence of store types differs by neighborhood characteristics. We built a 2018 list of probable tobacco retailers in the United States and calculated four measures of density for all census tracts (N = 71,495), including total count, and number of retailers per 1,000 people, square mile, and kilometers of roadway. We fit multivariable regression models testing associations between each density measure and tract-level sociodemographics. We fit logistic regression models testing associations between sociodemographics and the presence of a tobacco-selling pharmacy or tobacco shop. Across all measures, tracts with a greater percentage of residents living below 150% of the federal poverty level (FPL) had higher density. A higher percentage of Black residents, Hispanic or Latino residents, and vacant housing was inconsistently associated with density across measures. Neighborhoods with a greater percentage of Black residents had a lower odds of having a pharmacy (adjusted odds ratio [aOR] = 0.96, 95% confidence interval [CI; 0.95, 0.97]) and tobacco shop (aOR = 0.87, CI [0.86, 0.89]), while those with a greater percentage of residents living below 150% FPL had greater odds of having a tobacco shop (aOR = 1.18, CI [1.16, 1.20]). Researchers and policymakers should consider how various measures of retailer density may capture different aspects of the environment. Furthermore, there may be an inequitable impact of retailer-specific policies on tobacco availability

    County-level associations between tobacco retailer density and smoking prevalence in the USA, 2012

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    We examine whether county-level tobacco retailer density and adult smoking prevalence are positively associated in the United States and determine whether associations differ in metropolitan vs. nonmetropolitan counties. We merged a list of likely tobacco retailers from the 2012 National Establishment Time-Series with smoking prevalence data from the Behavioral Risk Factor Surveillance System for 2828 US counties, as well as state tobacco policy information and county-level demographic data for the same year. We modeled adult smoking prevalence as a function of tobacco retailer density, accounting for clustering of counties within states. Average density in US counties was 1.25 retailers per 1000 people (range = 0.3–4.5). Smoking prevalence was 0.86 percentage points higher in the most retailer-dense counties, compared to the least. This association, however, was only significant for metropolitan counties. Metropolitan counties in the highest tobacco retailer density quartile had smoking prevalence levels that were 1.9 percentage points higher than metropolitan counties in the lowest density quartile. Research should examine whether policies limiting the quantity, type and location of tobacco retailers could reduce smoking prevalence

    Trends in the Number and Type of Tobacco Product Retailers, United States, 2000-2017

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    Introduction: Tobacco product retailers provide access to tobacco products and exposure to tobacco marketing. Without a national tobacco retailer licensing system in the United States, there are no estimates of national trends in tobacco retailer numbers and store type over time. Methods: We developed a protocol to identify likely tobacco retailers across the United States between 2000 and 2017 using industry codes and retailer names in the annual National Establishment Time Series (NETS) database. We calculated annual counts of tobacco retailers in seven store-type categories and annual numbers of tobacco retailers that opened and closed. Results: We estimate that there were 317 492 tobacco product retailers in 2000; the number grew to 412 536 in 2009 before falling to 356 074 in 2017, for a net 12% increase overall. Gas/convenience stores and grocery stores accounted for more than two thirds of all retailers. On average, new openings accounted for 8.0% of the total retailers, whereas 7.3% of retailers closed or stopped selling tobacco each year, with stronger market volatility following the Great Recession. Since 2011, there was a disproportionate reduction in tobacco-selling pharmacies and an increase in both tobacco-specialty shops and tobacco-selling discount stores. Conclusions: During two decades when smoking declined, tobacco retailer availability increased in the United States. The economic climate, corporate and public policies, and new tobacco products may all contribute to trends in tobacco retailer availability. State and local jurisdictions considering tobacco retailer policies may find retailer trend information useful for forecasting or evaluating potential policy impacts. Implications: This study provides historic data tracking tobacco retailers in the United States between 2000 and 2017, documenting trends that unfolded as the general economic market contracted and grew, with greater regulation of the tobacco retailer environment. These data provide a context for better understanding future changes in the tobacco retailer market. In addition, the protocol established in this study could be applied in any US-based location without tobacco retailer licensing to allow identification of stores and tracking of trends
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