Smoke-free laws and adult smoking prevalence

Hahn, Ellen J.; Rayens, Mary Kay; Butler, Karen M.; Zhang, Mei; Durbin, Emily; Steinke, Doug

doi:10.1016/j.ypmed.2008.04.009

Cited by 82 publications

(64 citation statements)

References 22 publications

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“…Adoption of smoke-free laws in one Kentucky county had an apparent effect on the trend in adult smoking prevalence rates based on BRFSS data (Hahn et al, 2008), a finding consistent with reports on the impact of smoking restrictions on smoking habits (e.g., Fichtenberg and Glantz, 2002). Only 13 Kentucky communities had implemented smokefree ordinances (some also including coverage of charitable gaming facilities) by June 2007 (Pyles and Hahn, 2009).…”

supporting

confidence: 78%

Smoke-free laws and cigarette excise taxes in U.S. states with highest vs. lowest adult smoking rates in 2007

Polednak¹

2009

Preventive Medicine

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supporting

confidence: 78%

Smoke-free laws and cigarette excise taxes in U.S. states with highest vs. lowest adult smoking rates in 2007

Polednak¹

2009

Preventive Medicine

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“…Variables included age (18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50), and ‡ 51 years), education ( < high school, high school/General Educational Development (GED), and > high school), race (white vs. other), marital status at time of interview (never married, married/member of couple, and divorced/widowed/separated), employment (full-time, part-time, unemployed/disabled, other), occupation (professional as defined by a degree, skilled labor, unskilled labor, other), annual household income, and health insurance (private, government-assisted, none).…”

Section: Social and Demographic Characteristicsmentioning

confidence: 99%

Risk Factors for Smoking in Rural Women

Wewers

Salsberry

Ferketich

et al. 2012

Journal of Women's Health

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Background: This study examined the association between social, demographic, and psychologic factors and smoking status among Appalachian Ohio women. A secondary aim examined whether specific factors could be identified and segmented for future tailored treatment of tobacco dependence. Methods: A cross-sectional survey (n = 570) obtained information about social, demographic, and psychologic factors and smoking. Logistic regression described associations between these characteristics and smoking status. Chi-square automatic interaction detection (CHAID) analyses identified subgroups at risk for smoking. Results: Fifty-two percent never smoked, with 20.5% and 27.5% categorized as former and current smokers, respectively. Women with low adult socioeconomic position (SEP) were more likely to smoke (odds ratio [OR] 3.05, 95% confidence interval [CI] 1.74-5.34) compared to high SEP women. Other factors associated with current smoking included age 31-50 (OR 2.30, 95% CI 1.22-4.33), age 18-30 (OR 3.29, 95% CI 1.72-5.34), Center for Epidemiologic Studies Depression scale (CES-D) score ‡ 16 (OR 1.99, 95% CI 1.31-3.05), and first pregnancy at age < 20 (OR 1.74, 95% CI 1.14-2.66). The prevalence of smoking was 50% among those with four or more risk factors compared to 10% for those reporting no risk factors. CHAID analyses identified low adult SEP and depressive symptoms as the combination of risk factors most strongly associated with smoking; 49.3% of women in this subgroup currently smoked. Conclusions: Low SEP in adulthood, maternal circumstances, and depressive symptoms are associated with current smoking. Tailored cessation interventions that address these risk factors should be developed and further evaluated in an attempt to reduce disparities in smoking prevalence among this vulnerable group of women.

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“…There is signifi cant evidence that laws that restrict smoking in public places and workplaces result in less smoking ( Bauer, Hyland, Li, Steger, & Cummings, 2005 ;Fichtenberg & Glantz, 2002 ;Hahn et al, 2008 ;Moskowitz, Lin, & …”

Section: Introductionmentioning

confidence: 99%