Golden Shelley D, Kuo Tzy-Mey, Combs Todd, Kong Amanda Y, Ribisl Kurt M, Baggett Chris D
Health Behavior, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Tob Control. 2024 Aug 12. doi: 10.1136/tc-2024-058739.
Places with more tobacco retailers have higher smoking prevalence levels, but whether this is because retailers locate where people who smoke live or whether tobacco availability prompts tobacco use is unknown. In this study, we compare the role of consumer demand with that of tobacco supply in longitudinal, area-based associations of tobacco retailer density with smoking prevalence.
We merged annual adult smoking prevalence estimates derived from the USA Behavioural Risk Factor Surveillance System data with annual county estimates of tobacco retailer density calculated from the National Establishment Time Series data for 3080 counties between 2000 and 2010. We analysed relationships between retailer density and smoking in 3080 counties, using random intercept cross-lagged panel models and employing two measures of tobacco retailer density capturing the number of likely tobacco retailers in a county divided by either the population or land area.
Both density models provided evidence of significant demand and supply effects; in the population-based model, the association of smoking prevalence in 1 year with tobacco retailer density in the next year (standardised coefficient=0.038, p<0.01) was about double the association between tobacco retailer density with subsequent smoking prevalence (0.017, p<0.01). The reverse was true in the land area-based model, where the supply effect (0.042, p<0.01) was more than 10 times stronger than the demand effect (0.003, p<0.01).
Policies that restrict access to retail tobacco have the potential to reduce smoking prevalence, but pairing such policies with interventions to reduce consumer demand remains important.
烟草零售商较多的地区吸烟流行率较高,但这是因为零售商选址在吸烟者居住的地方,还是因为烟草的可及性促使人们吸烟尚不清楚。在本研究中,我们比较了消费者需求与烟草供应在基于地区的烟草零售商密度与吸烟流行率的纵向关联中的作用。
我们将源自美国行为风险因素监测系统数据的年度成人吸烟流行率估计值与根据2000年至2010年间3080个县的国家企业时间序列数据计算得出的年度县烟草零售商密度估计值进行合并。我们使用随机截距交叉滞后面板模型,并采用两种衡量烟草零售商密度的指标(即一个县中可能的烟草零售商数量除以人口或土地面积),分析了3080个县中零售商密度与吸烟之间的关系。
两种密度模型均提供了需求和供应效应显著的证据;在基于人口的模型中,某一年的吸烟流行率与下一年的烟草零售商密度之间的关联(标准化系数 = 0.038,p < 0.01)约为烟草零售商密度与随后吸烟流行率之间关联(0.017,p < 0.01)的两倍。在基于土地面积的模型中情况则相反,供应效应(0.042,p < 0.01)比需求效应(0.003,p < 0.01)强10倍以上。
限制零售烟草获取的政策有可能降低吸烟流行率,但将此类政策与减少消费者需求的干预措施相结合仍然很重要。