Higgins Stephen T, Kurti Allison N, Redner Ryan, White Thomas J, Keith Diana R, Gaalema Diann E, Sprague Brian L, Stanton Cassandra A, Roberts Megan E, Doogan Nathan J, Priest Jeff S
Vermont Center on Tobacco Regulatory Science, University of Vermont, United States.
Vermont Center on Tobacco Regulatory Science, University of Vermont, United States.
Prev Med. 2016 Nov;92:110-117. doi: 10.1016/j.ypmed.2016.02.025. Epub 2016 Feb 21.
Relatively little has been reported characterizing cumulative risk associated with co-occurring risk factors for cigarette smoking. The purpose of the present study was to address that knowledge gap in a U.S. nationally representative sample.
Data were obtained from 114,426 adults (≥18years) in the U.S. National Survey on Drug Use and Health (years 2011-13). Multiple logistic regression and classification and regression tree (CART) modeling were used to examine risk of current smoking associated with eight co-occurring risk factors (age, gender, race/ethnicity, educational attainment, poverty, drug abuse/dependence, alcohol abuse/dependence, mental illness).
Each of these eight risk factors was independently associated with significant increases in the odds of smoking when concurrently present in a multiple logistic regression model. Effects of risk-factor combinations were typically summative. Exceptions to that pattern were in the direction of less-than-summative effects when one of the combined risk factors was associated with generally high or low rates of smoking (e.g., drug abuse/dependence, age ≥65). CART modeling identified subpopulation risk profiles wherein smoking prevalence varied from a low of 11% to a high of 74% depending on particular risk factor combinations. Being a college graduate was the strongest independent predictor of smoking status, classifying 30% of the adult population.
These results offer strong evidence that the effects associated with common risk factors for cigarette smoking are independent, cumulative, and generally summative. The results also offer potentially useful insights into national population risk profiles around which U.S. tobacco policies can be developed or refined.
关于与吸烟并存的风险因素相关的累积风险，所报告的内容相对较少。本研究的目的是在美国具有全国代表性的样本中填补这一知识空白。
数据取自美国全国药物使用和健康调查（2011 - 13年）中的114,426名成年人（≥18岁）。使用多元逻辑回归以及分类与回归树（CART）建模来检验与八个并存风险因素（年龄、性别、种族/族裔、教育程度、贫困、药物滥用/依赖、酒精滥用/依赖、精神疾病）相关的当前吸烟风险。
在多元逻辑回归模型中，当这八个风险因素同时存在时，每一个都与吸烟几率的显著增加独立相关。风险因素组合的影响通常是累加的。当其中一个组合风险因素与普遍较高或较低的吸烟率相关时（例如，药物滥用/依赖、年龄≥65岁），这种模式会出现小于累加效应的例外情况。CART建模确定了亚人群风险概况，其中吸烟患病率根据特定的风险因素组合从低至11%到高至74%不等。大学毕业是吸烟状况最强的独立预测因素，可对30%的成年人口进行分类。
这些结果提供了有力证据，表明与吸烟常见风险因素相关的影响是独立的、累积的且通常是累加的。这些结果还为美国烟草政策可以据此制定或完善的全国人口风险概况提供了潜在有用的见解。
