Department of Family and Preventive Medicine, University of California, San Diego, La Jolla, CA 92093-0905, United States of America.
Glob Health Promot. 2010 Mar;17(1 Suppl):29-39. doi: 10.1177/1757975909358361.
Can an intervention program that is highly effective in reducing the prevalence of an unhealthy behavior in the general population also reduce the disparity among its subgroups? That depends on what measure of disparity is used. Using simple algebraic models, this study demonstrates that disparity measured in terms of relative difference between two groups tends to increase when the prevalence of the behavior is in decline. The study then shows an empirical example, by analyzing the effects of the California tobacco control program on smoking prevalence of two education groups, the lowest (less than 12 years) and the highest (16 years or more). It examines the data from four California Tobacco Surveys covering the years 1996, 1999, 2002, and 2005. The effects of three components of the tobacco control program known to be effective in decreasing prevalence (media, worksite policy, and price) on the two education groups are assessed. The smoking prevalence for the two groups is obtained from these four surveys and a regression line is computed for each education group from 1996 to 2005. Results show that the California program is effective with both low education and high education groups and that the rate of decline in smoking prevalence from 1996 to 2005 is no smaller for the low education group than for the high education group. The paper then discusses that an analysis of disparity based on relative difference, however, could result in misleading recommendations that an intervention like the California tobacco program needs to change from its current whole-population approach to one that focuses on targeting subgroups because it has not reduced disparity. It proposes that research should focus more on increasing the rate of change among less advantage groups and less on the relative disparity compared to some other group.
一项针对普通人群中某种不健康行为的干预措施若能非常有效地降低该行为的流行率，那么它是否也能降低该行为在其亚组人群中的差异程度呢？这取决于使用的差异衡量指标。本研究通过简单的代数模型证明，当行为流行率下降时，用两组间相对差异衡量的差异度趋于增加。然后，本研究通过分析加利福尼亚州控烟计划对两个受教育程度群体（受教育程度最低的群体，即低于 12 年；以及受教育程度最高的群体，即 16 年或以上）的吸烟流行率的影响，展示了一个实证案例。本研究分析了涵盖 1996 年、1999 年、2002 年和 2005 年四个加利福尼亚州烟草调查的数据。评估了已知能有效降低流行率的三个控烟计划组成部分（媒体、工作场所政策和价格）对这两个受教育程度群体的影响。从这四个调查中获取了这两个群体的吸烟流行率数据，并为每个受教育程度群体从 1996 年到 2005 年计算了一条回归线。结果表明，加利福尼亚州的控烟计划对受教育程度较低和较高的群体都有效，而且从 1996 年到 2005 年，吸烟流行率的下降速度在受教育程度较低的群体中并不比受教育程度较高的群体慢。然后，本文讨论了基于相对差异的差异度分析可能导致误导性建议，即像加利福尼亚州烟草计划这样的干预措施需要从当前针对整个人群的方法转变为针对亚组人群的方法，因为它没有降低差异度。本文建议研究应更多地关注增加弱势群体的变化率，而不是与其他群体相比的相对差异。
