Division of Health Policy and Management, School of Public Health, University of California, Berkeley, 239 University Hall, Berkeley, CA 94720-7360, USA.
Ann N Y Acad Sci. 2010 Feb;1186:240-51. doi: 10.1111/j.1749-6632.2009.05386.x.
This chapter discusses the current evidence base for policies that could address socioeconomic status (SES) health gradients in the United States. The present volume has documented an enormous amount of research on the linkages between SES and health, but there are still relatively few studies that rigorously establish the effectiveness of particular policies or interventions in reducing those gradients. Given the difficulty in developing randomized evidence for many types of interventions related to social determinants of health, we argue for conducting policy analysis from a Bayesian perspective. This Bayesian approach combines information on best available theory and evidence regarding probable health benefits and costs of an intervention, providing a framework that also incorporates the probable costs of inaction. The second half of the chapter adopts a ladder metaphor to classify policies and interventions that could reduce SES gradients in population health. Using this framework, we consider the evidence base for various types of policies, focusing primarily on the social determinants of health, under the rubric that "all policy is health policy." We conclude by discussing promising strategies for future strengthening of the evidence base for policy, including the role of health impact assessment.
本章讨论了当前针对美国社会经济地位（SES）健康梯度的政策的证据基础。本卷已经记录了大量关于 SES 与健康之间联系的研究，但仍有相对较少的研究严格证明了特定政策或干预措施在减少这些梯度方面的有效性。考虑到与健康的社会决定因素相关的许多类型的干预措施难以开展随机对照试验，我们主张从贝叶斯的角度进行政策分析。这种贝叶斯方法结合了关于干预措施可能带来的健康收益和成本的最佳现有理论和证据信息，提供了一个框架，还纳入了不采取行动的可能成本。本章的后半部分采用了阶梯隐喻来对可能降低人口健康中 SES 梯度的政策和干预措施进行分类。使用这个框架，我们根据“所有政策都是健康政策”这一说法，在健康的社会决定因素这一标题下，考虑了各种类型政策的证据基础，重点关注社会决定因素。最后，我们讨论了未来加强政策证据基础的有希望的策略，包括健康影响评估的作用。
