A Public Health of Consequence: Review of the October 2016 Issue of AJPH

In this issue of AJPH, Farley’s editorial “Asking the Right Questions: Research of Consequence to Solve Problems of Significance”¹ provides a helpful lens through which we can both think about scholarship of consequence and view the original research articles in this month’s issue of AJPH. Farley’s piece starts with a delightful quote from Thomas Pynchon: “If they can get you asking the wrong questions, they don’t have to worry about the answers.” This quote well illustrates the concept that has sometimes been referred to as “lamppost bias”; that is, unless we are looking for answers in the right places we are unlikely to find solutions to some of the more pressing public health problems of our time. Farley offers four priorities for research that asks the right questions. Here is a brief comment on each, with reference to some of the articles in this issue of AJPH.

UBIQUITOUS PROBLEMS

First, Farley suggests that to improve population health, we should be tackling ubiquitous problems—doing less for more people. This core principle of population health science posits that substantial improvements in population health are likelier through acting on exposures that are shared by many. This is simply and elegantly illustrated by Kennedy et al.² Cost-related nonadherence to treatment dropped from 5.4% to 3.6% among seniors after the implementation of Medicare Part D and from 9.1% to 7.9% among adults aged 26 to 64 years after the implementation of the Affordable Care Act (ACA). Kennedy’s analysis shows that Medicare Part D and the ACA did a little bit, but for a large number of people. These data highlight the potential of large-scale policy change, with both utility for real-life evaluation of active policy and guidance for future research and policy development.

THINKING FORWARD, WORKING BACKWARD

Second, Farley offers the interesting concept of thinking forward and working backward; namely, identifying policy prescriptions that can improve health or minimize social divides and then using these policies as a guide to the questions that may attend their implementations. As a practical example, Wendel et al.³ recruited students from elementary schools in Texas, calculating body mass index (BMI) before and after a two-year period of using standing desks. Despite some challenges to the intervention implementation, a 5.3% difference in BMI percentile change occurred among students in a stand-biased classroom compared with students in the control classroom. Will standing desks in elementary schools have a substantial impact on childhood obesity? This study is unable to answer that question but offers an opportunity to work backward and evaluate the idea and its feasibility for widespread implementation.

LEARNING BY WATCHING

Third, we can learn and observe by watching. Articulating a principle akin to using natural experiments (the subject of another invited commentary in this section⁴), Farley suggests that in a large heterogeneous country, broader-based action can be informed by the impact of particular jurisdictions, as illustrated by Falbe et al., who evaluated the impact of the tax on sugar-sweetened beverages in Berkeley, California.⁵ This first US jurisdiction to implement such a tax in March 2015 resulted in a 21% reduced in sugar-sweetened beverage consumption, while consumption increased in comparison cities; water consumption increased more in Berkeley than in comparison groups. Can excise taxes on sugar-sweetened beverages make a dent in obesity across the country? Perhaps. The article by Falbe et al. teaches us by watching an experiment that has taken place, and offers rationale and perhaps motivation for broader-based policies based on this particular jurisdictional effort.

LEARNING FROM SIDE EFFECTS

Fourth, Farley suggests that we may learn from side effects; that is, unintended consequences of particular public health actions. Since policies with the greatest impact on public health need to change environments that shape the experience of populations, their consequences may extend well beyond the policies’ intended impact. Although none of the articles in this issue of AJPH captures the full spirit of Farley’s prescription, two articles broadly illustrate it. Bernstein et al. show an association between “blue” voting patterns and vaccination rates for adolescent coverage of indicated vaccines.⁶ Changes in vaccination rates linked to political voting patterns does not represent a side effect of a policy change per se, but it does illustrate the long-tail consequences of political choices for the health of the public. Seward et al. assess the benefits of traffic-light food labeling at a university.⁷ They found no association between traffic-light food labeling and dietary quality, even if students said that they both used the labels and wanted them to continue. We publish far fewer negative studies than we should, and the documentation of a policy that, in a particular context, does not achieve health impact is as valuable as the documentation of policies that do. Such scrutiny of policy actions paves the way toward policy implementation that can indeed make a difference.

INTELLIGENT POLICYMAKING

Farley concludes by noting that “the studies of greatest consequence will ask questions that enable intelligent policymaking.”^1(p1779) We could not agree more. His four clarifying research foci are demonstrated by articles in this issue of AJPH, and each can help guide scholarship of consequence going forward.