Annual Review of Public Health - Volume 39, 2018

Public health research has witnessed a rapid development in the use of location, environmental, behavioral, and biophysical sensors that provide high-resolution objective time-stamped data. This burgeoning field is stimulated by the development of novel multisensor devices that collect data for an increasing number of channels and algorithms that predict relevant dimensions from one or several data channels. Global positioning system (GPS) tracking, which enables geographic momentary assessment, permits researchers to assess multiplace personal exposure areas and the algorithm-based identification of trips and places visited, eventually validated and complemented using a GPS-based mobility survey. These methods open a new space-time perspective that considers the full dynamic of residential and nonresidential momentary exposures; spatially and temporally disaggregates the behavioral and health outcomes, thus replacing them in their immediate environmental context; investigates complex time sequences; explores the interplay among individual, environmental, and situational predictors; performs life-segment analyses considering infraindividual statistical units using case-crossover models; and derives recommendations for just-in-time interventions.

Alcohol consumption is responsible for 3.3 million deaths globally or nearly 6% of all deaths. Alcohol use contributes to both communicable and noncommunicable diseases, as well as violence and injuries. The purpose of this review is to discuss, in the context of the expansion of transnational alcohol corporations and harms associated with alcohol use, policy options for regulating exposure to alcohol marketing. We first provide an overview of the public health problem of harmful alcohol consumption and describe the association between exposure to alcohol marketing and alcohol consumption. We then discuss the growth and concentration of global alcohol corporations and their marketing practices in low- and middle-income countries, as well as in higher-income societies. We review the use and effectiveness of various approaches for regulating alcohol marketing in various countries before discussing challenges and opportunities to protect public health.

Dietary supplements are a global business worth more than US$100 billion annually. These supplements are taken by up to 50% of adults and perhaps one-third of children in economically advanced economies. Definitions of dietary supplements differ from country to country, and regulation is generally lax and often seems to be directed more toward promoting commerce than protecting public health. Supplements may directly cause toxic reactions or may interact with other supplements or pharmaceuticals. Some supplements are found to have been contaminated with heavy metals, and others do not contain the expected quantities of active ingredients. In general, supplements are not needed except in cases of established deficiencies, and excess of some nutrients can increase cancer rates. There are important public health reasons for taking some supplements, including folate and iodine in pregnancy. This review discusses the public health concerns associated with dietary supplements and suggests directions for further regulation.

The Mental Health Parity and Addiction Equity Act (MHPAEA) of 2008 changed the landscape of mental health and substance use disorder coverage in the United States. The MHPAEA's comprehensiveness compared with past parity laws, including its extension of parity to plan management strategies, the so-called nonquantitative treatment limitations (NQTL), led to significant improvements in mental health care coverage. In this article, we review the history of this landmark legislation and its recent expansions to new populations, describe past research on the effects of this and other mental health/substance use disorder parity laws, and describe some directions for future research, including NQTL compliance issues, effects of parity on individuals with severe mental illness, and measurement of benefits other than mental health care use.

Rich federal data resources provide essential data inputs for monitoring the health and health care of the US population and are essential for conducting health services policy research. The six household surveys we document in this article cover a broad array of health topics, including health insurance coverage (American Community Survey, Current Population Survey), health conditions and behaviors (National Health Interview Survey, Behavioral Risk Factor Surveillance System), health care utilization and spending (Medical Expenditure Panel Survey), and longitudinal data on public program participation (SIPP). New federal activities are linking federal surveys with administrative data to reduce duplication and response burden. In the private sector, vendors are aggregating data from medical records and claims to enhance our understanding of treatment, quality, and outcomes of medical care. Federal agencies must continue to innovate to meet the continuous challenges of scarce resources, pressures for more granular data, and new multimode data collection methodologies.

The difference in difference (DID) design is a quasi-experimental research design that researchers often use to study causal relationships in public health settings where randomized controlled trials (RCTs) are infeasible or unethical. However, causal inference poses many challenges in DID designs. In this article, we review key features of DID designs with an emphasis on public health policy research. Contemporary researchers should take an active approach to the design of DID studies, seeking to construct comparison groups, sensitivity analyses, and robustness checks that help validate the method's assumptions. We explain the key assumptions of the design and discuss analytic tactics, supplementary analysis, and approaches to statistical inference that are often important in applied research. The DID design is not a perfect substitute for randomized experiments, but it often represents a feasible way to learn about casual relationships. We conclude by noting that combining elements from multiple quasi-experimental techniques may be important in the next wave of innovations to the DID approach.

The United States has a complex governmental public health system. Agencies at the federal, state, and local levels all contribute to the protection and promotion of the population's health. Whether the modern public health system is well situated to deliver essential public health services, however, is an open question. In some part, its readiness relates to how agencies are funded and to what ends. A mix of Federalism, home rule, and happenstance has contributed to a siloed funding system in the United States, whereby health agencies are given particular dollars for particular tasks. Little discretionary funding remains. Furthermore, tracking how much is spent, by whom, and on what is notoriously challenging. This review both outlines the challenges associated with estimating public health spending and explains the known sources of funding that are used to estimate and demonstrate the value of public health spending.

Health care expenditures and use are challenging to model because these dependent variables typically have distributions that are skewed with a large mass at zero. In this article, we describe estimation and interpretation of the effects of a natural experiment using two classes of nonlinear statistical models: one for health care expenditures and the other for counts of health care use. We extend prior analyses to test the effect of the ACA's young adult expansion on three different outcomes: total health care expenditures, office-based visits, and emergency department visits. Modeling the outcomes with a two-part or hurdle model, instead of a single-equation model, reveals that the ACA policy increased the number of office-based visits but decreased emergency department visits and overall spending.

The Affordable Care Act (ACA) of 2010 placed a substantial emphasis on public health and prevention. Subsequent research on its effects reveals some notable successes and some missteps and offers important lessons for future legislators. The ACA's Prevention and Public Health Fund, intended to give public health budgetary flexibility, provided crucial funding for public health services during the Great Recession but proved highly vulnerable to subsequent budget cuts. Several programs that aimed to increase strategic thinking and planning around public health at the state level have proven to be more enduring, suggesting that the convening authority of the federal government can be a powerful tool for progress, especially when buttressed by some funding. Most important, by expanding insurance and mandating a minimum level of coverage, the ACA both increased access to clinical preventive services and freed up local public health budgets to engage in population health activities.

Treatment for opioid use disorder in the United States evolved in response to changing federal policy and advances in science. Inpatient care began in 1935 with the US Public Health Service Hospitals in Lexington, Kentucky, and Fort Worth, Texas. Outpatient clinics emerged in the 1960s to provide aftercare. Research advances led to opioid agonist and opioid antagonist therapies. When patients complete opioid withdrawal, return to use is often rapid and frequently deadly. US and international authorities recommend opioid agonist therapy (i.e., methadone or buprenorphine). Opioid antagonist therapy (i.e., extended-release naltrexone) may also inhibit return to use. Prevention efforts emphasize public and prescriber education, use of prescription drug monitoring programs, and safe medication disposal options. Overdose education and naloxone distribution promote access to rescue medication and reduce opioid overdose fatalities. Opioid use disorder prevention and treatment must embrace evidence-based care and integrate with physical and mental health care.