Annual Review of Public Health - Volume 41, 2020

This article reviews the essential ingredients and innovations in the design and analysis of group-randomized trials. The methods literature for these trials has grown steadily since they were introduced to the biomedical research community in the late 1970s, and we summarize those developments. We review, in addition to the group-randomized trial, methods for two closely related designs, the individually randomized group treatment trial and the stepped-wedge group-randomized trial. After describing the essential ingredients for these designs, we review the most important developments in the evolution of their methods using a new bibliometric tool developed at the National Institutes of Health. We then discuss the questions to be considered when selecting from among these designs or selecting the traditional randomized controlled trial. We close with a review of current methods for the analysis of data from these designs, a case study to illustrate each design, and a brief summary.

Machine learning approaches to modeling of epidemiologic data are becoming increasingly more prevalent in the literature. These methods have the potential to improve our understanding of health and opportunities for intervention, far beyond our past capabilities. This article provides a walkthrough for creating supervised machine learning models with current examples from the literature. From identifying an appropriate sample and selecting features through training, testing, and assessing performance, the end-to-end approach to machine learning can be a daunting task. We take the reader through each step in the process and discuss novel concepts in the area of machine learning, including identifying treatment effects and explaining the output from machine learning models.

Racism. Sexism. Heterosexism. Gender binarism. Together, they comprise intimately harmful, distinct, and entangled societal systems of self-serving domination and privilege that structure the embodiment of health inequities. Guided by the ecosocial theory of disease distribution, I synthesize key features of the specified “isms” and provide a measurement schema, informed by research from both the Global North and the Global South. Metrics discussed include (a) structural, including explicit rules and laws, nonexplicit rules and laws, and area-based or institutional nonrule measures; and (b) individual-level (exposures and internalized) measures, including explicit self-report, implicit, and experimental. Recommendations include (a) expanding the use of structural measures to extend beyond the current primary emphasis on psychosocial individual-level measures; (b) analyzing exposure in relation to both life course and historical generation; (c) developing measures of anti-isms; and (d) developing terrestrially grounded measures that can reveal links between the structural drivers of unjust isms and their toll on environmental degradation, climate change, and health inequities.

The human microbiome represents a new frontier in understanding the biology of human health. While epidemiology in this area is still in its infancy, its scope will likely expand dramatically over the coming years. To rise to the challenge, we argue that epidemiology should capitalize on its population perspective as a critical complement to molecular microbiome research, allowing for the illumination of contextual mechanisms that may vary more across populations rather than among individuals. We first briefly review current research on social context and the gut microbiome, focusing specifically on socioeconomic status (SES) and race/ethnicity. Next, we reflect on the current state of microbiome epidemiology through the lens of one specific area, the association of the gut microbiome and metabolic disorders. We identify key methodological shortcomings of current epidemiological research in this area, including extensive selection bias, the use of noncompositionally robust measures, and a lack of attention to social factors as confounders or effect modifiers.

The concept of sleep health provides a positive holistic framing of multiple sleep characteristics, including sleep duration, continuity, timing, alertness, and satisfaction. Sleep health promotion is an underrecognized public health opportunity with implications for a wide range of critical health outcomes, including cardiovascular disease, obesity, mental health, and neurodegenerative disease. Using a socioecological framework, we describe interacting domains of individual, social, and contextual influences on sleep health. To the extent that these determinants of sleep health are modifiable, sleep and public health researchers may benefit from taking a multilevel approach for addressing disparities in sleep health. For example, in addition to providing individual-level sleep behavioral recommendations, health promotion interventions need to occur at multiple contextual levels (e.g., family, schools, workplaces, media, and policy). Because sleep health, a key indicator of overall health, is unevenly distributed across the population, we consider improving sleep health a necessary step toward achieving health equity.

Disease surveillance systems are a cornerstone of public health tracking and prevention. This review addresses the use, promise, perils, and ethics of social media– and Internet-based data collection for public health surveillance. Our review highlights untapped opportunities for integrating digital surveillance in public health and current applications that could be improved through better integration, validation, and clarity on rules surrounding ethical considerations. Promising developments include hybrid systems that couple traditional surveillance data with data from search queries, social media posts, and crowdsourcing. In the future, it will be important to identify opportunities for public and private partnerships, train public health experts in data science, reduce biases related to digital data (gathered from Internet use, wearable devices, etc.), and address privacy. We are on the precipice of an unprecedented opportunity to track, predict, and prevent global disease burdens in the population using digital data.

Creating more physical activity–supportive built environments is recommended by the World Health Organization for controlling noncommunicable diseases. The IPEN (International Physical Activity and Environment Network) Adult Study was undertaken to provide international evidence on associations of built environments with physical activity and weight status in 12 countries on 5 continents (n > 14,000). This article presents reanalyzed data from eight primary papers to identify patterns of findings across studies. Neighborhood environment attributes, whether measured objectively or by self-report, were strongly related to all physical activity outcomes (accelerometer-assessed total physical activity, reported walking for transport and leisure) and meaningfully related to overweight/obesity. Multivariable indexes of built environment variables were more strongly related to most outcomes than were single-environment variables. Designing activity-supportive built environments should be a higher international health priority. Results provide evidence in support of global initiatives to increase physical activity and control noncommunicable diseases while achieving sustainable development goals.

Antimicrobial use (AMU) in animal agriculture contributes to antimicrobial resistance (AMR) in humans, which imposes significant health and economic costs on society. Economists call these costs negative externalities, societal costs that are not properly reflected in market prices. We review the relevant literature and develop a model to quantify the external costs of AMU in animal agriculture on AMR in humans. Parameters required for this estimate include (a) the health and economic burden of AMR in humans,(b) the impact of AMU in animal agriculture on AMR in animals, (c) the fraction of AMR in humans attributable to animal agriculture, and (d) AMU in animals. We use a well-documented historic case to estimate an externality cost of about US$1,500 per kilogram of fluoroquinolones administered in US broiler chicken production. Enhanced data collection, particularly on the third and fourth parameters, is urgently needed to quantify more fully the externalities of AMU in animal agriculture.

The number of refugee youth worldwide receives international attention and is a top priority in both academic and political agendas. This article adopts a critical eye in summarizing current epidemiological knowledge of refugee youth mental health as well as interventions aimed to prevent or reduce mental health problems among children and adolescents in both high- and low-to-middle-income countries. We highlight current challenges and limitations of extant literature and present potential opportunities and recommendations in refugee child psychiatric epidemiology and mental health services research for moving forward. In light of the mounting xenophobic sentiments we are presently witnessing across societies, we argue that, as a first step, all epidemiological and intervention research should advocate for social justice to guarantee the safety of and respect for the basic human rights of all refugee populations during their journey and resettlement. A constructive dialogue between scholars and policy makers is warranted.

In recent decades, there has been remarkable growth in scholarship examining the usefulness of community-engaged research (CEnR) and community-based participatory research (CBPR) for eliminating health inequities.This article seeks to synthesize the extant literature of systematic reviews, scoping reviews, and other related reviews regarding the context, processes, and research designs and interventions underlying CEnR that optimize its effectiveness. Through a scoping review, we have utilized an empirically derived framework of CBPR to map this literature and identify key findings and priorities for future research. Our study found 100 reviews of CEnR that largely support the CBPR conceptual framework.

There is growing recognition in the fields of public health and mental health services research that the provision of clinical services to individuals is not a viable approach to meeting the mental health needs of a population. Despite enthusiasm for the notion of population-based approaches to mental health, concrete guidance about what such approaches entail is lacking, and evidence of their effectiveness has not been integrated. Drawing from research and scholarship across multiple disciplines, this review provides a concrete definition of population-based approaches to mental health, situates these approaches within their historical context in the United States, and summarizes the nature of these approaches and their evidence. These approaches span three domains: (a) social, economic, and environmental policy interventions that can be implemented by legislators and public agency directors, (b) public health practice interventions that can be implemented by public health department officials, and (c) health care system interventions that can be implemented by hospital and health care system leaders.

A growing literature suggests that exposure to adverse social conditions may accelerate biological aging, offering one mechanism through which adversity may increase risk for age-related disease. As one of the most extensively studied biological markers of aging, telomere length (TL) provides a valuable tool to understand potential influences of social adversity on the aging process. Indeed, a sizeable literature now links a wide range of stressors to TL across the life span. The aim of this article is to review and evaluate this extant literature with a focus on studies that investigate psychosocial stress exposures and experiences in early life and adulthood. We conclude by outlining potential biological and behavioral mechanisms through which psychosocial stress may influence TL, and we discuss directions for future research in this area.

Homelessness is a devastating experience for children and their families. Families, the majority of whose members are children, now comprise more than one-third of the overall US homeless population. Most of these children are less than six years old. Various assumptions have driven policy and the allocation of resources to programs serving these families. Although decades of research and field experience suggest strategies for preventing and reducing this problem, perspectives differ, hindering the development of effective solutions. In this article, we explore some of these assumptions, including (a) definitions of homelessness used to count the numbers of families and determine resource allocation, (b) the needs of children and responses to the impact of adverse childhood experiences, and (c) whether services matter and should be integrated with affordable housing. We conclude by suggesting various directions to ensure that these children are protected and have the opportunity to grow and thrive.

In developed and developing countries, social, economic, and environmental transitions have led to physical inactivity and large amounts of time spent sitting. Research is now unraveling the adverse public health consequences of too much sitting. We describe improvements in device-based measurement that are providing new insights into sedentary behavior and health. We consider the implications of research linking evidence from epidemiology and behavioral science with mechanistic insights into the underlying biology of sitting time. Such evidence has led to new sedentary behavior guidelines and initiatives. We highlight ways that this emerging knowledge base can inform public health strategy: First, we consider epidemiologic and experimental evidence on the health consequences of sedentary behavior; second, we describe solutions-focused research from initiatives in workplaces and schools. To inform a broad public health strategy, researchers need to pursue evidence-informed collaborations with occupational health, education, and other sectors.

Undocumented Latinx immigrants experience unique factors prior to migration, during migration, and after migration that shape their health. Our review summarizes the limited but growing literature highlighting how exposure to trauma, immigration enforcement, changes to social networks, and discrimination negatively affect the mental and physical health of undocumented Latinx immigrants. We also discuss how policies and social ties can promote their health. We focus on areas of particular concern, including health care, mental health, and HIV. Future research should use interdisciplinary approaches and intersectional frameworks to understand and address health inequities. Conducting research with undocumented Latinx immigrant communities requires community engagement, assurance of confidentiality, and creative recruitment and retention strategies. Recommendations for public health practice include investing in community health centers and organizations to ensure access to health and social services; presenting results with sufficient contextualization to interpret their generalizability; and advocating for federal-, state-, and local-level policy changes that reduce the negative health consequences associated with being undocumented.

Exposure to traffic noise is associated with stress and sleep disturbances. The World Health Organization (WHO) recently concluded that road traffic noise increases the risk for ischemic heart disease and potentially other cardiometabolic diseases, including stroke, obesity, and diabetes. The WHO report focused on whole-day noise exposure, but new epidemiological and translational field noise studies indicate that nighttime noise, in particular,is an important risk factor for cardiovascular disease (CVD) through increased levels of stress hormones and vascular oxidative stress, leading to endothelial dysfunction and subsequent development of various CVDs. Novel experimental studies found noise to be associated with oxidative stress–induced vascular and brain damage, mediated by activation of the NADPH oxidase, uncoupling of endothelial and neuronal nitric oxide synthase, and vascular/brain infiltration with inflammatory cells. Noise-induced pathophysiology was more pronounced in response to nighttime as compared with daytime noise. This review focuses on the consequences of nighttime noise.

Autonomous vehicles (AVs) have the potential to shape urban life and significantly modify travel behaviors. “Autonomous technology” means technology that can drive a vehicle without active physical control or monitoring by a human operator. The first AV fleets are already in service in US cities. AVs offer a variety of automation, vehicle ownership, and vehicle use options. AVs could increase some health risks (such as air pollution, noise, and sedentarism); however, if proper regulated, AVs will likely reduce morbidity and mortality from motor vehicle crashes and may help reshape cities to promote healthy urban environments. Healthy models of AV use include fully electric vehicles in a system of ridesharing and ridesplitting. Public health will benefit if proper policies and regulatory frameworks are implemented before the complete introduction of AVs into the market.

The quality of the environment is a major determinant of the health and well-being of a population. The role of scientific evidence is central in the network of laws addressing environmental pollution in the United States and has been critical in addressing the myriad sources of environmental pollution and the burden of disease attributable to environmental factors. We address the shift away from reasoned action and science to a reliance on belief and document the efforts to separate regulation from science and to remove science-based regulations and policies intended to protect public health. We outline the general steps for moving from research to policy, show how each has been undermined, offer specific examples, and point to resources that document the enormity of the current efforts to set aside scientific evidence.

With the rapid increase in electronic cigarette (e-cig) users worldwide, secondhand exposure to e-cig aerosols has become a serious public health concern. We summarize the evidence on the effects of e-cigs on indoor air quality, chemical compositions of mainstream and secondhand e-cig aerosols, and associated respiratory and cardiovascular effects. The use of e-cigs in indoor environments leads to high levels of fine and ultrafine particles similar to tobacco cigarettes (t-cigs). Concentrations of chemical compounds in e-cig aerosols are generally lower than those in t-cig smoke, but a substantial amount of vaporized propylene glycol, vegetable glycerin, nicotine, and toxic substances, such as aldehydes and heavy metals, has been reported. Exposures to mainstream e-cig aerosols have biologic effects but only limited evidence shows adverse respiratory and cardiovascular effects in humans. Long-term studies are needed to better understand the dosimetry and health effects of exposures to secondhand e-cig aerosols.