Search

The article discusses the publication's editorial team's benchmark of processing 10,000 submissions as of September 2018 since it began its activity in June 2015 and offers a description of how the editorial process works for full-length papers.

[...]despite the large influx of papers, our peer reviewers managed to keep pace and render 2105 decision recommendations to our editors, most within 12 days of accepting the invitation to review. "9 Articles in the journal also echoed the uproar against racism and assertions of White supremacy articulated in the massive demonstrations that followed the murder of George Floyd.10,11 From the beginning of the pandemic, our editorial strategy has been to focus on post-COVID-19 reconstruction. Because it takes three to four months from submission to publication of a research paper or analytic essay in AJPH, we could not publish time-sensitive results about the evolution of the pandemic. Alpren et al. described the control of an outbreak of HIV infection among people who inject drugs during 2015 to 2018 in two cities in northeastern Massachusetts, which resulted in a significant decline in new HIV diagnoses, but also observed that opioid use was fueling HIV transmission in Massachusetts and likely in other urban settings.17 Cicero et al. also reported that polysubstance use needed to be taken into consideration to effectively meet the treatment, prevention, and policymaking challenges ofthe opioid epidemic.18 Another significant area of public health in which the pandemic exacerbated problems is workplace health and safety. A meta-analysis by Wang et al., showing that e-cigarettes used as consumer products are not associated with increased smoking cessation but that free e-cigarettes provided as a clinical intervention are, contributes support to the FDA strategy.23 Finally, Norris et al. described the evolution of abortion access in Ohio between 2010 and 2018,24 an issue that has been exacerbated by the imperviousness ofthe previous administration to the anxiety of pregnant women infected by COVID-19.

Objectives. To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. Methods. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based risk assessment. We compared different models and determined the strongest predictors of adverse birth outcomes using positive predictive value as the metric for selection. Results. Machine learning algorithms performed similarly, outperforming the current paper-based risk assessment by up to 36%; a refined paper-based assessment outperformed the current assessment by up to 22%. We estimate that these improvements will allow 100 to 170 additional high-risk pregnant women screened for program eligibility each year to receive services that would have otherwise been unobtainable. Conclusions. Our analysis exhibits the potential for machine learning to move government agencies toward a more data-informed approach to evaluating risk and providing social services. Overall, such efforts will improve the efficiency of allocating resource-intensive interventions.

Language is important. The call for papers in this supplement was entitled health equity. Yet the call asked for papers that address disparities in health. In the United States, disparities, most often, has been used to refer to racial/ethnic differences in health, or more commonly health care. We note that the call in this supplement expands the focus and highlights differences by socioeconomic status and geographic location, among others. By tradition, in the United Kingdom we have used the term inequalities to describe the differences in health between groups defined on the basis of socioeconomic conditions. To reduce health inequalities requires action to reduce socioeconomic and other inequalities. There are other factors that influence health, but these are outweighed by the overwhelming impact of social and economic factors—the material, social, political, and cultural conditions that shape our lives and our behaviors. Much of the evidence describing this was set out in the World Health Organization Global Commission on the Social Determinants of Health.1 In fact, so close is the link between social conditions and health, that the magnitude of health inequalities is an indicator of the impact of social and economic inequalities on people’s lives. Health then becomes an important further cause for concern about the rapid increase in inequalities of wealth and income in our societies. Increasingly, we are using the language of health inequity to describe those health inequalities that, though avoidable, are not avoided and hence are unfair. Two particular issues stand in the way before we can act on knowledge of social determinants of health to address health equities: lifestyle drift and overconcentration on health care.2 Lifestyle drift describes the tendency in public health to focus on individual behaviors, such as smoking, diet, alcohol, and drugs, that are undoubted causes of health inequities, but to ignore the drivers of these behaviors—the causes of the causes. Too often health is equated only with health care. Lack of access to health care has dominated the debate in the United States because of egregious inequities in access, despite spending far more on health care than any other country. A recent study by the Commonwealth Fund found that compared with other countries the US health system performed relatively poorly in terms of cost, equity, and efficiency.3 The Veterans Health Administration, however, does have a strong focus on equity. The Office of Health Equity ensures that the health care provision for veterans provides equitable care appropriate for the individual’s circumstance and irrespective of geography, gender, race/ethnicity, age, culture, or sexual orientation. There is importance, too, in incorporating socioeconomic factors into provision of equitable access and care. The Office of Health Equity also brings an equity focus into organizational discussions of policy, decision-making, resource allocation, practice, and performance plans throughout the Veterans Health Administration—a health equity in all policies approach that could be extended to other relevant organizations and stakeholders. Universal access to high quality care and a focus on equitable outcomes, then, is central to challenging health inequities. So too is challenging inequities in social conditions which lead to health inequalities. Attempts have been made to apportion determinants of health status of populations—see Figure 1, showing the relatively significant proportion of inequity attributed to social determinants. FIGURE 1— Estimates of the contribution of the main drivers of health status. The Robert Wood Johnson Foundation in the United States also sets out how social factors have as much, or even more impact on health as the medical care system, and it urges leaders across the United States to shift funding priorities to emphasize 3 areas essential to improving the nation’s health: Increasing access to early childhood development programs; revitalizing low-income neighborhoods; and broadening the mission of health care providers beyond medical treatment.5 Important goals, too, for the Veterans Health Administration. In our English review of health inequalities, in 2010, we enlisted the help of 80 or so experts and set out a large evidence base, which demonstrated the most important influences on health and health inequalities.6 We made recommendations in six priority areas. None was in health care because there is evidence of reasonably equitable, universal access to health care in England. The six priority areas were: quality of experiences in the early years, education and building personal and community resilience, good quality employment and working conditions, having sufficient income to lead a healthy life, healthy environments, and priority public health conditions—taking a social determinants approach to tackling smoking, alcohol, and obesity. At the heart of our approach is the finding that health inequalities are not limited to poor health for the worst off, or the most socially disadvantaged. There is a striking social gradient in health and disease running from top to bottom of society.7 The social gradient has now been shown to be widespread across the world in countries at low, middle, and high income.6 Figure 2 shows this gradient in England for life expectancy and healthy life expectancy. FIGURE 2— Life expectancy and disability-free life expectancy (DFLE) at birth by neighborhood income and deprivation: 1999–2003. There has been considerable progress in the recognition and adoption of the social determinants of health approach to health equity. Internationally, organizations such as the United Nations have expressed their broad commitment to health equity through action on the social determinants, and the European Union and World Health Organization have also acted on the social determinants of health and adopted this approach at the heart of their health improvement and health equity strategies. There have also been advancements at the national level—in many countries national governments have acted. There have been some great strides by local governments and authorities too. In England, 75% of local authorities have adopted this approach. However, and it is a significant however, there are many further challenges to greater health equity and to the social determinants of health.

Objectives. To determine the association between e-cigarette use and smoking cessation. Methods. We searched PubMed, Web of Science Core Collection, and EMBASE and computed the association of e-cigarette use with quitting cigarettes using random effects meta-analyses. Results. We identified 64 papers (55 observational studies and 9 randomized clinical trials [RCTs]). In observational studies of all adult smokers (odds ratio [OR] = 0.947; 95% confidence interval [CI] = 0.772, 1.160) and smokers motivated to quit smoking (OR = 0.851; 95% CI = 0.684, 1.057), e-cigarette consumer product use was not associated with quitting. Daily e-cigarette use was associated with more quitting (OR = 1.529; 95% CI = 1.158, 2.019) and less-than-daily use was associated with less quitting (OR = 0.514; 95% CI = 0.402, 0.665). The RCTs that compared quitting among smokers who were provided e-cigarettes to smokers with conventional therapy found e-cigarette use was associated with more quitting (relative risk = 1.555; 95% CI = 1.173, 2.061). Conclusions. As consumer products, in observational studies, e-cigarettes were not associated with increased smoking cessation in the adult population. In RCTs, provision of free e-cigarettes as a therapeutic intervention was associated with increased smoking cessation. Public Health Implications. E-cigarettes should not be approved as consumer products but may warrant consideration as a prescription therapy.

Background. Since 2005, most US states have expanded civilian rights to use deadly force in self-defense outside the home. In most cases, legislation has included removing the duty to retreat anywhere one may legally be, commonly known as stand-your-ground laws. The extent to which these laws affect public health and safety is widely debated in public and policy discourse. Objectives. To synthesize the available evidence on the impacts and social inequities associated with changing civilian rights to use deadly force in self-defense on violence, injury, crime, and firearm-related outcomes. Search Methods. We searched MEDLINE, Embase, PsycINFO, Scopus, Web of Science, Sociological Abstracts, National Criminal Justice Reference Service Abstracts, Education Resources Information Center, International Bibliography of the Social Sciences, ProQuest Dissertations and Theses, Google Scholar, National Bureau of Economic Research working papers, and SocArXiv; harvested references of included studies; and consulted with experts to identify studies until April 2020. Selection Criteria. Eligible studies quantitatively estimated the association between laws that expanded or restricted the right to use deadly force in self-defense and population or subgroup outcomes among civilians with a comparator. Data Collection and Analysis. Two reviewers extracted study data using a common form. We assessed study quality using the Risk of Bias in Nonrandomized Studies of Interventions tools adapted for (controlled) before–after studies. To account for data dependencies, we conducted graphical syntheses (forest plots and harvest plots) to summarize the evidence on impacts and inequities associated with changing self-defense laws. Main Results. We identified 25 studies that estimated population-level impacts of laws expanding civilian rights to use deadly force in self-defense, all of which focused on stand-your-ground or other expansions to self-defense laws in the United States. Studies were scored as having serious or critical risk of bias attributable to confounding. Risk of bias was low across most other domains (i.e., selection, missing data, outcome, and reporting biases). Stand-your-ground laws were associated with no change to small increases in violent crime (total and firearm homicide, aggravated assault, robbery) on average across states. Florida-based studies showed robust increases (24% to 45%) in firearm and total homicide while self-defense claims under stand-your-ground law were more often denied when victims were White, especially when claimants were racial minorities. Author’s Conclusions. The existing evidence contradicts claims that expanding self-defense laws deters violent crime across the United States. In at least some contexts, including Florida, stand-your-ground laws are associated with increases in violence, and there are racial inequities in the application of these laws. Public Health Implications. In some US states, most notably Florida, stand-your-ground laws may have harmed public health and safety and exacerbated social inequities. Our findings highlight the need for scientific evidence on both population and equity impacts of self-defense laws to guide legislative action that promotes public health and safety for all. Trial Registration. Open Science Framework (https://osf.io/uz68e).

Prescription drug monitoring programs (PDMPs) have become a widely embraced policy to address the US opioid crisis. Despite mixed scientific evidence on their effectiveness at improving health and reducing overdose deaths, 49 states and Washington, DC have adopted PDMPs, and they have received strong bipartisan legislative support. This article explores the history of PDMPs, tracking their evolution from paper-based administrative databases in the early 1900s to modern-day electronic systems that intervene at the point of care. We focus on two questions: how did PDMPs become so widely adopted in the United States, and how did they gain popularity as an intervention in the contemporary opioid crisis? Through this historical approach, we evaluate what PDMPs reflect about national drug policy and broader cultural understandings of substance use disorder in the United States today. (Am J Public Health. 2020;110:1191–1197. 10.2105/AJPH.2020.305696)

Prescription drug monitoring programs (PDMPs) have become a widely embraced policy to address the US opioid crisis. Despite mixed scientific evidence on their effectiveness at improving health and reducing overdose deaths, 49 states and Washington, DC have adopted PDMPs, and they have received strong bipartisan legislative support. This article explores the history of PDMPs, tracking their evolution from paper-based administrative databases in the early 1900s to modern-day electronic systems that intervene at the point of care. We focus on two questions: how did PDMPs become so widely adopted in the United States, and how did they gain popularity as an intervention in the contemporary opioid crisis? Through this historical approach, we evaluate what PDMPs reflect about national drug policy and broader cultural understandings of substance use disorder in the United States today. (

The authors reflect on the process of mentoring for publication in the "American Journal of Public Health (AJPH)." Topics include the challenges of publishing a first-authored, peer-reviewed journal articles in the field of public health research, the role of mentorship in guiding mentees through the peer-review process and teaching them how to assess and surmount rejection, and the inauguration of the "AJPH" Early Career Trainee Paper of the Year Award.

This paper examines the combined effects of a severe economic decline since 1989 and a tightening of the US embargo in 1992 on health and health care in Cuba.Data from surveillance systems for nutrition, reportable diseases, and hospital diagnoses were reviewed. These sources were supplemented with utilization data from the national health system and interviews with health leaders.Changes in Cuba include declining nutritional levels, rising rates of infectious diseases and violent death, and a deteriorating public health infrastructure. But despite these threats, mortality levels for children and women remain low. Instead, much of the health impact of the economic decline of Cuba has fallen on adult men and the elderly.To be consistent with international humanitarian law, embargoes must not impede access to essential humanitarian goods. Yet this embargo has raised the cost of medical supplies and food Rationing, universal access to primary health services, a highly educated population, and preferential access to scarce goods for women and children help protect most Cubans from what otherwise might have been a health disaster.

With this editorial we launch a new section in AJPH that we are calling “A Public Health of Consequence.” This monthly section builds on our previous work, calling for scholarship of consequence1,2 and on a growing body of work by several authors that urges public health to engage issues of relevance to the public health.3,4 We take that call for scholarship of consequence one step further, and ask for, whenever possible, an elegant visual display of the results with the goal of maximizing the ease of conveyance, or a description of the results in context, to again maximize the illustration of the importance of the results. We offer details, clarification, and examples below. We ground this section in a foundational appreciation of what public health is. The Institute of Medicine has defined public health as “what we, as a society, do collectively to assure the conditions for people to be healthy.”5(p1017) We have little argument with that definition, seeing it as both aspirational and forward looking. The role of scholarship in public health should therefore be to generate the knowledge that can inform public health action aiming to improve the conditions that makes us all healthy. But does our scholarship today do that? We have previously observed that while indeed some articles in our field do indeed lay down the knowledge base that can help make for healthier people, much else in our scholarship focuses on approaches to health problems that cannot be considered, to be particularly helpful to our cause.2,6 We are all guilty of this. We both have written article that, when viewed through the rearview mirror, have scant bearing on the goals of public health. And AJPH, arguably the world’s premiere peer-reviewed journal for public health scholarship, has published its fair share of articles that are of little consequence, or present the data in a way that obscures the consequence; hidden behind a table of coefficients without explanation. Take for instance an important hypothesis related to older adults. Gerst-Emerson and Jayawardhana asked, in AJPH, whether extended loneliness affects health care utilization.7 The main test of their hypothesis was a negative binomial regression where number of doctor visits was the outcome and extended loneliness was the primary independent variable, adjusted for several covariates. The description and interpretation of this analysis was provided as “Loneliness was statistically significant and positively associated with the number of doctor visits only for persons lonely at both time points (b = 0.075, SE = 0.034).”7(p1015) This result may be statistically correct but stops short of delivering the corresponding public health message in context. What does b = 0.075 mean, regardless of its statistical significance? What could have Gerst-Emerson and Jayawardhana have done with this b = 0.075? Recall that the parameter estimate, the “b” from negative binomial regression, is the difference in the log of the expected count at one level of the covariate and the log of the expected count and one unit lower of the covariate (in this case the log of the expected doctor visits among those who were lonely at both times minus the log of the expected doctor visits among those who were not lonely at either time), or by properties of logs, the log of the ratio of those expectations. Unlogging that quotient (i.e., eb) produces the incidence rate ratio. In this example, e0.075 yields approximately 1.08 or 8% higher count rate in the lonely group compared with nonlonely group. Assuming a nonlonely rate of approximately 9 visits per year gleaned from Table 2 in Gerst-Emerson and Jayawardhana, we might conclude that on average, holding all other covariates constant, that those chronically lonely made less than one additional doctor visits (8% of 9 visits). One more or less doctor visit per year versus b = 0.075. Which is easier to understand? The authors might have rightly assumed that the readers would have been able to make that inference given the other valuable information in the article, but we hope that going forward, AJPH and its authors can partner to make results more transparent and again, steeped in context to highlight the consequence. We are well aware that science is incremental, and that our hope for any article is that it makes a small contribution toward a larger tapestry of scholarship. And we are aware that at some level, every internally valid contribution might matter. But, surely we should be interested in asking ourselves, what matters most. At core, we are interested in articles that tackle problems that challenge the health of populations, and that provide us, brick by brick, with the knowledge we need to better learn how we should be building better conditions that produce a healthier society. To this end, we are launching a section in each issue of AJPH that attempts to explore a perhaps deceptively simple question: why do these articles matter? To do so we will, in each issue of AJPH, highlight a few papers that are, in our assessment, consequential for public health and present the results in a clear but statistically valid manner. We will discuss why we have chosen these articles and discuss how they pave a way forward, and what way that might be. We will offer alternative and additional examples of the presentation of results, relying primarily on visuals and less on dense tables and text. Some of the articles we highlight will be commissioned to illustrate a particular aspect of a public health that matters, but most will be selected from articles submitted to AJPH and scheduled for publication. Our hope is that this new section of AJPH will have 3 outcomes. First, and most importantly, we hope to prod us collectively, as a field, to ask questions of consequence, to push us to think about everything we do: Is this worth doing? Why does this matter? Does it matter? How can our work matter more? How can we present the results in a way that best communicates the consequence? We will strive to not hide the ball. Second, we hope to develop a more robust intellectual architecture that informs how we think about the very idea of a public health of consequence. We will attempt to use each of our commentaries to center around a particular aspect of the notion, pushing to the surface, and making explicit, why it is that some work may matter, and how this can suggest directions for future work. Third, we hope to provoke discussion and disagreement. We are well aware that some of this exercise may infuriate authors and readers alike (“why was my article not included in the section?”). We see debate as a productive force in science and hope that through debate we can find better answers. We are, at the end, interested principally in producing better public health knowledge that can make people healthier. If disagreement with us serves as one vehicle to get the field there, it will be well worth the effort, both our risking our ideas, and the reader’s voicing their disagreement. We also hope that some readers will agree with us, at least sometimes, and look forward to hearing about that too. We hope this perspective has resonance, although holding ourselves to these standards will take some diligence and perseverance. We look forward to your help and feedback as we attempt to encourage, practice, and publish scholarship of consequence.