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Objectives. To understand how Twitter bots and trolls (“bots”) promote online health content. Methods. We compared bots’ to average users’ rates of vaccine-relevant messages, which we collected online from July 2014 through September 2017. We estimated the likelihood that users were bots, comparing proportions of polarized and antivaccine tweets across user types. We conducted a content analysis of a Twitter hashtag associated with Russian troll activity. Results. Compared with average users, Russian trolls (χ 2 (1) = 102.0; P < .001), sophisticated bots (χ 2 (1) = 28.6; P < .001), and “content polluters” (χ 2 (1) = 7.0; P < .001) tweeted about vaccination at higher rates. Whereas content polluters posted more antivaccine content (χ 2 (1) = 11.18; P < .001), Russian trolls amplified both sides. Unidentifiable accounts were more polarized (χ 2 (1) = 12.1; P < .001) and antivaccine (χ 2 (1) = 35.9; P < .001). Analysis of the Russian troll hashtag showed that its messages were more political and divisive. Conclusions. Whereas bots that spread malware and unsolicited content disseminated antivaccine messages, Russian trolls promoted discord. Accounts masquerading as legitimate users create false equivalency, eroding public consensus on vaccination. Public Health Implications. Directly confronting vaccine skeptics enables bots to legitimize the vaccine debate. More research is needed to determine how best to combat bot-driven content.

Objectives. To assess if historical redlining, the US government’s 1930s racially discriminatory grading of neighborhoods’ mortgage credit-worthiness, implemented via the federally sponsored Home Owners’ Loan Corporation (HOLC) color-coded maps, is associated with contemporary risk of preterm birth (< 37 weeks gestation). Methods. We analyzed 2013–2017 birth certificate data for all singleton births in New York City (n = 528 096) linked by maternal residence at time of birth to (1) HOLC grade and (2) current census tract social characteristics. Results. The proportion of preterm births ranged from 5.0% in grade A (“best”—green) to 7.3% in grade D (“hazardous”—red). The odds ratio for HOLC grade D versus A equaled 1.6 and remained significant (1.2; P < .05) in multilevel models adjusted for maternal sociodemographic characteristics and current census tract poverty, but was 1.07 (95% confidence interval = 0.92, 1.20) after adjustment for current census tract racialized economic segregation. Conclusions. Historical redlining may be a structural determinant of present-day risk of preterm birth. Public Health Implications. Policies for fair housing, economic development, and health equity should consider historical redlining’s impacts on present-day residential segregation and health outcomes.

Background: Transgender individuals experience unique vulnerabilities to intimate partner violence (IPV) and may experience a disproportionate IPV burden compared with cisgender (nontransgender) individuals. Objectives: To systematically review the quantitative literature on prevalence and correlates of IPV in transgender populations. Search Methods: Authors searched research databases (PubMed, CINAHL), gray literature (Google), journal tables of contents, and conference abstracts, and consulted experts in the field. Authors were contacted with data requests in cases in which transgender participants were enrolled in a study, but no disaggregated statistics were provided for this population. Selection Criteria: We included all quantitative literature published before July 2019 on prevalence and correlates of IPV victimization, perpetration, or service utilization in transgender populations. There were no restrictions by sample size, year, or location. Data Collection and Analysis: Two independent reviewers conducted screening. One reviewer conducted extraction by using a structured database, and a second reviewer checked for mistakes or omissions. We used random-effects meta-analyses to calculate relative risks (RRs) comparing the prevalence of IPV in transgender individuals and cisgender individuals in studies in which both transgender and cisgender individuals were enrolled. We also used meta-analysis to compare IPV prevalence in assigned-female-sex-at-birth and assigned-male-sex-at-birth transgender individuals and to compare physical IPV prevalence between nonbinary and binary transgender individuals in studies that enrolled both groups. Main Results: We identified 85 articles from 74 unique data sets (n total  = 49 966 transgender participants). Across studies reporting it, the median lifetime prevalence of physical IPV was 37.5%, lifetime sexual IPV was 25.0%, past-year physical IPV was 16.7%, and past-year sexual IPV was 10.8% among transgender individuals. Compared with cisgender individuals, transgender individuals were 1.7 times more likely to experience any IPV (RR = 1.66; 95% confidence interval [CI] = 1.36, 2.03), 2.2 times more likely to experience physical IPV (RR = 2.19; 95% CI = 1.66, 2.88), and 2.5 times more likely to experience sexual IPV (RR = 2.46; 95% CI = 1.64, 3.69). Disparities persisted when comparing to cisgender women specifically. There was no significant difference in any IPV, physical IPV, or sexual IPV prevalence between assigned-female-sex-at-birth and assigned-male-sex-at-birth individuals, nor in physical IPV prevalence between binary- and nonbinary-identified transgender individuals. IPV victimization was associated with sexual risk, substance use, and mental health burden in transgender populations. Authors’ Conclusions: Transgender individuals experience a dramatically higher prevalence of IPV victimization compared with cisgender individuals, regardless of sex assigned at birth. IPV prevalence estimates are comparably high for assigned-male-sex-at-birth and assigned-female-sex-at-birth transgender individuals, and for binary and nonbinary transgender individuals, though more research is needed. Public Health Implications: Evidence-based interventions are urgently needed to prevent and address IPV in this high-risk population with unique needs. Lack of legal protections against discrimination in employment, housing, and social services likely foster vulnerability to IPV. Transgender individuals should be explicitly included in US Preventive Services Task Force recommendations promoting IPV screening in primary care settings. Interventions at the policy level as well as the interpersonal and individual level are urgently needed to address epidemic levels of IPV in this marginalized, high-risk population.

Background. Research has found a strong link between ageism, in the form of negative stereotypes, prejudice, and discrimination toward older people, and risks to their physical and mental health. Little is known, however, about the effectiveness of strategies to reduce ageism. Objectives. To assess the relative effects of 3 intervention types designed to reduce ageism among youths and adults—education, intergenerational contact, and combined education and intergenerational contact—by conducting a systematic review and meta-analysis. Search Methods. We searched PubMed, PsycINFO, AgeLine, EBSCO, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Global Index Medicus, Database of Abstracts of Reviews of Effects (DARE), Epistemonikos, Cochrane Database of Systematic Reviews, Campbell Collaboration, PROSPERO, GreyLit, and OpenGrey. We identified additional records by hand-searching reference lists of relevant review articles as well as records included in the meta-analysis. Two independent reviewers completed the search and screening process. Selection Criteria. Eligible studies were those that (1) evaluated an intervention designed to reduce ageism, (2) examined at least 1 ageism outcome in relation to older adults, (3) used a design with a comparison group (randomized or nonrandomized), and (4) were published after 1970, when the ageism concept was developed. Data Collection and Analysis. Two independent reviewers extracted study-level data from records using a common data collection spreadsheet. They also assessed study quality by using the Cochrane Risk of Bias Tool, and used the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) tool to assess quality of outcome evidence. Primary outcomes were attitudes toward older people and accuracy of knowledge about aging and older people. Secondary outcomes included comfort with older adults, anxiety about one’s own aging, and interest in working in the field of geriatrics or gerontology. We carried out meta-analyses with statistical mixed models. Main Results. We identified 63 eligible studies (1976–2018) with a total sample of 6124 participants. Ageism interventions demonstrated a strongly significant effect on attitudes (differences of standardized mean differences [d D ] = 0.33; P < .001), knowledge (d D  = 0.42; P < .001), and comfort (d D  = 0.50; P < .001), but no significant effect on anxiety (d D  = 0.13; P = .33) or working with older adults (d D  = −0.09; P = .40). Combined interventions with education and intergenerational contact showed the largest effects on attitudes. We found stronger effects for females and for adolescent and young adult groups. Authors’ Conclusions. Interventions are associated with substantial reduction in ageism and should be part of an international strategy to improve perceptions of older people and the aging process. Additional research using more rigorous designs to examine the effects of interventions is strongly recommended. Public Health Implications. Ageism has well-established negative effects on the physical and mental health of older people. Findings suggest that relatively low-cost, feasible strategies involving education and intergenerational contact can serve as the basis of effective interventions to reduce ageism.

Objectives. To understand important changes in co-occurring opioid and nonopioid drug use (i.e., polysubstance use) within the opioid epidemic in the United States. Methods. We analyzed survey data on the past month co-use of prescription and illicit opioids and 12 nonopioid psychoactive drug classes from a national sample of 15 741 persons entering treatment of opioid use disorder. Results. Past-month illicit opioid use increased from 44.8% in 2011 to 70.1% in 2018, while the use of prescription opioids alone dropped from 55.2% to 29.9%, yet overall remained high (94.5% to 85.2%). Past-month use of at least 1 nonopioid drug occurred in nearly all participants (> 90%), with significant increases in methamphetamine (+85%) and decreases across nonopioid prescription drug classes (range: −40% to –68%). Conclusions. Viewing opioid trends in a “silo” ignores the fact not only that polysubstance use is ubiquitous among those with opioid use disorder but also that significant changes in polysubstance use should be monitored alongside opioid trends. Public Health Implications. Treatment, prevention, and policymaking must address not only the supply and demand of a singular drug class but also the global nature of substance use overall.

Background. Corporate interests have the potential to influence public debate and policymaking by influencing the research agenda, namely the initial step in conducting research, in which the purpose of the study is defined and the questions are framed. Objectives. We conducted a scoping review to identify and synthesize studies that explored the influence of industry sponsorship on research agendas across different fields. Search Methods. We searched MEDLINE, Scopus, and Embase (from inception to September 2017) for all original research and systematic reviews addressing corporate influence on the research agenda. We hand searched the reference lists of included studies and contacted experts in the field to identify additional studies. Selection Criteria. We included empirical articles and systematic reviews that explored industry sponsorship of research and its influence on research agendas in any field. There were no restrictions on study design, language, or outcomes measured. We excluded editorials, letters, and commentaries as well as articles that exclusively focused on the influence of industry sponsorship on other phases of research such as methods, results, and conclusions or if industry sponsorship was not reported separately from other funding sources. Data Collection and Analysis. At least 2 authors independently screened and then extracted any quantitative or qualitative data from each study. We grouped studies thematically for descriptive analysis by design and outcome reported. We developed the themes inductively until all studies were accounted for. Two investigators independently rated the level of evidence of the included studies using the Oxford Centre for Evidence-Based Medicine ratings. Main Results. We included 36 articles. Nineteen cross-sectional studies quantitatively analyzed patterns in research topics by sponsorship and showed that industry tends to prioritize lines of inquiry that focus on products, processes, or activities that can be commercialized. Seven studies analyzed internal industry documents and provided insight on the strategies the industry used to reshape entire fields of research through the prioritization of topics that supported its policy and legal positions. Ten studies used surveys and interviews to explore the researchers’ experiences and perceptions of the influence of industry funding on research agendas, showing that they were generally aware of the risk that sponsorship could influence the choice of research priorities. Conclusions. Corporate interests can drive research agendas away from questions that are the most relevant for public health. Strategies to counteract corporate influence on the research agenda are needed, including heightened disclosure of funding sources and conflicts of interest in published articles to allow an assessment of commercial biases. We also recommend policy actions beyond disclosure such as increasing funding for independent research and strict guidelines to regulate the interaction of research institutes with commercial entities. Public Health Implications. The influence on the research agenda has given the industry the potential to affect policymaking by influencing the type of evidence that is available and the kinds of public health solutions considered. The results of our scoping review support the need to develop strategies to counteract corporate influence on the research agenda.

Objectives. To examine 47 years of US urban and rural mortality trends at the county level, controlling for effects of education, income, poverty, and race. Methods. We obtained (1) Centers for Disease Control and Prevention WONDER (Wide-ranging ONline Data for Epidemiologic Research) data (1970–2016) on 104 million deaths; (2) US Census data on education, poverty, and race; and (3) Bureau of Economic Analysis data on income. We calculated ordinary least square regression models, including interaction models, for each year. We graphed standardized parameter estimates for 47 years. Results. Rural–urban mortality disparities increased from the mid-1980s through 2016. We found education, race, and rurality to be strong predictors; we found strong interactions between percentage poverty and percentage rural, indicating that the largest penalty was in high-poverty, rural counties. Conclusions. The rural–urban mortality disparity was persistent, growing, and large when compared to other place-based disparities. The penalty had evolved into a high-poverty, rural penalty that rivaled the effects of education and exceeded the effects of race by 2016. Public Health Implications. Targeting public health programs that focus on high-poverty, rural locales is a promising strategy for addressing disparities in mortality.

Background. Shift work is characterized by employees working outside the standard hours of 7:00 am to 6:00 pm. Because shift work includes night work, the normal sleep–wake cycle (circadian rhythm) is disrupted, with potential consequences for shift workers’ physical and mental health. Objectives. To assess the pooled effects of shift work on mental health and to evaluate whether these differ in men and women. Search Methods. We searched PubMed, Scopus, and Web of Science databases for peer-reviewed or government reports published up to August 2018 Selection Criteria. To be included, studies had to be longitudinal or case–control studies of shift work exposure associated with adverse mental health outcomes. For subanalyses, we grouped these outcomes as anxiety symptoms, depressive symptoms, or general poor mental health symptoms. Data Collection and Analysis. We followed the Meta-Analysis of Observational Studies in Epidemiology Group guidelines. We extracted adjusted risk estimates for each study to calculate pooled effect sizes (ESs) using random effect models and metaregression analysis to explore sources of heterogeneity. Main Results. We included 7 longitudinal studies, with 28 431 unique participants. Shift work was associated with increased overall risk of adverse mental health outcomes combined (ES = 1.28; 95% confidence interval [CI] = 1.02, 1.62; I 2  = 70.6%) and specifically for depressive symptoms (ES = 1.33; 95% CI = 1.02, 1.74; I 2  = 31.5%). Gender differences explained more than 90% of heterogeneity, with female shift workers more likely to experience depressive symptoms than female non–shift workers (odds ratio = 1.73; 95% CI = 1.39, 2.14). Authors’ Conclusions. To our knowledge, this is the first meta-analysis to investigate the pooled effects of shift work on the risk of poor mental health, including subanalyses by type of poor mental health and gender. Shift workers, particularly women, are at increased risk for poor mental health, particularly depressive symptoms. Public Health Implications. Depression accounts for 4.3% of the global burden of disease and incidence, with mental disorders worldwide predicted to cost US $16.3 million by 2030. With 1 in 5 people in the United States and Europe doing shift work, and the increased risk of poor mental health among shift workers, shift work industries are a priority context for reducing this burden. Workplace health promotion programs and policies are needed to minimize shift workers’ risk of poor mental health.

Background. Transgender women (transwomen) in the United States have been shown to have high HIV risk with Black and Hispanic transwomen being particularly vulnerable. Growing research on transgender men (transmen) also shows increased HIV risk and burden, although not as much is known for this transgender population. Objectives. This systematic review estimates the prevalence of self-reported and laboratory-confirmed HIV infection, reported sexual and injection behaviors, and contextual factors associated with HIV risk of transgender persons living in the United States. Search Methods. We searched the HIV Prevention Research Synthesis database and MEDLINE, EMBASE, PsycINFO, CINAHL, and Sociological Abstracts databases from January 2006 to March 2017 and January 2006 to May 2017, respectively. Additional hand searches were conducted in December 2017 to obtain studies not found in the literature searches. Selection Criteria. Eligible reports were published US-based studies that included transgender persons and reported HIV status. Data collection and analysis. Data were double-coded and quality assessed. We used random-effects models employing the DerSimonian–Laird method to calculate overall prevalence of HIV infection, risk behaviors, and contextual factors for transwomen, transmen, and race/ethnicity subgroups. Main Results. We reviewed 88 studies, the majority of which were cross-sectional surveys. Overall laboratory-confirmed estimated prevalence of HIV infection was 9.2% (95% confidence interval [CI] = 6.0%, 13.7%; κ = 24). Among transwomen and transmen, HIV infection prevalence estimates were 14.1% (95% CI = 8.7%, 22.2%; κ = 13) and 3.2% (95% CI = 1.4%, 7.1%; κ = 8), respectively. Self-reported HIV infection was 16.1% (95% CI = 12.0%, 21.2%; κ = 44), 21.0% (95% CI = 15.9%, 27.2%; κ = 30), and 1.2% (95% CI = 0.4%, 3.1%; κ = 7) for overall, transwomen, and transmen, respectively. HIV infection estimates were highest among Blacks (44.2%; 95% CI = 23.2%, 67.5%; κ = 4). Overall, participation in sex work was 31.0% (95% CI = 23.9%, 39.0%; κ = 39). Transwomen (37.9%; 95% CI = 29.0%, 47.7%; κ = 29) reported higher participation in sex work than transmen (13.1%; 95% CI = 6.6%, 24.3%; κ = 10; P = .001). Most outcomes indicated high heterogeneity in the overall and subgroup analyses. Conclusions. The availability of more data allowed us to calculate estimates separately for transwomen and transmen. HIV prevalence estimates for US transwomen were lower than previous estimates, but estimates for HIV prevalence and participation in sex work were higher when compared with transmen. Evidence gaps remain for transmen and the syndemic relationship of HIV, risky behaviors, and contextual factors specific to the transgender experience. Public Health Implications. This study highlights gender disparities for HIV and risky sexual behavior, as well as evidence gaps that exist for transmen. Tailored programs and services for the transgender population need to be developed to encourage use of and access to HIV prevention services.

Objectives. To examine emerging adults’ experiences of food insecurity in relation to measures of diet quality, food literacy, home food availability, and health behaviors. Methods. We used EAT 2010–2018 (Eating and Activity over Time) study data on 1568 participants who completed surveys as adolescents in 2009 to 2010 and follow-up surveys in 2017 to 2018 (mean age = 22.0 ±2.0 years; 58% female). At baseline, participants were recruited from 20 urban schools in Minneapolis–St Paul, Minnesota. Food insecurity was defined by emerging adult report of both eating less than they thought they should and not eating when hungry because of lack of money. Results. The prevalence at follow up of experiencing food insecurity in the past year was 23.3% among emerging adults. Food insecurity was associated with poorer diet quality (e.g., less vegetables and whole grains, more sugar-sweetened drinks and added sugars), lower home availability of healthy foods, skipping breakfast, frequently eating at fast-food restaurants, binge eating, binge drinking, and substance use (all P < .01). Conclusions. Assistance programs and policies are needed to address food insecurity among emerging adults and should be coordinated with other services to protect health.