Epidemiologic Reviews最新文献

For lethal means safety counseling (LMSC) interventions to reduce population-level suicide rates, interventions must be deployed across many settings and populations. We conducted a systematic search in 6 databases to review the current state of LMSC interventions across study designs, settings, intervention providers, populations, and injury prevention levels (eg, universal). Eligibility criteria were as follows: any individual or group receiving an LMSC intervention involving a human-to-human component aiming to influence adult behaviors related to lethal suicide methods, and outcome assessment of storage behaviors and/or suicidal self-directed violence (SDV). Risk of bias was assessed using the Effective Public Health Practice Project quality assessment tool. A descriptive synthesis approach was used for analysis. Twenty-two studies were included that reported medication- and/or firearm-storage behaviors and/or SDV after LMSC. Of the 19 studies assessing behavioral change, 14 reported a significant improvement in safe storage behaviors, and all studies measuring acceptability reported that participants found the interventions favorable. The quality of evidence was limited. No studies were rated low risk of bias, and 77% were rated high risk of bias. There was substantial heterogeneity in the settings, populations, injury prevention levels, delivery methods, and intervention elements. Many included studies focused on caregivers of pediatric populations, and few studies assessed SDV outcomes. Higher-quality trials conducted across a variety of settings, particularly those focusing on adults at risk of suicide, are needed. This review was preregistered with the International Prospective Register of Systematic Reviews (no. CRD42021230668).

Progress toward racial health equity cannot be made if we cannot measure its fundamental driver: structural racism. As in other epidemiologic studies, the first step is to measure the exposure. But how to measure structural racism is an ongoing debate. To characterize the approaches epidemiologists and other health researchers use to quantitatively measure structural racism, highlight methodological innovations, and identify gaps in the literature, we conducted a scoping review of the peer-reviewed and gray literature published during 2019-2021 to accompany the 2018 published work of Groos et al., in which they surveyed the scope of structural racism measurement up to 2017. We identified several themes from the recent literature: the current predominant focus on measuring anti-Black racism; using residential segregation as well as other segregation-driven measures as proxies of structural racism; measuring structural racism as spatial exposures; increasing calls by epidemiologists and other health researchers to measure structural racism as a multidimensional, multilevel determinant of health and related innovations; the development of policy databases; the utility of simulated counterfactual approaches in the understanding of how structural racism drives racial health inequities; and the lack of measures of antiracism and limited work on later life effects. Our findings sketch out several steps to improve the science related to structural racism measurements, which is key to advancing antiracism policies.

The incidence of invasive fungal infection (IFI) is increasing, especially among patients diagnosed with hematological malignancies due to their immunocompromised nature. Other risk factors include advanced age, exposure to immunosuppressants, neutropenia, and catheter use. Some of the most common IFI organisms reported are Candida and Aspergillus species, and other fungal species, including Scedosporium, Trichosporon, Cryptococcus, and Fusarium have also increasingly been reported in the past years. However, the epidemiologic data on IFI among patients with hematological malignancies in Asian countries are lacking. Therefore, we investigated published epidemiologic data on such cases from the past 10 years (2011-2021) and discuss the challenges faced in the diagnosis and management of IFIs in Asia.

The relevance of the study is conditioned upon the widespread occurrence of knee injuries in athletes when playing basketball, in particular, damage to the cartilage system of the knee joint. Such a feature of injury causes the fact that basketball players may develop post-traumatic chondropathy with a subsequent change in the functional state of knee joints, which is inextricably linked with a decrease in the quality of life, the occurrence of pain syndrome, shortening of career duration, an increased risk of surgical interventions, and possible disability in the long-term perspective. This paper is aimed at uncovering modern ideas about the impact of post-traumatic chondropathy on the functional state of knee joints in athletes during basketball games. The method for this paper was the search for relevant studies concerning the formulated problem, the collection of information and drawing conclusions. Given the character of the basketball game, knee injuries, both acute and chronic, are widespread among athletes of this sport, including cartilaginous defects of the knee joint, which often occur in athletes. The materials of the paper are of practical value for sports medicine doctors, physiotherapists, traumatologists since it presents the main mechanisms of knee injuries in athletes when playing basketball and the possible consequences of these injuries in the long term.

Racial discrimination is a well-known risk factor of racial disparities in health. Although progress has been made in identifying multiple levels through which racism and racial discrimination influences health, less is known about social factors that may buffer racism's associations with health. We conducted a systematic review of the literature with a specific focus on social connectedness, racism, and health, retrieving studies conducted in the United States and published between January 1, 2012, and July 30, 2022, in peer-reviewed journals. Of the 787 articles screened, 32 were selected for full-text synthesis. Most studies (72%) were at the individual level, cross-sectional, and among community/neighborhood, school, or university samples. Studies had good methodological rigor and low risk of bias. Measures of racism and racial discrimination varied. Discrimination scales included unfair treatment because of race, schedule of racist events, experiences of lifetime discrimination, and everyday discrimination. Measures of social connectedness (or disconnectedness) varied. Social-connectedness constructs included social isolation, loneliness, and social support. Mental health was the most frequently examined outcome (75%). Effect modification was used in 56% of studies and mediation in 34% of studies. In 81% of studies, at least 1 aspect of social connectedness significantly buffered or mediated the associations between racism and health. Negative health associations were often weaker among people with higher social connectedness. Social connectedness is an important buffering mechanism to mitigate the associations between racial discrimination and health. In future studies, harmonizing metrics of social connectedness and racial discrimination can strengthen causal claims to inform interventions.

Race is a social construct, commonly used in epidemiologic research to adjust for confounding. However, adjustment of race may mask racial disparities, thereby perpetuating structural racism. We conducted a systematic review of articles published in Epidemiology and American Journal of Epidemiology between 2020 and 2021 to (1) understand how race, ethnicity, and similar social constructs were operationalized, used, and reported; and (2) characterize good and poor practices of utilization and reporting of race data on the basis of the extent to which they reveal or mask systemic racism. Original research articles were considered for full review and data extraction if race data were used in the study analysis. We extracted how race was categorized, used-as a descriptor, confounder, or for effect measure modification (EMM)-and reported if the authors discussed racial disparities and systemic bias-related mechanisms responsible for perpetuating the disparities. Of the 561 articles, 299 had race data available and 192 (34.2%) used race data in analyses. Among the 160 US-based studies, 81 different racial categorizations were used. Race was most often used as a confounder (52%), followed by effect measure modifier (33%), and descriptive variable (12%). Fewer than 1 in 4 articles (22.9%) exhibited good practices (EMM along with discussing disparities and mechanisms), 63.5% of the articles exhibited poor practices (confounding only or not discussing mechanisms), and 13.5% were considered neither poor nor good practices. We discuss implications and provide 13 recommendations for operationalization, utilization, and reporting of race in epidemiologic and public health research.

The conventional use of racial categories in health research naturalizes "race" in problematic ways that ignore how racial categories function in service of a White-dominated racial hierarchy. In many respects, racial labels are based on geographic designations. For instance, "Asians" are from Asia. Yet, this is not always a tenable proposition. For example, Afghanistan resides in South Asia, and shares a border with China and Pakistan. Yet, people from Afghanistan are not considered Asian, but Middle Eastern, by the US Census. Furthermore, people on the west side of the Island of New Guinea are considered Asian, whereas those on the eastern side are considered Pacific Islander. In this article, we discuss the complexity of the racial labels related to people originating from Oceania and Asia, and, more specifically, those groups commonly referred to as Pacific Islander, Middle Eastern, and Asian. We begin with considerations of the aggregation fallacy. Just as the ecological fallacy refers to erroneous inferences about individuals from group data, the aggregation fallacy refers to erroneous inferences about subgroups (eg, Hmong) from group data (ie, all Asian Americans), and how these inferences can contribute to stereotypes such as the "model minority." We also examine how group averages can be influenced merely by the composition of the subgroups, and how these, in turn, can be influenced by social policies. We provide a historical overview of some of the issues facing Pacific Islander, Middle Eastern, and Asian communities, and conclude with directions for future research.

To mitigate the structural and institutional biases that contribute to inequities in health, we need a diverse cadre of individuals to feel included and advance within our field in order to bring a multicultural set of perspectives to the studies we conduct, the science we generate, the health and academic systems we design, and the medical and scientific knowledge we impart. There has been increasing focus on diversity, inclusion, and equity in recent years; however, often these terms are presented without adequate precision and, therefore, the inability to effectively operationalize inclusion and achieve diversity within organizations. This narrative review details several key studies, with the primary objective of presenting a roadmap to guide defining, measuring, and operationalizing inclusion within work and learning environments.

Critical analysis of the determinants of current and changing racialized health inequities, including the central role of racism, is an urgent priority for epidemiology, for both original research studies and epidemiologic review articles. Motivating our systematic overview review of Epidemiologic Reviews articles is the critical role of epidemiologic reviews in shaping discourse, research priorities, and policy relevant to the social patterning of population health. Our approach was first to document the number of articles published in Epidemiologic Reviews (1979-2021; n = 685) that either: (1) focused the review on racism and health, racial discrimination and health, or racialized health inequities (n = 27; 4%); (2) mentioned racialized groups but did not focus on racism or racialized health inequities (n = 399; 59%); or (3) included no mention of racialized groups or racialized health inequities (n = 250; 37%). We then conducted a critical content analysis of the 27 review articles that focused on racialized health inequities and assessed key characteristics, including (1) concepts, terms, and metrics used regarding racism and racialized groups (notably only 26% addressed the use or nonuse of measures explicitly linked to racism; 15% provided explicit definitions of racialized groups); (2) theories of disease distribution guiding (explicitly or implicitly) the review's approach; (3) interpretation of findings; and (4) recommendations offered. Guided by our results, we offer recommendations for best practices for epidemiologic review articles for addressing how epidemiologic research does or does not address ubiquitous racialized health inequities.

Improving race and ethnicity (hereafter, race/ethnicity) data quality is imperative to ensure underserved populations are represented in data sets used to identify health disparities and inform health care policy. We performed a scoping review of methods that retrospectively improve race/ethnicity classification in secondary data sets. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searches were conducted in the MEDLINE, Embase, and Web of Science Core Collection databases in July 2022. A total of 2 441 abstracts were dually screened, 453 full-text articles were reviewed, and 120 articles were included. Study characteristics were extracted and described in a narrative analysis. Six main method types for improving race/ethnicity data were identified: expert review (n = 9; 8%), name lists (n = 27, 23%), name algorithms (n = 55, 46%), machine learning (n = 14, 12%), data linkage (n = 9, 8%), and other (n = 6, 5%). The main racial/ethnic groups targeted for classification were Asian (n = 56, 47%) and White (n = 51, 43%). Some form of validation evaluation was included in 86 articles (72%). We discuss the strengths and limitations of different method types and potential harms of identified methods. Innovative methods are needed to better identify racial/ethnic subgroups and further validation studies. Accurately collecting and reporting disaggregated data by race/ethnicity are critical to address the systematic missingness of relevant demographic data that can erroneously guide policymaking and hinder the effectiveness of health care practices and intervention.