Current Epidemiology Reports最新文献

Purpose of Review

Health fairs could increase screening uptake and ultimately contribute to reducing inequalities in cancer outcomes between low- and middle-income countries (LMIC) and developed countries. Reviews on this topic have been limited to health fairs in the USA. In this paper, we review the scientific literature for evidence that support health fairs as a strategy to improve cancer prevention.

Recent Findings

Studies across the USA consistently reported that health fairs were effective in providing cancer education and screening tests to historically marginalized groups. The studies reviewed were mostly observational and rarely reported data on health outcomes following the health fair. Nigeria, Honduras, Kenya and Uganda were the only countries outside of the USA identified from our review. Compared to the USA, these LMICs showed greater emphasis for promoting screening in the general population and self-administered cervical cancer screening.

Summary

Although the quality of scientific evidence is not convincing, health fairs appear to accelerate cancer prevention in historically marginalised groups. More robust research is needed to examine the role of health fairs in cancer prevention in LMICs; particularly, in small islands.

Purpose of Review

The objective of this paper is to discuss the complexities of identifying prenatal care visits in insurance claims databases, review existing methods to identify prenatal care encounters, and explore how different study goals should inform the definition of prenatal care employed by investigators.

Recent Findings

Insurance claims data are routinely used to conduct perinatal epidemiology studies focused on the effects of medical interventions. Prenatal care, an important medical intervention and an indicator of ongoing pregnancy, lacks a consistent definition among clinical and research-based sources.

Summary

We have categorized definitions of prenatal care in three groups: all healthcare received while pregnant, pregnancy-specific healthcare, and guideline-concordant healthcare. In studies using insurance claims data, we found five common methods to identify prenatal care encounters. Using example study goals, we outline important considerations investigators must make when applying different methods to identify prenatal care visits in studies using insurance claims data.

Purpose of Review

When a causal question can be reasonably approached using more than one set of causal assumptions (i.e., using different identification strategies), triangulation can be used to compare estimates relying on these different assumption sets to gain insight into the validity of the causal assumptions used. This review covers the current understanding of triangulation from a counterfactual causal inference perspective.

Recent Findings

We use counterfactuals to clarify and supplement the current understanding of triangulation. We propose a counterfactual definition of triangulation, propose assumptions on which triangulation relies, and discuss important practical issues such as triangulation with different estimands and the role of random error. Lastly, we examine two published examples of triangulation to illustrate these points.

Summary

Triangulation, by leveraging causal inference reasoning and substantive knowledge, can potentially allow us to gain more insight into the validity of causal assumptions underlying many study designs than we would by considering each study design in isolation.

Purpose of Review

Segregation has traditionally been measured at the metropolitan area or county level, but a growing number of population health studies have measured segregation at the neighborhood or local level. In this review, we highlight the ways local racial and ethnic residential segregation has been measured in recently published population health studies (June 1, 2019–June 30, 2022).

Recent Findings

We identified 40 local segregation studies based on our search criteria. The majority used racial or ethnic composition to measure segregation, but several additional measures were identified that reflect different dimensions of segregation and the segregation process.

Summary

The choice of how best to operationalize segregation should be guided by the historical and geographic context surrounding the population under study. Our findings highlight several options available to support the development of meaningful and useful measures of segregation to study their impact on health inequities across a diverse range of outcomes and settings.

Purpose of Review

The objective of this review is to examine the application of target trial emulation in perinatal pharmacoepidemiology research. Given that randomized clinical trials—the gold standard for causal inference—are often not feasible or ethical for studying medication safety during pregnancy, alternative methodologies are critically needed. This paper delves into the challenges and potential mitigation strategies of using target trial emulation in the specific context of perinatal pharmacoepidemiology research.

Recent Findings

Our review of identified studies (n = 9) reveals several unique considerations when leveraging target trial emulation for perinatal pharmacoepidemiology research. These include the alignment of the research question with the clinically relevant outcomes, identification of etiologically relevant time windows, defining relevant treatment strategies, and anchoring of exposure, eligibility criteria, and the start of follow-up. Despite these challenges, the methodology shows promise in bridging the gap between randomized clinical trials and observational research through the employment of a transparent and well-defined approach.

Summary

Target trial emulation serves as a valuable tool in perinatal pharmacoepidemiology, allowing researchers to generate more reliable evidence concerning medication safety during pregnancy. Although the approach comes with specific challenges, strategies can be implemented to mitigate these difficulties. Overall, the adoption of target trial emulation has the potential to substantially enhance evidence quality, inform clinical decisions, and ultimately improve health outcomes for birthing people and their infants.

There are >1.9 million survivors of adolescent and young adult cancers (AYA, diagnosed at ages 15-39) living in the U.S. today. Epidemiologic studies to address the cancer burden in this group have been a relatively recent focus of the research community. In this article, we discuss approaches and data resources for cancer epidemiology and health services research in the AYA population. We consider research that uses data from cancer registries, vital records, healthcare utilization, and surveys, and the accompanying challenges and opportunities of each. To illustrate the strengths of each data source, we present example research questions or areas that are aligned with these data sources and salient to AYAs. Integrating the respective strengths of cancer registry, vital records, healthcare data, and survey-based studies sets the foundation for innovative and impactful research on AYA cancer treatment and survivorship to inform a comprehensive understanding of diverse AYA needs and experiences.