American journal of epidemiology最新文献

Structural racism has likely shaped the geographic distribution and resource allocation of rural populations and marginalized racial/ethnic groups. We sought to 1) quantify disparities in severe maternal morbidity (SMM) and distributions of resources by race and racial composition of county, and 2) determine whether a hypothetical intervention on resources would reduce racial disparities in SMM, using linked birth certificates and claims from Medicaid beneficiaries giving birth from 2014-2019 in rural North Carolina (61 rural counties, 77,665 births). We used ratio of mediator probability weights to enact a hypothetical intervention that would equalize distributions of pregnancy care provider ratios and obstetric units across race and racial composition of county. Despite observed disparities in the distributions of resources and SMM, we were unable to demonstrate that the hypothetical interventions would reduce SMM. This may be due to a lack of common support - marginalized groups never experienced the more optimal extremes of the healthcare resources distributions that privileged groups did. Our findings may have implications for the use of causal inference methods for addressing health disparities more broadly: if distributions of resources among privileged groups are outside those that marginalized groups experience, hypothetical interventions on these distributions cannot be emulated with data.

In this manuscript, we present the results of a series of workshops convened in conjunction with the 2023 Society for Epidemiologic Research (SER) annual meeting. The overall objective of the workshops was to develop a set of core competencies for PhD students in epidemiology. The topics presented in the lists of competencies are organized using a framework similar to many graduate programs in epidemiology, proceeding from basic to advanced topics. Given the breadth of substantive topics in the fields of epidemiology and public health, this list of competencies focuses on methodologic topics that are relevant to all students, regardless of research interest. The final topic lists were developed based on discussions including a large and diverse group of epidemiologists with different areas of expertise. By creating this resource, we aim to facilitate training of future generations of epidemiologists.

Despite the value of modern therapeutics, many obstacles prevent their optimal use. Overuse, underuse, and misuse are common, resulting in morbidity and mortality affecting billions of individuals across the world. Pharmacoepidemiology provides important insights into drug utilization, safety, and effectiveness in large populations, and it is an important method to identify opportunities to improve the value of therapeutics in clinical practice. However, for these opportunities to be realized, interventions to improve prescribing must be developed, evaluated, and implemented in the real world. We provide an overview of this process, focusing especially on how such interventions can be designed and deployed to maximize scalability, adoption, and impact. Prescribing represents a complex behavior with barriers and enablers, and interventions to improve prescribing will be most successful when developed, piloted and refined to maximize provider and patient acceptability. Carefully developed evaluations of interventions are also critical, and varied methods are available to empirically evaluate the intended and potential unintended consequences of interventions. With illustrative examples from the peer-reviewed literature, we provide readers with an overview of approaches to the essential and growing field of interventional pharmacoepidemiology. This article is part of a Special Collection on Pharmacoepidemiology.

Postmenopausal women experience significant changes in body composition, particularly abdominal adipose tissue (AAT) deposition patterns, which influence cardiometabolic risk. Physical activity has demonstrable effects on body composition and overall health; however, there is little evidence for how physical activity influences AAT patterns and body composition in postmenopausal women. We emulated a target trial of physical activity interventions, including the 2018 Physical Activity Guidelines for Americans recommendations (≥150 minutes/week), on 3-year changes in AAT and body composition. We analyzed data from 4451 postmenopausal women aged 50-79 years in the Women's Health Initiative (WHI) with repeated whole body Dual X-Ray Absorptiometry (DXA) scans with derived abdominal visceral (VAT) and subcutaneous adipose tissue (SAT). The mean AAT and body composition measures were estimated with the parametric-g formula. Over 3 years, interventions of increasing minutes of moderate activity would result in dose-dependent reductions in AAT, overall body fat and increases in lean soft tissue, with the greatest estimated benefit at the 2018 physical activity guideline recommendations. Compared to no intervention, if all participants had adhered to ≥150 mins/week of moderate physical activity, they would have 16.8 cm2 lower VAT (95% CI: -23.1, -10.4), 26.8 cm2 lower SAT (95% CI: -36.3, -17.3), 1.3% lower total body fat (95% CI: -1.8, -0.7), 1.2% higher total lean soft tissue (95% CI: 0.7-1.8), and 2.6 kg lower bodyweight (95% CI, -3.6, -1.5). We saw similar patterns in vigorous-intensity activity interventions. These results suggest that postmenopausal women who adhere to physical activity guideline recommendations would experience beneficial body composition changes over 3 years.

Nguyễn et al. (Am J Epidemiol. 2024;193(10):1343-1351) analyzed data from the US National Survey of Drug Use and Health (NSDUH) to show that Asian American Native Hawaiian/Pacific Islander (AANHPI) adults with limited English proficiency have substantially lower levels of mental health services utilization compared with White adults without limited English proficiency. The findings add to the growing literature using an intersectionality framework to understand health and health care disparities. We comment on the authors' notable examination of intersecting minoritized identities in mental health services utilization and the welcome emphasis on AANHPI health. We discuss the limitations of the NSDUH data, which are administered in English and Spanish only, and their limited ability to support analyses disaggregated by ethnoracial subgroups. We conclude by identifying gaps related to funding, training, and data disaggregation, and we highlight the role of mixed-methods approaches to advance our understanding of intersectionality and health disparities research. This article is part of a Special Collection on Mental Health.

Etiological heterogeneity occurs when distinct sets of events or exposures give rise to different subtypes of disease. Inference about subtype-specific exposure effects from two-phase outcome-dependent sampling data requires adjustment for both confounding and the sampling design. Common approaches to inference for these effects do not necessarily adjust appropriately for these sources of bias, or allow for formal comparisons of effects across different subtypes. We show that using inverse probability weighting (IPW) to fit a multinomial model to yield valid inference with this sampling design for subtype-specific exposure effects, and contrasts thereof. We compare the IPW approach to common regression-based methods for assessing exposure effect heterogeneity using simulations. The methods are applied to estimate subtype-specific effects of various exposures on breast cancer risk in the Carolina Breast Cancer Study (1993-2001).

The test-negative design (TND) has been commonly used to study vaccine effectiveness (notably regarding COVID-19 and influenza vaccines) and recently has been proposed as a valid design to study causal risk factors of diseases during an outbreak. In April 2022, there was a worldwide outbreak of mpox (formerly called monkeypox) that resulted in an international public health emergency. The TND has been used in a few studies to investigate vaccine effectiveness and risk factors of mpox, using epidemiologic databases. However, several issues prevent such a study design from being valid for this purpose. Problems stem from stigma surrounding mpox, which affects a person's decision to seek health care. This poses a challenge to the similar health care-seeking behavior assumption that is central for test-negative studies. Further limitations include the differential diagnoses of mpox, which have notable differences from mpox that may be easily detected by clinicians or patients but are unlikely to be included in epidemiologic databases or electronic health records. Herein, the caveats regarding the use of the TND are discussed in the context of the mpox outbreak, as well as potential steps that may allow it to be used effectively.

We investigated the association between outdoor artificial light-at-night (ALAN) exposure and cardiometabolic risk in the GCAT study. We included 9752 participants from Barcelona (59% women) and used satellite images (30 m resolution) and estimated photopic illuminance and the circadian regulation-relevant melanopic equivalent daylight illuminance (melanopic EDI). We explored the association between ALAN exposure and prevalent obesity, hypertension, and diabetes with logistic regressions and assessed the relationship with incident cardiometabolic diseases ascertained through electronic health records (mean follow-up 6.5 years) with Cox proportional hazards regressions. We observed an association between photopic illuminance and melanopic EDI and prevalent hypertension, odds ratio (OR) = 1.09 (95% CI, 1.01-1.16) and 1.08 (1.01-1.14) per interquartile range increase (0.59 and 0.16 lux, respectively). Both ALAN indicators were linked to incident obesity (hazard ratio [HR] = 1.29, 1.11-1.48 and 1.19, 1.05-1.34) and hemorrhagic stroke (HR = 1.73, 1.00-3.02 and 1.51, 0.99-2.29). Photopic illuminance was associated with incident hypercholesterolemia in all participants (HR = 1.17, 1.05-1.31) and with angina pectoris only in women (HR = 1.55, 1.03-2.33). Further research in this area and increased awareness on the health impacts of light pollution are needed. Results should be interpreted carefully since satellite-based ALAN data do not estimate total individual exposure. This article is part of a Special Collection on Environmental Epidemiology.

CpG site methylation patterns have potential to improve differentiation of high-grade screening-detected cervical abnormalities. We assessed CpG differential methylation (DM) and differential variability (DV) in high-grade (CIN2+) vs low-grade (≤ CIN1) lesions. In ≤ CIN1 (n = 117) and CIN2+ (n = 31) samples, cervical sample DNA underwent testing with Illumina HumanMethylation arrays. We assessed DM and DV of CpG methylation M-values among 9 cervical cancer-associated genes. We fit CpG-specific linear models and estimated empirical Bayes standard errors and false discovery rates (FDRs). An exploratory epigenome-wide association study (EWAS) aimed to detect novel DM and DV CpGs (FDR < 0.05) and Gene Ontology (GO) term enrichment. Compared to ≤ CIN1, CIN2+ exhibited greater methylation at CCNA1 cluster 1 (M-value difference 0.24; 95% CI, 0.04-0.43) and RARB cluster 2 (0.16; 95% CI, 0.05-0.28), and lower methylation at CDH1 cluster 1 (-0.15; 95% CI, -0.26 to -0.04). CIN2+ exhibited lower variability at CDH1 cluster 2 (variation difference -0.24; 95% CI, -0.41 to -0.05) and FHIT cluster 1 (-0.30; 95% CI, -0.50 to -0.09). EWAS detected 3534 DM and 270 DV CpGs. Forty-four GO terms were enriched with DM CpGs related to transcriptional, structural, developmental, and neuronal processes. Methylation patterns may help triage screening-detected cervical abnormalities and inform US screening algorithms. This article is part of a Special Collection on Gynecological Cancer.