American journal of epidemiology最新文献

Although the public health field has increasingly studied the collateral consequences of incarceration, we know little about the health consequences of other forms of criminal legal contact, including probation and parole. Understanding spatial and racial-ethnic variation in probation/parole across US states provides new insights into how community supervision impacts population health disparities. However, state-level probation/parole prevalence has not been adequately described. Using data from the Bureau of Justice Statistics and the Census for the years 2001 to 2018, we provide the first state-level estimates of probation and parole populations by race over time in the US. We find large variation in disparities across states and time that is masked by national-level estimates. The US probation population decreased, and its racial composition remained steady between 2001 and 2018. However, in all but five states, the Black-White gap in probation rates declined. The Black-White gap in parole rates declined in all but seven states. The extent to which these race-specific changes in probation or parole over time reflect adjudication processes favoring White people, and/or affect population health, warrant further investigation.

Persistent racial and ethnic disparities exist in severe maternal and neonatal morbidity, which may be due in part to differences in labor and delivery unit practices across hospitals. We used data collected from 184 hospitals in California (2015-2018) to assess whether nulliparous individuals with low-risk pregnancies differ by race and ethnicity in giving birth at hospitals that tend to use lower-interventional labor and delivery unit practices, and whether such differences contribute to disparities in severe maternal and neonatal morbidity. We classified labor and delivery units as higher- or lower-interventional based on a latent class analysis of survey responses about the frequency of using lower-interventional practices. We used a modified doubly robust g-estimator to estimate counterfactual disparity measures, setting all hospitals to be lower-interventional. Among 348,990 low-risk livebirths, the proportion occurring at lower-interventional hospitals was lowest in Black and Latino individuals (17% and 16%, respectively) and highest in American Indian and Alaska Native (AI/AN) and White individuals (29% in both). Severe maternal and neonatal morbidity occurred most frequently among AI/AN individuals. Counterfactual disparity measures suggested that if all births occurred at lower-interventional hospitals, racial and ethnic disparities in the outcomes would modestly increase, except for severe neonatal morbidity among AI/AN individuals.

The Green Heart Project is a controlled, community-based clinical trial to evaluate the effects of increasing greenery on community health. The study was initiated in 2018 in a low-to-middle-income residential area of nearly 30,000 racially diverse residents in Louisville, KY. Community engagement was maintained throughout the project, with feedback integrated into its design and implementation. Based on land use, demographics, and greenness in the area, we designated 8 paired clusters of demographically- and environmentally matched "target" (T) and adjacent "control" (C) areas (total of 16 clusters). Levels of ultrafine particles, ozone, and nitrogen oxides were measured in each cluster. In-person exams were conducted for 735 participants in Wave 1 (2018-2019) and 545 participants in Wave 2 (2021). Blood, urine, nail, and hair samples were collected to evaluate cardiovascular risk, inflammation, stress, and pollutant exposure. Demographic and psychosocial data were collected as well. Cardiovascular function was assessed by measuring arterial stiffness and flow-mediated dilation. After Wave 2, more than 8,000 mature, mostly evergreen, trees and shrubs were planted in the T clusters. Post planting data were collected during Wave 3 (2022) from 561 participants. We plan to follow changes in area characteristics and participant health to evaluate the long-term impact of the greening intervention.

Pubertal trends, wherein adolescents today are experiencing puberty earlier than prior generations, have coincided with the expansion of the criminal legal system, which is disproportionately impacting communities of color. However, whether pubertal development and criminal legal system exposure among adolescents are inter-related is unknown. We tested whether family members' criminal legal system exposure predicted adolescents' pubertal development, whether family strain explained the relation between criminal legal system exposure and pubertal development, and whether race/ethnicity moderated our results. We used three yearly waves of longitudinal data among a national sample of 9,518 adolescents. Results illustrated that 40% of Black, 20% of Latinx, 16% of Other, and 10% of White adolescents experienced one or more family criminal legal system exposures. In structural equation models within a case-crossover design controlling for measured confounders and unmeasured confounders that do not change over time, including neighborhood-level socioeconomic status and crime, family criminal legal system exposure predicted adolescents' advanced pubertal development, and family strain explained this relation between family criminal legal system exposure and pubertal development. The United States' approach to law and order has public health implications that may be perpetuating health inequities, as accelerated pubertal development can have downstream consequences across the life course.

Neisseria gonorrhoeae has developed resistance to all antibiotics recommended for treatment and reports of reduced susceptibility to ceftriaxone, the last-line treatment, are increasing. Since many asymptomatic infections remain undiagnosed and most diagnosed infections do not undergo antibiotic susceptibility testing, surveillance systems may underestimate resistant infections. In this modeling study, we simulated the spread of a new strain of ceftriaxone non-susceptible N. gonorrhoeae in a population comprising men who have sex with men as well as heterosexual men and women. We compared scenarios with varying strain characteristics and surveillance capacity. For each scenario, we estimated (i) the number of undetected infections of the novel strain and (ii) the likelihood of strain persistence in the absence of newly reported cases. Upon detection of one non-susceptible isolate, the undetected burden was an estimated 5.4 infections with substantial uncertainty (0-18 infections, 95% uncertainty interval). Without additional reports of non-susceptible infections over the subsequent 180 days, the estimate declined to 2.5 infections (0-10 infections). The likelihood of ongoing transmission also declined from 66% (26-86%) at first detection to 2% (0-10%) after 180 days. To extend the useful lifespan of last-line antibiotics, our model estimated the infection landscapes that could underlie data from surveillance systems.

We investigated associations between neighborhood walkability and physical activity using twins (5477 monozygotic and same-sex dizygotic pairs) as "quasi-experimental" controls of genetic and shared environment (familial) factors that would otherwise confound exposure-outcome associations. Walkability comprised intersection density, population density, and destination accessibility. Outcomes included self-reported weekly minutes of neighborhood walking and moderate-to-vigorous physical activity (MVPA) and days per week using transit services (eg, bus, commuter rail). There was a positive association between walkability and walking, which remained significant after controlling for familial and demographic factors: a 1% increase in walkability was associated with a 0.42% increase in neighborhood walking. There was a positive association between walkability and MVPA, which was not significant after considering familial and demographic factors. In twins with at least 1 day of transit use, a 1-unit increase in log (walkability) was associated with a 6.7% increase in transit use days; this was not significant after considering familial and demographic factors. However, higher walkability reduced the probability of no transit use by 32%, considering familial and demographic factors. Using a twin design to improve causal inference, walkability was associated with walking, whereas walkability and both MVPA and absolute transit use were confounded by familial and demographic factors. This article is part of a Special Collection on Environmental Epidemiology.

This paper considers methodological approaches that can help better understand inequity in healthcare, focusing on five key domains: availability, patient-centeredness, access, effectiveness, and implementation. We present conceptual definitions of each of these domains, example research questions pertaining to inequity in each domain, and methodological approaches that can contribute to research about health inequities. We discuss the role of multilevel, participatory, and longitudinal research, particularly using representative, real-world data. We propose alternatives to randomized controlled trials that better suit questions regarding inequities in healthcare. We discuss challenges and considerations for research on inequities in healthcare alongside opportunities for innovation and prioritization of methodologies that are underutilized in epidemiology and health services research. We emphasize throughout that each of these five domains are interconnected and essential to be understood jointly if we are to improve our understanding of the role of healthcare in perpetuating health inequities.

Within epidemiological research, estimating treatment effects from observational data presents notable challenges. Targeted Maximum Likelihood Estimation (TMLE) emerges as a robust method, addressing these challenges by accurately modeling treatment effects. This approach uniquely combines the precision of correctly specified models with the versatility of data-adaptive, flexible machine learning algorithms. Despite its effectiveness, TMLE's integration of complex algorithms can introduce bias and under-coverage. This issue is addressed through the Double Cross-fit TMLE (DC-TMLE) approach, enhancing accuracy and reducing biases inherent in observational studies. However, DC-TMLE's potential remains underexplored in epidemiological research, primarily due to the lack of comprehensive methodological guidance and the complexity of its computational implementation. Recognizing this gap, our paper contributes a detailed, reproducible guide for implementing DC-TMLE in R, aimed specifically at epidemiological applications. We demonstrate the utility of this method using an openly available clinical dataset, underscoring its relevance and adaptability for robust epidemiological analysis. This guide aims to facilitate broader adoption of DC-TMLE in epidemiological studies, promoting more accurate and reliable treatment effect estimations in observational research.

Living in racially and ethnically segregated neighborhoods may increase the risk of breast cancer. We examined associations between neighborhood racial and ethnic composition typology and incident primary invasive breast cancer risk in a population-based sample of 102,615 African American/Black, Japanese American, Native Hawaiian, Latino, and White females residing in California and Hawaii from the Multiethnic Cohort (MEC) study between 1993-2019. Hazard ratios (HRs) and 95% confidence intervals (CI) were estimated using multivariable Cox proportional hazards regression. In California, African American/Black females in predominantly White neighborhoods had decreased breast cancer risk compared to African American/Black females in predominantly Black neighborhoods (HR=0.71, 95% CI=0.50-0.99). Latino females in mixed White and Asian American/Pacific Islander neighborhoods had increased breast cancer risk (HR=1.59, 95% CI=1.20-2.11) in comparison to Latino females in predominantly Hispanic neighborhoods. In Hawaii, Japanese American females in multiethnic neighborhoods had increased breast cancer risk (HR=1.49, 95% CI=1.24-1.78) compared to Japanese American females in predominantly Asian American neighborhoods. Native Hawaiian females in predominantly Asian American neighborhoods had increased breast cancer risk (HR=1.23, 95% CI=1.04-1.45) compared to Native Hawaiian females in mixed Native Hawaiian neighborhoods. Our findings can inform future studies to identify specific pathways through which segregation influences cancer risk in multiethnic populations.