American journal of epidemiology最新文献

Although 1990-1991 Gulf War deployment has been linked to worse health outcomes such as chronic multisymptom illness (CMI), often referred to as Gulf War Illness, among deployed Gulf War Veterans, less is known regarding Gulf War service and mortality. Using 20 years of longitudinal data from Gulf War Veteran and Era personnel from the Millennium Cohort Study (2001-2021; n=45381), Cox proportional hazard models estimated the relative effects of Gulf War service status, CMI, and their corresponding interaction on all-cause mortality. Although age- and sex-adjusted mortality ratios suggested that Gulf War Veterans had higher mortality rates than Era personnel, no association was observed between Gulf War service status and mortality risk. Screening positive for CMI was associated with greater risk of all-cause mortality compared with those who did not screen positive across both GWV and Era personnel; interactions between CMI and Gulf War status were not statistically significant. This finding suggests that CMI increases mortality risk regardless of whether the symptomology is associated with Gulf War deployment. Future research is necessary to examine specific occupational and environmental exposures experienced during deployments and service in support of the 1990-1991 Gulf War and their association with mortality in this population.

Unmeasured confounding is a major concern in many epidemiologic studies that are not randomized. Negative control methods can detect and reduce confounding by leveraging the proxies of the unmeasured confounders, including negative control outcomes (NCO) and exposures (NCE). An NCO is presumably unaffected by the exposure of interest but would be associated with unmeasured confounders; an NCE presumably does not affect the outcome of interest but would be associated with unmeasured confounders. A recently proposed double negative control method leverages both NCO and NCE for unmeasured confounding bias. To demonstrate this relatively new methodology in pharmacoepidemiologic studies, we re-analyzed data from a prior safety study of Recombinant Zoster Vaccine (RZV). The prior study compared risk of safety outcomes of RZV versus unvaccinated comparators, using logistic regression with propensity score adjustment. We identified NCOs and NCEs that could be used to adjust for unmeasured confounding bias that could arise if RZV recipients are incomparable to the comparators due to unmeasured factors. The double negative control analysis yielded relative risk estimates slightly closer to 1.0 than those reported previously, providing additional evidence of RZV safety that is less vulnerable to unmeasured confounding.

In 1992, Wacholder and colleagues developed a theoretical framework for case-control studies to minimize bias in control selection. They described three comparability principles (study base, deconfounding, and comparable accuracy) to reduce the potential for selection bias, confounding, and information bias in case-control studies. Wacholder et al. explained how these principles apply to traditional sources of controls for case-control studies, including population controls, hospital controls, controls from a medical practice, friend or relative controls, and deceased controls. The goal of the current manuscript is to extend this seminal work on case-control studies by providing a modern perspective on sources of controls. Today, there are many more potential sources of controls for case-control studies than there were in the 1990s. This is due to technological advances in computing power, internet access, and availability of 'big data' resources. These advances have vastly expanded the quantity and diversity of data available for case-control studies. In this manuscript, we discuss control selection from electronic health records, health insurance claims databases, publicly available online data sources, and social media-based data. We focus on practical considerations for unbiased control selection, emphasizing the strengths and weaknesses of each modern source of controls for case-control studies.

Structural cisheterosexism is a root cause of LGBTQ health inequities. Amidst ongoing legal attacks on LGBTQ populations' rights, research is needed to examine changes in policy contexts over time and associated implications for population health and inequities. To address this gap, we constructed state-level structural cisheterosexism trajectories for each U.S. state/D.C. from 1996-2016. We used sequence analysis to quantify differences between trajectories and cluster analysis to group similar trajectories. We evaluated associations between trajectory clusters and individual-level health(care) outcomes (self-rated health, frequent mental distress, lacking insurance, lacking a doctor, avoiding care due to cost) from the 2017 Behavioral Risk Factor Surveillance System, in the overall sample and by LGBTQ status (LGBTQ vs. cisheterosexual), using multilevel logistic models. From 38 unique trajectories, we identified five trajectory clusters: "consistently-predominantly-discriminatory", "consistently-fairly-discriminatory", "moderate-with-increasing-protection", "discriminatory-change-to-fairly-protective", and "fairly-discriminatory-change-to-predominantly-protective." Overall, health(care) was worse in states characterized by consistently discriminatory laws compared to states with increasingly protective laws and disproportionately so for LGBTQ people. Findings underscore the need to abolish harmful, cisheterosexist state laws and enact protective laws to advance LGBTQ health equity. More broadly, this study demonstrates the utility of sequence and cluster analysis for assessing long-term population health impacts of structural-level determinants.

Findings for greenspace's impacts on birth outcomes are largely dependent on vegetation indexes. Examinations are needed for various greenspace indicators given varying pathways for fetal development. This prospective cohort study assessed the impacts of prenatal greenspace exposure on preterm birth (PTB), term low birthweight (TLBW), birthweight, and estimated fetal weight (EFW) for pregnant women in the New York City area, 2016-2023 (n=2765). Longitudinal greenspace exposure was measured for residential histories during pregnancy using the Enhanced Vegetation Index (EVI) for 1000m buffers and four park metrics, namely, the total number, sum of area, and the accessibility of parks within residential buffers (500 m) and the distance to the closest park. Multivariable regression models were used to estimate the associations for quartiles of exposure (with the first quartile [Q1] as reference). Greenspace exposure was not associated with TLBW, birthweight, or EFW. Odds ratios of PTB for the Q2, Q3, and Q4 EVI exposure groups compared to the Q1 group were 0.65 (95% CI: 0.43-0.98), 0.51 (0.32-0.80), and 0.56 (0.35-0.90), respectively. PTB risks decreased in higher exposure groups (Q2-Q4) of the total park number. Results indicate the benefits of prenatal greenspace exposure for fetal maturity and neonatal outcomes.

This study explores how discrimination experiences during the COVID-19 pandemic relate to anxiety and depressive symptoms in U.S. adults. Using a national representative intensive longitudinal survey, the study evaluates rapid subsequent changes in anxiety and depression when individuals undergo heightened discrimination beyond their usual experiences. The study used 23 survey timepoints, primarily with 2-week intervals, from the Understanding America Study (n=8,198). Time-varying and time-lagged associations between discrimination experiences and anxiety and depression were modeled using multi-level logistic random-effect repeated-measures regression models. The results showed that discrimination experiences were associated with moderate-to-severe anxiety and depressive symptoms, as well as more than one comorbid psychological distress symptom (adjusted Odds Ratios [AORs]=1.10 to 1.13). The association remained significant regardless of inter-individual differences in exposure to discrimination. Non-Hispanic Blacks, Asians, and other race/ethnicities exhibited stronger associations between discrimination and psychological distress (AORs=1.63 to 1.93) compared to Hispanic and White respondents (AORs=1.13 to 1.25). Our findings suggest that individuals experience a rapid deterioration in their emotional well-being when subjected to heightened levels of discrimination beyond their typical experiences.

Extant research shows that race adjustment in epidemiologic analyses could lead to masking of systemic racism. In this study, we compare race-adjusted and -unadjusted years of life lost (YLL), a measure of societal burden, to understand the impact of race adjustment in YLL estimation. We used North Carolina (NC) Violent Death Reporting System data from 2006-2019 linked to 2006-2019 race-adjusted and -unadjusted life tables from the Centers for Disease Control and Prevention by calendar year and age at death. We calculated total YLL and YLL per death from suicide and homicide deaths for non-Hispanic black and non-Hispanic white NC residents using both the race-adjusted and -unadjusted life tables. We found that YLL and YLL/death from suicide and homicide deaths for non-Hispanic white individuals were almost identical regardless of race adjustment. However, race-adjusted life tables vastly underestimated total YLL and YLL per death for non-Hispanic black NC residents. Overall, race adjustment resulted in an underestimation of 14,907 YLL from homicide deaths (3.1 fewer YLL/death) and 4,414 YLL from suicide deaths (2.8 YLL/death) for black NC residents. Our study shows that the baked-in underestimation of YLL for non-Hispanic Black Americans when using race-adjusted life tables hides racialized health disparity and perpetuates inequity.

We investigated California mortality and social determinants of health, as measured by the Healthy Places Index (HPI), which is a composite measure of 23 indicators of neighborhood (census tract) economic conditions, education, transportation, housing, social capital, environmental pollution, built-environment, and access to health care. We aggregated deaths to 2010 census tract boundaries for leading causes, 2015 to 2019, and COVID-19, 2020-2021, from death certificates and populations from the American Community Survey, 2015 to 2019. We age-adjusted and stratified death rates by HPI deciles, age, gender, and race/ethnicity, and examined HPI dose-response with segmental regression. For all causes, cancer, cardiovascular disease, COVID-19, diabetes, cirrhosis of the liver, injuries, and Alzheimer's disease (ages 65-74 years), mortality rates were inversely related to HPI decile. For all causes mortality, the rate ratio between the 1st and 10th decile (reference) was 1.63 (CI95%: 1.60-1.66), and, for COVID-19, the rate ratio was 7.61 (CI95%: 7.14-8.12). The population attributable fraction was 24% for all causes and 72% for COVID-19. Age, gender, race/ethnicity modified the steepness and shape of dose-response curves. The findings illustrate opportunities to incorporate area-based socioeconomic measures in routine public health surveillance, and to reinforce policies and programs that reduce health inequities.

We prospectively examined whether community-level social capital plays a significant role in developing Posttraumatic Growth (PTG) among older survivors of the 2011 Japan Earthquake and Tsunami. The baseline survey was conducted 7 months before the disaster among residents of a city located 80km west of the earthquake epicenter. The survey inquired about participants' health status and social capital (informal socializing and social participation, and social cohesion). Approximately 2.5 years after the disaster, we surveyed older survivors to assess their disaster experiences. A follow-up survey in 2022 inquired about PTG in the 11 years following experiences of the disaster (n = 1,819). Multilevel linear regression analysis showed that pre-disaster community-level informal socializing and social participation was associated with higher PTG scores (coefficient = 0.25, 95% CI: 0.02, 0.47). In cross-classified multilevel regression, maintenance of higher community-level informal socializing and social participation during the post-disaster period was associated with higher scores of PTG (coefficient = 0.22, 95% CI: 0.07, 0.37). Pre-disaster community-level informal socializing and social participation was associated with higher PTG scores among older survivors. Interventions encouraging social interactions among neighbors may be effective in promoting PTG of survivors after natural disasters.