American journal of epidemiology最新文献

The assumption that serious adverse events (SAEs) do not affect subsequent exposure might not hold when evaluating 2-dose vaccine safety through a self-controlled case series (SCCS) design. To address this, we developed: (1) propensity score SCCS (PS-SCCS) using a propensity score model involving SAEs during the risk interval after dose 1 (${R}_1$), and (2) partitioned SCCS (P-SCCS) estimating relative incidence (RI) separately for doses 1 and 2. In simulations, both provided unbiased RIs. Conversely, standard SCCS overestimated RI after dose 2. We applied these approaches to assess myocarditis/pericarditis risks after 2-dose mRNA coronavirus disease 2019 (COVID-19) vaccination in 12- to 39-year-olds. For BNT162b2, PS-SCCS yielded RIs of 1.85 (95% CI, 0.75-4.59) and 11.05 (95% CI, 6.53-18.68) 14 days after doses 1 and 2 respectively; standard SCCS provided similar RI after dose 1 and RI of 12.92 (95% CI, 7.56-22.09) after dose 2. For mRNA-1273, standard SCCS showed RIs of 1.96 (95% CI, 0.56-6.91) after dose 1 and 7.87 (95% CI, 3.33-18.57) after dose 2. As no mRNA-1273 recipients with SAEs during ${R}_1$ received dose 2, P-SCCS was used, yielding similar RI after dose 1 and RI of 6.48 (95% CI, 2.83-14.83) after dose 2. mRNA vaccines were associated with elevated myocarditis/pericarditis risks following dose 2 in 12- to 39-year-olds.

In cohort studies, it can be infeasible to collect specimens on an entire cohort. For example, to estimate sensitivity of multiple multi-cancer detection (MCD) assays, we desire an extra 80 mL of cell-free DNA (cfDNA) blood, but this much extra blood is too expensive for us to collect on everyone. We propose a novel epidemiologic study design that efficiently oversamples those at highest baseline disease risk from whom to collect specimens, to increase the number of future cases with cfDNA blood collection. The variance reduction ratio from our risk-based subsample versus a simple random (sub)sample (SRS) depends primarily on the ratio of risk model sensitivity to the fraction of the cohort selected for specimen collection subject to constraining the risk model specificity. In a simulation where we chose 34% of the Prostate, Lung, Colorectal, and Ovarian Screening Trial cohort at highest risk of lung cancer for cfDNA blood collection, we could enrich the number of lung cancers 2.42-fold. The standard deviation of lung-cancer MCD sensitivity was 31%-33% reduced versus SRS. Risk-based collection of specimens on a subsample of the cohort could be a feasible and efficient approach to collecting extra specimens for molecular epidemiology.

Telomere length is associated with chronic diseases and, in younger populations, may represent a biomarker of disease susceptibility. As growing evidence suggests that environmental factors, including metals, may impact telomere length. We investigated the association between 17 metals measured in toenail samples and leukocyte relative telomere length (RTL), among 472 5- to 7-year-old children enrolled in the Bangladesh Environmental Research in Children's Health (BiRCH) cohortIn single-exposure linear regression models, a doubling of arsenic (As) and mercury (Hg) (μg/g) were associated with a -0.21 (95% CI, -0.032 to -0.010; P = .0005) and -0.017 (95% CI, -0.029 to -0.004; P = .006) difference in RTL, respectively. In Bayesian Kernel Machine Regression (BKMR) mixture models, the overall metal mixture was inversely associated with RTL (P-for-trend < 0.001). Negative associations with RTL were observed with both log2-As and log2-Hg, while an inverted U-shaped association was observed for log2-zinc (Zn) with RTL. We found little evidence of interaction among metals. Sex-stratification identified stronger associations of the overall mixture and log2-As with RTL among females compared to males. Our study suggests that As and Hg may independently influence RTL in mid-childhood. Further studies are needed to investigate potential long-term impacts of metal-associated telomere shortening in childhood on health outcomes in adult life.

Confounding by indication is a key challenge for pharmacoepidemiologists. Although self-controlled study designs address time-invariant confounding, indications sometimes vary over time. For example, infection might act as a time-varying confounder in a study of antibiotics and uveitis, because it is time-limited and a direct cause of both receipt of antibiotics and uveitis. Methods for incorporating active comparators in self-controlled studies to address such time-varying confounding by indication have only recently been developed. In this paper, we formalize these methods and provide a detailed description for how the active comparator rate ratio can be derived in a self-controlled case series: either by explicitly comparing the regression coefficients for a drug of interest and an active comparator under certain circumstances using a simple ratio approach or through the use of a nested regression model. The approaches are compared in 2 case studies, one examining the association between thiazolidinedione use and fractures and one examining the association between fluoroquinolone use and uveitis, using the United Kingdom's Clinical Practice Research Datalink. Finally, we provide recommendations for the use of these methods, which we hope will support the design, execution, and interpretation of self-controlled case series using active comparators and thereby increase the robustness of pharmacoepidemiologic studies. This article is part of a Special Collection on Pharmacoepidemiology.

The current study estimated effects of intervention dose (attendance) of a cognitive behavioral prevention (CBP) program on depression-free days (DFDs) in adolescent offspring of parents with a history of depression. As part of secondary analyses of a multisite randomized controlled trial, we analyzed the complete intention-to-treat sample of 316 at-risk adolescents ages 13 to 17 years. Youth were randomly assigned to the CBP program plus usual care (n = 159) or to usual care alone (n = 157). The CBP program involved 8 weekly acute sessions and 6 monthly continuation sessions. Results showed that higher CBP program dose predicted more DFDs, with a key threshold of approximately 75% of a full dose in analyses employing instrumental variable methodology to control multiple channels of bias. Specifically, attending at more than 75% of acute phase sessions led to 45.3 more DFDs over the 9-month period after randomization, which accounted for over 12% of the total follow-up days. Instrument sets were informed by study variables and external data, including weather and travel burden. In contrast, conventional analysis methods failed to find a significant dose-outcome relation. Application of the instrumental variable approach, which better controls the influence of confounding, demonstrated that higher CBP program dose resulted in more DFDs. This article is part of a Special Collection on Mental Health.

Endometrial cancer is one of few cancers that has continued to rise in incidence over the past decade, with disproportionate increases in adults younger than 50 years old. We used data from the Surveillance, Epidemiology, and End Results Registry (2000-2019) to examine endometrial cancer incidence trends by race/ethnicity and age of onset among women in the United States. Case counts and proportions, age-adjusted incidence rates (per 100 000), and average annual percent changes were calculated by race/ethnicity, overall and stratified by age of onset (early vs late). We found a disproportionate increase in endometrial cancer incidence among women of color, for both early and late onset endometrial cancer. The highest increases in early onset endometrial cancer (<50 years old) were observed among American Indian/Alaska Native women (4.8), followed by Black (3.3), Hispanic/Latina (3.1), and Asian and Pacific Islander women (2.4), whereas White women (0.9) had the lowest increase. Late onset (≥50 years old) endometrial cancer incidence followed a similar pattern, with the greatest increases for women of color. The increasing burden of endometrial cancer among women of color, particularly those younger than 50 years old, is a major public health problem necessitating further research and clinical efforts focused on health equity. This article is part of a Special Collection on Gynecological Cancer.

The objective of this study was to determine whether exposure to structural racism-related state laws is associated with cardiovascular health among a racially and ethnically diverse sample of US adults. Data were from the Database of Structural Racism-Related State Laws and the Behavioral Risk Factor Surveillance System (BRFSS). The sample included 958 019 BRFSS 2011 and 2013 respondents aged 18 years or older from all 50 US states. The exposure was a summary index of 22 state laws related to the criminal legal system, economics and labor, education, health care, housing, immigration, and political participation. The outcome was the American Heart Association's Life's Simple 7 (LS7), a summary index of 7 cardiovascular health indicators. Linear regression models included fixed effects for year and state to control for time trends and unmeasured, time-invariant, state-level contextual factors. In the full sample, a 1 SD increase in the structural racism state legal index was associated with a 0.06-unit decrease in the LS7 (b = -0.06; 95% CI, -0.09 to 0.02; P = .001), controlling for individual- and state-level covariates. Contrary to expectations, stratified models revealed no statistically significant differences by race and ethnicity in the association between the structural racism state legal index and the LS7.

Gynecological cancers are the most prevalent cancers in women, making them a major public health concern for decades. Health disparities and inequalities in access to care among different racial groups have been a major concern in the US healthcare system. This study was aimed at investigating cause-specific survival rates among non-White women with gynecological cancer and to identify risk factors associated with gynecological cancer mortality by race. The Kaplan-Meier method was used to calculate 5-year survival estimates and various risk factors for gynecological cancer among non-White women were analyzed using Cox proportional hazard model. The findings of this study highlight the need for targeted interventions to improve access to care and reduce health disparities for non-White women with gynecological cancer. This article is part of a Special Collection on Gynecological Cancer.

Employment and working conditions are strong social determinants of health, yet many epidemiologic studies fail to account for their impact on life expectancy calculations. Integration of working conditions into health estimates requires both valid methodology and data sources. Using the French national Health and Career Path Survey and French life tables, we quantified the impact of 4 major work-related factors (lack of job control, job insecurity, unemployment, and occupational physical activity) in explaining socio-occupational inequalities in life expectancy. Using a formula-based approach, we computed work-related loss in life expectancy according to socio-occupational group, separately by sex. Based on life expectancy at age 35 years, we estimated that 1.3-3.3 years of life lost for men and 0.5-1.8 years for women are attributable to a combination of these 4 key factors. Although subject to sources of under- and overestimation, the differential life expectancy at age 35 years between senior executives and manual workers would substantially decrease if these exposures were set at the theoretical minimum level. This proof-of-concept analysis demonstrates the utility of accounting for occupational factors and the potential to quantify improvements in life expectancy that would occur by modifying working and employment conditions.