American journal of epidemiology最新文献

Causal inference research typically estimates effects on population average health rather than impacts on health disparities. We present a standardization-based approach to simulate how altering population distributions of exposures might change health disparities, with explicit consideration of two mechanisms: differential exposure distributions and heterogeneous exposure effects across social groups. Using data from the Health and Retirement Study (n=11,322) and the English Longitudinal Study of Ageing (n=5,179), we examined how hypothetical interventions reducing social isolation and loneliness might affect socioeconomic and racial disparities in cognitive functioning among older adults. Social isolation was longitudinally associated with lower average cognitive functioning in both HRS and ELSA, with evidence of effect heterogeneity in the HRS sample, where the adverse association was stronger among individuals with lower education, Black race, and paradoxically, higher income/wealth. Simulations demonstrated that reducing social isolation would narrow cognitive disparities across income, wealth, education, and race. Interventions specifically targeting exposure disparities achieved greater reductions than uniform approaches. This framework enables researchers to move beyond estimating average treatment effects to quantifying how different intervention strategies might reduce health disparities between social groups.

Most previous studies of increased hypertension (HTN) incidence following COVID-19 infection lack longitudinal testing and diagnostic information and under-represent minorities. We examined this relationship using a case-control time-to-event-study of 39,746 individuals continuously incarcerated from January 1, 2019 to March 1, 2020 (pandemic start), followed until March 1, 2023 in 31 California state prisons. Those included had no pre-pandemic HTN diagnosis and no blood pressure-altering medication prescriptions; had BMI and blood pressure measurements before and during the pandemic; and were tested for COVID-19. Exposure began 31 days after COVID-19 positivity. Clinical diagnosis established incident HTN. Multivariate Cox proportional hazards models adjusted for age, sex, race/ethnicity, BMI, baseline blood pressure, and frequency of healthcare contacts and COVID-19 testing. We assessed confounding from changes in HTN testing post-COVID. 21,480 individuals tested COVID-19 positive prior to HTN diagnosis (or censoring). The subsequent crude HTN incidence rate was 32.5 per 1,000 person-years (exposed) [95%CI: 30.5-34.6] versus 27.1 (unexposed) [25.8-28.5]. COVID-19 infection was associated with significantly increased HTN incidence (main effects HRR: 1.44 [1.32-1.57]; including interactions: HRR: 2.05 [1.50-2.79]), with stronger association for higher BMI, higher pre-pandemic blood pressure, and older age. Potential confounding from post-COVID increases in HTN diagnostic testing cannot explain these results.

There is substantial interest in estimating the health effects of exposure to environmental mixtures. Bayesian kernel machine regression (BKMR) has emerged as a popular tool for mixture analyses. The health effects of environmental exposures, including mixture exposures, often differ among subpopulations. However, there is little guidance on how to assess such heterogeneity for mixture effects. We provide tools and guidance to conduct BKMR analyses with effect modification, including estimating group-specific effects and between-group differences in effects. We propose a new group-separable BKMR variant for mixture analyses with effect modification by a categorical variable. We compare this new method to a stratified analysis and to a model that includes the categorical modifier directly in the BKMR kernel function in both a simulation study and the analysis of a metals mixture on children's neurodevelopment with child sex as a binary modifier in a rural Bangladesh cohort. Both stratified BKMR and the new group-separable BKMR have the flexibility to capture interactions and estimate between-group differences. The group-separable BKMR has lower variance compared to stratified BKMR, particularly when there are small subgroup sizes. We provide code and data to implement the methods and reproduce simulations and analyses.

Historical redlining, a 1930s residential segregation policy, has been associated with contemporary breast cancer survival, but the role of contemporary neighborhood socioeconomic condition is unclear. We investigated mediating and modifying effects of neighborhood socioeconomic condition. This New York State Cancer Registry-based cohort included 60,773 invasive breast cancer cases. Cases were assigned a historical redlining grade (A-D) through linkage to residential census tract at diagnosis. We used labor class index of concentration at the extremes to proxy neighborhood socioeconomic condition. Four-way decomposition evaluated mediation and modification of neighborhood socioeconomic condition on redlining and breast cancer survival. The total effect (risk ratio, RR) on 5-year mortality from D-grade vs. A-grade =1.20 (95% CI: 1.09, 1.31), which decomposed to a controlled direct effect excess RR (ERR)=0.10 (95% CI: -0.01, 0.21) and a pure indirect effect ERR=0.09 (95% CI: 0.05, 0.13); significant interaction was not detected. Results were consistent among hormone receptor+, local-, and regional-stage tumors, but not HR- or distant-stage tumors. Decomposition differs by race/ethnicity. Contemporary neighborhood socioeconomic condition mediates approximately half the association between historical redlining and all-cause breast cancer survival, while the other half is attributed to historical redlining. Interventions addressing neighborhood socioeconomic condition may attenuate redlining-based breast cancer survival disparities.

Persistent tinnitus is common, often disabling, and challenging to treat. Greater adherence to healthy diet patterns was associated with 30% lower risk of hearing loss. Dietary factors have also been implicated in tinnitus, but findings are not consistent and longitudinal studies are scarce. We examined the longitudinal associations of healthy diet patterns, specific food groups, individual foods and risk of developing persistent tinnitus in two independent cohorts of 113,554 women, the Nurses' Health Study (NHS)(1984-2022;n=42,504) and NHS2 (1991-2021;n= 71,050). Validated food frequency questionnaires assessed diet every 4 years. We used multivariable-adjusted Cox proportional hazards regression to examine independent associations in cohort-specific and pooled analyses. After 2,643,510 person-years of follow-up, 22,879 cases of incident tinnitus were reported. While greater adherence to overall healthy diet patterns did not consistently reduce risk, in both cohorts we observed higher fruit intake was associated with reduced risk, and higher intakes of whole grains, legumes and sugar-sweetened beverages (SSBs) were associated with greater risk of incident tinnitus. Comparing highest to lowest quintiles of intake, the pooled MVHRs were: 0.81 (0.77,0.85)(p-trend<0.0001) for fruit; 1.26 (1.20,1.32)(p-trend<0.0001) for whole grains; 1.13 (1.08,1.18)(p-trend<0.0001) for legumes; and 1.12 (1.07,1.17)(p-trend<0.0001) for SSBs. Diet composition appears to alter the risk of developing tinnitus.

The birth and diagnosis of a child with congenital abnormalities can alter parental reproductive patterns, yet its association with subsequent fecundability remains insufficiently explored. We conducted a government-supported matched cohort study in China to evaluate this association and assess whether it varies by the severity of the child's condition and parental characteristics. A total of 2448 couples from the National Free Pre-conception Check-up Project between 2012 and 2018 attempting to conceive again were included: 612 exposed couples with children affected by congenital abnormalities and 1836 non-exposed couples with unaffected children and no adverse pregnancy history. Participants were followed via telephone every 3 months for one year to track pregnancy outcomes. Cox proportional hazards models with a shared frailty were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for fecundability. Overall, exposed couples demonstrated a 28% higher fecundability than non-exposed couples (HR 1.28, 95% CI: 1.10-1.49). This association was primarily observed among parents with "healthy" characteristics and those whose children had single-system/body-part congenital abnormalities (HR 1.27, 95% CI: 1.09-1.48). These findings highlight the importance of integrated fertility counseling, prenatal screening, and psychological support for families seeking subsequent pregnancies after the birth of a child with congenital abnormalities.

The fragility index is generally presented as a metric to assess how sensitive the passing of a particular p-value threshold is to the number of changes in event status. In many cases, the "statistical significance" of a result may be quite fragile. An alternative interpretation of the fragility index is proposed that reframes it as a sensitivity analysis or bias analysis for particular forms of misclassification. The reframing also makes clear the comparative relevance of different analogues of the fragility index for survival data, such as that proposed by Xing, et al. (Am J Epidemiol. 0000;000(00):0000-0000) and others, and further moves away from more dichotomous interpretations concerning p-value thresholds.

Though American mortality conditions have deteriorated in recent years, one bright spot has been Black life expectancy. Between 1994 and 2019, Black life expectancy rose by five years for women and seven years for men, with most of these gains attributed to improving social and economic conditions for Black Americans. Over this same period, immigration also increased, with immigrants and their children now making up 22% of the Black population. This study shows that rising immigration is directly responsible for nearly 15% of the improvement in Black life expectancy. In 2019, immigrants added 1.5 years to overall Black life expectancy for men and 1.0 years for women. At the working ages, immigration reduces mortality by 15% and is projected to reduce overall Black mortality by 30% in the coming decades. During the COVID-19 pandemic, life expectancy for the US-born Black population with US-born parents fell by three years, but the foreign-born Black population experienced a 7-year drop, among the largest year-over-year declines for any major population subgroup. The story about rising Black life expectancy is thus more complicated-there has been a very real story of racial progress, but that story is overinflated when not considering the role of immigration.

The COVID-19 pandemic highlighted deep-rooted health inequities globally, with marginalized populations showing disproportionate disease burden. We employed Serfling regression models and multivariable analyses to estimate excess mortality across geographic, demographic, and poverty groups from 2020-2022 in Chile. Elderly populations (80+ years) experienced the highest excess mortality (267.35 per 10,000 population), more than eight times higher than those under 80 years (30.80 per 10,000 population). Multivariable linear regression models showed both Indigenous proportion (coefficient=53.66, p<0.001) and elderly population proportion (coefficient=5.68, p<0.01) as the strong predictors of comuna level excess mortality. Poverty correlated significantly with excess mortality (r=0.23, p<0.001) but this association weakened after adjustment for other covariates in multivariable models. Excess mortality peaked in 2021 rather than in 2020 for most groups, with males initially experiencing higher rates during early pandemic waves. Spatial analyses revealed statistically significant clustering (Moran's I=0.119, p<0.001) with identifiable hotspots in northern Chile and parts of the south. These findings indicated persistent mortality disparities by age and Indigenous status, independent of poverty, and highlight the urgent need for equity-focused pandemic preparedness. An effective pandemic response should integrate biomedical measures, such as vaccination, with culturally grounded strategies that address structural barriers and the broader social determinants of health.