Contextual Deprivation, Race and Ethnicity, and Income in Air Pollution and Cardiovascular Disease.

Importance: Socioeconomically disadvantaged subpopulations are more vulnerable to fine particulate matter (PM2.5) exposure. However, as prior studies focused on individual-level socioeconomic characteristics, how contextual deprivation modifies the association of PM2.5 exposure with cardiovascular health remains unclear. Objective: To assess disparities in PM2.5 exposure association with cardiovascular disease among subpopulations defined by different socioeconomic characteristics. Design, Setting, and Participants: This cohort study used longitudinal data on participants with electronic health records (EHRs) from the All of Us Research Program between calendar years 2016 and 2022. Statistical analysis was performed from September 25, 2023, through February 23, 2024. Exposure: Satellite-derived 5-year mean PM2.5 exposure at the 3-digit zip code level according to participants' residential address. Main Outcome and Measures: Incident myocardial infarction (MI) and stroke were obtained from the EHRs. Stratified Cox proportional hazards regression models were used to estimate the hazard ratio (HR) between PM2.5 exposure and incident MI or stroke. We evaluated subpopulations defined by 3 socioeconomic characteristics: contextual deprivation (less deprived, more deprived), annual household income (≥$50 000, <$50 000), and race and ethnicity (non-Hispanic Black, non-Hispanic White). We calculated the ratio of HRs (RHR) to quantify disparities between these subpopulations. Results: A total of 210 554 participants were analyzed (40% age >60 years; 59.4% female; 16.7% Hispanic, 19.4% Non-Hispanic Black, 56.1% Non-Hispanic White, 7.9% other [American Indian, Asian, more than 1 race and ethnicity]), among whom 954 MI and 1407 stroke cases were identified. Higher PM2.5 levels were associated with higher MI and stroke risks. However, disadvantaged groups (more deprived, income <$50 000 per year, Black race) were more vulnerable to high PM2.5 levels. The disparities were most pronounced between groups defined by contextual deprivation. For instance, increasing PM2.5 from 6 to 10 µg/m3, the HR for stroke was 1.13 (95% CI, 0.85-1.51) in the less-deprived vs 2.57 (95% CI, 2.06-3.21) in the more-deprived cohort; 1.46 (95% CI, 1.07-2.01) in the $50 000 or more per year vs 2.27 (95% CI, 1.73-2.97) in the under $50 000 per year cohort; and 1.70 (95% CI, 1.35-2.16) in White individuals vs 2.76 (95% CI, 1.89-4.02) in Black individuals. The RHR was highest for contextual deprivation (2.27; 95% CI, 1.59-3.24), compared with income (1.55; 95% CI, 1.05-2.29) and race and ethnicity (1.62; 95% CI, 1.02-2.58). Conclusions and Relevance: In this cohort study, while individual race and ethnicity and income remained crucial in the adverse association of PM2.5 with cardiovascular risks, contextual deprivation was a more robust socioeconomic characteristic modifying the association of PM2.5 exposure.

Assessment of unmeasured confounding in the association between perceived discrimination and mental health in a predominantly African American cohort using g-estimation.

BACKGROUND: Perceived discrimination in health care settings can have adverse consequences on mental health in minority groups. However, the association between perceived discrimination and mental health is prone to unmeasured confounding. The study aims to quantitatively evaluate the influence of unmeasured confounding in this association, using g-estimation. METHODS: In a predominantly African American cohort, we applied g-estimation to estimate the association between perceived discrimination and mental health, adjusted and unadjusted for measured confounders. Mental health was measured using clinical diagnoses of anxiety, depression and bipolar disorder. Perceived discrimination was measured as the number of patient-reported discrimination events in health care settings. Measured confounders included demographic, socioeconomic, residential and health characteristics. The influence of confounding was denoted as α1 from g-estimation. We compared α1 for measured and unmeasured confounding. RESULTS: Strong associations between perceived discrimination in health care settings and mental health outcomes were observed. For anxiety, the odds ratio (95% confidence interval) unadjusted and adjusted for measured confounders were 1.30 (1.21, 1.39) and 1.26 (1.17, 1.36), respectively. The α1 for measured confounding was -0.066. Unmeasured confounding with α1=0.200, which was over three times that of measured confounding, corresponds to an odds ratio of 1.12 (1.01, 1.24). Similar results were observed for other mental health outcomes. CONCLUSION: Compared with measured confounding, unmeasured that was three times measured confounding was not enough to explain away the association between perceived discrimination and mental health, suggesting that this association is robust to unmeasured confounding. This study provides a novel framework to quantitatively evaluate unmeasured confounding.

Long-term exposure to ambient air pollution and measures of central hemodynamics and arterial stiffness among multiethnic Chicago residents.

OBJECTIVES: To examine whether long-term air pollution exposure is associated with central hemodynamic and brachial artery stiffness parameters. METHODS: We assessed central hemodynamic parameters including central blood pressure, cardiac parameters, systemic vascular compliance and resistance, and brachial artery stiffness measures [including brachial artery distensibility (BAD), compliance (BAC), and resistance (BAR)] using waveform analysis of the arterial pressure signals obtained from a standard cuff sphygmomanometer (DynaPulse2000A, San Diego, CA). The long-term exposures to particles with an aerodynamic diameter < 2.5 µm (PM2.5) and nitrogen dioxide (NO2) for the 3-year periods prior to enrollment were estimated at residential addresses using fine-scale intra-urban spatiotemporal models. Linear mixed models adjusted for potential confounders were used to examine associations between air pollution exposures and health outcomes. RESULTS: The cross-sectional study included 2,387 Chicago residents (76% African Americans) enrolled in the ChicagO Multiethnic Prevention And Surveillance Study (COMPASS) during 2013-2018 with validated address information, PM2.5 or NO2, key covariates, and hemodynamics measurements. We observed long-term concentrations of PM2.5 and NO2 to be positively associated with central systolic, pulse pressure and BAR, and negatively associated with BAD, and BAC after adjusting for relevant covariates. A 1-µg/m3 increment in preceding 3-year exposures to PM2.5 was associated with 1.8 mmHg higher central systolic (95% CI: 0.98, 4.16), 1.0 mmHg higher central pulse pressure (95% CI: 0.42, 2.87), a 0.56%mmHg lower BAD (95% CI: -0.81, -0.30), and a 0.009 mL/mmHg lower BAC (95% CI: -0.01, -0.01). CONCLUSION: This population-based study provides evidence that long-term exposures to PM2.5 and NO2 is related to central BP and arterial stiffness parameters, especially among African Americans.

Uterine Fibroid Prevalence in a Predominantly Black, Chicago-Based Cohort.

(1) Objectives: To investigate the effect of individual-level, neighborhood, and environmental variables on uterine fibroid (UF) prevalence in a Chicago-based cohort. (2) Methods: Data from the Chicago Multiethnic Prevention and Surveillance Study (COMPASS) were analyzed. Individual-level variables were obtained from questionnaires, neighborhood variables from the Chicago Health Atlas, and environmental variables from NASA satellite ambient air exposure levels. The Shapiro-Wilk test, logistic regression models, and Spearman's correlations were used to evaluate the association of variables to UF diagnosis. (3) Results: We analyzed 602 participants (mean age: 50.3 ± 12.3) who responded to a question about UF diagnosis. More Black than White participants had a UF diagnosis (OR, 1.32; 95% CI, 0.62-2.79). We observed non-significant trends between individual-level and neighborhood variables and UF diagnosis. Ambient air pollutants, PM2.5, and DSLPM were protective against UF diagnosis (OR 0.20, CI: 0.04-0.97: OR 0.33, CI: 0.13-0.87). (4) Conclusions: Associations observed within a sample in a specific geographic area may not be generalizable and must be interpreted cautiously.

Air quality and cancer risk in the All of Us Research Program.

INTRODUCTION: The NIH All of Us Research Program has enrolled over 544,000 participants across the US with unprecedented racial/ethnic diversity, offering opportunities to investigate myriad exposures and diseases. This paper aims to investigate the association between PM2.5 exposure and cancer risks. MATERIALS AND METHODS: This work was performed on data from 409,876 All of Us Research Program participants using the All of Us Researcher Workbench. Cancer case ascertainment was performed using data from electronic health records and the self-reported Personal Medical History questionnaire. PM2.5 exposure was retrieved from NASA's Earth Observing System Data and Information Center and assigned using participants' 3-digit zip code prefixes. Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI). Generalized additive models (GAMs) were used to investigate non-linear relationships. RESULTS: A total of 33,387 participants and 46,176 prevalent cancer cases were ascertained from participant EHR data, while 20,297 cases were ascertained from self-reported survey data from 18,133 participants; 9,502 cancer cases were captured in both the EHR and survey data. Average PM2.5 level from 2007 to 2016 was 8.90 µg/m3 (min 2.56, max 15.05). In analysis of cancer cases from EHR, an increased odds for breast cancer (OR 1.17, 95% CI 1.09-1.25), endometrial cancer (OR 1.33, 95% CI 1.09-1.62) and ovarian cancer (OR 1.20, 95% CI 1.01-1.42) in the 4th quartile of exposure compared to the 1st. In GAM, higher PM2.5 concentration was associated with increased odds for blood cancer, bone cancer, brain cancer, breast cancer, colon and rectum cancer, endocrine system cancer, lung cancer, pancreatic cancer, prostate cancer, and thyroid cancer. CONCLUSIONS: We found evidence of an association of PM2.5 with breast, ovarian, and endometrial cancers. There is little to no prior evidence in the literature on the impact of PM2.5 on risk of these cancers, warranting further investigation.

Duration-sensitive association between air pollution exposure and changes in cardiometabolic biomarkers: Evidence from a predominantly African American cohort.

BACKGROUND: Ambient fine particulate matter (PM2.5) exposure has been related to cardiometabolic diseases, but the underlying biological pathways remain unclear at the population level. OBJECTIVE: To investigate the effect of PM2.5 exposure on changes in multiple cardiometabolic biomarkers across different exposure durations. METHOD: Data from a prospective cohort study were analyzed. Ten cardiometabolic biomarkers were measured, including ghrelin, resistin, leptin, C-peptide, creatine kinase myocardial band (CK-MB), monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor alpha (TNF-alpha), N-terminal pro B-type natriuretic peptide (NT-proBNP), troponin, and interleukin-6 (IL-6). PM2.5 levels across exposure durations from 1 to 36 months were assessed. Mixed effect model was used to estimate changes in biomarker levels against 1 µg/m3 increase in PM2.5 level across different exposure durations. RESULTS: Totally, 641 participants were included. The average PM2.5 exposure level was 9 µg/m3. PM2.5 exposure was inversely associated with ghrelin, and positively associated with all other biomarkers. The magnitudes of these associations were duration-sensitive and exhibited a U-shaped or inverted-U-shaped trend. For example, the association of resistin were ß = 0.05 (95% CI: 0.00, 0.09) for 1-month duration, strengthened to ß = 0.27 (95% CI: 0.14, 0.41) for 13-month duration, and weakened to ß = 0.12 (95% CI: -0.03, 0.26) for 24-month duration. Similar patterns were observed for other biomarkers except for CK-MB, of which the association direction switched from negative to positive as the duration increased. Resistin, leptin, MCP-1, TNF-alpha, and troponin had a sensitive exposure duration of nearly 12 months. Ghrelin and C-peptide were more sensitive to longer-term exposure (>18 months), while NT-proBNP and IL-6 were more sensitive to shorter-term exposure (<6 months). CONCLUSION: PM2.5 exposure was associated with elevated levels in cardiometabolic biomarkers related to insulin resistance, inflammation, and heart injury. The magnitudes of these associations depended on the exposure duration. The most sensitive exposure durations of different biomarkers varied.

Evaluating the impact of sickle cell disease on COVID-19 susceptibility and severity: a retrospective cohort study based on electronic health record.

Background: Sickle cell trait/disease (SCT/SCD) are enriched among Black people and associated with various comorbidities. The overrepresentation of these characteristics prevents traditional regression approach obtaining convincing evidence for the independent effect of SCT/SCD on other health outcomes. This study aims to investigate the association between SCT/SCD and COVID-19-related outcomes using causal inference approaches that balance the covariate. Methods: We leveraged electronic health record (EHR) data from the University of Chicago Medicine between March 2020 and December 2021. Demographic characteristics were retrieved. Medical conditions were identified using ICD-10 codes. Five approaches, including two traditional regression approaches (unadjusted and adjusted) and three causal inference approaches [covariate balancing propensity score (CBPS) matching, CBPS weighting, and CBPS adjustment], were employed. Results: A total of 112,334 patients were included in the study, among which 504 had SCT and 388 SCD. Patients with SCT/SCD were more likely to be non-Hispanic Black people, younger, female, non-smokers, and had a diagnosis of diabetes, heart failure, asthma, and cerebral infarction. Causal inference approaches achieved a balanced distribution of these covariates while traditional approaches failed. Across these approaches, SCD was consistently associated with COVID-19-related pneumonia (odds ratios (OR) estimates, 3.23 (95% CI: 2.13-4.89) to 2.57 (95% CI: 1.10-6.00)) and pain (OR estimates, 6.51 (95% CI: 4.68-9.06) to 2.47 (95% CI: 1.35-4.49)). While CBPS matching suggested an association between SCD and COVID-19-related acute respiratory distress syndrome (OR = 2.01, 95% CI: 0.97-4.17), this association was significant in other approaches (OR estimates, 2.96 (95% CI: 1.69-5.18) to 2.50 (95% CI: 1.43-4.37)). No association was observed between SCT and COVID-19-related outcomes in causal inference approaches. Conclusion: Using causal inference approaches, we provide comprehensive evidence for the link between SCT/SCD and COVID-19-related outcomes.

Etiology of lung cancer: Evidence from epidemiologic studies.

Lung cancer is one of the leading causes of cancer incidence and mortality worldwide. While smoking, radon, air pollution, as well as occupational exposure to asbestos, diesel fumes, arsenic, beryllium, cadmium, chromium, nickel, and silica are well-established risk factors, many lung cancer cases cannot be explained by these known risk factors. Over the last two decades the incidence of adenocarcinoma has risen, and it now surpasses squamous cell carcinoma as the most common histologic subtype. This increase warrants new efforts to identify additional risk factors for specific lung cancer subtypes as well as a comprehensive review of current evidence from epidemiologic studies to inform future studies. Given the myriad exposures individuals experience in real-world settings, it is essential to investigate mixture effects from complex exposures and gene-environment interactions in relation to lung cancer and its subtypes.

Etiology of non-Hodgkin lymphoma: A review from epidemiologic studies.

Non-Hodgkin lymphoma (NHL) contributes to significant cancer burden and mortality globally. In recent years, much insight into the causes of NHL has been gained by evaluating global differences through international collaboration and data pooling. NHL comprises different subtypes that are known to behave differently, exhibit different prognoses, and start in distinct cell types (B-cell, T-cell, and NK-cell, predominantly), and there is increasing evidence that NHL subtypes have different etiologies. Classification of NHL can be complex, with varying subtype frequencies, and is a consideration when evaluating geographic differences. Because of this, international pooling of well-executed epidemiologic studies has conferred power to evaluate NHL by subtype and confidence with minimal misclassification. Given the decreasing burden in some regions while cases rise in Asia, and especially China, this report focuses on a review of the established etiology of NHL from the epidemiologic literature in recent decades, highlighting work from China. Topics covered include demographic patterns and genetic determinants including family history of NHL, as well as infection and immunosuppression, lifestyle, environment, and certain occupational exposures contributing to increased disease risk.