John L. Pearce

Exposure to certain chemicals can promote adipogenesis, but less is known about whether exposure to human-relevant chemical mixtures behaves similarly. Chemical concentrations from the serum of mothers enrolled in the Environmental Influences on Child Health Outcomes—Fetal Growth Study (n = 813) were used in a self-organizing map algorithm to identify five distinct patterns of real-world exposure mixtures containing p,p′-DDE, PCB153, BDE47, and PFOS. Each mixture profile was exposed to 3T3-L1 cells at 1×, 50×, and 500× serum levels over a 14-day adipogenic differentiation period. Cells were assessed for triglycerides and markers of adipocyte formation and maturation. The results indicate that a mixture dominated by high BDE47 levels (Profile 3) behaved differently than BDE47 alone. BDE47 alone increased expression of Fsp27, Fabp4, and Cpt1, while the Profile 3 mixture inhibited expression of these three genes. In contrast, mixtures dominated by either p,p′-DDE or PFOS (Profiles 1 and 4) behaved similarly to their dominant chemicals. Exposures inducing Pparγ increased Fsp27 levels, while those inducing Ampk reduced Fsp27 levels. These findings suggest that individual chemicals alter transcription factors that control adipogenesis, and the interplay between transcription factors yields synergistic or antagonistic chemical interactions in real-world mixture exposures.

Poly- and perfluorinated alkyl substances (PFAS) are a group of chemicals that are widely used, prevalent in the environment, associated with several toxic effects, and often have long half-lives. Their persistence and relevant toxicity are the primary causes of environmental and human health concerns, and they are referred to as “forever chemicals” because of their persistence. Environmental accumulation caused by slow natural biodegradation and subsequent long environmental half-lives leads to bioaccumulation and makes PFAS more likely to be chronically toxic with potential transgenerational effects. Ultimately, it is this persistence that causes the greatest concern because PFAS-contaminated sites need costly remediation techniques, or else the contaminated areas will not be available for proper economic development because of social and economic suppression. Non-PFAS, alternative Aqueous Film Forming Foams (AFFF) that are considered environmentally friendly, are being heavily considered or currently used for fire suppression instead of PFAS-based products. The bioaccumulation and toxicity of alternative AFFF are just starting to be studied. The purpose of this review is to discuss the basic environmental and human health effects of PFAS and alternative AFFF that propel regulatory changes, increase clean-up costs, reduce economic development, and drive the development of novel alternatives.

Background: We evaluated air emissions of industrial compounds, many of which have carcinogenic or endocrine-disrupting properties, in relation to breast cancer incidence. Methods: Using the United States Environmental Protection Agency’s Toxics Release Inventory, we quantified air emissions of 28 compounds near Sister Study participants’ residences during the 10 years leading up to study enrollment (2003–2006; n = 46,150). We used Cox proportional hazards regression to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for associations of residential emission levels of single pollutants with incident breast cancer. We assessed pollutant mixtures using an exposure continuum mapping (ECM) framework and characterized associations using a joint-exposure response function. Results: During follow-up (median = 13.4 years), we identified 4155 breast cancer cases. We observed nonmonotonic but elevated associations with breast cancer for emissions within 3 km of the residence for nickel compounds (HR_{quintile5vs.none} = 1.3; 95% CI = 1.0, 1.6) and trichloroethylene (HR_{quintile5vs.none} = 1.3; 95% CI = 1.0, 1.6). ECM identified 25 mixture profiles that explained 72% of the variance in emissions patterns, with most participants experiencing relatively low emissions profiles. The joint-exposure response function suggested that a higher incidence of breast cancer occurred among individuals with relatively rare, high emissions profiles; however, the overall trend was not associated with breast cancer (P = 0.09). Conclusions: In our study, breast cancer incidence was associated with air emissions of certain industrial carcinogens. Although the overall emissions mixture did not show a trend related to breast cancer, this may not reflect the importance of individual compounds or specific emissions sources.

Preterm delivery (PTD) complications are a major cause of childhood morbidity and mortality. We aimed to assess trends in PTD and small for gestational age (SGA) and whether trends varied between race–ethnic groups in South Carolina (SC). We utilized 2015–2021 SC vital records linked to hospitalization and emergency department records. PTD was defined as clinically estimated gestation less than (<) 37 weeks (wks.) with subgroup analyses of PTD < 34 wks. and < 28 wks. SGA was defined as infants weighing below the 10th percentile for gestational age. This retrospective study included 338,532 (243,010 before the COVID-19 pandemic and 95,522 during the pandemic) live singleton births of gestational age ≥ 20 wks. born to 260,276 mothers in SC. Generalized estimating equations and a change-point during the first quarter of 2020 helped to assess trends. In unadjusted analyses, pre-pandemic PTD showed an increasing trend that continued during the pandemic (relative risk (RR) = 1.04, 95% CI: 1.02–1.06). PTD < 34 wks. rose during the pandemic (RR = 1.07, 95% CI: 1.02–1.12) with a significant change in the slope. Trends in SGA varied by race and ethnicity, increasing only in Hispanics (RR = 1.02, 95% CI: 1.00–1.04) before the pandemic. Our study reveals an increasing prevalence of PTD and a rise in PTD < 34 wks. during the pandemic, as well as an increasing prevalence of SGA in Hispanics during the study period.

While telemedicine infrastructure was in place within the Veterans Health Administration (VHA) healthcare system before the onset of the COVID-19 pandemic, geographically varying ordinances/closures disrupted vital care for chronic disease patients such as those with type 2 diabetes. We created a national cohort of 1,647,158 non-Hispanic White, non-Hispanic Black, and Hispanic veterans with diabetes including patients with at least one primary care visit and HbA1c lab result between 3.5% and 20% in the fiscal year (FY) 2018 or 2019. For each VAMC, the proportion of telehealth visits in FY 2019 was calculated. Two logistic Bayesian spatial models were employed for in-person primary care or telehealth primary care in the fourth quarter of the FY 2020, with spatial random effects incorporated at the VA medical center (MC) catchment area level. Finally, we computed and mapped the posterior probability of receipt of primary care for an “average” patient within each catchment area. Non-Hispanic Black veterans and Hispanic veterans were less likely to receive in-person primary care but more likely to receive tele-primary care than non-Hispanic white veterans during the study period. Veterans living in the most socially vulnerable areas were more likely to receive telehealth primary care in the fourth quarter of FY 2020 compared to the least socially vulnerable group but were less likely to receive in-person care. In summary, racial minorities and those in the most socially vulnerable areas were less likely to receive in-person primary care but more likely to receive telehealth primary care, potentially indicating a disparity in the impact of the pandemic across these groups.

Background: A better understanding of neighborhood-level factors’ contribution is needed in order to increase the precision of cancer control interventions that target geographic determinants of cancer health disparities. This study characterized the distribution of neighborhood deprivation in a racially diverse cohort of prostate cancer survivors. Methods: A retrospective cohort of 253 prostate cancer patients who were treated with radical prostatectomy from 2011 to 2019 was established at the Medical University of South Carolina. Individual-level data on clinical variables (e.g., stage, grade) and race were abstracted. Social Deprivation Index (SDI) and Healthcare Professional Shortage (HPS) status was obtained from the Robert Graham Center and assigned to participants based on their residential census tract. Data were analyzed with descriptive statistics and multivariable logistic regression. Results: The cohort of 253 men consisted of 168 white, 81 African American, 1 Hispanic and 3 multiracial men. Approximately 49% of 249 men lived in areas with high SDI (e.g., SDI score of 48 to 98). The mean for SDI was 44.5 (+27.4), and the range was 97 (1–98) for all study participants. African American men had a significantly greater likelihood of living in a socially deprived neighborhood compared to white men (OR = 3.7, 95% C.I. 2.1–6.7, p < 0.01), while men who lived in areas with higher HPS shortage status were significantly more likely to live in a neighborhood that had high SDI compared to men who lived in areas with lower HPS shortages (OR = 4.7, 95% C.I. = 2.1–10.7, p < 0.01). African Americans had a higher likelihood of developing biochemical reoccurrence (OR = 3.7, 95% C.I. = 1.7–8.0) compared with white men. There were no significant association between SDI and clinical characteristics of prostate cancer. Conclusions: This study demonstrates that SDI varies considerably by race among men with prostate cancer treated with radical prostatectomy. Using SDI to understand the social environment could be -particularly useful as part of precision medicine and precision public health approaches and could be used by cancer centers, public health providers, and other health care specialists to inform operational decisions about how to target health promotion and disease prevention efforts in catchment areas and patient populations.

The purpose of this study was to examine the association between neighborhood social deprivation and individual-level characteristics on breast cancer staging in African American and white breast cancer patients. We established a retrospective cohort of patients with breast cancer diagnosed from 1996 to 2015 using the South Carolina Central Cancer Registry. We abstracted sociodemographic and clinical variables from the registry and linked these data to a county-level composite that captured neighborhood social conditions—the social deprivation index (SDI). Data were analyzed using chi-square tests, Student’s t-test, and multivariable ordinal regression analysis to evaluate associations. The study sample included 52,803 female patients with breast cancer. Results from the multivariable ordinal regression model demonstrate that higher SDI (OR = 1.06, 95% CI: 1.02–1.10), African American race (OR = 1.35, 95% CI: 1.29–1.41), and being unmarried (OR = 1.17, 95% CI: 1.13–1.22) were associated with a distant stage at diagnosis. Higher tumor grade, younger age, and more recent year of diagnosis were also associated with distant-stage diagnosis. As a proxy for neighborhood context, the SDI can be used by cancer registries and related population-based studies to identify geographic areas that could be prioritized for cancer prevention and control efforts.

Asthma in children poses a significant clinical and public health burden. We examined the association between reported neighborhood traffic (a proxy for traffic-related air pollution) and asthma among 855 multi-racial children aged 4–8 years old who participated in the Environmental Influences on Child Health Outcomes (ECHO) cohort. We hypothesized that high neighborhood traffic density would be associated with the prevalence of asthma. Asthma/asthma-like symptoms (defined as current and/or past physician diagnosed asthma, past wheezing, or nighttime cough or wheezing in the past 12 months) was assessed by parental report. The relationship between neighborhood traffic and asthma/asthma-like symptoms was assessed using logistic regression. The prevalence of asthma/asthma-like symptoms among study participants was 23%, and 15% had high neighborhood traffic. Children with significant neighborhood traffic had a higher odds of having asthma/asthma-like symptoms than children without neighborhood traffic [adjusted OR = 2.01 (95% CI: 1.12, 3.62)] after controlling for child’s race-ethnicity, age, sex, maternal education, family history of asthma, play equipment in the home environment, public parks, obesity and prescribed asthma medication. Further characterization of neighborhood traffic is needed since many children live near high traffic zones and significant racial/ethnic disparities exist.

Introduction: The response to the COVID-19 pandemic became increasingly politicized in the United States (US) and political affiliation of state leaders may contribute to policies affecting the spread of the disease. This study examined differences in COVID-19 infection, death, and testing by governor party affiliation across 50 US states and the District of Columbia. Methods: A longitudinal analysis was conducted in December 2020 examining COVID-19 incidence, death, testing, and test positivity rates from March 15 through December 15, 2020. A Bayesian negative binomial model was fit to estimate daily risk ratios (RRs) and posterior intervals (PIs) comparing rates by gubernatorial party affiliation. The analyses adjusted for state population density, rurality, census region, age, race, ethnicity, poverty, number of physicians, obesity, cardiovascular disease, asthma, smoking, and presidential voting in 2020. Results: From March to early June, Republican-led states had lower COVID-19 incidence rates compared to Democratic-led states. On June 3, the association reversed, and Republican-led states had higher incidence (RR=1.10, 95% PI=1.01, 1.18). This trend persisted through early December. For death rates, Republican-led states had lower rates early in the pandemic, but higher rates from July 4 (RR=1.18, 95% PI=1.02, 1.31) through mid-December. Republican-led states had higher test positivity rates starting on May 30 (RR=1.70, 95% PI=1.66, 1.73) and lower testing rates by September 30 (RR=0.95, 95% PI=0.90, 0.98). Conclusion: Gubernatorial party affiliation may drive policy decisions that impact COVID-19 infections and deaths across the US. Future policy decisions should be guided by public health considerations rather than political ideology.