Gabriela R. Oates

Neighborhood factors, encompassing social, built, and natural environments, may explain geographic differences in the impact of COVID-19 pandemic on populations. Data from pre-existing national, population-based cohorts could be leveraged to better understand how pre-existing conditions (both individual and neighborhood) contribute to risk factor development and disease progression. We catalogued spatial and neighborhood data in the Collaborative Cohort of Cohorts for COVID-19 Research (C4R), comprising 14 diverse US cohorts (>50,000 participants). The C4R sample is generally spatially and socially representative of the overall nation, with C4R’s calculated spatial coverage representing 28% of US land area and 52% of the total US population. However, C4R (vs. non C4R) areas were more urban, wealthy, with more foreign-born residents, and less car-dependent with lower proportion employed and green. Twelve cohorts collected neighborhood characteristics – most commonly social environment data on neighborhood socioeconomic status– based on participants’ addresses. The most common built environment measures were related to food access, followed by other destination-based measures such as walkability. Natural environment data were available in the fewest cohorts, with emphasis on air quality or greenspace. This work provides clarity on available neighborhood and spatial data and facilitates future harmonization of data from C4R cohorts. Ultimately, this may enable future longitudinal and comparative analyses of neighborhood influences on COVID-19.

Background: There is a paucity of knowledge regarding the joint and cumulative effects of multiple exposures from the physical, built, and social environments for chronic obstructive pulmonary disease (COPD) outcomes. Objectives: We assessed the separate and joint contributions of such factors for initial lung function and annual rate of change in a clinical cohort of patients with COPD. Design: Retrospective cohort study using electronic medical records. Methods: Data on individuals with an ICD-10 diagnosis of COPD were extracted from the University of Alabama at Birmingham Health System (2010–2020). Analyses were restricted to those who met spirometric criteria for a COPD diagnosis (FEV ₁ /FVC < 0.7). The predicted FEV ₁ values (FEV ₁ %) were calculated using 2022 GLI race-neutral equations. The earliest residential address during the study period was geocoded and linked to neighborhood characteristics at the Census tract level, including social vulnerability, environmental burden, walkability, residential segregation, rurality, and food access. Analyses adjusted for age, sex, race/ethnicity, marital status, smoking status, obesity, and comorbidities. Results: The analytic sample included 5652 patients. Social and environmental exposures differed by race ( p < 0.001), with Black patients living in more urban and segregated environments with worse exposures. Adverse exposures were significantly associated with lower baseline FEV ₁ %: overall environmental justice score, −11.43%; overall social vulnerability score, −12.29%; neighborhood socioeconomic status, −11.96%; residential segregation, −9.44%. Most associations remained significant after adjusting for patient demographic and clinical characteristics. When the multiple aspects of the environment were considered simultaneously, the dominant factor for baseline FEV ₁ % was the overall social vulnerability (−12.31%, p < 0.001 unadjusted; −9.96%, p < 0.001 adjusted). Residence in a food desert was negatively associated with the annual rate of FEV ₁ % decline (−0.41% unadjusted, p = 0.004; −0.39% adjusted, p = 0.009). Conclusion: Aspects of the physical, built, and social environments affect COPD outcomes. Findings can be used in risk prediction models and for the development of tools that incorporate such exposures at the point of care for individualized disease management.

Background: Our prior work revealed multilevel barriers to smoking cessation interventions among cystic fibrosis (CF) families and clinical providers. Here, we assess qualitatively the implementation of CEASE‐CF, a multicomponent smoking cessation intervention tailored to the needs of CF caregivers and delivered by a tobacco treatment specialist (TTS) integrated into the CF care team (NCT04777344). Methods: We conducted interviews with CF caregivers in the CEASE‐CF intervention arm and with CF clinical care providers. Interviews were recorded and transcribed. Data analysis was completed by two independent coders using NVivo. Themes were generated using a content analysis approach with a constant comparative method. Results: In 22 interviews with caregivers ( n = 12) and providers ( n = 10), four overarching themes emerged: (1) Increased caregiver awareness about the sources and harms of smoke exposure; (2) Increased caregiver self‐efficacy for quitting; (3) Caregiver endorsement of the effectiveness of counseling by TTS; and (4) Provider endorsement of the integration of TTS in the CF care team. Conclusion: CEASE‐CF positively impacted caregivers by increasing their awareness of the sources and harms of smoke exposure, equipping them with tools to change habits, and enhancing their self‐reported confidence and self‐efficacy for quitting. Consistent and multifaceted cessation support provided by a trained TTS is practice‐changing and can be successfully integrated in CF care delivery.

Stark racial and socioeconomic disparities in COVID-19 case rates manifested across the U.S. during the COVID-19 pandemic and were also observed in rates of COVID-19 testing. Targeted testing of populations at greatest risk for COVID-19, while effective in containing the spread of COVID-19, could propagate stigma and discrimination, especially when directed toward already marginalized communities. As is known from other health areas, stigmatization can drive people to deny or hide their illness, prevent or delay timely healthcare seeking, and can discourage people from adopting healthy behaviors, such as testing or precautions. In this study we sought to adapt and validate two scales from the HIV stigma literature to measure aspects of COVID-19 stigma, including measures of 1) negative attitudes toward people who get COVID-19 and 2) perceptions of stigma faced by people who get COVID-19 in the community. After working with stigma experts and community partners to adapt the scales, we implemented the items in a community-based survey of African American residents of neighborhoods with high social vulnerability in two counties in Alabama (n=302). Analytic methods included internal reliability testing and scale item reduction, construct validity examination, and bivariable and multivariable linear regression analyses to examine associations with conceptually important and statistically significant predictors. The final COVID-19 stigma scales developed through this process have good reliability and validity and can be used in future research and programs to understand and address disparities in uptake of testing and precautions for COVID-19 and future pandemics.

Key Points: Only one third of intensive care unit patients who developed severe AKI received Kidney Disease Improving Global Outcomes–recommended follow-up care within 3 months of AKI. Both individual-level and neighborhood-level socioeconomic disadvantages are associated with decreased post-AKI follow-up care. Background: Individual-level and neighborhood-level social determinants of health (SDOH) measures have been associated with higher incidence of AKI, lower likelihood of recovery, and higher risk of mortality after AKI. The association of SDOH measures with posthospitalization AKI follow-up care is unknown. Methods: Using a retrospective cohort design, we evaluated the association of individual-level (insurance status, race, ethnicity) and neighborhood-level (socioeconomic deprivation, rurality, residential segregation, and social vulnerability to natural or human-caused disasters) SDOH measures with receipt of posthospitalization follow-up for AKI within 3 months of hospital discharge among intensive care unit (ICU) survivors with AKI stage 2 or 3 hospitalized between 2012 and 2023 at a major academic medical center. The primary outcome, posthospitalization AKI follow-up, was defined as the occurrence of at least one of the following within 3 months of hospital discharge: a nephrology outpatient visit, serum creatinine measurement, or urine protein measurement. We used pooled logistic regression models with inverse probability of censoring weighting to adjust for demographics, comorbidities, and hospitalization characteristics and to account for the competing risks of death, rehospitalization, or dialysis initiation. Results: Among 13,392 adult ICU survivors with AKI stages 2 or 3, 5970 (45%) were female, 4488 (34%) were of Black race, and 1561 (12%) were uninsured. A total of 7316 (61%) received posthospitalization follow-up for AKI within 3 months of hospital discharge. Uninsured individuals (adjusted odds ratio [aOR], 0.77; 95% confidence interval [CI], 0.70 to 0.84), individuals residing in a neighborhood with greater socioeconomic deprivation (aOR, 0.86; 95% CI, 0.81 to 0.92), greater rurality (aOR, 0.86; 95% CI, 0.81 to 0.92), greater segregation (aOR, 0.92; 95% CI, 0.87 to 0.98), and greater social vulnerability (aOR, 0.83; 95% CI, 0.77 to 0.89) all experienced significantly lower odds of posthospitalization AKI care. Conclusions: Both individual-level and neighborhood-level SDOH were associated with lower odds of post-AKI follow-up among ICU survivors with severe AKI.

Background/Objectives: Later-stage melanoma at diagnosis is associated with increased mortality. Health care access, socioeconomic status, and neighborhood-level factors likely influence stage at presentation. This study aimed to examine whether neighborhood disadvantage, as measured by the Area Deprivation Index (ADI), is associated with later-stage melanoma diagnosis. Methods: We conducted a cross-sectional analysis of a retrospective cohort of 941 patients diagnosed with melanoma at a large academic medical center between 2010 and 2019. Residential addresses were geocoded and linked to ADI and rurality data. Covariates included race, ethnicity, age, gender, and insurance status. Multivariable logistic regression models with robust standard errors clustered at the census tract level were used to assess associations with melanoma stage at diagnosis. Results: Of 941 patients (63% male, 92.8% non-Hispanic White, mean age 64 years), 432 (46%) were diagnosed with late-stage melanoma. Mean ADI was higher among late-stage cases (5.4) compared to early-stage cases (3.3) (p < 0.001), even after adjustment for covariates. Non-Hispanic White race, private insurance, older age, and urban residences were associated with earlier stage at diagnosis. Racial disparities were attenuated after adjusting for ADI, with no significant interaction between race and ADI. Conclusions: Neighborhood disadvantage is significantly associated with later-stage melanoma diagnosis and contributes to observed racial and socioeconomic disparities. These findings highlight the need for targeted educational interventions and health policy initiatives to reduce late-stage melanoma diagnoses in vulnerable populations.

Background: Medication adherence is essential in managing cystic fibrosis (CF). The role of socioeconomic factors for medication adherence in people with CF is poorly understood, and their differential impact across the life course is underexplored. This study investigates associations between measures of socioeconomic status (SES)—educational attainment, household income, and health insurance type—and adherence to CF medications across age groups. Methods: We conducted a cross‐sectional analysis of data collected during the validation of the Daily Care Check‐In, a measure of adherence barriers in people with CF. Adherence was measured as a composite medication possession ratio (cMPR) averaged across five CF‐specific medications, with data collected from pharmacy records. Sociodemographic and clinical data were collected through self‐report and medical record review. Results: A total of 405 participants completed the study, with an overall cMPR of 45.6%, lowest (38.5%) among young adults (aged 18−26 years) and highest (53.0%) among adolescents (aged 13−17 years). Lower household income and lack of college degree were associated with lower cMPR, more interference from adherence barriers, and decreased self‐efficacy, as well as with increased depressive and anxiety symptoms. Similar associations, but less consistent, were observed for public health insurance. When stratified by age, associations between SES measures and adherence were most evident in adolescents, followed by adults, but absent in young adults, bringing into focus challenges with measuring SES in the 18−25 years age group. Conclusion: Lower SES is associated with worse medication adherence, more interference from adherence barriers, and lower self‐efficacy. Associations vary by SES measure and age group, calling for a nuanced approach to adherence interventions in this population.