Association Between Neighborhood Opportunity, Allostatic Load, and All-Cause Mortality in Patients With Breast Cancer.

PURPOSE: Adverse neighborhood contextual factors may affect breast cancer outcomes through environmental, psychosocial, and biological pathways. The objective of this study is to examine the relationship between allostatic load (AL), neighborhood opportunity, and all-cause mortality among patients with breast cancer. METHODS: Women age 18 years and older with newly diagnosed stage I-III breast cancer who received surgical treatment between January 1, 2012, and December 31, 2020, at a National Cancer Institute Comprehensive Cancer Center were identified. Neighborhood opportunity was operationalized using the 2014-2018 Ohio Opportunity Index (OOI), a composite measure derived from neighborhood level transportation, education, employment, health, housing, crime, and environment. Logistic and Cox regression models tested associations between the OOI, AL, and all-cause mortality. RESULTS: The study cohort included 4,089 patients. Residence in neighborhoods with low OOI was associated with high AL (adjusted odds ratio, 1.21 [95% CI, 1.05 to 1.40]). On adjusted analysis, low OOI was associated with greater risk of all-cause mortality (adjusted hazard ratio [aHR], 1.45 [95% CI, 1.11 to 1.89]). Relative to the highest (99th percentile) level of opportunity, risk of all-cause mortality steeply increased up to the 70th percentile, at which point the rate of increase plateaued. There was no interaction between the composite OOI and AL on all-cause mortality (P = .12). However, there was a higher mortality risk among patients with high AL residing in lower-opportunity environments (aHR, 1.96), but not in higher-opportunity environments (aHR, 1.02; P interaction = .02). CONCLUSION: Lower neighborhood opportunity was associated with higher AL and greater risk of all-cause mortality among patients with breast cancer. Additionally, environmental factors and AL interacted to influence all-cause mortality. Future studies should focus on interventions at the neighborhood and individual level to address socioeconomically based disparities in breast cancer.

Neighborhood Disadvantage and Autism Spectrum Disorder in a Population With Health Insurance.

Importance: Family socioeconomic status has been associated with autism spectrum disorder (ASD) diagnoses. Less is known regarding the role of neighborhood disadvantage in the United States, particularly when children have similar access to health insurance. Objective: To evaluate the association between neighborhood disadvantage and the diagnosis of ASD and potential effect modification by maternal and child demographic characteristics. Design, Setting, and Participants: This cohort study examined a retrospective birth cohort from Kaiser Permanente Southern California (KPSC), an integrated health care system. Children born in 2001 to 2014 at KPSC were followed up through KPSC membership records. Electronic medical records were used to obtain an ASD diagnosis up to December 31, 2019, or the last follow-up. Data were analyzed from February 2022 to September 2023. Exposure: Socioeconomic disadvantage at the neighborhood level, an index derived from 7 US census tract characteristics using principal component analysis. Main Outcomes and Measures: Clinical ASD diagnosis based on electronic medical records. Associations between neighborhood disadvantage and ASD diagnosis were determined by hazard ratios (HRs) from Cox regression models adjusted for birth year, child sex, maternal age at delivery, parity, severe prepregnancy health conditions, maternal race and ethnicity, and maternal education. Effect modification by maternal race and ethnicity, maternal education, and child sex was assessed. Results: Among 318 372 mothers with singleton deliveries during the study period, 6357 children had ASD diagnoses during follow-up; their median age at diagnosis was 3.53 years (IQR, 2.57-5.34 years). Neighborhood disadvantage was associated with a higher likelihood of ASD diagnosis (HR, 1.07; 95% CI, 1.02-1.11, per IQR = 2.70 increase). Children of mothers from minoritized racial and ethnic groups (African American or Black, Asian or Pacific Islander, Hispanic or Latinx groups) had increased likelihood of ASD diagnosis compared with children of White mothers. There was an interaction between maternal race and ethnicity and neighborhood disadvantage (difference in log-likelihood = 21.88; P < .001 for interaction under χ24); neighborhood disadvantage was only associated with ASD among children of White mothers (HR, 1.17; 95% CI, 1.09-1.26, per IQR = 2.00 increase). Maternal education and child sex did not significantly modify the neighborhood-ASD association. Conclusions and Relevance: In this study, children residing in more disadvantaged neighborhoods at birth had higher likelihood of ASD diagnosis among a population with health insurance. Future research is warranted to investigate the mechanisms behind the neighborhood-related disparities in ASD diagnosis, alongside efforts to provide resources for early intervention and family support in communities with a higher likelihood of ASD.

Neighborhood socioeconomic disadvantage measures in rehabilitation clinical trials: Lessons learned in recruitment.

PURPOSE: The Area Deprivation Index (ADI) measures the relative disadvantage of an individual or social network using US Census indicators. Although a strong re-hospitalization predictor, ADI has not been routinely incorporated into rehabilitation research. The purposes of this paper are to examine the use of ADI related to study recruitment, association with carepartner psychosocial factors, and recruitment strategies to increase participant diversity. METHODS: Descriptive analysis of baseline data from a pilot stroke carepartner-integrated therapy trial. Participants were 32 carepartners (N = 32; 62.5 % female; mean age 57.8 ± 13.0 years) and stroke survivors (mean age (60.6 ± 14.2) residing in an urban setting. Measures included ADI, Bakas Caregiver Outcome Scale, Caregiver Strain Index, and Family Assessment Device. RESULTS: Most carepartners were Non-Hispanic White participants (61.3 %), part or fully employed (43 %), with >$50,000 (67.7 %) income, and all had some college education. Most stroke survivors were Non-Hispanic White participants (56.3 %) with some college (81.3 %). Median ADI state deciles were 3.0 (interquartile range 1.5-5, range 1-9), and mean national percentiles were 41.7 ± 23.5 with only 6.3 % of participants from the most disadvantaged neighborhoods. For the more disadvantaged half of the state deciles, the majority were Black or Asian participants. No ADI and carepartner factors were statistically related. CONCLUSIONS: The use of ADI data highlighted a recruitment gap in this stroke study, lacking the inclusivity of participants from disadvantaged neighborhoods and with lower education. Using social determinants of health indicators to identify underrepresented neighborhoods may inform recruitment methods to target marginalized populations and broaden the generalizability of clinical trials.

Neighborhood Disadvantage and Breast Cancer-Specific Survival.

Importance: Neighborhood-level disadvantage is an important factor in the creation and persistence of underresourced neighborhoods with an undue burden of disparate breast cancer-specific survival outcomes. Although studies have evaluated neighborhood-level disadvantage and breast cancer-specific survival after accounting for individual-level socioeconomic status (SES) in large national cancer databases, these studies are limited by age, socioeconomic, and racial and ethnic diversity. Objective: To investigate neighborhood SES (using a validated comprehensive composite measure) and breast cancer-specific survival in a majority-minority population. Design, Setting, and Participants: This retrospective multi-institutional cohort study included patients with stage I to IV breast cancer treated at a National Cancer Institute-designated cancer center and sister safety-net hospital from January 10, 2007, to September 9, 2016. Mean (SD) follow-up time was 60.3 (41.4) months. Data analysis was performed from March 2022 to March 2023. Exposures: Neighborhood SES was measured using the Area Deprivation Index (tertiles), a validated comprehensive composite measure of neighborhood SES. Main Outcomes and Measures: The primary outcome was breast cancer-specific survival. Random effects frailty models for breast cancer-specific survival were performed controlling for individual-level sociodemographic, comorbidity, breast cancer risk factor, access to care, tumor, and National Comprehensive Cancer Network guideline-concordant treatment characteristics. The Area Deprivation Index was calculated for each patient at the census block group level and categorized into tertiles (T1-T3). Results: A total of 5027 women with breast cancer were included: 55.8% were Hispanic, 17.5% were non-Hispanic Black, and 27.0% were non-Hispanic White. Mean (SD) age was 55.5 (11.7) years. Women living in the most disadvantaged neighborhoods (T3) had shorter breast cancer-specific survival compared with those living in the most advantaged neighborhoods (T1) after controlling for individual-level sociodemographic, comorbidity, breast cancer risk factor, access to care, tumor, and National Comprehensive Cancer Network guideline-concordant treatment characteristics (T3 vs T1: hazard ratio, 1.29; 95% CI, 1.01-1.65; P < .04). Conclusions and Relevance: In this cohort study, a shorter breast cancer-specific survival in women from disadvantaged neighborhoods compared with advantaged neighborhoods was identified, even after controlling for individual-level sociodemographic, comorbidity, breast cancer risk factor, access to care, tumor, and National Comprehensive Cancer Network guideline-concordant treatment characteristics. The findings suggest potential unaccounted mechanisms, including unmeasured social determinants of health and access to care measures. This study also lays the foundation for future research to evaluate whether social adversity from living in a disadvantaged neighborhood is associated with more aggressive tumor biologic factors, and ultimately shorter breast cancer-specific survival, through social genomic and/or epigenomic alterations.

Neighborhood disadvantage and dementia incidence in a cohort of Asian American and non-Latino White older adults in Northern California.

INTRODUCTION: Some evidence suggests that neighborhood socioeconomic disadvantage is associated with dementia-related outcomes. However, prior research is predominantly among non-Latino Whites. METHODS: We evaluated the association between neighborhood disadvantage (Area Deprivation Index [ADI]) and dementia incidence in Asian American (n = 18,103) and non-Latino White (n = 149,385) members of a Northern California integrated health care delivery system aged 60 to 89 at baseline. Race/ethnicity-specific Cox proportional hazards models adjusted for individual-level age, sex, socioeconomic measures, and block group population density estimated hazard ratios (HRs) for dementia. RESULTS: Among non-Latino Whites, ADI was associated with dementia incidence (most vs. least disadvantaged ADI quintile HR = 1.09, 95% confidence interval [CI] = 1.02-1.15). Among Asian Americans, associations were close to null (e.g., most vs. least disadvantaged ADI quintile HR = 1.01, 95% CI = 0.85-1.21). DISCUSSION: ADI was associated with dementia incidence among non-Latino Whites but not Asian Americans. Understanding the potentially different mechanisms driving dementia incidence in these groups could inform dementia prevention efforts.

Neighborhood disadvantage is associated with KRAS-mutated non-small cell lung cancer risk.

PURPOSE: It remains unclear why individuals living in disadvantaged neighborhoods have shorter non-small cell lung cancer (NSCLC) survival. It is possible that living in these deprived areas is linked with increased risk of developing aggressive NSCLC biology. Here, we explored the association of somatic KRAS mutations, which are associated with shorter survival in NSCLC patients, and 11 definitions of neighborhood disadvantage spanning socioeconomic and structural environmental elements. METHODS: We analyzed data from 429 NSCLC patients treated at a Comprehensive Cancer Center from 2015 to 2018. Data were abstracted from medical records and each patient's home address was used to assign publicly available indices of neighborhood disadvantage. Prevalence Ratios (PRs) for the presence of somatic KRAS mutations were estimated using modified Poisson regression models adjusted for age, sex, smoking status, race/ethnicity, educational attainment, cancer stage, and histology. RESULTS: In the NSCLC cohort, 29% had KRAS mutation-positive tumors. We found that five deprivation indices of socioeconomic disadvantage were associated with KRAS mutation. A one decile increase in several of these socioeconomic disadvantage indices was associated with a 1.06 to 1.14 increased risk of KRAS mutation. Measures of built structural environment were not associated with KRAS mutation status. CONCLUSION: Socioeconomic disadvantage at the neighborhood level is associated with higher risk of KRAS mutation while disadvantage related to built environmental structural measures was inversely associated. Our results indicate not only that neighborhood disadvantage may contribute to aggressive NSCLC biology, but the pathways linking biology to disadvantage are likely operating through socioeconomic-related stress.

Organizational Characteristics Associated with High Performance in Medicare's Comprehensive End-Stage Renal Disease Care Initiative.

BACKGROUND AND OBJECTIVES: Medicare plans to extend financial structures tested through the Comprehensive End-Stage Renal Disease Care (CEC) Initiative-an alternative payment model for maintenance dialysis providers-to promote high-value care for beneficiaries with kidney failure. The End-Stage Renal Disease Seamless Care Organizations (ESCOs) that formed under the CEC Initiative varied greatly in their ability to generate cost savings and improve patient health outcomes. This study examined whether organizational or community characteristics were associated with ESCOs' performance. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We used a retrospective pooled cross-sectional analysis of all 37 ESCOs participating in the CEC Initiative during 2015-2018 (n=87 ESCO-years). Key exposures included ESCO characteristics: number of dialysis facilities, number and types of physicians, and years of CEC Initiative experience. Outcomes of interest included were above versus below median gross financial savings (2.4%) and standardized mortality ratio (0.93). We analyzed unadjusted differences between high- and low-performing ESCOs and then used multivariable logistic regression to construct average marginal effect estimates for parameters of interest. RESULTS: Above-median gross savings were obtained by 23 (52%) ESCOs with no program experience, 14 (32%) organizations with 1 year of experience, and seven (16%) organizations with 2 years of experience. The adjusted likelihoods of achieving above-median gross savings were 23 (95% confidence interval, 8 to 37) and 48 (95% confidence interval, 24 to 68) percentage points higher for ESCOs with 1 or 2 years of program experience, respectively (versus none). The adjusted likelihood of achieving above-median gross savings was 1.7 (95% confidence interval, -3 to -1) percentage points lower with each additional affiliated dialysis facility. Adjusted mortality rates were lower for ESCOs located in areas with higher socioeconomic status. CONCLUSIONS: Smaller ESCOs, organizations with more experience in the CEC Initiative, and those located in more affluent areas performed better under the CEC Initiative.