Pathways between objective and perceived neighborhood factors among Black breast cancer survivors

Background Mounting evidence supports associations between objective neighborhood disorder, perceived neighborhood disorder, and health, yet alternative explanations involving socioeconomic and neighborhood social cohesion have been understudied. We tested pathways between objective and perceived neighborhood disorder, perceived neighborhood social cohesion, and socioeconomic factors within a longitudinal cohort. Methods Demographic and socioeconomic information before diagnosis was obtained at interviews conducted approximately 10 months post-diagnosis from participants in the Women’s Circle of Health Follow-up Study – a cohort of breast cancer survivors self-identifying as African American or Black women (n = 310). Neighborhood perceptions were obtained during follow-up interviews conducted approximately 24 months after diagnosis. Objective neighborhood disorder was from 9 items audited across 23,276 locations using Google Street View and scored to estimate disorder values at each participant’s residential address at diagnosis. Census tract socioeconomic and demographic composition covariates were from the 2010 U.S. Census and American Community Survey. Pathways to perceived neighborhood disorder were built using structural equation modelling. Model fit was assessed from the comparative fit index and root mean square error approximation and associations were reported as standardized coefficients and 95% confidence intervals. Results Higher perceived neighborhood disorder was associated with higher objective neighborhood disorder (β = 0.20, 95% CI: 0.06, 0.33), lower neighborhood social cohesion, and lower individual-level socioeconomic factors (final model root mean square error approximation 0.043 (90% CI: 0.013, 0.068)). Perceived neighborhood social cohesion was associated with individual-level socioeconomic factors and objective neighborhood disorder (β = − 0.11, 95% CI: − 0.24, 0.02). Conclusion Objective neighborhood disorder might be related to perceived disorder directly and indirectly through perceptions of neighborhood social cohesion

Area-Based Socioeconomic Position and Adult Glioma: A Hierarchical Analysis of Surveillance Epidemiology and End Results Data

<div><p>Background</p><p>Glioma rates vary by demographic factors and geo-political boundaries and this variation suggests higher glioma rates in groups of higher socioeconomic position. The primary goal of this analysis is to investigate the relationship between glioma and county socioeconomic position using U.S. Surveillance Epidemiology and End Results (SEER) data.</p> <p>Methods</p><p>Cases were individuals 25+ years diagnosed with glioma between 2000 and 2006 and residing within the SEER-17 catchment area. County-, sex-, race-, age-specific rates were created in order to investigate individual-level associations (population data from U.S. Census 2000). A Bayesian hierarchical Poisson spatial conditionally autoregressive (CAR) model was utilized to simultaneously estimate individual- and county-level associations while controlling for county spatial dependence.</p> <p>Results</p><p>Those residing in counties of the second, third, and fourth highest quartiles of socioeconomic position have glioma incidence rates that are 1.10 (95% CI: 1.02,1.19), 1.11 (95% CI: 1.02,1.20), 1.14 (95% CI: 1.05,1.23) times that of the first quartile, respectively. A CAR model properly controlled for error spatial dependence. Investigated lag times suggest year 2000 census data yields superior model fit.</p> <p>Conclusion</p><p>Demographically adjusted rates of glioma are elevated in counties of higher socioeconomic position. More well-grounded theory concerning the glioma-socioeconomic position association along with socioeconomic data collected at multiple levels is recommended for future studies investigating this relationship.</p> </div

PCA Factor Loadings of Six SEP Measures of 404 SEER-17 Counties, 1990 and 2000.

a<p>Log transformed prior to PCA analysis.</p><p>Bold: Variables loading heavily on respective factors.</p><p>Abbreviations: PCA, Principal component analysis; SEER, Surveillance Epidemiology and End Results; SEP, Socioeconomic position.</p

Socioeconomic Scores (2000 U.S. Census Bureau) for Counties Within the SEER 17 Study Area.

<p>Socioeconomic Scores (2000 U.S. Census Bureau) for Counties Within the SEER 17 Study Area.</p

Histologic breakdown of glioma cases diagnosed within the SEER Program (17 registries), 2000–2006.

a<p>International Classification of Disease – Oncology – Version 3 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060910#pone.0060910-World1" target="_blank">[9]</a>.</p

Bar Chart Summary of Estimated Log Rates by Subdemographic and County Random Intercept Decile^a,b.

<p>^aUnstandardized rates produced from model 2, year 2000 estimates. ^bDeciles (D1–D10) represent the median random intercept values within each decile of random intercepts.</p

Estimated coefficients, 95% credible intervals, model fit statistics, and Moran’s I values for the two basic models estimating glioma risk using 1990 and 2000 census data.

a<p>Individual level covariates with a county random intercept+socioeconomic county covariates in a second level.</p>b<p>Model 1+ conditionally autoregressive prior on random intercepts.</p>c<p>Model intercepts may be interpreted as estimated rates per 100,000 among the young adult, black, female subgroup for a ‘typical’ county (a county with estimated random intercept = 0).</p><p>Abbreviations: CI, Credible Interval; DIC, Deviance Information Criterion; RR, Rate Ratio.</p

Age-adjusted County Glioma Incidence Rates per 100,000 Within the SEER-17 Study Area, 2000–2006.

<p>Age-adjusted County Glioma Incidence Rates per 100,000 Within the SEER-17 Study Area, 2000–2006.</p

Oncotype DX Test Receipt among Latina/Hispanic Women with Early Invasive Breast Cancer in New Jersey: A Registry-Based Study

Oncotype DX® (ODX) is a valid test of breast cancer (BC) recurrence risk and chemotherapy benefit. The purpose of this study was to examine prevalence of and factors associated with receipt of ODX testing among eligible Latinas/Hispanics diagnosed with BC. Sociodemographic and tumor data of BC cases diagnosed between 2008 and 2017 among Latina/Hispanic women (n = 5777) were from the New Jersey State Cancer Registry (NJSCR). Eligibility for ODX testing were based on National Comprehensive Cancer Network guidelines. Multivariable logistic regression models of ODX receipt among eligible women were used to estimate adjusted odds ratios (AOR) and 95% confidence intervals (CI) by demographic and clinicopathologic factors. One-third of Latinas/Hispanics diagnosed with BC were eligible for ODX testing. Among the eligible, 60.9% received ODX testing. Older age (AOR 0.08, 95% CI: 0.04, 0.14), low area-level SES (AOR 0.58, 95% CI: 0.42, 0.52), and being uninsured (AOR 0.58, 95% CI: 0.39, 0.86) were associated with lower odds of ODX testing. While there was relatively high ODX testing among eligible Latina/Hispanic women with BC in New Jersey, our findings suggest that age, insurance status, and area-level SES contribute to unequal access to genetic testing in this group, which might impact BC outcomes

The impact of socioeconomic status on changes in cancer prevention behavior during the COVID-19 pandemic.

BackgroundThe impacts of socioeconomic status (SES) on COVID-19-related changes in cancer prevention behavior have not been thoroughly investigated. We conducted a cohort study to examine the effects of SES on changes in cancer prevention behaviors during the COVID-19 pandemic.MethodsWe invited adult participants from previous studies conducted at Ohio State University to participate in a study assessing the impact of COVID-19 on various behaviors. Post-COVID-19 cancer prevention behaviors, including physical activity, daily intake of fruits and vegetables, alcohol and tobacco consumption, and qualitative changes in post-COVID-19 behaviors relative to pre-COVID levels, were used to construct a prevention behavior change index that captures the adherence status and COVID-related changes in each behavior, with higher index scores indicating desirable changes in prevention behaviors. Participants were classified into low, middle, or high SES based on household income, education, and employment status. Adjusted regression models were used to examine the effects of SES on changes in cancer prevention behaviors during the COVID-19 pandemic.ResultsThe study included 6,136 eligible participants. The average age was 57 years, 67% were women, 89% were non-Hispanic Whites, and 33% lived in non-metro counties. Relative to participants with high SES, those with low SES had a 24% [adjusted relative ratio, aRR = 0.76 (95%CI 0.72-0.80)], 11% [aRR = 0.89 (95%CI 0.86-0.92)], and 5% [aRR = 0.95 (95%CI 0.93-0.96)], lower desirable changes in prevention behaviors for physical activity, fruit and vegetable intake, and tobacco use, respectively. Low SES had a higher desirable change in alcohol consumption prevention behaviors, 16% [aRR = 1.16 (95%CI 1.13-1.19)] relative to high SES. The adjusted odds of an overall poor change in prevention behavior were adjusted odds ratio (aOR) 1.55 (95%CI 1.27 to 1.89) and aOR 1.40 (95%CI 1.19 to 1.66), respectively, higher for those with low and middle SES relative to those with high SES.ConclusionThe adverse impacts of COVID-19 on cancer prevention behaviors were seen most in those with lower SES. Public health efforts are currently needed to promote cancer prevention behaviors, especially amongst lower SES adults