Residential Mobility and Geospatial Disparities in Colon Cancer Survival

Ethnic enclaves and colon cancer stage at diagnosis among New Jersey Hispanics

Ethnic enclaves are neighborhoods with high concentrations of individuals of the same ethnic origin. Researchers have hypothesized that residence in ethnic enclaves may contribute to cancer outcomes through detrimental or protective pathways. A limitation of previous work, however, is their cross-sectional approach whereby an individual's residence at the time of diagnosis was used to capture residence in an ethnic enclave at a single point in time. This study addresses this limitation by adopting a longitudinal approach to investigating the association between the duration of residence in an ethnic enclave and the colon cancer (CC) stage at diagnosis. Colon cancer incidence cases diagnosed between 2006 and 2014, for Hispanics aged 18 years and older from the New Jersey State Cancer Registry (NJSCR) were linked to residential histories obtained from a commercial database LexisNexis, Inc. We examined associations between residence in an enclave and stage at diagnosis using binary and multinomial logistic regression, adjusted for age, sex, primary payer, and marital status. Among the 1076 Hispanics diagnosed with invasive colon cancer in New Jersey from 2006 to 2014, 48.4% lived in a Hispanic enclave at the time of diagnosis. Over the ten years preceding CC diagnosis, 32.6% lived in an enclave for the entire period. We found that Hispanics living in an ethnic enclave at diagnosis had significantly lower odds of distant-stage CC than Hispanics not living in an enclave at the time of diagnosis. Additionally, we found a significant association between living in an enclave for an extended period (e.g., over ten years) and lower odds of being diagnosed with distant stage CC. Integrating residential histories opens research possibilities to examine how minorities' residential mobility and residence in enclaves affect cancer diagnosis over time.

Colon cancer transcriptome

Over the last four decades, methodological innovations have continuously changed transcriptome profiling. It is now feasible to sequence and quantify the transcriptional outputs of individual cells or thousands of samples using RNA sequencing (RNA-seq). These transcriptomes serve as a connection between cellular behaviors and their underlying molecular mechanisms, such as mutations. This relationship, in the context of cancer, provides a chance to unravel tumor complexity and heterogeneity and uncover novel biomarkers or treatment options. Since colon cancer is one of the most frequent malignancies, its prognosis and diagnosis seem to be critical. The transcriptome technology is developing for an earlier and more accurate diagnosis of cancer which can provide better protectivity and prognostic utility to medical teams and patients. A transcriptome is a whole set of expressed coding and non-coding RNAs in an individual or cell population. The cancer transcriptome includes RNA-based changes. The combined genome and transcriptome of a patient may provide a comprehensive picture of their cancer, and this information is beginning to affect treatment decision-making in real-time. A full assessment of the transcriptome of colon (colorectal) cancer has been assessed in this review paper based on risk factors such as age, obesity, gender, alcohol use, race, and also different stages of cancer, as well as non-coding RNAs like circRNAs, miRNAs, lncRNAs, and siRNAs. Similarly, they have been examined independently in the transcriptome study of colon cancer.

Relative impact of genetic ancestry and neighborhood socioeconomic status on all-cause mortality in self-identified African Americans

Self-identified race/ethnicity is a correlate of both genetic ancestry and socioeconomic factors, both of which may contribute to racial disparities in mortality. Investigators often hold a priori assumptions, rarely made explicit, regarding the relative importance of these factors. We studied 2,239 self-identified African Americans (SIAA) from the Prostate, Lung, Colorectal and Ovarian screening trial enrolled from 1993–1998 and followed prospectively until 2019 or until death, whichever came first. Percent African genetic ancestry was estimated using the GRAF-Pop distance-based method. A neighborhood socioeconomic status (nSES) index was estimated using census tract measures of income, housing, and employment and linked to participant residence in 2012. We used Directed Acyclic Graphs (DAGs) to represent causal models favoring (1) biomedical and (2) social causes of mortality. Hazard ratios were estimated using Cox models adjusted for sociodemographic, behavioral, and neighborhood covariates guided by each DAG. 901 deaths occurred over 40,767 person-years of follow-up. In unadjusted (biomedical) models, a 10% increase in percent African ancestry was associated with a 7% higher rate of all-cause mortality (HR: 1.07, 95% CI: 1.02, 1.12). This effect was attenuated in covariate adjusted (social) models (aHR: 1.01, 95% CI: 0.96, 1.06). Mortality was lower comparing participants in the highest to lowest nSES quintile following adjustment for covariates and ancestry (aHR: 0.74, 95% CI: 0.57, 0.98, Ptrend = 0.017). Higher African ancestry and lower nSES were associated with higher mortality, but African ancestry was not associated with mortality following covariate adjustment. Socioeconomic factors may be more important drivers of mortality in African Americans.

Systematic review of neighborhood socioeconomic indices studied across the cancer control continuum

BACKGROUND

There is extensive interest in understanding how neighborhood socioeconomic status (nSES) may affect cancer incidence or survival. However, variability regarding items included and approaches used to form a composite nSES index presents challenges in summarizing overall associations with cancer. Given recent calls for standardized measures of neighborhood sociodemographic effects in cancer disparity research, the objective of this systematic review was to identify and compare existing nSES indices studied across the cancer continuum (incidence, screening, diagnosis, treatment, survival/mortality) and summarize associations by race/ethnicity and cancer site to inform future cancer disparity studies.

METHODS

Using PRISMA guidelines, peer-reviewed articles published between 2010 and 2019 containing keywords related to nSES and cancer were identified in PubMed.

RESULTS

Twenty-four nSES indices were identified from 75 studies. In general, findings indicated a significant association between nSES and cancer outcomes (n = 64/75 studies; 85.33%), with 42/64 (65.63%) adjusting for highly-correlated individual SES factors (e.g., education). However, the direction of association differed by cancer site, race/ethnicity, and nSES index.

CONCLUSIONS

This review highlights several methodologic and conceptual issues surrounding nSES measurement and potential associations with cancer disparities. Recommendations pertaining to the selection of nSES measures are provided, which may help inform disparity-related disease processes and improve the identification of vulnerable populations in need of intervention.

Examining socio-spatial mobility patterns among colon cancer patients after diagnosis

Given the growing number of cancer survivors, it is important to better understand socio-spatial mobility patterns of cancer patients after diagnosis that could have public health implications regarding post-diagnostic access to care for treatment and follow-up surveillance. In this exploratory study, residential histories from LexisNexis were linked to New Jersey colon cancer cases diagnosed from 2006 to 2011 to examine differences in socio-spatial mobility patterns after diagnosis by stage at cancer diagnosis, sex, and race/ethnicity. For the colon cancer cases, we summarized and compared the number of residences and changes in the residential census tract and neighborhood poverty after the diagnosis. We found only minor changes in neighborhood poverty among the cases during the follow-up period after diagnosis. During the follow-up period of up to 10 years after diagnosis, 67% of the patients did not move to a different residential census tract, and 10.8% moved from New Jersey to another state. Cases that moved to a different census tract changed after diagnosis were generally less wealthy than non-movers, but the destination of relocation varied by race/ethnicity and socioeconomic status. We also found a significant association between residential mobility and stage at diagnosis, whereby patients diagnosed with colon cancer at an early stage were more likely to be movers. This study contributes to understanding of the socio-spatial mobility patterns in colon cancer patients and may help to inform cancer research by summarizing the extent to which colon cancer patients move after diagnosis.

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Post-diagnosis socio-spatial mobility is relatively low among colon cancer patients.

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Post-diagnosis, ∼67% of all colon cancer patients in NJ did not change residence.

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Movers spent more time living in high-poverty neighborhoods than non-movers.

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Approximately 10% of all patients left New Jersey for other states.

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Geographic destinations vary by race/ethnicity and socioeconomic status.

Measuring Neighborhood Landscapes: Associations between a Neighborhood's Landscape Characteristics and Colon Cancer Survival

Landscape characteristics have been shown to influence health outcomes, but few studies have examined their relationship with cancer survival. We used data from the National Land Cover Database to examine associations between regional-stage colon cancer survival and 27 different landscape metrics. The study population included all adult New Jersey residents diagnosed between 2006 and 2011. Cases were followed until 31 December 2016 (N = 3949). Patient data were derived from the New Jersey State Cancer Registry and were linked to LexisNexis to obtain residential histories. Cox proportional hazard regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI95) for the different landscape metrics. An increasing proportion of high-intensity developed lands with 80–100% impervious surfaces per cell/pixel was significantly associated with the risk of colon cancer death (HR = 1.006; CI95 = 1.002–1.01) after controlling for neighborhood poverty and other individual-level factors. In contrast, an increase in the aggregation and connectivity of vegetation-dominated low-intensity developed lands with 20–<40% impervious surfaces per cell/pixel was significantly associated with the decrease in risk of death from colon cancer (HR = 0.996; CI95 = 0.992–0.999). Reducing impervious surfaces in residential areas may increase the aesthetic value and provide conditions more advantageous to a healthy lifestyle, such as walking. Further research is needed to understand how these landscape characteristics impact survival.

A Renewed Focus on Health Disparities in the Year 2020: Reexamining Geospatial Disparities

To achieve the ultimate goal of health equity for all people in the United States, new methods are necessary to further understand health disparities in cancer. Geospatial approaches to examine outcomes in cancer control and population sciences in the United States is an area of growing interest, but traditional methods are hindered by the use of a single location at the time of diagnosis. Incorporating residential histories into geospatial analyses overcomes this challenge and is a step forward in improving our understanding of geospatial disparities in cancer outcomes.See related article by Wiese et al., p. 2119.