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

Abstract

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.

The Intersectionality between Race, Ethnicity, and Residential-Level Socioeconomic Status in Disparities of Head and Neck Cancer Outcomes: A SEER Study

“…Prior research by Reitzel and colleagues showed an increased risk of mortality among oropharyngeal cancer patients living in the most deprived neighborhoods ( 17 ). Patients living in lower SES neighborhoods lack adequate healthcare facilities, may have less access to cancer screening, have insufficient knowledge of the signs and symptoms of cancer, and have higher levels of stress leading to poorer cancer outcomes ( 43–45 ). Notably, our analysis examining cumulative incidence curves demonstrated a consistent pattern of disparities and a higher risk of HNC-specific mortality in Black patients, followed by Hispanic and Asian/PI patients who had survived for one year or more following diagnosis.…”

Neighborhood Disadvantage and Breast Cancer–Specific Survival

“…Studies have found associations between neighborhood-level measures, such as socioeconomic status (SES), with disparities in breast cancer survival . However, many measures of neighborhood SES previously used do not encapsulate the various domains and complexities that contribute to neighborhood disadvantage . Previous analyses also have methodologic limitations associated with confounding between neighborhood and individual-level factors or their design independently assesses only these measures of disadvantage rather than their joint outcome .…”

“… 14 , 15 However, many measures of neighborhood SES previously used do not encapsulate the various domains and complexities that contribute to neighborhood disadvantage. 16 Previous analyses also have methodologic limitations associated with confounding between neighborhood and individual-level factors or their design independently assesses only these measures of disadvantage rather than their joint outcome. 15 , 17 Moreover, these studies predominantly use national cancer databases that have limited data on key variables, such as age (eg, only include individuals aged ≥65 years), SES (eg, do not include uninsured, Medicare-ineligible populations), and racial and ethnic diversity (eg, only 5% of patients are Hispanic) along with an inability to capture National Comprehensive Cancer Network (NCCN) guideline-concordant treatment.…”

Understanding Health Equity in Public Health Practice in the United States

“…For example, one state developed a statewide “scorecard” for tracking social determinants of health at the zip code level. Outside the health department, traditional public health surveillance systems (eg, disease registries, ongoing surveys of behavioral risk factors, hospital discharge data) can be supplemented with a variety of indices of social deprivation (eg, area deprivation index, social deprivation index) 24. Forging information partnerships that leverage the data on social determinants of health from the clinical setting in a standardized fashion provides an opportunity for public health to use these data upstream to support health equity goals 25.…”