Over the past several years, there has been greater appreciation for the impact of structural and contextual factors on disease outcomes, including cancer (1,2). Given that these structural and contextual factors are distributed inequitably across population groups, there is also increased attention and research focused on understanding how these factors produce and sustain health inequities (3). Place and context is dynamic, however, and the distinct concept of how attributes of place change over time can be meaningful for health.
Areas of persistent poverty, conceptualized as places where large concentrations of residents live in poverty for prolonged periods of time, can be a consequence of racial and/or economic segregation and persistent disinvestment in a particular area. These regions may also reflect a lack of opportunities for residents to rise out of poverty. The US Department of Agriculture operationalizes counties in persistent poverty as those with 20% or more residents classified as living below the federal poverty level over a 4-decade period (ie, based on data for decennial censuses in 1980, 1990, and 2000 and American Community Survey’s 5-year [2007-2011] estimates). In 2007-2011, a total of 395 (13%) counties in the United States were classified as experiencing persistent poverty; more than 80% of these are rural, and nearly 80% are in the South (4). Relative to nonpersistent poverty counties, persistent poverty counties had a higher proportion of residents of minoritized Black race, lower educational level, and/or lower income, although these characteristics were not different between persistent poverty counties and those counties currently in poverty (4).
In this issue of the Journal, Moss et al. (5) examined cancer mortality disparities (using rate differences and rate ratios) between persistent poverty and nonpoverty counties, by race (Black and White) and rurality (rural and urban), for overall cancer mortality and specifically for 7 cancer sites, between 2 time periods, 1990-1992 and 2014-2018, spanning roughly 25 years. Mortality rates were nearly always higher in persistent poverty than in nonpersistent poverty counties. Absolute and relative mortality rate disparities between persistent and nonpersistent poverty counties widened over time for colorectal and breast cancers, but patterns were stable or mixed for other cancer sites. Of particular note, the authors observed the highest cancer mortality rates among Black residents of rural, persistent poverty counties for all cancer sites combined and for colorectal, oropharyngeal, breast, cervical, and prostate cancers. However, patterns in rate differences between persistent and nonpersistent poverty counties by race and rurality differed depending on the cancer site. For example, among Black residents, for most cancer sites studied (prostate, breast, cervical, oropharyngeal, colorectal, and lung and bronchus), persistent poverty counties had higher rates than nonpersistent poverty counties only for rural but not urban regions; an opposite pattern was seen for liver cancer. Yet, different patterns were seen for White residents with regard to mortality rate differences by persistent poverty and rurality, suggesting that the pathways and mechanisms by which contextual factors influence cancer mortality can differ by social determinants of health and their interactions. It’s important to note that persistent poverty is defined based on counties being in poverty over the 4-decade period, and thus, in Moss and colleagues’ paper (5), mortality rates for persistent poverty counties for the earlier time period, 1990-1992, reflect exposure to poverty from the period between 1980 and 1990, a 1-decade period. A follow-up key question is whether we might expect to see a trajectory of increasing disparities the longer a region is in poverty, among these persistent poverty regions.
This work should motivate several areas of research inquiry for future studies. In studies of structural and contextual determinants of health, we need to understand the impact of change, and different trajectories of change, in these contextual attributes. Studies are needed on how best to measure change and how to address geographic boundaries that change over time. Research is also needed to examine contextual effects at more granular area levels that more meaningfully capture how local policies affect resource availability and access. Census tract-level measures of persistent poverty recently became available (https://cancercontrol.cancer.gov/sites/default/files/2021-12/PP%20CT%20data-final.pdf), which hopefully will stimulate further studies to evaluate how cancer patterns differ by persistent poverty at small geographic areas. Descriptive studies are necessary and should continue, however, we also need studies that identify the pathways and mechanisms through which such structural and contextual factors such as persistent poverty impact outcomes (6). Finally, as illustrated by the findings from Moss et al. (5), effects of structural and neighborhood determinants vary across population groups, thus it is imperative to assess differential impacts among intersections of minoritized social identities, given the implications for interventions in achieving social justice and health equity. The National Cancer Institute recently released a notice of intent to publish a request for applications for research in persistent poverty areas, with the goal of advancing research into building sustainable cancer prevention and control solutions for persistent poverty areas, in partnership with local communities, health-care facilities, and community organizations. As persistent poverty arises from structural segregation and sustained disinvestment, to address cancer inequities in these areas will require research and ultimately solutions at the structural level.
Funding
None.
Notes
Role of the funder: Not applicable.
Disclosures: The authors have no disclosures. SLG, who is a JNCI Associate Editor and a co-author on this editorial, was not involved in the editorial review or decision to publish the editorial.
Author contributions: Writing—original draft: IC, SLG, SSM. Writing—revision & editing: IC, SLG, SSM.
Data Availability
No new data was generated or used for this editorial.
Contributor Information
Scarlett Lin Gomez, Greater Bay Area Cancer Registry, University of California, San Francisco, CA, USA; Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA.
Salma Shariff-Marco, Greater Bay Area Cancer Registry, University of California, San Francisco, CA, USA; Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA.
Iona Cheng, Greater Bay Area Cancer Registry, University of California, San Francisco, CA, USA; Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA.
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Data Availability Statement
No new data was generated or used for this editorial.