Geographic disparities in breast cancer mortality: how where you live could matter

By Dr. Liji Thomas, MDReviewed by Danielle Ellis, B.Sc.Sep 14 2023

Most women who die of cancer in the USA have breast cancer. There are biological risk factors, including specific mutations that increase the risk of this condition, and lifestyle and behavioral risk factors. This has shaped interventions for the early diagnosis and prevention of breast cancer.

However, such studies assume that the response and the variable are linked the same way, irrespective of geographic locality, leaving disparities in breast cancer death rates across locations unexplained.

A new paper recently published in JAMA Network Open explores the differential mortality rates across various US counties regarding their geographic location associated with multiple sociodemographic factors.

Introduction

The factors affecting breast cancer mortality may show different effects depending on locally acting factors, such as specific but geographically circumscribed interventions that improve local healthcare access or make it easier to live healthier lifestyles. Such effects are better studied using multiscale geographically weighted regression (MGWR) approaches that include both location and scale as determinants in the analysis.

The current study used data from the Surveillance, Epidemiology, and End Results (SEER) database that includes women with breast cancer. A cross-section of such data was available for adjusted mortality analysis, covering 2015-2019 across 2176 US counties.

The researchers examined demographics, environment, pollution, lifestyle, and healthcare access factors as potential modifiers of breast cancer mortality across counties. They aimed to challenge the current hypothesis that mortality determinants act similarly, irrespective of geographic location.

“The goal of this study is to enable location-specific interventions that can be addressed at various levels of public health.”

What did the study show?

High age-adjusted breast cancer mortality was found in a stretch extending from Virginia to South Carolina and from Kansas to Oklahoma, including Arkansas, Louisiana, Mississippi, Alabama, and Georgia. Low mortality rates were found across California, Arizona, many Northeast counties, and some Midwestern counties. Certain hotspots, like Buffalo county in New York State, and low outliers, like Madison County in Tennessee, were also identified.

The study showed that obesity significantly affected breast cancer mortality across all locations. Conversely, mammogram screening uptake among adults was inversely proportional to mortality from breast cancer regardless of location.

On the other hand, multiple other factors were found to exert varying levels of impact on breast cancer mortality in different counties. Smoking, food environment index (FEI – representing both physical access to healthy food and its affordability for the individual), exercise, and racial segregation were negatively associated with breast cancer deaths.

So were mental healthcare availability and primary healthcare availability. Healthcare availability was assessed in terms of the physician ratio in that field. However, light pollution in terms of the mean radiance was shown to be a risk factor for higher breast cancer mortality.

While all these factors were negatively related to breast cancer mortality, the effect size varied with location, as did the level of significance of each. Smoking and mental health care access, for instance, was significantly associated with fewer breast cancer deaths in about a seventh of US counties each, but the FEI showed a significant correlation with lower mortality in 80%.

The FEI effect was especially prominent in places that have been identified as having a high incidence among the non-Hispanic Black female population.

Light pollution and primary healthcare were associated with fewer deaths from breast cancer in about 40% of counties each.

The magnitude of these effects was different between counties. Interestingly, disability significantly increased the risk of breast cancer deaths in almost half the locations, but it was not an overall risk factor if the geographic location was disregarded in the analysis.  

The FEI was associated with more breast cancer deaths in southern and eastern US counties but not western US counties. The largest effects were seen in some southern and eastern states.

Similarly, exercise opportunities were significantly linked to breast cancer deaths in the central US and Florida but not the rest of the country. These areas have a high proportion of Indigenous Native American and Latino communities. Finally, deaths were not higher in the uninsured population of women in any county but were associated with a greater proportion of uninsured women overall.

Significant variation between counties in terms of breast cancer deaths was seen in northern Alabama but much less in the southern part of the state, providing a clear example of the association of geographic location with different outcomes even when the same health program was being applied.

What are the implications?

“The MGWR model demonstrated that factors known to be associated with breast cancer have heterogenous effects across geographic regions.”

This pioneering study shows the need for public health to be aware of geographically active determinants of breast cancer mortality before launching new interventions since all social factors that influence this outcome are not similar in their effect across geographic locations. For instance, geographically targeted programs to improve food access and change eating habits in high-risk areas identified by the FEI-mortality association could reduce the disparity in risk in these regions.  

Culturally appropriate programs to encourage exercise among women of non-White backgrounds in high-risk regions could also reduce breast cancer mortality rate. “This approach may have an unparalleled ability to identify vulnerable populations and geographic areas where targeted interventions may lead to healthier communities.”