Background: Despite consistent improvements in cancer prevention and care, rural and urban disparities in cancer incidence persist in the United States. Our objective was to further examine rural–urban differences in cancer incidence and trends. Methods: We used the North American Association of Central Cancer Registries dataset to investigate rural–urban differences in 5-year age-adjusted cancer incidence (2015–2019) and trends (2000–2019), also examining differences by region, sex, race/ethnicity, and tumor site. Age-adjusted rates were calculated using SEER∗Stat 8.4.1, and trend analysis was done using Joinpoint, reporting annual percent changes (APC). Results: We observed higher all cancer combined 5-year incidence rates in rural areas (457.6 per 100,000) compared with urban areas (447.9), with the largest rural–urban difference in the South (464.4 vs. 449.3). Rural populations also exhibited higher rates of tobacco-associated, human papillomavirus–associated, and colorectal cancers, including early-onset cancers. Tobacco-associated cancer incidence trends widened between rural and urban from 2000 to 2019, with significant, but varying, decreases in urban areas throughout the study period, whereas significant rural decreases only occurred between 2016 and 2019 (APC = −0.96). Human papillomavirus–associated cancer rates increased in both populations until recently with urban rates plateauing whereas rural rates continued to increase (e.g., APC = 1.56, 2002–2019). Conclusions: Rural populations had higher overall cancer incidence rates and higher rates of cancers with preventive opportunities compared with urban populations. Improvements in these rates were typically slower in rural populations. Impact: Our findings underscore the complex nature of rural–urban disparities, emphasizing the need for targeted interventions and policies to reduce disparities and achieve equitable health outcomes.

PURPOSE: Medicaid expansion was designed to increase access to health care. Evidence is mixed, but theory and empirical data suggest that lower cost of care through greater access to insurance increases health care utilization and possibly improves the health of poor and sick populations. However, this major health policy has yet to be thoroughly investigated for its effect on health disparities. The current study is motivated by one of today’s most stark inequalities: the disparity in breast cancer mortality rates between Black and White women. METHODS: This analysis used a difference-in-difference fixed effects regression model to evaluate the impact of Medicaid expansion on the disparity between Black and White breast cancer mortality rates. State-level breast cancer mortality data were obtained from the Centers for Disease Control and Prevention. Each state’s Medicaid expansion status was provided by a Kaiser Family Foundation white paper. Two tests were conducted, one compared all expanding states with all nonexpanding states, and the second compared all expanding states with nonexpanding states that voted to expand—but did not by 2014. The difference-in-difference regression models considered the year 2014 a washout period and compared 2012 and 2013 (pretreatment) with 2015 and 2016 (posttreatment). RESULTS: Medicaid expansion did not lower the disparity in breast cancer mortality. In contrast to expectations, the Black/White mortality ratio increased in states expanding Medicaid for all Medicaid-eligible age groups, with significant effects in younger age groups ( P = .01 to .15). CONCLUSION: These results suggest that states cannot solely rely on access to insurance to alleviate disparities in cancer or other chronic conditions. More exploration of the impacts of low-quality health systems is warranted.

We examine the Affordable Care Act Medicaid expansion effects on self-rated health status over 5 years. The study uses data from the Behavioral Risk Factor Surveillance System for 2011-2018 and a difference-in-differences design. There is improvement in health status on a 1 to 5 point scale from poor to excellent health among individuals below 100% of the federal poverty line by 0.031, 0.068, 0.031, 0.064, and 0.087 points in 2014, 2015, 2016, 2017, and 2018, respectively. Changes in 2015, 2017, and 2018 are statistically significant (p < .05), and the 2014 change is marginally significant. The difference between 2014 and 2018 effects is statistically significant (p < .05). In most years, we cannot distinguish changes in days not in good physical or mental health from no effect. Overall, there is only minimal evidence for effects intensifying over time, suggesting that health gains thus far have mostly occurred early on due to unmet needs among those previously uninsured.

Medicaid expansion narrowed racial and ethnic disparities in health coverage, but few studies have explored differential impact by exposure to structural racism. We analyzed data on historical residential redlining in US metropolitan areas from the Mapping Inequality project, along with data on uninsurance from the American Community Survey, to test whether Medicaid expansion differentially reduced uninsurance rates among nonelderly adults exposed to historical redlining. Our difference-in-differences analysis compared uninsurance rates in Medicaid expansion and nonexpansion states both before (2009-13) and after (2015-19) the state option to expand Medicaid pursuant to the Affordable Care Act took effect in 2014. We found that Medicaid expansion had the greatest impact on lowering uninsurance rates in census tracts with the highest level of redlining. Within each redline category, there were no significant differences by race and ethnicity. Our results highlight the importance of considering contextual factors, such as structural racism, when evaluating health policies. States that opt not to expand Medicaid delay progress toward health equity in historically redlined communities.