Volume 74, Issue 2 p. 136-166
ARTICLE
Open Access

American Cancer Society’s report on the status of cancer disparities in the United States, 2023

Farhad Islami MD, PhD

Corresponding Author

Farhad Islami MD, PhD

American Cancer Society, Atlanta, Georgia, USA

Correspondence

Farhad Islami, Cancer Disparity Research, American Cancer Society, 270 Peachtree Street NW, Suite 1300, Atlanta, GA 30303, USA.

Email: [email protected]

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Jordan Baeker Bispo PhD

Jordan Baeker Bispo PhD

American Cancer Society, Atlanta, Georgia, USA

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Hyunjung Lee PhD, MS, MPP, MBA

Hyunjung Lee PhD, MS, MPP, MBA

American Cancer Society, Atlanta, Georgia, USA

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Daniel Wiese PhD

Daniel Wiese PhD

American Cancer Society, Atlanta, Georgia, USA

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K. Robin Yabroff PhD

K. Robin Yabroff PhD

American Cancer Society, Atlanta, Georgia, USA

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Priti Bandi PhD

Priti Bandi PhD

American Cancer Society, Atlanta, Georgia, USA

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Kirsten Sloan BA

Kirsten Sloan BA

American Cancer Society, Atlanta, Georgia, USA

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Alpa V. Patel PhD

Alpa V. Patel PhD

American Cancer Society, Atlanta, Georgia, USA

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Elvan C. Daniels MD, MPH

Elvan C. Daniels MD, MPH

American Cancer Society, Atlanta, Georgia, USA

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Arif H. Kamal MD, MBA, MHS

Arif H. Kamal MD, MBA, MHS

American Cancer Society, Atlanta, Georgia, USA

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Carmen E. Guerra MD, MSCE

Carmen E. Guerra MD, MSCE

Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

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William L. Dahut MD

William L. Dahut MD

American Cancer Society, Atlanta, Georgia, USA

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Ahmedin Jemal DVM, PhD

Ahmedin Jemal DVM, PhD

American Cancer Society, Atlanta, Georgia, USA

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First published: 14 November 2023
Citations: 3

Abstract

In 2021, the American Cancer Society published its first biennial report on the status of cancer disparities in the United States. In this second report, the authors provide updated data on racial, ethnic, socioeconomic (educational attainment as a marker), and geographic (metropolitan status) disparities in cancer occurrence and outcomes and contributing factors to these disparities in the country. The authors also review programs that have reduced cancer disparities and provide policy recommendations to further mitigate these inequalities. There are substantial variations in risk factors, stage at diagnosis, receipt of care, survival, and mortality for many cancers by race/ethnicity, educational attainment, and metropolitan status. During 2016 through 2020, Black and American Indian/Alaska Native people continued to bear a disproportionately higher burden of cancer deaths, both overall and from major cancers. By educational attainment, overall cancer mortality rates were about 1.6–2.8 times higher in individuals with ≤12 years of education than in those with ≥16 years of education among Black and White men and women. These disparities by educational attainment within each race were considerably larger than the Black–White disparities in overall cancer mortality within each educational attainment, ranging from 1.03 to 1.5 times higher among Black people, suggesting a major role for socioeconomic status disparities in racial disparities in cancer mortality given the disproportionally larger representation of Black people in lower socioeconomic status groups. Of note, the largest Black–White disparities in overall cancer mortality were among those who had ≥16 years of education. By area of residence, mortality from all cancer and from leading causes of cancer death were substantially higher in nonmetropolitan areas than in large metropolitan areas. For colorectal cancer, for example, mortality rates in nonmetropolitan areas versus large metropolitan areas were 23% higher among males and 21% higher among females. By age group, the racial and geographic disparities in cancer mortality were greater among individuals younger than 65 years than among those aged 65 years and older. Many of the observed racial, socioeconomic, and geographic disparities in cancer mortality align with disparities in exposure to risk factors and access to cancer prevention, early detection, and treatment, which are largely rooted in fundamental inequities in social determinants of health. Equitable policies at all levels of government, broad interdisciplinary engagement to address these inequities, and equitable implementation of evidence-based interventions, such as increasing health insurance coverage, are needed to reduce cancer disparities.

INTRODUCTION

The American Cancer Society (ACS) first reported on cancer disparities by race and income in the United States in 1986,1, 2 followed by numerous publications in the following years (a few examples are included as references3-8). The American Cancer Society’s Report on the Status of Cancer Disparities in the United States, started in 2021, is a biennial publication to examine disparities in cancer occurrence and outcomes and contributing factors to these disparities in the United States by race/ethnicity, socioeconomic status (SES), and geographic location. This report also provides information on a variety of programs and resources targeting cancer disparities and policy recommendations.

MATERIALS AND METHODS

Data sources

Cancer occurrence

Data on cancer incidence were obtained from the Centers for Disease Control and Prevention’s (CDC’s) National Program of Cancer Registries and the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program,9 and data on cancer mortality were obtained from the CDC’s National Center for Health Statistics.10 Data included incident cancer cases diagnosed and cancer deaths that occurred from 2016 through 2020 for all cancers combined and for leading causes of cancer death in each sex (cancers of the lung and bronchus [lung], female breast [breast], prostate, colorectum, and pancreas, all of which, except pancreatic cancer, are screenable cancers) and cervical cancer (the other screenable cancer), stratified by sex, age group, race/ethnicity, and urbanicity of the county of residence.

We used two age groups, younger than 65 years and 65 years and older, because Americans become age-eligible for Medicare coverage at age 65 years, and previous studies have shown greater cancer disparities in ages younger than 65 years compared with older ages.11 Race/ethnicity categories included non-Hispanic White (White), non-Hispanic Black (Black), non-Hispanic American Indian and Alaska Native (AIAN), non-Hispanic Asian and Pacific Islander (API), and Hispanic-Latinx (Hispanic) populations. Urbanicity was defined based on the 2013 Rural–Urban Continuum Codes12 but using three consolidated categories: county of residence in a large metropolitan area (with a population ≥1 million), a small-to-medium metropolitan area (with a population <1 million), and a nonmetropolitan area. Data on cancer stage at diagnosis (2016–2020)13 and survival (cancer in patients aged 99 years and older diagnosed in 2014–2020)14 were obtained from the SEER 22 cancer registries (survival data excluding Illinois and Massachusetts), stratified by sex, age group, race/ethnicity, and urbanicity of the county of residence. Cancer incidence, stage at diagnosis, and survival data for AIAN people were further confined to individuals residing in Purchased/Referred Care Delivery Area (PRCDA) counties, covering approximately two thirds of the AIAN population, to minimize racial misclassification.8, 15 Mortality rates for the AIAN population (for the entire United States) were adjusted for racial misclassification on death certificates using classification ratios previously published by the National Center for Health Statistics.16

Socioeconomic status and social determinants of health

Data on limited educational attainment (high school diploma or less), income below the federal poverty level (FPL), delay or nonreceipt of medical care because of cost, measures of housing insecurity (not owning a house) and food insecurity (family could not afford to eat balanced meals), and health insurance coverage were obtained from self-reported measures in the 2021 National Health Interview Survey (NHIS).17 Categories of health insurance coverage for individuals younger than 65 years were uninsured, Medicaid or other public only, and private; in those aged 65 years and older, categories of health insurance coverage were Medicare (including Medicare Advantage) only, Medicare plus public (Medicare dually eligible) only, and Medicare plus private (Medicare supplemental). More information on insurance categories is available in the Supporting Methods.

Cancer risk factors and screening

Some surveys do not collect data on the same items every survey cycle. Data on the prevalence of ever and current cigarette smoking (2021), obesity (2021), heavy alcohol drinking (2020), and physical inactivity (2020) by sex, age group, and urbanicity of the county of residence in individuals aged 18 years and older were obtained from self-reported measures in the NHIS.17 Ever cigarette smoking was defined as smoking at least 100 cigarettes in a lifetime. Current cigarette smoking was defined as smoking at least 100 cigarettes in a lifetime and currently smoking every day or some days. Obesity was defined as a body mass index (BMI) ≥30 kg/m2. Heavy alcohol drinking was defined as greater than 14 drinks per week in the past year for men or greater than seven drinks per week in the past year for women. Physical inactivity was defined as no aerobic leisure-time physical activity. Data on being up to date with the utilization of screening according to the ACS guidelines and US Preventive Services Task Force recommendations for cancers of the female breast, colorectum, cervix, and prostate by age group and urbanicity of the county of residence were based on data from the 2021 NHIS.17 Data on cancer risk factors and screening by race/ethnicity were obtained from a recent ACS report,18 except for data on obesity, which were obtained from a CDC report based on National Health and Nutrition Examination Survey data from 2017 to March 2020.19 We relied on a previous report and method to estimate lung cancer screening rates nationally and by state in 2020 because the NHIS has not collected detailed smoking history or lung cancer screening data since 2015.20

Statistical methods

Age-standardized incidence and mortality rates per 100,000 population and 5-year relative survival were calculated using SEER*Stat software, version 8.4.1 (National Cancer Institute). Incidence and mortality rate ratios (RRs) and their 95% confidence intervals (CIs) were calculated using SEER*Stat software and Stata, version 15.1 (StataCorp), based on age-adjusted rates and Tiwari and colleagues’ method.21 For reasons of confidentiality and to produce more stable results, rates were suppressed when there were <16 cancer cases or deaths in each group.22 Weighted prevalence estimates for measures of SES, risk factors, and cancer screening by corresponding stratifications were calculated using Stata and SAS-callable SUDAAN, release 11.0.4 (SAS Institute, Inc.), and accounted for the complex survey designs. To obtain stable results, prevalence estimates were suppressed when a sample size was <50 or residual standard error was ≥0.3.18

DISPARITIES IN CANCER OCCURRENCE

Cancer incidence

During 2016 through 2020, incidence rates for all cancer and for the evaluated cancer types were higher among Black people than White people, except for all cancers combined, lung cancer, and breast cancer among females (Table 1). Compared with White people, incidence rates of colorectal and cervical cancer were also higher among AIAN people. API and Hispanic people had lower incidence rates compared with their White counterparts, except that Hispanic females had a higher cervical cancer rate. By age group, disparities in cancer incidence rates by race/ethnicity were generally larger in the group younger than 65 years than in the older age group, with a notable exception of cervical cancer in Black females, among whom the disparity was greater in those aged 65 years and older (see Table S1).

TABLE 1. Age-standardized incidence and mortality rates for select cancers by sex and race/ethnicity, and corresponding rate ratios for disparities by race/ethnicity: United States, 2016–2020.
Cancer site by sex NH White NH Black NH AIAN NH API Hispanic-Latinx
Ratea Rate Rate ratio Rate Rate ratio (95% CI) Rate Rate ratio (95% CI) Rate Rate ratio (95% CI)
Incidence
All cancers 494.2 476.6 0.96 (0.96–0.97) 416.8 0.90 (0.89–0.91) 310.0 0.63 (0.63–0.63) 362.8 0.73 (0.73–0.74)
Males 531.9 553.3 1.04 (1.04–1.04) 431.5 0.87 (0.86–0.88) 307.5 0.58 (0.57–0.58) 382.9 0.72 (0.72–0.72)
Females 468.7 425.1 0.91 (0.90–0.91) 409.4 0.93 (0.92–0.95) 316.4 0.68 (0.67–0.68) 355.3 0.76 (0.76–0.76)
Lung and bronchus 63.1 59.8 0.95 (0.94–0.95) 57.4 0.98 (0.95–1.00) 35.4 0.56 (0.55–0.57) 29.7 0.47 (0.47–0.47)
Males 69.6 76.4 1.10 (1.09–1.11) 62.1 0.96 (0.92–1.00) 43.1 0.62 (0.61–0.63) 36.1 0.52 (0.51–0.53)
Females 58.1 48.4 0.83 (0.83–0.84) 53.9 1.00 (0.96–1.03) 29.6 0.51 (0.50–0.52) 25.1 0.43 (0.43–0.44)
Breast, female 142.9 136.1 0.95 (0.95–0.96) 106.8 0.80 (0.78–0.82) 108.6 0.76 (0.75–0.77) 102.6 0.72 (0.71–0.72)
Prostate 112.3 188.2 1.68 (1.67–1.69) 78.2 0.75 (0.72–0.77) 61.2 0.55 (0.54–0.55) 89.7 0.80 (0.79–0.81)
Colorectum 39.6 44.4 1.12 (1.11–1.13) 42.4 1.15 (1.11–1.19) 30.5 0.77 (0.76–0.78) 34.3 0.87 (0.86–0.88)
Males 44.9 52.6 1.17 (1.16–1.18) 47.9 1.15 (1.10–1.20) 36.1 0.81 (0.79–0.82) 40.4 0.90 (0.89–0.91)
Females 34.8 38.5 1.10 (1.09–1.12) 37.8 1.17 (1.12–1.22) 25.9 0.74 (0.73–0.76) 29.4 0.84 (0.83–0.85)
Pancreas 14.2 17.3 1.21 (1.20–1.23) 12.8 0.97 (0.91–1.02) 10.3 0.72 (0.71–0.74) 12.6 0.89 (0.87–0.90)
Males 16.4 19.0 1.16 (1.14–1.18) 14.1 0.92 (0.85–1.00) 11.2 0.68 (0.66–0.70) 13.5 0.82 (0.80–0.84)
Females 12.3 15.9 1.29 (1.27–1.32) 11.6 1.01 (0.93–1.10) 9.5 0.78 (0.76–0.80) 11.8 0.97 (0.95–0.99)
Uterine cervix 7.7 9.1 1.18 (1.16–1.21) 10.0 1.40 (1.27–1.53) 6.4 0.83 (0.80–0.86) 10.0 1.30 (1.27–1.33)
Mortality
All cancers 154.4 174.7 1.13 (1.13–1.14) 179.3 1.16 (1.15–1.18) 94.5 0.61 (0.61–0.62) 108.2 0.70 (0.70–0.70)
Males 182.5 216.0 1.18 (1.18–1.19) 216.5 1.19 (1.16–1.21) 110.4 0.60 (0.60–0.61) 129.6 0.71 (0.71–0.72)
Females 133.0 149.2 1.12 (1.12–1.13) 153.7 1.16 (1.13–1.18) 82.9 0.62 (0.62–0.63) 93.2 0.70 (0.70–0.71)
Lung and bronchus 38.0 37.2 0.98 (0.97–0.99) 42.3 1.11 (1.08–1.14) 19.8 0.52 (0.51–0.53) 15.4 0.41 (0.40–0.41)
Males 44.7 51.0 1.14 (1.13–1.15) 51.0 1.14 (1.10–1.19) 25.6 0.57 (0.56–0.58) 20.9 0.47 (0.46–0.48)
Females 32.8 27.8 0.85 (0.84–0.86) 36.0 1.10 (1.05–1.14) 15.4 0.47 (0.46–0.48) 11.4 0.35 (0.34–0.35)
Breast, female 19.7 27.6 1.40 (1.39–1.42) 20.5 1.04 (0.99–1.10) 11.7 0.59 (0.58–0.61) 13.7 0.69 (0.68–0.71)
Prostate 17.8 37.5 2.11 (2.08–2.14) 21.9 1.23 (1.15–1.31) 8.6 0.48 (0.47–0.50) 15.3 0.86 (0.84–0.88)
Colorectum 13.1 17.6 1.34 (1.33–1.36) 18.6 1.42 (1.36–1.48) 9.1 0.70 (0.68–0.71) 10.7 0.82 (0.81–0.83)
Males 15.5 22.3 1.44 (1.42–1.47) 22.6 1.46 (1.38–1.55) 10.9 0.71 (0.69–0.73) 13.5 0.88 (0.86–0.89)
Females 11.1 14.3 1.29 (1.27–1.31) 15.6 1.41 (1.32–1.50) 7.7 0.70 (0.68–0.72) 8.5 0.77 (0.75–0.78)
Pancreas 11.2 13.6 1.21 (1.19–1.23) 11.8 1.05 (1.00–1.11) 7.5 0.67 (0.66–0.69) 8.8 0.78 (0.77–0.79)
Males 13.1 15.3 1.17 (1.15–1.19) 13.5 1.03 (0.96–1.11) 8.2 0.63 (0.61–0.65) 9.6 0.73 (0.72–0.75)
Females 9.6 12.3 1.27 (1.25–1.30) 10.6 1.10 (1.02–1.19) 7.0 0.72 (0.70–0.75) 8.0 0.83 (0.81–0.85)
Uterine cervix 2.0 3.3 1.63 (1.57–1.70) 3.2 1.56 (1.36–1.79) 1.6 0.81 (0.76–0.87) 2.5 1.23 (1.18–1.28)
  • Note: Rates are per 100,000 population and age adjusted to the 2000 US standard population. Incidence rates for the AIAN population are based on Purchased/Referred Care Delivery Area (PRCDA) counties. Mortality rates for the AIAN population (for the entire United States) are adjusted for racial misclassification on death certificates using classification factors from the National Center for Health Statistics. Hispanic and non-Hispanic incidence data were suppressed for North Dakota.
  • Abbreviations: AIAN, American Indian and Alaska Native; API, Asian and Pacific Islander; CI, confidence interval; NH, non-Hispanic.
  • a The White population is the reference group for rate ratios.
  • Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results (incidence) and National Center for Health Statistics (mortality) data.

By area of residence, overall cancer incidence rates during 2016 through 2020 were higher in counties in nonmetropolitan areas than in counties in large metropolitan areas with a population ≥1 million, by 8% among males and by 5% among females (Table 2). The difference was greater for cancer types that are largely attributable to potentially modifiable risk factors,23 with about 40% higher rates of lung cancer, 30% higher rates of cervical cancer, and about 20% higher rates of colorectal cancer in nonmetropolitan areas. In contrast, incidence rates of breast and prostate cancer were lower in nonmetropolitan than large metropolitan areas, whereas incidence rates of pancreatic cancer in these areas were similar. Generally, these differences were larger in ages younger than 65 years than ages 65 years and older (Figure 1, Table S2). Cancer incidence rates in small-to-medium metropolitan areas with a population <1 million were generally higher than the rates in large metropolitan areas and lower than the rates in nonmetropolitan areas (Table 2).

TABLE 2. Age-standardized incidence and mortality rates for select cancers by sex and urbanicity of county of residence, and corresponding rate ratios for disparities by urbanicity: United States, 2016–2020.
Cancer site by sex Metropolitan, ≥1 million population Metropolitan, <1 million population Non-metropolitan
Ratea Rate Rate ratio (95% CI) Rate Rate ratio (95% CI)
Incidence
All cancers 431.7 446.9 1.04 (1.03–1.04) 460.8 1.07 (1.06–1.07)
Males 468.0 490.1 1.05 (1.04–1.05) 505.7 1.08 (1.08–1.09)
Females 409.0 417.0 1.02 (1.02–1.02) 427.9 1.05 (1.04–1.05)
Lung and bronchus 46.5 52.7 1.13 (1.12–1.14) 64.0 1.38 (1.36–1.39)
Males 51.8 59.8 1.15 (1.14–1.17) 73.8 1.43 (1.41–1.44)
Females 42.7 47.2 1.10 (1.09–1.12) 56.1 1.31 (1.30–1.33)
Breast, female 128.4 126.2 0.98 (0.98–0.99) 118.1 0.92 (0.91–0.93)
Prostate 114.1 114.6 1.00 (1.00–1.01) 106.9 0.94 (0.93–0.95)
Colorectum 35.6 36.8 1.03 (1.02–1.04) 42.3 1.19 (1.17–1.20)
Males 41.0 42.1 1.03 (1.02–1.04) 48.6 1.19 (1.17–1.20)
Females 31.1 32.2 1.03 (1.02–1.05) 36.5 1.17 (1.15–1.19)
Pancreas 13.3 13.3 1.00 (0.99–1.01) 13.3 1.00 (0.98–1.02)
Males 15.1 15.2 1.00 (0.99–1.02) 15.1 1.00 (0.97–1.02)
Females 11.8 11.7 0.99 (0.97–1.01) 11.6 0.98 (0.96–1.01)
Uterine cervix 7.4 8.0 1.08 (1.05–1.11) 9.5 1.29 (1.24–1.34)
Mortality
All cancers 142.7 152.0 1.06 (1.06–1.07) 166.9 1.17 (1.17–1.17)
Males 168.4 180.9 1.07 (1.07–1.08) 200.0 1.19 (1.18–1.19)
Females 124.5 130.2 1.05 (1.04–1.05) 140.9 1.13 (1.13–1.14)
Lung and bronchus 31.4 36.5 1.16 (1.16–1.17) 43.4 1.38 (1.37–1.39)
Males 37.5 44.1 1.18 (1.17–1.19) 53.0 1.41 (1.40–1.43)
Females 26.9 30.5 1.14 (1.13–1.14) 35.5 1.32 (1.31–1.33)
Breast, female 19.5 19.6 1.00 (0.99–1.01) 20.0 1.02 (1.01–1.04)
Prostate 18.8 18.5 0.98 (0.97–0.99) 19.3 1.03 (1.01–1.04)
Colorectum 12.6 12.9 1.03 (1.02–1.04) 15.4 1.23 (1.22–1.24)
Males 15.0 15.4 1.02 (1.01–1.04) 18.5 1.23 (1.21–1.25)
Females 10.6 10.8 1.02 (1.01–1.04) 12.8 1.21 (1.19–1.22)
Pancreas 11.0 11.1 1.01 (1.00–1.02) 11.5 1.05 (1.04–1.06)
Males 12.6 12.7 1.00 (0.99–1.02) 13.3 1.05 (1.04–1.07)
Females 9.6 9.6 1.01 (0.99–1.02) 9.9 1.03 (1.01–1.05)
Uterine cervix 2.1 2.2 1.06 (1.02–1.09) 2.7 1.27 (1.22–1.32)
  • Note: Rates per 100,000 population and age adjusted to the 2000 US standard population.
  • Abbreviation: CI, confidence interval.
  • a Large metropolitan areas with a population of ≥1 million are the reference group for rate ratios.
  • Source: Surveillance, Epidemiology, and End Results 22 registries (incidence; covering 48% of the US population) and National Center for Health Statistics (mortality) data.
Details are in the caption following the image

Ratio of cancer incidence and mortality rates in nonmetropolitan versus large metropolitan (≥1 million population) areas overall and for select cancers by sex and age group, United States, 2016–2020. Rate ratios are based on rates age adjusted to the 2000 US standard population. CI indicates confidence interval; RR, rate ratio. Source: Surveillance, Epidemiology, and End Results 22 registries (incidence; covering 48% of the US population) and National Center for Health Statistics (mortality) data.

Cancer survival

The 5-year age-standardized relative survival rate during 2014 through 2020 for all cancers combined was higher for White people compared with other racial/ethnic groups; the rate was generally lowest among Black or AIAN people for all evaluated cancers (see Figure S1). Previous studies have also shown lower stage-specific survival among Black people than among White people for many cancer types, e.g., 21% versus 32% 5-year survival for distant-stage breast cancer diagnosed from 2012 through 2018.24, 25 By area of residence, the age-standardized 5-year relative cancer survival for evaluated cancers during 2014 through 2020 was lower in nonmetropolitan areas than in large metropolitan areas overall (Figure 2) and for each stage at diagnosis (see Table S3). For all stages and all cancers combined, for example, 5-year relative survival was 62% in nonmetropolitan areas and 67% in large metropolitan areas (Figure 2).

Details are in the caption following the image

Five-year relative cancer survival for select cancers by age group and urbanicity of county of residence, SEER 22 registries, 2014–2020. Five-year survival for patients with cancer aged ≤99 years diagnosed in 2014–2020 excluding in situ carcinomas, age standardized to ICSS age standard 1 for all cancer types shown in this figure, except cancer of the cervix uteri, for which ICSS age standard 2 was used. Age groups used for age standardization were 15–44, 45–54, 55–64, and 65–74 years, and 75 years or older, except for prostate cancer (15–54, 55–64, 65–74, and 75–84 years, and 85 years or older). ICSS indicates International Cancer Survival Standard; SEER, Surveillance, Epidemiology, and End Results program. Source: SEER Program 22 cancer registries (excluding Illinois and Massachusetts) data.

Cancer mortality

The overall cancer mortality rate during 2016 through 2020 was 18%–19% higher among Black and AIAN males than among White males (Table 1). AIAN and Black females had 16% and 12% higher overall cancer mortality rates than White females, respectively, despite having 7% and 9% lower incidence rates, respectively. By cancer type, AIAN and Black people had the highest lung cancer mortality rates among males; among females, AIAN females had the highest rate. Compared with White people, mortality rates for prostate and colorectal cancer were also substantially higher among Black and AIAN people. Black females had a 40% higher breast cancer mortality rate than White females despite their 5% lower incidence rate. As previously demonstrated, the Black–White disparity in breast cancer mortality is larger in younger ages, with about 85% higher rates among Black women aged 30–49 years and 136% higher rates among Black women aged 20–29 years.26

Cancer mortality rates are generally higher among people of lower SES.27, 28 During 2016 through 2020, for example, overall cancer mortality rates among Black and White men and women aged 25–74 years were 1.58–2.79 times higher in individuals with ≤12 years of education than in those with ≥16 years of education (Table 3). These disparities by educational attainment within each race were considerably larger than the Black–White disparities in overall cancer mortality within each educational attainment, ranging from 1.03 to 1.46 times higher among Black people. These findings suggest a major role for SES disparities in racial disparities in cancer mortality in view of disproportionally larger representation of Black people in lower SES groups. For evaluated cancer types, mortality rates within each educational attainment category were higher among Black people than White people, except for lung cancer in people who had ≤15 years of education, among whom the rates in Black and White people were similar or were lower among Black people. Of note, the Black–White disparities in mortality from all cancers combined and from most major cancers within each educational attainment category were largest in the highest educational attainment category.

TABLE 3. Age-standardized cancer mortality rates from common cancers among Black and White adults aged 25–74 years by sex and educational attainment, and corresponding rate ratios for disparities by education and race/ethnicity: United States, 2016–2020.
Cancer site by sex Mortality rate Black vs. White adults, RR (95% CI)
All races/ethnicities Non-Hispanic White Non-Hispanic Black
Male
All cancers
≤12 years of education 213.5 241.6 258.0 1.07 (1.06–1.08)
13–15 114.6 119.3 133.3 1.12 (1.10–1.13)
≥16 85.1 86.6 112.1 1.29 (1.27–1.32)
RR, ≤12 vs. ≥16 years of education (95% CI) 2.51 (2.50–2.52) 2.79 (2.77–2.81) 2.30 (2.26–2.35)
Lung and bronchus
≤12 years of education 62.0 75.3 70.5 0.94 (0.92–0.95)
13–15 25.7 27.6 28.2 1.02 (0.99–1.06)
≥16 12.8 12.8 16.7 1.30 (1.24–1.37)
RR, ≤12 vs. ≥16 years of education (95% CI) 4.85 (4.79–4.92) 5.89 (5.80–5.98) 4.23 (4.03–4.44)
Colorectum
≤12 years of education 20.6 22.0 28.5 1.29 (1.26–1.33)
13–15 12.0 12.0 16.4 1.37 (1.31–1.43)
≥16 9.2 9.2 14.9 1.62 (1.54–1.71)
RR, ≤12 vs. ≥16 years of education (95% CI) 2.24 (2.20–2.28) 2.40 (2.35–2.45) 1.92 (1.82–2.02)
Prostate
≤12 years of education 11.1 10.1 24.6 2.43 (2.37–2.50)
13–15 7.1 6.5 15.3 2.36 (2.25–2.47)
≥16 6.2 5.9 15.7 2.65 (2.51–2.79)
RR, ≤12 vs. ≥16 years of education (95% CI) 1.79 (1.76–1.83) 1.71 (1.67–1.75) 1.57 (1.49–1.66)
Female
All cancers
≤12 years of education 160.8 186.7 191.8 1.03 (1.02–1.04)
13–15 97.3 98.5 127.1 1.29 (1.27–1.31)
≥16 83.6 83.2 121.2 1.46 (1.43–1.48)
RR, ≤12 vs. ≥16 years of education (95% CI) 1.92 (1.91–1.94) 2.24 (2.23–2.26) 1.58 (1.56–1.61)
Lung and bronchus
≤12 years of education 42.0 55.6 37.8 0.68 (0.67–0.69)
13–15 19.9 21.9 20.9 0.95 (0.93–0.98)
≥16 11.4 11.7 14.0 1.20 (1.15–1.26)
RR, ≤12 vs. ≥16 years of education (95% CI) 3.68 (3.63–3.74) 4.76 (4.68–4.84) 2.70 (2.58–2.82)
Colorectum
≤12 years of education 13.2 14.8 17.7 1.19 (1.16–1.23)
13–15 8.3 8.2 11.6 1.43 (1.37–1.49)
≥16 7.0 6.9 11.5 1.67 (1.59–1.76)
RR, ≤12 vs. ≥16 years of education (95% CI) 1.89 (1.85–1.93) 2.16 (2.11–2.22) 1.54 (1.46–1.63)
Breast
≤12 years of education 24.8 26.6 37.8 1.42 (1.39–1.45)
13–15 18.6 17.8 29.3 1.65 (1.60–1.69)
≥16 18.6 18.2 31.1 1.71 (1.66–1.76)
RR, ≤12 vs. ≥16 years of education (95% CI) 1.33 (1.31–1.35) 1.46 (1.44–1.49) 1.22 (1.17–1.26)
  • Note: Rates are per 100,000 population and age adjusted to the 2000 US standard population. Cancer deaths with missing education attainment data were excluded.
  • Abbreviations: CI, confidence interval; RR, rate ratio.
  • Source: National Center for Health Statistics (mortality) and US Census Bureau (population) data.

By area of residence, mortality rates during 2016 through 2020 were higher in nonmetropolitan areas than in large metropolitan areas overall and for all evaluated cancer types, including for breast and prostate cancers, despite lower incidence rates (Table 2). These differences were more prominent in individuals younger than 65 years than those aged 65 years and older. For example, lung cancer mortality rates among females in nonmetropolitan versus large metropolitan areas were 80% higher (RR, 1.80; 95% CI, 1.76–1.83) in those younger than 65 years and 19% higher (RR, 1.19; 95% CI, 1.17–1.20) in those aged 65 years and older (Figure 1). In contrast to younger age groups, in individuals aged 65 years and older, mortality rates for pancreatic and cervical cancer in nonmetropolitan areas were similar to or slightly lower than rates in large metropolitan areas.

In analyses stratified by both urbanicity and race/ethnicity, overall cancer mortality rates in individuals younger than 65 years were higher in nonmetropolitan areas than in large metropolitan areas among both males and females across all evaluated racial/ethnic groups except Hispanic females, whereas disparities were smaller or did not exist in those aged 65 years or older (Table 4). However, disparities in overall cancer mortality between Black and White people younger than 65 years were larger in large metropolitan areas than in nonmetropolitan areas. Compared to their White counterparts, for example, the overall cancer mortality rate in Black females younger than 65 years was 39% higher in large metropolitan areas compared with 19% in nonmetropolitan areas. This may reflect wider racial disparities in access to or quality of care in large metropolitan areas, which tend to be more affluent than nonmetropolitan areas. This finding is similar to the Black–White disparities by educational attainment, which showed larger disparities in the highest educational attainment category.

TABLE 4. Age-standardized overall cancer mortality rates by sex, age group, race/ethnicity, and urbanicity of county of residence, and corresponding rate ratios for disparities by race/ethnicity and urbanicity: United States, 2016–2020.
Sex, age group, and race/ethnicity Metropolitan, ≥1 million population Metropolitan, <1 million population Non-metropolitan Non-metropolitan vs. metropolitan ≥1 million population, RR (95% CI)
Male
All ages
NH White, mortality rate 173.8 183.8 201.6 1.16 (1.15–1.17)
NH Black, mortality rate 209.0 223.2 241.9 1.16 (1.14–1.18)
RR vs. NH White (95% CI) 1.20 (1.19–1.21) 1.21 (1.20–1.23) 1.20 (1.18–1.22)
NH API, mortality rate 109.5 114.6 109.8 1.00 (0.95–1.06)
RR vs. NH White (95% CI) 0.63 (0.62–0.64) 0.62 (0.61–0.64) 0.54 (0.52–0.58)
Hispanic-Latinx, mortality rate 128.9 132.5 126.8 0.98 (0.96–1.01)
RR vs. NH White (95% CI) 0.74 (0.74–0.75) 0.72 (0.71–0.73) 0.63 (0.61–0.64)
Younger than 65 years
NH White, mortality rate 45.6 53.9 61.8 1.35 (1.34–1.37)
NH Black, mortality rate 61.0 68.4 76.9 1.26 (1.23–1.29)
RR vs. NH White (95% CI) 1.34 (1.32–1.35) 1.27 (1.25–1.29) 1.25 (1.22–1.28)
NH API, mortality rate 31.2 34.2 37.2 1.19 (1.09–1.31)
RR vs. NH White (95% CI) 0.68 (0.67–0.70) 0.64 (0.61–0.66) 0.60 (0.55–0.66)
Hispanic-Latinx, mortality rate 33.8 36.7 36.5 1.08 (1.04–1.12)
RR vs. NH White (95% CI) 0.74 (0.73–0.75) 0.68 (0.67–0.69) 0.59 (0.57–0.61)
Aged 65 years and older
NH White, mortality rate 1060.2 1082.0 1168.5 1.10 (1.10–1.11)
NH Black, mortality rate 1232.0 1292.9 1382.4 1.12 (1.10–1.14)
RR vs. NH White (95% CI) 1.16 (1.15–1.17) 1.20 (1.18–1.21) 1.18 (1.16–1.20)
NH API, mortality rate 651.2 670.2 612.1 0.94 (0.88–1.01)
RR vs. NH White (95% CI) 0.61 (0.61–0.62) 0.62 (0.60–0.64) 0.52 (0.49–0.56)
Hispanic-Latinx, mortality rate 786.3 794.9 751.2 0.96 (0.93–0.98)
RR vs. NH White (95% CI) 0.74 (0.73–0.75) 0.73 (0.72–0.75) 0.64 (0.62–0.66)
Female
All ages
NH White, mortality rate 129.5 133.0 142.7 1.10 (1.10–1.11)
NH Black, mortality rate 148.9 149.4 151.8 1.02 (1.00–1.04)
RR vs. NH White (95% CI) 1.15 (1.14–1.16) 1.12 (1.11–1.13) 1.06 (1.05–1.08)
NH API, mortality rate 81.7 85.8 93.4 1.14 (1.09–1.20)
RR vs. NH White (95% CI) 0.63 (0.62–0.64) 0.65 (0.63–0.66) 0.65 (0.62–0.69)
Hispanic-Latinx, mortality rate 92.5 95.6 91.5 0.99 (0.96–1.02)
RR vs. NH White (95% CI) 0.71 (0.71–0.72) 0.72 (0.71–0.73) 0.64 (0.62–0.66)
Younger than 65 years
NH White, mortality rate 42.2 47.5 54.1 1.28 (1.27–1.30)
NH Black, mortality rate 58.5 60.4 64.5 1.10 (1.07–1.13)
RR vs. NH White (95% CI) 1.39 (1.37–1.40) 1.27 (1.25–1.29) 1.19 (1.16–1.23)
NH API, mortality rate 30.0 31.7 35.8 1.19 (1.09–1.30)
RR vs. NH White (95% CI) 0.71 (0.70–0.72) 0.67 (0.64–0.69) 0.66 (0.61–0.72)
Hispanic-Latinx, mortality rate 33.0 35.1 34.0 1.03 (0.99–1.07)
RR vs. NH White (95% CI) 0.78 (0.77–0.79) 0.74 (0.72–0.75) 0.63 (0.60–0.65)
Aged 65 years and older
NH White, mortality rate 732.7 724.1 755.0 1.03 (1.02–1.04)
NH Black, mortality rate 773.3 764.5 754.9 0.98 (0.96–1.00)
RR vs. NH White (95% CI) 1.06 (1.05–1.06) 1.06 (1.04–1.07) 1.00 (0.98–1.02)
NH API, mortality rate 439.2 459.8 492.0 1.12 (1.05–1.19)
RR vs. NH White (95% CI) 0.60 (0.59–0.61) 0.64 (0.62–0.65) 0.65 (0.61–0.69)
Hispanic-Latinx, mortality rate 503.7 513.9 489.0 0.97 (0.94–1.01)
RR vs. NH White (95% CI) 0.69 (0.68–0.69) 0.71 (0.70–0.72) 0.65 (0.63–0.67)
  • Note: Rates are per 100,000 population and age adjusted to the 2000 US standard population. The American Indian or Alaska Native population is not included in this analysis because classification factors from the National Center for Health Statistics to adjust for racial misclassification on death certificates for this population are not available by urbanicity of the county of residence.
  • Abbreviations: API, Asian and Pacific Islander; CI, confidence interval; NH, non-Hispanic; RR, rate ratio.
  • Source: National Center for Health Statistics data.

Similar to the national patterns, overall cancer mortality rates were higher in nonmetropolitan areas than in large metropolitan areas in the majority of states (Figure 3). For example, overall cancer mortality rates per 100,000 among males in Georgia were 212.6 in nonmetropolitan counties, 196.0 in small-to-medium metropolitan counties, and 172.3 in large metropolitan counties. In a few states, however, overall cancer mortality rates in nonmetropolitan and metropolitan areas were equally low (e.g., Colorado and Connecticut) or equally high (e.g., Alabama and Mississippi). The states with equally high cancer mortality rates by urbanicity were generally in the South and East North-Central division of the Midwest, areas with historically high smoking prevalence and weak tobacco-control policies.29, 30 Furthermore, most of these states have not yet expanded Medicaid income eligibility under the Patient Protection and Affordable Care Act (ACA).31 Disparities by urbanicity in overall cancer mortality rates in each state were often more prominent among individuals younger than 65 years compared with older individuals (see Figure S2).

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Mortality rates for all cancers combined by sex, urbanicity of county of residence, and state, United States, 2016–2020. Rates are per 100,000 population and age adjusted to the 2000 US standard population. Source: National Center for Health Statistics data.

FACTORS CONTRIBUTING TO CANCER DISPARITIES

Social determinants of health

Disparities in cancer occurrence have largely been attributed to differences in exposure to risk factors, early detection, and access to preventive care and treatment,28 which themselves are influenced by social determinants of health (Figure 4).32-34 Social determinants are a mix of the conditions where individuals live, work, learn, play, worship, and age along with the complex systemic and social structures that influence these conditions, such as policy and the economic climate.35 Structural racism and discrimination are deeply rooted social determinants of health that have downstream effects resulting in social inequities and discriminatory policies, which are significant root causes of health disparities.32, 36-38 For example, mortgage lending bias has resulted in residential segregation and underinvestment in some communities, with inequities in wealth accumulated across generations.39-41 Residential segregation has been associated with poorer living environments, including higher exposure to ambient air pollution or other environmental pollutants,42-45 and higher risk of late-stage cancer diagnosis, poorer survival, and higher cancer mortality.39, 40, 46-49

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Social determinants of health and cancer disparities.

Social determinants of health could positively or negatively affect cancer occurrence through their effects on educational and job opportunities, income, housing, transportation, public safety, food security, social inclusion, and access to high-quality and affordable health services.32, 36-38 Inequities in social determinants of health are disproportionately seen by race/ethnicity, SES, and place of residence. Compared with White people, for example, people of color generally were more likely to have lower educational attainment and to experience poverty, food insecurity, and housing insecurity in 2021 (Figure 5); e.g., the proportion of people aged 18–64 years who did not own a house was about twice as high among Black people (55.3%) as among White people (28.2%). Similar disparities existed by place of residence, especially in younger ages, except that the proportion of individuals who did not own a house was smaller in nonmetropolitan areas, likely because of the lower average price of houses in those areas.50

Details are in the caption following the image

Select socioeconomic characteristics by age group, race/ethnicity, and urbanicity of county of residence, United States, 2021. Data are age-adjusted prevalence in individuals aged 18 years and older (25 and older years for education level). AIAN indicates American Indian and Alaska Native; GED, General Educational Development (equivalent to high school diploma); metro, metropolitan; NH, non-Hispanic; pop, population. Source: National Health Interview Survey data.

Through their effects on occupation and income, social determinants of health have a substantial influence on insurance coverage, which is a major determinant of access to and receipt of health care services and cancer outcomes in the United States.51-54 Compared with insured individuals aged 18–64 years, for example, uninsured individuals were more likely to delay or not receive needed medical care because of cost (26.7% vs. 7.2%–7.7%) or not to be up to date with screening for colorectal cancer (79.3% vs. 42.6%–52.4%) or female breast cancer (70.5% vs. 32.0%–41.6%) in 2021 (Figure 6). Individuals who are not up to date with recommended cancer screenings are more likely to be diagnosed with an advanced disease, which can adversely affect cancer survival.55

Details are in the caption following the image

Disparities in access to care by age group and health insurance coverage, United States, 2021. Being up to date for colorectal cancer screening was defined as receipt of fecal occult blood test/fecal immunochemical test, sigmoidoscopy, colonoscopy, computed tomography colonography, or stool DNA test in the past 1, 5, 10, 5, and 3 years, respectively, in individuals aged 45 years and older. Being up to date for breast cancer screening was defined as receipt of mammogram within the past year (aged 45–54 years) or the past 2 years (aged 55 years and older). Both definitions were based on the American Cancer Society’s guidelines for cancer screening. Source: National Health Interview Survey data.

Because the vast majority of people aged 65 years and older are age-eligible for Medicare coverage, almost all individuals without health insurance coverage are younger than 65 years. Among people aged 18–64 years, the age-adjusted proportion of individuals with no health insurance in 2021 was higher among Black (13.7%), AIAN (18.7%), and Hispanic (28.7%) people than among White (7.8%) or Asian (5.9%) people and among residents of nonmetropolitan areas (14.4%) than among residents of large metropolitan areas (12.0%); the proportion was also substantially higher among people with lower education or income levels and in the South region (Table 5).

TABLE 5. Prevalence of insurance coverage (%) by age group, race/ethnicity, socioeconomic characteristics, urbanicity of county of residence, and region: United States, 2021.
Aged 18–64 years 65 years and older
Uninsured Medicaid or other public only Private (any) Medicare only Medicare + Medicaid or other public only Medicare + private supplemental
Race/ethnicity
Non-Hispanic White only 7.8 10.9 77.2 46.0 3.6 42.2
Non-Hispanic Black only 13.7 22.5 57.8 48.7 14.9 26.6
Non-Hispanic AIAN only or multiple 18.7 31.8 44.9 NA NA NA
Non-Hispanic Asian only 5.9 13.4 78.7 45.3 21.3 25.5
Hispanic-Latinx 28.7 17.7 50.4 50.9 19.5 18.9
Educational attainment (aged 25 years and older)
Some high school or less 36.9 28.6 30.7 49.6 20.7 20.3
High school graduate 18.0 19.7 57.2 46.5 8.1 36.3
Some college 11.1 14.7 68.6 46.3 4.5 38.7
College graduate or higher 4.7 4.7 87.5 45.5 2.3 45.1
Income level
<100% FPL 25.0 46.3 24.0 45.7 32.2 12.7
100% to <200% FPL 23.9 29.6 40.7 54.4 13.4 23.7
≥200% FPL 8.3 5.9 82.2 44.4 2.5 44.3
Urbanicity of county of residence
Metropolitan, ≥1 million population 12.0 12.6 71.9 49.6 7.9 34.6
Metropolitan, <1 million population 13.1 15.2 66.9 44.6 5.4 40.0
Nonmetropolitan 14.4 18.4 62.2 40.7 7.3 42.7
US region
Northeast 7.1 17.6 72.6 41.6 8.0 43.7
Midwest 9.0 13.6 73.9 42.8 4.2 45.1
South 17.7 11.1 65.9 47.8 7.2 34.8
West 11.9 16.9 67.7 52.1 8.5 30.5
United States 12.7 14.1 69.2 46.6 7.0 37.6
  • Note: Percentages may not add up to 100% because a small proportion of people do not fall into a category shown in this table; for example, individuals aged 65 years and older who are uninsured.
  • Abbreviations: AIAN, American Indian and Alaska Native; FPL, federal poverty level; NA, not available (sparse data).
  • Source: National Health Interview Survey data.

Disparities in exposure to major modifiable cancer risk factors

Modifiable risk factors account for greater than 45% of all cancer deaths in the United States.23 In particular, cigarette smoking accounts for nearly 30% of all cancer deaths, and obesity, unhealthy diet, physical inactivity, and alcohol consumption together account for about 16% of cancer deaths.23 Many of the racial, SES, and geographic disparities in cancer mortality rates reflect differences in the prevalence of these modifiable risk factors. For example, the prevalence of current cigarette smoking in 2021 was substantially higher in nonmetropolitan areas than in large metropolitan areas, particularly in younger ages (23.5% vs. 10.9% among males and 18.2% vs. 7.4% among females aged 18–64 years; Table 6), in part reflected in the high burden of smoking-related cancers (listed in Table S4), including lung, colorectal, pancreatic, and cervical cancers in those younger than 65 years in nonmetropolitan areas (Figure 1). Of note, about 80% of lung cancer cases, 20% of cervical cancer cases, and 10%–12% of pancreatic and colorectal cancer cases in the United States have been attributed to cigarette smoking.23 Similarly, current cigarette smoking prevalence in 2021 was greater than four times higher among individuals without a high school diploma (21.1%) than among those with a college degree (4.6%),18 consistent with the four-fold difference in the lung cancer mortality rate between these two population groups (Table 3). Likewise, exposure to second-hand smoke among people who did not smoke during 2017 through 2018 was substantially higher among people with limited incomes (44.7% vs. 21.3% among individuals living below and above the poverty level, respectively) and among Black people (48.0% vs. 22.0% among White people).56

TABLE 6. Prevalence of major risk factors for cancer and being up to date with cancer screening (%) by sex (for risk factors), age group, and urbanicity of county of residence: United States, 2020–2021.a
All ages Younger than 65 years 65 years and older
Metropolitan, ≥1 million population Metropolitan, <1 million population Non-metropolitan Metropolitan, ≥1 million population Metropolitan, <1 million population Non-metropolitan Metropolitan, ≥1 million population Metropolitan, <1 million population Non-metropolitan
Risk factorb
Ever smoking, 18 years and older (2021)
Males 35.7 43.3 48.0 32.4 40.3 45.4 51.6 58.0 60.8
Females 23.5 32.0 38.1 21.0 30.0 38.3 35.9 41.4 36.7
Current smoking, 18 years and older (2021)
Males 10.5 15.4 21.5 10.9 16.7 23.5 8.8 9.1 11.4
Females 7.2 12.9 16.6 7.4 13.7 18.2 6.0 8.7 9.2
Obesity, 18 years and older (2021)
Males 29.6 35.1 36.6 30.4 41.2 39.9 25.7 28.0 33.4
Females 29.2 37.1 38.2 30.0 44.0 42.5 25.6 31.7 35.0
Heavy alcohol drinking, 18 years and older (2020)
Males 5.7 6.5 6.8 5.8 6.8 7.4 4.8 5.3 4.0
Females 6.2 6.3 4.7 6.4 6.7 5.1 5.1 4.3 3.1
Physical inactivity, 18 years and older (2020)
Males 21.9 25.6 31.8 20.0 23.5 29.4 31.4 35.8 43.6
Females 24.8 30.3 34.2 22.0 27.5 31.8 38.3 43.7 46.0
Screening
Breast cancer (2021)c
ACS, 45 years and older 63.9 64.7 61.1 61.2 62.4 57.5 67.0 66.9 66.2
USPSTF, 50–75 years 76.6 76.5 72.8 76.4 76.4 71.0 77.0 76.7 76.9
Colorectal cancer (2021)d
ACS, 45 years and older 59.7 59.0 56.1 50.3 48.5 46.8 76.3 77.5 72.3
USPSTF, 45–75 years 58.9 57.5 55.4 51.6 50.0 48.3 83.4 83.1 79.5
Cervical cancer (2021)e
ACS, 25–65 years 75.8 76.5 71.8 76.1 76.6 71.8
USPSTF, 21–65 years 73.5 74.2 71.0 73.8 74.3 71.0
Prostate cancer (2021)f
ACS, 50 years and older 34.8 36.3 35.0 25.9 26.7 28.3 45.5 47.7 43.0
USPSTF, 55–69 years 33.6 35.9 36.1 29.6 31.5 33.6 44.0 47.2 42.6
  • Abbreviations: ACS, according to the American Cancer Society guidelines; USPSTF, according to the US Preventive Services Task Force recommendations.
  • a Estimates are age-adjusted prevalence. Lower and upper bounds for those younger than 65 years and aged 65 years and older are based on age ranges shown in the first column, e.g., the age range for those younger than 65 years for ever smoking is from 18 to younger than 65 years.
  • b Ever cigarette smoking was defined as smoking at least 100 cigarettes in a lifetime. Current cigarette smoking was defined as smoking at least 100 cigarettes in a lifetime and currently smoking every day or some days. Obesity was defined as body mass index ≥30 kg/m2. Heavy alcohol consumption was defined as >14 drinks per week in the past year (men) or more than seven drinks per week in the past year (women). Physical inactivity was defined as no aerobic leisure-time physical activity.
  • c Mammogram within the past year (ages 45–54 years) or past 2 years (aged 55 years and older) based on ACS guidelines (aged 45 years and older); past 2 years based on USPSTF recommendations (aged 50–75 years).
  • d Fecal occult blood test/fecal immunochemical test, sigmoidoscopy, colonoscopy, computed tomography colonography, or stool DNA test in the past 1, 5, 10, 5, and 3 years, respectively, based on ACS guidelines (aged 45 years and older) and USPSTF recommendations (aged 45–75 years).
  • e Papanicolaou test in the past 3 years (aged 25–65 years based on ACS guidelines and 21–65 years based on USPSTF recommendations) or Papanicolaou test and human papillomavirus test within the past 5 years (aged 30–65 years). Results for those aged 65 years and older are not shown for cervical cancer screening because only women aged 65 years in this age group were age-eligible for the screening.
  • f Serum prostate-specific antigen testing in the past year (aged 50 years and older based on ACS guidelines and 55–69 years based on USPSTF recommendations) among men who have not been diagnosed with prostate cancer. Both the ACS and the USPSTF recommend prostate cancer screening after shared decision making, for which data were not available from the National Health Interview Survey.
  • Source: National Health Interview Survey data.

In 2021, the prevalence of obesity, heavy drinking (among younger males), and physical inactivity were higher in nonmetropolitan areas than in large metropolitan areas, with larger differences in obesity in those aged 18–64 years (Table 6). The prevalence of obesity was comparable among White, Black, and Hispanic males (40.4%–45.2%) but was higher among Black (57.9%) and Hispanic (45.7%) women than among White women (39.6%) aged 20 years and older during 2017 through March 2020; the prevalence of obesity was substantially lower among Asian women (14.5%) and men (17.6%).19 In 2021, the prevalence of heavy alcohol drinking was higher in AIAN (8.9%) and White (7.2%) people than in other racial/ethnic groups (2.5%–4.9%); and the prevalence of physical inactivity was the highest among Hispanic people (31.4%), followed by Black (28.3%), AIAN (26.6%), White (20.2%), and Asian (17.8%) people.18 These patterns have likely contributed to higher incidence rates of cancers associated with obesity, alcohol consumption, and physical inactivity (listed in Table S4), such as colorectal and pancreatic cancer, in nonmetropolitan areas and among Black and AIAN people, especially for obesity-related cancers in younger age groups. Previous studies have reported a rise in the incidence rates of several obesity-related cancers among younger generations, likely in part reflecting the obesity epidemic.57

Disparities in early detection and receipt of treatment

Disparities in early detection (stage at diagnosis) and treatment are other important factors contributing to disparities in cancer survival and mortality, notably for cancers with disproportionally larger disparities in mortality than incidence, including most cancer types with racial/ethnic disparities in mortality, as listed in Table 1. Disparities by urbanicity in cancer mortality rates were also disproportionally larger than disparities in incidence rates for all cancers combined and for cancers of the breast, prostate, colorectum, and pancreas (Table 2). Compared with large metropolitan areas, for example, overall cancer mortality rates in nonmetropolitan areas were higher by 19% among males and by 13% among females, whereas incidence rates were 8% and 5% higher among males and females, respectively; these differences between incidence and mortality rates were greater in those younger than 65 years (Figure 1).

Disparities in early detection (including cancer screening)

Differences in stage at diagnosis comprise a major contributing factor to disparities in cancer survival and mortality.58 For lung, breast, and cervical cancers, people residing in nonmetropolitan counties had the lowest proportions of localized-stage cancers and the highest proportions of distant-stage cancers compared with people residing in counties in large metropolitan areas during 2016 through 2020 (Figure 7). Disparities in the proportion of localized-stage cancer diagnosis between nonmetropolitan and large metropolitan areas were generally similar in individuals younger than 65 years and aged 65 years and older, except for cervical cancer, which showed greater disparities in those younger than 65 years. By race/ethnicity, Black people generally had the lowest proportion of localized-stage cancer and the highest proportion of distant-stage cancer compared with other racial/ethnic groups during 2016 through 2020, except for prostate and lung cancer, for which AIAN and API people had the highest proportion of distant-stage disease, respectively (see Figure S3). For example, the percentage of localized-stage diagnoses among Black and White females was 57% versus 68% for breast cancer and 35% versus 43% for cervical cancer, respectively.

Details are in the caption following the image

Stage at diagnosis for select cancers by age group and urbanicity of county of residence, SEER 22 registries, 2016–2020. SEER indicates Surveillance, Epidemiology, and End Results program. Source: SEER Program 22 cancer registries data.

In 2021, the prevalence of being up to date with breast, colorectal, and cervical cancer screening was slightly lower in nonmetropolitan areas than in large metropolitan areas (Table 6), notably for breast cancer screening in individuals younger than 65 years, which may have contributed to the higher proportion of late-stage diagnosis for these cancers in younger age groups in nonmetropolitan areas (Figure 7). Previous studies have reported wider variations in the estimated prevalence of screening across counties, e.g., from 39.8% to 74.4% for colorectal cancer screening in 2018.59 The prevalence of cancer screening is also generally lower among people of color, those with lower SES, and those without health insurance coverage. In 2021, for example, the prevalence of being up to date with colorectal cancer screening ranged from 58.2% among individuals without a high school diploma to 77.5% among individuals with a college degree; by race/ethnicity, the prevalence was 73.8% among White people but ranged from 60.2% to 71.7% in other racial/ethnic groups.18 There are also disparities by race/ethnicity, SES, and provider type in follow-up of abnormal cancer screening tests60-62 and receipt of surveillance testing or screening for other cancers among cancer survivors.63-65 Disparities in access to care for following suspicious symptoms can also result in disparities in stage at diagnosis of cancers for which routine screening is not recommended.66

The prevalence of lung cancer screening in 2020 was low nationally (6.5%), with substantial variation across states, ranging from 1.1% in California to 19.7% in Massachusetts; states with the highest prevalence of lung cancer screening were in the Northeast and Midwest.20

Disparities in receipt of treatment

An extensive literature has documented disparities in the receipt of different cancer treatments by race/ethnicity, SES, geographic location, and type of health insurance coverage,34, 67-73 including studies showing disparities in the receipt of guideline-concordant treatment for many cancer types, such as cancers of the lung,74, 75 colorectum,76, 77 breast,78, 79 pancreas,80, 81 uterus,82, 83 ovary,84, 85 esophagus,86 and head and neck.87 Even if they receive cancer treatment, people of color and of lower SES are more likely to experience treatment delays, which can adversely affect the outcome.88, 89 For example, in a study of >557,000 women aged 65 years and older diagnosed with stage 0–III breast cancer from 2010 to 2017, Black, Hispanic, AIAN, and Asian women were about twice as likely to experience a delay in breast cancer treatment initiation (>90 days after diagnosis) compared with White women.89 Longer time to initiation may also be associated with poorer adherence to cancer treatment.90

The high cost of treatment for many cancer types91, 92 and increases in private health insurance plans’ cost sharing93, 94 can make treatments less affordable to individuals with limited incomes or no or suboptimal insurance, and many individuals with cancer experience challenges in paying for their treatments.95, 96 This financial hardship or financial toxicity results in higher prevalence of financial distress, asset depletion, medical debt, and bankruptcy, especially among people of color and of lower SES,95-98 and has been associated with elevated mortality risk among cancer survivors in the United States.99 For many cancer types, the out-of-pocket cost of treatment has continued to increase during the past decades. For example, in a study of claims of >50 million privately insured individuals aged 18–64 years, average inflation-adjusted out-of-pocket costs increased by 2.0%–2.7% annually from 2009 to 2016 for all four evaluated cancer types, including lung, breast, prostate, and colorectal cancers.92 Increased use of precision medicine and other innovative, advanced medical technologies, which are generally associated with higher costs, may result in further widening of disparities in the receipt of guideline-concordant cancer treatments if affordability is not addressed effectively.100-103

There are also disparities in receipt of treatment among people with private and public insurance. For example, people enrolled in high-deductible health plans can experience substantially higher out-of-pocket costs compared with their counterparts who have traditional insurance.104, 105 Without Health Savings Accounts, which allow pretax contributions to qualified health care expenses, they are also more likely to forgo subsequent diagnostic tests after abnormal cancer screening test results or to delay or forgo cancer care.61, 106 Disruptions in health insurance coverage have also been associated with lower receipt of cancer prevention, screening, and treatment.107 Because of fluctuations in income below and above the income-eligibility threshold or administrative errors, disruptions in insurance coverage have historically been common among Medicaid enrollees.108 Individuals who have Medicaid coverage disruptions are shown to have poorer survival after a cancer diagnosis compared with individuals who do not have coverage disruptions.107 The Families First Coronavirus Response Act of 2020 required that Medicaid programs provide continuous coverage for enrollees during the pandemic; this provision ended on March 31, 2023. It has been estimated that about 7.8–24.4 million people could lose Medicaid coverage during the 12-month unwinding period.109 Moreover, variations in coverage, prior authorization for services, and copays across states can contribute to disparities in the receipt of certain treatments, such as targeted therapies, among individuals with Medicaid coverage.110

Health care system factors, including provider expertise and referral patterns, may also contribute to cancer disparities.111-113 For example, Black people are more likely than White people to undergo major surgeries at low-volume or low-quality hospitals, even if they live closer to higher quality hospitals, with a larger disparity in highly segregated areas.114 Care providers’ implicit or explicit racial bias could also lead to substandard medical treatment.68 Health care providers’ lack of population-specific knowledge and skills (e.g., for lesbian, gay, bisexual, transgender, queer, questioning, or another diverse gender identity [LGBTQ+] communities)115 may also create barriers in cancer care for the corresponding populations.

Because many providers are concentrated in cities and affluent suburbs, people living in rural areas may have limited access to oncologists and other specialty care providers, which may adversely affect health outcomes.116-122 Disparities in cancer screening by geographic location have also been attributed in part to differences in distance to screening facilities.123-125 Limited access to some cancer treatments can be aggravated by rural hospital closures, which have been more common in states that have not expanded Medicaid income eligibility, notably in the East and West Central divisions of the South,126, 127 areas with the highest overall cancer mortality rates in the United States.128 The use of telemedicine may help overcome some of the disparities in access to care in remote areas, but appropriate actions are needed to increase the accessibility of broadband and digital technologies in those areas.129-131

EFFECTS OF THE COVID-19 PANDEMIC ON CANCER OCCURRENCE

Overall cancer incidence rates in the United States were relatively stable during 2011 to 2019 but dropped by 11% from 2019 to 2020, the first year of the coronavirus disease 2019 (COVID-19) pandemic.132, 133 The relative decline from 2019 to 2020 was ≥12% for cancers of the colorectum (12%), lung (13%), prostate (15%), skin (melanoma; 15%), and thyroid (16%).132 The decline was largest for stage I disease, whereas the odds of being diagnosed with stage IV disease were higher in 2020 than in 2019 nationally and across most sociodemographic groups, especially among Hispanic and API people and uninsured individuals.133 The decline in early stage diagnosis was largely a result of reduced capacity for cancer screening and detection, disruptions in employment and health insurance, and fear of COVID-19 exposure.18, 24, 134 In contrast, overall cancer mortality rates continued the steady decline from 2011 to 2020.132 However, delays in diagnosis during the pandemic may result in an increase in advanced-stage cancer diagnosis, and consequently poorer survival, for several years after the height of the pandemic,135 for which cancer incidence and mortality data are not yet available. Previous studies have shown that, in 2020, disparities in cancer mortality by SES increased nationally and across all racial/ethnic groups, likely reflecting disproportionately larger declines in receipt of cancer care among people of lower SES during the pandemic.136

PROGRAMS AND RESOURCES TARGETING CANCER DISPARITIES

American Cancer Society programs

Cancer disparities research has been a major focus of the intramural research departments at the ACS, by publishing the ACS’s Report on the Status of Cancer Disparities in the United States,28 Cancer Facts & Figures for African American/Black People, and Cancer Facts & Figures for Hispanic/Latino People and their accompanying scientific articles6, 7 as well as multiple review articles8, 32, 34, 137 and original research articles documenting cancer disparities and the effects of interventions to reduce those disparities.54, 125, 128, 138, 139 Some other ongoing ACS research includes examining the effects of social determinants of health on cancer disparities140-143 and the effectiveness of insurance coverage expansion under the ACA in reducing disparities in cancer screening and cancer outcomes.144-147 The ACS has started recruiting participants for a new cohort study entitled VOICES of Black Women, which aims to enroll at least 100,000 Black women aged 25–55 years in the United States to better understand cancer and how to improve overall health among Black women.148

The ACS has also funded over 700 health equity research grants since 1999, including research on practice-based tactics for overcoming barriers to accessing care, inequities resulting from public policy and new cancer treatments, and the downstream effects of bias and discrimination based on factors such as age, sex, gender identity, race, ethnicity, literacy, geography, and SES.149, 150 In addition, recognizing that representation of all identities in the cancer research workforce is critical for addressing cancer disparities, the ACS invested over $35 million in 2022 to support several new initiatives to increase diversity in the cancer workforce and advance heath equity research. These initiatives include 4-year programs at minority-serving institutions to enhance cancer research and career development capacity for the Historically Black Colleges and Universities, a 10-year program to support cancer research internships for undergraduate students from under-represented racial/ethnic backgrounds, new postbaccalaureate fellowship programs at eight universities for recent graduates from under-represented racial/ethnic backgrounds seeking to pursue advanced degrees in cancer research, and a grant program to support health equity researchers, including those at minority-serving institutions, in conducting solution-based research addressing cancer disparities.151, 152

The ACS, alone or in collaboration with other institutions or companies, has invested in multiple cancer-control programs targeting cancer disparities, including programs to increase cancer information, cancer screening and early detection, human papillomavirus (HPV) vaccination, and access to care in populations that have been historically marginalized, generally administered through health care providers or research institutions. Some of these programs include the Community Health Advocates Implementing Nationwide Grants for Empowerment and Equity (CHANGE) grant program,153, 154 the National HPV Vaccination Roundtable,155 the National Colorectal Cancer Roundtable,156 the National Lung Cancer Roundtable,157 the National Breast Cancer Roundtable,158 the National Roundtable on Cervical Cancer,159 and the National Navigation Roundtable.160 Moreover, the ACS provides free services directly to people in active treatment for cancer, including the National Cancer Information Center,161 Hope Lodge,162 and Road to Recovery,163 providing trustworthy and up-to-date cancer information (including on insurance and obtaining assistance in paying for costs of treatment), accommodation while receiving treatment away from home, and transportation to and from treatment, respectively.

The ASC Cancer Action Network (ACS CAN), which is the advocacy affiliate of the ACS, has been actively advocating for policies to address cancer disparities, such as Medicaid expansion (with ongoing work in the 10 remaining states that have not adopted the expansion as of August 2023), maintaining patient protections that ensure that patients who have cancer can enroll in and maintain health insurance coverage, eliminating cost sharing for follow-on screening tests, and passage of the Diversifying Investigations Via Equitable Research Studies for Everyone (DIVERSE) Trials Act. The latter will work to increase diversity in clinical trials and make it easier for all people with cancer to participate in clinical trials by reducing barriers to enrollment.164 Some other activities of ACS CAN are mentioned below (see Future Directions).

Federal, state, and local policies and programs

The ACA was signed into law in March 2010 and went fully into effect in January 2014 to improve access to affordable care in the United States.137 Among provisions of this law are the establishment of individual and small business health insurance marketplaces, providing subsidies to help people with low and moderate incomes afford premiums and cost-sharing, and the expansion of Medicaid eligibility to broader groups of people with lower incomes (≤138% of FPL). This law has resulted in lower uninsured rates, and the expansion of Medicaid coverage in applicable states, in particular, has increased insurance coverage among people with limited incomes.137, 165 The ACA has been associated with improvements in cancer screening, early stage diagnosis, receipt of care, and cancer survival, especially among people with limited incomes in Medicaid expansion states.137, 144, 146, 166, 167

As of August 2023, however, 10 states have not adopted the Medicaid expansion, including Alabama, Florida, Georgia, Kansas, Mississippi, South Carolina, Tennessee, Texas, Wisconsin, and Wyoming.31 Most of these states have the highest proportions of people with lower incomes who have no health insurance. For example, among individuals aged 19–64 years with incomes below the FPL in 2021, the uninsured rate was 28.5%–46.9% in 13 states (Figure 8).31, 168 Of those 13 states, nine states have not yet adopted the Medicaid expansion; the other four states adopted the expansion in 2021 or afterward. In six states (Alabama, Florida, Georgia, Mississippi, South Carolina, and Texas) of the 10 states that have not adopted the Medicaid expansion, people of color constitute greater than one third of the population.169 Likely in part because of higher proportions of the Black population in nonexpansion states, Black people nationally saw smaller stage migration from late-stage to early stage diagnosis than White people after Medicaid expansion (from 2009–2013 to 2014–2017) for colorectal cancer (5.1% vs. 10.3%) and nonsmall cell lung cancer (6.7% vs. 8.1%).170

Details are in the caption following the image

Proportion of individuals aged 19–64 years with incomes below the federal poverty level and no health insurance by state and Medicaid expansion status, 2021. Categories are based on quartiles. Years indicate Medicaid expansion implementation year. (Non) represents states that have not expanded Medicaid eligibility (10 states as of August 2023). North Carolina (indicated as Other) has adopted Medicaid expansion but has not implemented it yet; the implementation is contingent on appropriations in the state fiscal year 2023–2024 biennial budget. Coverage in South Dakota started July 1, 2023. Coverage in Maine was retroactive to July 2, 2018. Source: Kaiser Family Foundation; Status of state Medicaid expansion decisions and Health insurance coverage of adults 19–64 living in poverty (under 100% FPL).31

Beyond the ACA, there are several other federal and state policies and programs to reduce disparities in prevention and cancer screening and increase access to care for people with limited incomes; select programs are listed in Table S5. For example, since 1991, the National Breast and Cervical Cancer Early Detection Program (NBCCEDP) has provided over 15 million breast and cervical cancer screening examinations to more than 6 million women with limited income and no or suboptimal health insurance.171 The NBCCEDP has been associated with more favorable disease stage at diagnosis and a reduction in years of life lost because of breast and cervical cancers among participants.172, 173 The NBCCEDP is expanding its scope to increase its reach to eligible women174 because the proportion of eligible women served by the program remains small (only about 15% for breast cancer screening services during 2016 through 2017 and 7% for cervical cancer screening services during 2015 through 2017).175 Further support will be needed to substantially increase the coverage. As another example, following a provision of the Inflation Reduction Act of 2022 to increase the affordability of medications for Medicare enrollees, in August 2023, the Centers for Medicare & Medicaid Services announced the first 10 drugs (including ibrutinib, which is used for some hematologic cancers) selected for negotiation in 2023 and 2024 with participating drug companies; any negotiated prices will become effective from 2026.176

Examples of state-initiated comprehensive programs to improve health across the population include the Massachusetts Healthcare Reform, which provided universal health insurance coverage by offering subsidized private insurance and expanding Medicaid to include broader groups of people with lower incomes,177 and the Delaware Cancer Consortium, which was a statewide cancer-control program for reducing the cancer burden and associated disparities in the state.178, 179 The Delaware Cancer Consortium coincided with a substantial reduction in Black–White disparities in receipt of colorectal cancer screening and colorectal cancer mortality rates.178

Several states are also developing health equity incentives within their Medicaid programs. For example, Oregon started coordinated care organizations in 2012 to facilitate multisector networks of providers working collaboratively to improve health (e.g., by navigating health and social services, educating about disease conditions, and facilitating engagement in primary care) among Medicare beneficiaries and to reduce health care costs.180, 181 This initiative has been associated with better access to care, as reported by Medicaid enrollees, and an accelerated decline in smoking prevalence in this group.182, 183 Since 2020, coordinated care organizations in Oregon are required to make investments in and provide services related to social determinants of health, such as food, housing, and education services.181 The effects of these requirements on health equity in the state are yet to be determined. Moreover, as of July 2022, 29 states allowed Medicaid payment for services provided by community health workers to address the health needs of marginalized populations, such as culturally appropriate health promotion and education, translation services, care coordination, and social support.184

Some examples of local programs to reduce cancer disparities include the New York Citywide Colon Cancer Control Coalition,185 the Boston Breast Cancer Equity Coalition,186 and the Chicago Cancer Health Equity Collaborative.187 For example, inception of the New York Citywide Colon Cancer Control Coalition was in 2003 and has coincided with the elimination of disparities in screening colonoscopy between White people and Black or Hispanic people in New York City.188

FUTURE DIRECTIONS

Important next steps to reduce cancer disparities in the United States are listed in Table 7. Some of these steps and some additional ACS CAN advocacy efforts are briefly described here; more detailed descriptions are provided in the Supporting Information.

TABLE 7. Future directions to reduce cancer disparities in the United States.
  • Expanding access to Medicaid

  • Making expanded marketplace subsidies permanent

  • Addressing high out-of-pocket costs of cancer care

  • Implementing/enforcing evidence-based tobacco cessation programs and policies

  • Advocating for the FDA to use its full authority to regulate tobacco products and prohibit all flavored products, including menthol

  • Increasing funding for cancer screening programs, including the National Breast and Cervical Cancer Early Detection Program

  • Supporting access to multicancer early detection tests

  • Ensuring coverage of biomarker testing

  • Increasing access to patient navigation services

  • Ensuring working people with cancer, survivors, and caregivers have paid leave

  • Improving data infrastructure and ensuring complete and timely collection and publication of data

  • Increasing diversity in the cancer care and research workforce

  • Increasing diverse representation in and access to clinical trials

  • Increasing access to telehealth for people living with and beyond cancer

  • Abbreviation: FDA, US Food and Drug Administration.

Strengthening access to and affordability of high-quality insurance coverage for patients with cancer and others in need of care is central to reducing cancer disparities. Medicaid helps to improve cancer outcomes by offering access to prevention services and timely cancer screening and early detection services, as well as affordable treatment services and care. However, there are millions of people who currently fall into the Medicaid coverage gap—in which individuals are ineligible for Medicaid coverage but earn too little to qualify for premium tax credits for qualified health plans in the marketplace. ACS CAN advocates for all states to expand Medicaid and for action from Congress to close the coverage gap for lower income Americans who live in states that have not expanded Medicaid income eligibility. ACS CAN also advocates for increasing access to Medicaid by improving processes for applying for and renewing Medicaid coverage and expanding Medicaid eligibility to additional enrollees—policies that are especially important while Medicaid programs conduct millions of eligibility redeterminations for Medicaid coverage to return to normal operations after pandemic-related continuous coverage provisions.

Provisions in the American Rescue Plan Act of 2021 expanded access to more subsidies and tax credits to improve the affordability of comprehensive coverage in the marketplace,189, 190 and the Inflation Reduction Act of 2022 extended increased subsidies for 3 more years (until December 31, 2025), making premiums and cost-sharing more affordable for millions of individuals.191 However, these provisions are not permanent, and, without further congressional action, many individuals needing insurance coverage through the marketplace may lose their coverage after these provisions expire. Some people with incomes just above the eligibility threshold for Medicaid (138% of FPL in expansion states; variable percentages of the FPL in the 10 states that have not expanded Medicaid income eligibility) may not be able to afford monthly premium payments for private health insurance plans, even with subsidies,109 and would benefit from policies to increase the affordability of coverage. ACS CAN advocates that these subsidies be made permanent so that patient costs stay affordable and individuals are not in danger of losing coverage.

Individuals with private or public health insurance coverage may not be able to afford their care because of high deductibles, copayments, or coinsurance.111 Moreover, private health insurance plans are required to have caps on out-of-pocket spending, but Medicare beneficiaries with fee-for-service coverage do not have an overall cap on their out-of-pocket expenses. Many Medicare beneficiaries are retired and living on a fixed income, which increases their possibility of experiencing financial toxicity associated with cancer treatment. The Inflation Reduction Act of 2022 institutes a cap ($2000 annually) on Medicare Part D drug out-of-pocket spending, to be implemented in 2025.192 Beginning in 2025, Medicare Part D enrollees will have the option to pay their out-of-pocket prescription drug costs in capped monthly installments.193 ACS CAN advocates for effective policies that address high out-of-pocket costs for patients with insurance coverage to ensure that all individuals diagnosed with cancer have access to treatment.

Cigarette smoking still accounts for about 30% of all cancer deaths in the United States23 and, in 2019 alone, was associated with about 2.2 million years of life lost because of premature cancer deaths among individuals aged 25–79 years.29 Communities of color, LGBTQ+ communities, and individuals with limited incomes have consistently been targeted by the tobacco industry.194-196 People with limited incomes are more sensitive to price than those with higher incomes and quit tobacco at greater rates after a tax increase.194, 197 Therefore, tobacco excise taxes can benefit people with limited incomes more and reduce tobacco-related health disparities, especially when excise tax revenues are dedicated to cessation programs that serve those people.198-200 In addition, sustained and dedicated federal investment in tobacco control through the CDC’s Office of Smoking and Health is necessary to prevent the initiation of tobacco products, monitor tobacco product use, identify tobacco-related disparities, and promote effective strategies to help individuals who use tobacco products to successfully quit. ACS CAN continues to advocate for evidence-based tobacco prevention and cessation programs and policies at the local, state, and federal levels that aim to reduce disparities and improve health outcomes for all individuals.

Black people have also historically been targeted by the tobacco industry for menthol-flavored tobacco product use201 and have a disproportionately high prevalence of menthol cigarette smoking among people who smoke (81% vs. 34% among White people in 2020).202 The US Food and Drug Administration’s plans to eliminate menthol as a characterizing flavor in cigarettes203, 204 are likely to induce further reductions in tobacco consumption, particularly among Black people. Comprehensive policies to end the sale of flavored tobacco products must include all tobacco products, all flavors, and all tobacco retailers. ACS CAN continues to urge the US Food and Drug Administration to use its full authority to regulate tobacco products and prohibit all flavored products, including menthol.

Ensuring adequate funding for successful cancer-control programs—such as the CDC’s NBCCEDP and the Colorectal Cancer Control Program (see Table S5)—can help all Americans benefit from early detection of these cancers, when treatment is generally more effective.205 ACS CAN urges Congress to increase funding for the NBCCEDP and all CDC cancer screening programs to ensure access to cancer screenings for all individuals.

Differences in social determinants of health, including housing, food insecurity, and transportation, among individuals diagnosed with cancer are associated with disparities in cancer care delivery and survival.206 Information on these determinants of health or how to address those that contribute to cancer disparities (e.g., by housing assistance, food programs, and improving the built environment) could inform and result in interventions with a much greater population-level impact.207, 208 More research is also needed on the implementation of known, effective interventions that are currently underutilized, such as housing voucher programs, which provide supportive housing to individuals with limited incomes.209 Moreover, cancers that have higher incidence rates in the non-Hispanic White population have usually received more research funding compared with cancers that have a higher burden among other racial/ethnic groups.210 More research funding should also be allocated to cancer types that have a disproportionately higher burden among people of color. ACS CAN supports funding and policies to promote timely collection and publication of demographic data that aid researchers and policymakers in identifying disparities to improve health equity in cancer prevention, early detection, and treatment.

Limitations

We have provided information on disparities in cancer occurrence and contributing factors by race/ethnicity, SES, and geographic location, for which more nationally representative data are available. However, cancer disparities can occur by other sociodemographic characteristics, such as sexual identity, disability status, and citizenship status. For example, previous studies have documented limited access to cancer screening and treatment in LGBTQ+ communities211-213 and in persons with disabilities.214-218 Moreover, other studies have reported substantial disparities in cancer occurrence among some subgroups within broad categories of race/ethnicity. Among AIAN females, for example, colorectal cancer incidence rates during 2014 through 2018 was about three times higher in PRCDA counties in Alaska (91.8 per 100,000) than in PRCDA counties in the Southwest (31.2 per 100,000).8 More research is needed to identify cancer disparities, contributing factors, and effective interventions to reduce disparities, particularly in populations that have been under-represented in research studies. There are also multiple measures to identify health disparities by geographic location and rural–urban residence.219 However, many of our findings by urbanicity are likely to be applicable to cancer disparities by geographic location identified using other measures. Moreover, the prevalence of obesity in the United States generally is estimated based on BMI values measured on physical examination in the National Health and Nutrition Examination Survey.220 We used BMI values from the NHIS based on self-reported measures to compare the prevalence of obesity across categories of urbanicity because data by urbanicity were not available from the National Health and Nutrition Examination Survey.

CONCLUSIONS

Despite substantial progress in cancer prevention, early detection, and treatments, the burden of cancer remains greater among populations that have been historically marginalized, including people of color, people with lower SES, and people living in nonmetropolitan areas. Progress against cancer will require equitable policies at all levels of government and broad interdisciplinary engagement to address fundamental inequities in social determinants of health. In the meantime, broad and equitable implementation of evidence-based interventions, such as increasing health insurance coverage, can reduce cancer disparities.

ACKNOWLEDGMENTS

We thank Gladys Arias, Anna Schwamlein Howard, Jennifer Hoque, Mark Fleury, Devon Adams, Katie McMahon, Christy Cushing, Sarah Long, and Sharon Shiver of the American Cancer Society Cancer Action Network for their comments and Emily Marlow and Adair Minihan of the American Cancer Society for their assistance with data acquisition. We gratefully acknowledge the contributions of state and regional cancer registry staff and health department personnel for their work in collecting the data used in this report. This work was supported by the American Cancer Society. The findings and conclusions in this article are those of the authors and do not necessarily represent the official positions of the American Cancer Society.

    CONFLICT OF INTEREST STATEMENT

    K. Robin Yabroff reports service on the Flatiron Health Equity Advisory Board and honoraria from the National Comprehensive Cancer Network outside the submitted work. Kirsten Sloan reports service as an unpaid member of The Alliance for Health Policy board outside the submitted work. Arif H. Kamal reports consultant fees from Acclivity Health and Homebase Medical outside the submitted work and is a fiduciary officer of Prepped Health. Carmen E. Guerra reports grants from the National Cancer Institute, Genentech, and the Lazarex Foundation; service as a member of the advisory board of Guardant Health; honoraria from the National Comprehensive Cancer Network; stock ownership in CRISPR Therapeautics, Beam Therapeutics, Editas, and Intellia Therapeutics; and support for other professional activities from Freenome outside the submitted work. Kirsten Sloan is employed by the American Cancer Society Cancer Action Network, and Farhad Islami, Jordan Baeker Bispo, Hyunjung Lee, Daniel Wiese, K. Robin Yabroff, Priti Bandi, Alpa V. Patel, Elvan C. Daniels, Arif H. Kamal, William L. Dahut, and Ahmedin Jemal are employed by the American Cancer Society, which receives grants from private and corporate foundations, including foundations associated with companies in the health sector for research outside the submitted work. All authors have nothing else to disclose.