Alternative Methods for Grouping Race and Ethnicity to Monitor COVID-19 Outcomes and Vaccination Coverage.

Population-based analyses of COVID-19 data, by race and ethnicity can identify and monitor disparities in COVID-19 outcomes and vaccination coverage. CDC recommends that information about race and ethnicity be collected to identify disparities and ensure equitable access to protective measures such as vaccines; however, this information is often missing in COVID-19 data reported to CDC. Baseline data collection requirements of the Office of Management and Budget's Standards for the Classification of Federal Data on Race and Ethnicity (Statistical Policy Directive No. 15) include two ethnicity categories and a minimum of five race categories (1). Using available COVID-19 case and vaccination data, CDC compared the current method for grouping persons by race and ethnicity, which prioritizes ethnicity (in alignment with the policy directive), with two alternative methods (methods A and B) that used race information when ethnicity information was missing. Method A assumed non-Hispanic ethnicity when ethnicity data were unknown or missing and used the same population groupings (denominators) for rate calculations as the current method (Hispanic persons for the Hispanic group and race category and non-Hispanic persons for the different racial groups). Method B grouped persons into ethnicity and race categories that are not mutually exclusive, unlike the current method and method A. Denominators for rate calculations using method B were Hispanic persons for the Hispanic group and persons of Hispanic or non-Hispanic ethnicity for the different racial groups. Compared with the current method, the alternative methods resulted in higher counts of COVID-19 cases and fully vaccinated persons across race categories (American Indian or Alaska Native [AI/AN], Asian, Black or African American [Black], Native Hawaiian or Other Pacific Islander [NH/PI], and White persons). When method B was used, the largest relative increase in cases (58.5%) was among AI/AN persons and the largest relative increase in the number of those fully vaccinated persons was among NH/PI persons (51.6%). Compared with the current method, method A resulted in higher cumulative incidence and vaccination coverage rates for the five racial groups. Method B resulted in decreasing cumulative incidence rates for two groups (AI/AN and NH/PI persons) and decreasing cumulative vaccination coverage rates for AI/AN persons. The rate ratio for having a case of COVID-19 by racial and ethnic group compared with that for White persons varied by method but was <1 for Asian persons and >1 for other groups across all three methods. The likelihood of being fully vaccinated was highest among NH/PI persons across all three methods. This analysis demonstrates that alternative methods for analyzing race and ethnicity data when data are incomplete can lead to different conclusions about disparities. These methods have limitations, however, and warrant further examination of potential bias and consultation with experts to identify additional methods for analyzing and tracking disparities when race and ethnicity data are incomplete.

Breast and cervical cancers diagnosed and stage at diagnosis among women served through the National Breast and Cervical Cancer Early Detection Program.

PURPOSE: To assess cancers diagnosed and the stage of cancer at the time of diagnosis among low-income, under-insured, or uninsured women who received services through the National Breast and Cervical Cancer Early Detection Program (NBCCEDP). METHODS: Using the NBCCEDP database, we examined the number and percent of women diagnosed during 2009-2011 with in situ breast cancer, invasive breast cancer, and invasive cervical cancer by demographic and clinical characteristics, including age, race and ethnicity, test indication (screening or diagnostic), symptoms (for breast cancer), and screening history (for cervical cancer). We examined these characteristics by stage at diagnosis, a new variable included in the database obtained by linking with state-based central cancer registries. RESULTS: There were 11,569 women diagnosed with invasive breast cancer, 1,988 with in situ breast cancer, and 583 with invasive cervical cancer through the NBCCEDP. Women who reported breast symptoms or who had diagnostic mammography were more likely to be diagnosed with breast cancer, and at a later stage, than those who did not have symptoms or who had screening mammography. Women who had been rarely or never screened for cervical cancer were more likely to be diagnosed with cervical cancer, and at a later stage, than women who received regular screenings. CONCLUSIONS: Women served through the NBCCEDP who have not had prior screening or who have symptoms were more often diagnosed with late-stage disease.

Ambient air pollution and brain cancer mortality.

OBJECTIVE: Growing evidence that ultrafine particles in ambient air can cause brain lesions in animals led us to investigate whether particulate components of air pollution may be associated with brain cancer risk in humans. Air pollution has been associated with respiratory disorders and cardiovascular morbidity and mortality, but associations between air pollutants and brain cancer have not been investigated in adults. METHODS: The analyses included 1,284 deaths due to brain cancer from the Cancer Prevention Study-II, an ongoing prospective mortality study of adults in the United States and Puerto Rico conducted by the American Cancer Society. Air pollution data from national databases for metropolitan areas were combined with residential history and vital status data to estimate exposure to particulate and gaseous air pollution. RESULTS: We found no elevated risk for estimated measures of air pollutants, an unanticipated reduction in risk was found between gaseous air pollutants and brain cancer mortality. CONCLUSION: The findings do not provide evidence of increased risk of brain cancer mortality due to air pollutants.

Cancer mortality in the United States by education level and race.

BACKGROUND: Although both race and socioeconomic status are well known to influence mortality patterns in the United States, few studies have examined the simultaneous influence of these factors on cancer incidence and mortality. We examined relationships among race, education level, and mortality from cancers of the lung, breast, prostate, colon and rectum, and all sites combined in contemporary US vital statistics. METHODS: Age-adjusted cancer death rates (with 95% confidence intervals [CIs]) were calculated for 137,708 deaths among 119,376,196 individuals aged 25-64 years, using race and education information from death certificates and population denominator data from the US Bureau of the Census, for 47 states and Washington, DC, in 2001. Relative risk (RR) estimates were used to compare cancer death rates in persons with 12 or fewer years of education with those in persons with more than 12 years of education. RESULTS: Educational attainment was strongly and inversely associated with mortality from all cancers combined in black and white men and in white women. The all-cancer death rates were nearly identical for black men and white men with 0-8 years of education (224.2 and 223.6 per 100,000, respectively). The estimated relative risk for all-cancer mortality comparing the three lowest (< or = 12 years) with the three highest (> 12 years) education categories was 2.38 (95% CI = 2.33 to 2.43) for black men, 2.24 (95% CI = 2.23 to 2.26) for white men, 1.43 (95% CI = 1.41 to 1.46) for black women, and 1.76 (95% CI = 1.75 to 1.78) for white women. For both men and women, the magnitude of the relative risks comparing the three lowest educational levels with the three highest within each race for all cancers combined and for lung and colorectal cancers was higher than the magnitude of the relative risks associated with race within each level of education, whereas for breast and prostate cancer the magnitude of the relative risks associated with race was higher than the magnitude of the relative risks associated with level of education within each racial group. Among the most important and novel findings were that black men who completed 12 or fewer years of education had a prostate cancer death rate that was more than double that of black men with more schooling (10.5 versus 4.8 per 100,000 men; RR = 2.17, 95% CI = 1.82 to 2.58) and that, in contrast with studies of mortality rates in earlier time periods, breast cancer mortality rates were higher among women with less education than among women with more education (37.0 and 31.1 per 100,000, respectively, for black women and 25.2 versus 18.6 per 100,000, respectively, for white women). CONCLUSION: Cancer death rates vary considerably by level of education. Identifying groups at high risk of death from cancer by level of education as well as by race may be useful in targeting interventions and tracking cancer disparities.

All-cause and cause-specific death rates by educational status for two million people in two American Cancer Society cohorts, 1959-1996.

Low socioeconomic status is associated with high mortality, but the extent to which socioeconomic status affects particular diseases and whether socioeconomic status effects have changed over time are uncertain. The authors used education as a marker for socioeconomic status in a study of two large American Cancer Society cohorts (follow-up, 1959-1996). Low education was associated with higher death rates in both cohorts from all causes and most specific causes, except breast cancer and external causes among women. Life expectancy in the more recent cohort was 4.8 years shorter for men and 2.7 years shorter for women for the least versus the most educated. The inverse relation between education and mortality was strongest for coronary heart disease, lung cancer, diabetes, and chronic obstructive pulmonary disease; moderate for colorectal cancer, external causes (men only), and stroke; weak for prostate cancer; and reversed for external causes among women. The direction of a weak gradient for breast cancer differed for those with and without prevalent breast cancer at baseline. Adjustment for conventional risk factors, probable intermediate variables between education and mortality, diminished but did not eliminate the observed educational/mortality gradients. Temporal trends showed increasing mortality differences by education for coronary heart disease, diabetes, and lung cancer for women.

Individual- and area-level socioeconomic status variables as predictors of mortality in a cohort of 179,383 persons.

The authors have studied whether area-level socioeconomic status predicts mortality independently of individual-level socioeconomic status in 179,383 persons in the American Cancer Society Nutrition Cohort, followed for mortality from 1992 to 2000 (17,383 deaths). They used an area-level variable based on census blocks that was an average of home value, income, education, and occupation. Education was the individual-level socioeconomic status variable. The authors studied socioeconomic status-mortality trends with each socioeconomic status variable adjusted for the other. For all causes, an individual's education was strongly and inversely associated with mortality; a weak but significant inverse trend was also present for area-level socioeconomic status. A similar pattern was seen for all-vascular disease. For all cancers, there was again a significant inverse trend with education but no trend with area-level socioeconomic status. Adjustment for conventional (non-socioeconomic status) individual-level risk factors diminished the effect of both socioeconomic status variables, although significant trends remained for men between education and all-cause, all-cancer, and all-vascular disease mortality. Study data indicate that the predictive value of area-level socioeconomic status variables varies by cause of death but is less important than individual-level socioeconomic status variables. Multivariate models that consider socioeconomic status as a potential confounder may not need to consider area-level socioeconomic status if data are available on individual-level education.