Dataset Information

Risk of being killed by police use of force in the United States by age, race-ethnicity, and sex.

ABSTRACT: We use data on police-involved deaths to estimate how the risk of being killed by police use of force in the United States varies across social groups. We estimate the lifetime and age-specific risks of being killed by police by race and sex. We also provide estimates of the proportion of all deaths accounted for by police use of force. We find that African American men and women, American Indian/Alaska Native men and women, and Latino men face higher lifetime risk of being killed by police than do their white peers. We find that Latina women and Asian/Pacific Islander men and women face lower risk of being killed by police than do their white peers. Risk is highest for black men, who (at current levels of risk) face about a 1 in 1,000 chance of being killed by police over the life course. The average lifetime odds of being killed by police are about 1 in 2,000 for men and about 1 in 33,000 for women. Risk peaks between the ages of 20 y and 35 y for all groups. For young men of color, police use of force is among the leading causes of death.

SUBMITTER: Edwards F

PROVIDER: S-EPMC6708348 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Risk of being killed by police use of force in the United States by age, race-ethnicity, and sex.

Edwards Frank F Lee Hedwig H Esposito Michael M

Proceedings of the National Academy of Sciences of the United States of America 20190805 34

We use data on police-involved deaths to estimate how the risk of being killed by police use of force in the United States varies across social groups. We estimate the lifetime and age-specific risks of being killed by police by race and sex. We also provide estimates of the proportion of all deaths accounted for by police use of force. We find that African American men and women, American Indian/Alaska Native men and women, and Latino men face higher lifetime risk of being killed by police than ...[more]

PMID: 31383756

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Project description:ImportanceHealth equity is an often-cited goal of public health, included among the 4 overarching goals of the Department of Health and Human Services' Healthy People 2020. Yet it is difficult to find summary assessments of national progress toward this goal.ObjectivesTo identify variation in several measures of health equity from 1993 to 2017 in the United States and to test whether there are significant time trends.Design, setting, and participantsSurvey study using 25 years of data, from January 1, 1993, to December 31, 2017, from the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System to assess trends in health equity and health justice by race/ethnicity, sex, and income in 3 categories by year.Main outcomes and measuresHealth equity was assessed separately for each of 2 health constructs: healthy days-the average of physical and mental healthy days over the previous 30 days-and general health in 5 categories, rescaled to approximate a continuous variable. For each health construct, average health was calculated along with 4 measures of health equity: disparities across 3 income groups; black-white disparities; health justice-a measure of the correlation of health outcomes with income, race/ethnicity and sex; and a summary health equity metric.ResultsAmong the 5 456 006 respondents, the mean (SD) age was 44.5 (12.7) years; 3 178 688 (58.3%) were female; 4 163 945 (76.3%) were non-Latinx white; 474 855 (8.7%) were non-Latinx black; 419 542 (7.7%) were Latinx; and 397 664 (7.3%) were of other race/ethnicity. The final sample included 5 456 006 respondents for self-reported health and 5 349 527 respondents for healthy days. During the 25-year period, the black-white gap showed significant improvement (year coefficient: healthy days, 0.021; 97.5% CI, 0.012 to 0.029; P < .001; self-reported health, 0.030; 97.5% CI, 0.025 to 0.035; P < .001). The health equity metric for self-reported health showed no significant trend. For healthy days, the Health Equity Metric declined over time (year coefficient: healthy days, -0.025; 97.5% CI, -0.033 to -0.017; P < .001). Health justice declined over time (year coefficient: healthy days, -0.045; 97.5% CI, -0.053 to -0.038; P < .001; self-reported health, -0.035; 97.5% CI, -0.046 to-0.023; P < .001), and income disparities worsened (year coefficient: healthy days, -0.060; 97.5% CI, -0.076 to -0.044; P < .001; self-reported health, -0.029; 97.5% CI, -0.046 to -0.012; P < .001).Conclusions and relevanceResults of this analysis suggest that there has been a clear lack of progress on health equity during the past 25 years in the United States. Achieving widely shared goals of improving health equity will require greater effort from public health policy makers, along with their partners in medicine and the sectors that contribute to the social determinants of health.

Project description:The relevance of race and ethnicity to genetics and medicine has long been a matter of debate. An emerging consensus holds that race and ethnicity are social constructs and thus poor proxies for genetic diversity. The goal of this study was to evaluate the relationship between race, ethnicity, and clinically relevant pharmacogenomic variation in cosmopolitan populations. We studied racially and ethnically diverse cohorts of 65,120 participants from the United States All of Us Research Program (All of Us) and 31,396 participants from the United Kingdom Biobank (UKB). Genome-wide patterns of pharmacogenomic variation-6311 drug response-associated variants for All of Us and 5966 variants for UKB-were analyzed with machine learning classifiers to predict participants' self-identified race and ethnicity. Pharmacogenomic variation predicts race/ethnicity with averages of 92.1% accuracy for All of Us and 94.3% accuracy for UKB. Group-specific prediction accuracies range from 99.0% for the White group in UKB to 92.9% for the Hispanic group in All of Us. Prediction accuracies are substantially lower for individuals who identified with more than one group in All of Us (16.7%) or as Mixed in UKB (70.7%). There are numerous individual pharmacogenomic variants with large allele frequency differences between race/ethnicity groups in both cohorts. Frequency differences for toxicity-associated variants predict hundreds of adverse drug reactions per 1000 treated participants for minority groups in All of Us. Our results indicate that race and ethnicity can be used to stratify pharmacogenomic risk in the US and UK populations and should not be discounted when making treatment decisions. We resolve the contradiction between the results reported here and the orthodoxy of race and ethnicity as non-genetic, social constructs by emphasizing the distinction between global and local patterns of human genetic diversity, and we stress the current and future limitations of race and ethnicity as proxies for pharmacogenomic variation.

Dataset Information

Risk of being killed by police use of force in the United States by age, race-ethnicity, and sex.

Publications

Risk of being killed by police use of force in the United States by age, race-ethnicity, and sex.

Similar Datasets

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