Abstract PO-192: Comparing the association of self-reported race-ethnicity and genetic ancestry with all-cause mortality: A pan-cancer survivor analysis in the PLCO Screening Trial

Abstract Having more years of education is independently associated with lower mortality, but it is unclear whether other attributes of schooling matter. We examined the association of high school quality and all-cause mortality across race/ethnicity. In 1960, about 5% of US high schools participated in Project Talent (PT), which collected information about students and their schools. Over 21,000 PT respondents were followed for mortality into their eighth decade of life using the National Death Index. A school quality factor, capturing term length, class size, and teacher qualifications, was used as the main predictor. First, we estimated overall and sex-stratified Cox proportional hazards models with standard errors clustered at the school level, adjusting for age, sex, composite measure of parental socioeconomic status, and 1960 cognitive ability. Second, we added an interaction between school quality and race/ethnicity. Among this diverse cohort (60% non-Hispanic Whites, 23% non-Hispanic Blacks, 7% Hispanics, 10% classified as another race/s) there were 3,476 deaths (16.5%). School quality was highest for Hispanic respondents and lowest for non-Hispanic Blacks. Non-Hispanic Blacks also had the highest mortality risk. In the whole sample, school quality was not associated with mortality risk. However, higher school quality was associated with lower mortality among those classified as another race/s (HR 0.75, 95% CI: 0.56-0.99). For non-Hispanic Blacks and Whites, the HR point estimates were unreliable, but suggest that higher school quality is associated with increased mortality. Future work will disentangle these differences in association of school quality across race/ethnicity and examine cause-specific mortality.

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Disparities in pan-cancer patients undergoing germline cancer risk assessment by self-reported race/ethnicity and ancestry.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.10508 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 10508-10508

Author(s):

Ying L Liu ◽

Anna Maio ◽

Yelena Kemel ◽

Erin E. Salo-Mullen ◽

Margaret Sheehan ◽

...

Keyword(s):

Cancer Risk ◽

Cancer Patients ◽

Cancer Genetics ◽

Statistical Tests ◽

Cancer Risk Assessment ◽

Clinical Genetics ◽

Multiple Tumor ◽

Race Ethnicity ◽

Pan Cancer

10508 Background: Disparities in access to germline testing for cancer patients (pts) have been demonstrated; however, disparities in post-testing care are unknown. We sought to evaluate germline findings and subsequent genetic counseling/care in cancer pts undergoing tumor-germline sequencing to explore differences by self-reported ancestry. Methods: Pan-cancer pts were prospectively consented to tumor-normal sequencing via a custom NGS panel (MSK-IMPACT) from 1/2015-12/2019 inclusive of germline analysis up to 88 genes. Germline analysis was performed as a research non-billable test in 97.5% of cases. Referral to clinical genetics service (CGS) was recommended for all pts with a new positive (likely pathogenic/pathogenic) germline variant (PV). Ancestry was defined using self-reported Federal definitions of race/ethnicity and designations of Ashkenazi Jewish (AJ) ancestry. Pts were categorized into mutually exclusive groups: AJ, White, Non-White (Asian, Black/African American, Hispanic, Other), and unknown. All pts self-identifying as Hispanic were classified as such, regardless of race. Abstracted data on germline findings and downstream CGS follow-up were compared across groups using non-parametric statistical tests. Results: Among the 15,775 pts in this cohort (59.6% White, 15.7% AJ, 20.5% Non-White [6.9% Asian, 6.8% Black, 6.7% Hispanic, 0.1% Other], and 4.2% unknown), 2663 (17%) had a PV. AJ pts had the highest rates of PV (n = 683, 27.6%), and Non-White pts had a lower proportion of PV (n = 433, 13.6%) compared to Whites (n = 1451, 15.5%), p < 0.01, with differences mostly due to increased prevalence of moderate/low penetrance variants in White and AJ pts . These findings were consistent across multiple tumor types. Prior knowledge of the PV (424/2663, 16%) was more common in Non-White (19.9%) and AJ (19.2%) than White pts (13.4%), p < 0.01. Among 2239 pts with new PV, all were referred to CGS, and 1652 (73.8%) pts were seen. Non-White pts had lower rates of completing visits (67.7%) than White (73.7%) and AJ pts (78.8%), p < 0.01, with the lowest rates occurring in Black (63%) and Hispanic (68.1%) pts. All pts without a visit (n = 587) received a close out letter including 139 pts (6.2% of pts with new PV) who had no documentation of receipt of results in the medical record. Higher rates of non-disclosure were observed in Non-White (6.7%) compared to White (5.4%) and AJ (3.4%) pts with new PV, p = 0.032; non-disclosure did not vary by gene penetrance. There was a non-significant trend towards lower rates of cascade testing at CGS in Asian and Black pts with ongoing analysis. Conclusions: Even when traditional barriers to genetic testing were minimized, Non-White pts were less likely to receive recommended cancer genetics follow-up for subsequent cancer risk counseling, with potential implications for oncological care, cancer risk reduction, and at-risk family members.

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Excess Mortality During the COVID-19 Pandemic in Philadelphia

American Journal of Public Health ◽

10.2105/ajph.2021.306285 ◽

2021 ◽

pp. e1-e6

Author(s):

Megan Todd ◽

Meagan Pharis ◽

Sam P. Gulino ◽

Jessica M. Robbins ◽

Cheryl Bettigole

Keyword(s):

Public Health ◽

Excess Mortality ◽

Poisson Model ◽

People Of Color ◽

Mortality Data ◽

Registration System ◽

Vital Registration System ◽

All Cause Mortality ◽

Race Ethnicity ◽

Excess Deaths

Objectives. To estimate excess all-cause mortality in Philadelphia, Pennsylvania, during the COVID-19 pandemic and understand the distribution of excess mortality in the population. Methods. With a Poisson model trained on recent historical data from the Pennsylvania vital registration system, we estimated expected weekly mortality in 2020. We compared these estimates with observed mortality to estimate excess mortality. We further examined the distribution of excess mortality by age, sex, and race/ethnicity. Results. There were an estimated 3550 excess deaths between March 22, 2020, and January 2, 2021, a 32% increase above expectations. Only 77% of excess deaths (n=2725) were attributed to COVID-19 on the death certiﬁcate. Excess mortality was disproportionately high among older adults and people of color. Sex differences varied by race/ethnicity. Conclusions. Excess deaths during the pandemic were not fully explained by COVID-19 mortality; ofﬁcial counts signiﬁcantly undercount the true death toll. Far from being a great equalizer, the COVID-19 pandemic has exacerbated preexisting disparities in mortality by race/ethnicity. Public Health Implications. Mortality data must be disaggregated by age, sex, and race/ethnicity to accurately understand disparities among groups. (Am J Public Health. Published online ahead of print June 10, 2021: e1–e6. https://doi.org/10.2105/AJPH.2021.306285 )

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The Independent And Combined Effects Of Aerobic Physical Activity And Muscular Strengthening Activity On All-Cause Mortality: An Analysis Of Effect Modification By Race-Ethnicity

Medicine & Science in Sports & Exercise ◽

10.1249/01.mss.0000675180.77844.c3 ◽

2020 ◽

Vol 52 (7S) ◽

pp. 158-158

Author(s):

William Boyer ◽

James Churilla ◽

Amy Miller ◽

Trevor Gillum ◽

Marshare Penny

Keyword(s):

Physical Activity ◽

Effect Modification ◽

Combined Effects ◽

All Cause Mortality ◽

Race Ethnicity

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Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies

The American Journal of Human Genetics ◽

10.1016/j.ajhg.2019.08.012 ◽

2019 ◽

Vol 105 (4) ◽

pp. 763-772 ◽

Cited By ~ 18

Author(s):

Huaying Fang ◽

Qin Hui ◽

Julie Lynch ◽

Jacqueline Honerlaw ◽

Themistocles L. Assimes ◽

...

Keyword(s):

Association Studies ◽

Genetic Ancestry ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Race Ethnicity

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Abstract 3724: Race/ethnicity, genetic ancestry, and breast cancer-related lymphedema

10.1158/1538-7445.am2015-3724 ◽

2015 ◽

Author(s):

Marilyn L. Kwan ◽

Valerie S. Lee ◽

Janise M. Roh ◽

Isaac J. Ergas ◽

Yali Zhang ◽

...

Keyword(s):

Breast Cancer ◽

Genetic Ancestry ◽

Race Ethnicity ◽

Breast Cancer Related Lymphedema

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The Independent and Combined Effects of Aerobic Physical Activity and Muscular Strengthening Activity on All-Cause Mortality: An Analysis of Effect Modification by Race-Ethnicity

Journal of Physical Activity and Health ◽

10.1123/jpah.2019-0581 ◽

2020 ◽

Vol 17 (9) ◽

pp. 881-888

Author(s):

William Boyer ◽

James Churilla ◽

Amy Miller ◽

Trevor Gillum ◽

Marshare Penny

Keyword(s):

Physical Activity ◽

Mexican American ◽

Significant Risk ◽

Potential Effect ◽

Effect Modification ◽

Health And Nutrition ◽

All Cause Mortality ◽

Cox Proportional Hazard Models ◽

Race Ethnicity ◽

Hispanic White

Background: The effects of aerobic physical activity (PA) and muscular strengthening activity (MSA) on all-cause mortality risk need further exploration among ethnically diverse populations. Purpose: To examine potential effect modification of race-ethnicity on meeting the PA guidelines and on all-cause mortality. Methods: The study sample (N = 14,384) included adults (20–79 y of age) from the 1999–2006 National Health and Nutrition Examination Survey. PA was categorized into 6 categories based on the 2018 PA guidelines: category 1 (inactive), category 2 (insufficient PA and no MSA), category 3 (active and no MSA), category 4 (no PA and sufficient MSA), category 5 (insufficient PA and sufficient MSA), and category 6 (meeting both recommendations). Race-ethnic groups examined included non-Hispanic white, non-Hispanic black, and Mexican American. Cox-proportional hazard models were used. Results: Significant risk reductions were found for categories 2, 3, and 6 for non-Hispanic white and non-Hispanic black. Among Mexican American, significant risk reductions were found in category 6. Conclusion: In support of the 2018 PA guidelines, meeting both the aerobic PA and MSA guidelines significantly reduced risk for all-cause mortality independent of race-ethnicity. The effects of aerobic PA alone seem to be isolated to non-Hispanic white and non-Hispanic black.

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Rural-Urban Mortality Disparities: Variations Across Causes of Death and Race/Ethnicity, 2013–2017

American Journal of Public Health ◽

10.2105/ajph.2020.305703 ◽

2020 ◽

Vol 110 (9) ◽

pp. 1325-1327 ◽

Cited By ~ 1

Author(s):

Janice C. Probst ◽

Whitney E. Zahnd ◽

Peiyin Hung ◽

Jan M. Eberth ◽

Elizabeth L. Crouch ◽

...

Keyword(s):

Respiratory Disease ◽

Alaska Native ◽

Causes Of Death ◽

The United States ◽

Death Rates ◽

All Cause Mortality ◽

Race Ethnicity ◽

Black Populations ◽

Lower Respiratory Disease ◽

Hispanic White

Objectives. To examine rural-urban disparities in overall mortality and leading causes of death across Hispanic (any race) and non-Hispanic White, Black, American Indian/Alaska Native (AI/AN), and Asian/Pacific Islander populations. Methods. We performed a retrospective analysis of age-adjusted death rates for all-cause mortality and 5 leading causes of death (cardiovascular, cancer, unintentional injuries, chronic lower respiratory disease, and stroke) by rural versus urban county of residence in the United States and race/ethnicity for the period 2013 to 2017. Results. Rural populations, across all racial/ethnic groups, had higher all-cause mortality rates than did their urban counterparts. Comparisons within causes of death documented rural disparities for all conditions except cancer and stroke among Hispanic individuals; Hispanic rural residents had death rates similar to or lower than urban residents. Rural Black populations experienced the highest mortality for cardiovascular disease, cancer, and stroke. Unintentional injury and chronic lower respiratory disease mortality were highest in rural AI/AN and rural non-Hispanic White populations, respectively. Conclusions. Investigating rural-urban disparities without also considering race/ethnicity leaves minority health disparities unexamined and thus unaddressed. Further research is needed to clarify local factors associated with these disparities and to test appropriate interventions.

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