scholarly journals Commentary: Understanding religious involvement and mortality risk in the United States: comment on Bagiella, Hong, and Sloan

2005 ◽  
Vol 34 (2) ◽  
pp. 452-453 ◽  
Author(s):  
Robert A Hummer
Author(s):  
Esteban Correa-Agudelo ◽  
Tesfaye B. Mersha ◽  
Adam J. Branscum ◽  
Neil J. MacKinnon ◽  
Diego F. Cuadros

We characterized vulnerable populations located in areas at higher risk of COVID-19-related mortality and low critical healthcare capacity during the early stage of the epidemic in the United States. We analyze data obtained from a Johns Hopkins University COVID-19 database to assess the county-level spatial variation of COVID-19-related mortality risk during the early stage of the epidemic in relation to health determinants and health infrastructure. Overall, we identified highly populated and polluted areas, regional air hub areas, race minorities (non-white population), and Hispanic or Latino population with an increased risk of COVID-19-related death during the first phase of the epidemic. The 10 highest COVID-19 mortality risk areas in highly populated counties had on average a lower proportion of white population (48.0%) and higher proportions of black population (18.7%) and other races (33.3%) compared to the national averages of 83.0%, 9.1%, and 7.9%, respectively. The Hispanic and Latino population proportion was higher in these 10 counties (29.3%, compared to the national average of 9.3%). Counties with major air hubs had a 31% increase in mortality risk compared to counties with no airport connectivity. Sixty-eight percent of the counties with high COVID-19-related mortality risk also had lower critical care capacity than the national average. The disparity in health and environmental risk factors might have exacerbated the COVID-19-related mortality risk in vulnerable groups during the early stage of the epidemic.


2019 ◽  
Vol 23 (10) ◽  
pp. 1382-1391 ◽  
Author(s):  
David B. Braudt ◽  
Elizabeth M. Lawrence ◽  
Andrea M. Tilstra ◽  
Richard G. Rogers ◽  
Robert A. Hummer

2013 ◽  
Vol 178 (4) ◽  
pp. 521-533 ◽  
Author(s):  
S.-W. Lin ◽  
D. C. Wheeler ◽  
Y. Park ◽  
M. Spriggs ◽  
A. R. Hollenbeck ◽  
...  

2004 ◽  
Vol 97 (12) ◽  
pp. 1223-1230 ◽  
Author(s):  
Robert A. Hummer ◽  
Christopher G. Ellison ◽  
Richard G. Rogers ◽  
Benjamin E. Moulton ◽  
Ron R. Romero

2013 ◽  
Vol 32 (3) ◽  
pp. 325-352 ◽  
Author(s):  
Richard G. Rogers ◽  
Patrick M. Krueger ◽  
Richard Miech ◽  
Elizabeth M. Lawrence ◽  
Robert Kemp

2020 ◽  
Author(s):  
Nam Pho ◽  
Arjun K Manrai ◽  
John T Leppert ◽  
Glenn M Chertow ◽  
John P A Ioannidis ◽  
...  

Abstract Background Physicians sometimes consider whether or not to perform diagnostic testing in healthy people, but it is unknown whether nonextreme values of diagnostic tests typically encountered in such populations have any predictive ability, in particular for risk of death. The goal of this study was to quantify the associations among population reference intervals of 152 common biomarkers with all-cause mortality in a representative, nondiseased sample of adults in the United States. Methods The study used an observational cohort derived from the National Health and Nutrition Examination Survey (NHANES), a representative sample of the United States population consisting of 6 survey waves from 1999 to 2010 with linked mortality data (unweighted N = 30 651) and a median followup of 6.1 years. We deployed an X-wide association study (XWAS) approach to systematically perform association testing of 152 diagnostic tests with all-cause mortality. Results After controlling for multiple hypotheses, we found that the values within reference intervals (10–90th percentiles) of 20 common biomarkers used as diagnostic tests or clinical measures were associated with all-cause mortality, including serum albumin, red cell distribution width, serum alkaline phosphatase, and others after adjusting for age (linear and quadratic terms), sex, race, income, chronic illness, and prior-year healthcare utilization. All biomarkers combined, however, explained only an additional 0.8% of the variance of mortality risk. We found modest year-to-year changes, or changes in association from survey wave to survey wave from 1999 to 2010 in the association sizes of biomarkers. Conclusions Reference and nonoutlying variation in common biomarkers are consistently associated with mortality risk in the US population, but their additive contribution in explaining mortality risk is minor.


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