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10.1111/jrh.12557 http://scihub22266oqcxt.onion/10.1111/jrh.12557 33619746!8014225!33619746     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Rural+Health 2021 ; 37 (2): 278-286 Nephropedia Template TP {{tp|p=33619746|t=2021. The Association of Social Determinants of Health With COVID-19 Mortality in Rural and Urban Counties |pdf=|usr=}}{{33619746}} gab.com Text The Association of Social Determinants of Health With COVID-19 Mortality in Rural and Urban Counties JO: J Rural Health http://www.kidney.de/pget.php?&tw=1&pmid=33619746 #FOAvip PURPOSE: To identify the county-level effects of social determinants of health (SDoH) on COVID-19 (corona virus disease 2019) mortality rates by rural-urban residence and estimate county-level exceedance probabilities for detecting clusters. METHODS: The county-level data on COVID-19 death counts as of October 23, 2020, were obtained from the Johns Hopkins University. SDoH data were collected from the County Health Ranking and Roadmaps, the US Department of Agriculture, and the Bureau of Labor Statistics. Semiparametric negative binomial regressions with expected counts based on standardized mortality rates as offset variables were fitted using integrated Laplace approximation. Bayesian significance was assessed by 95% credible intervals (CrI) of risk ratios (RR). County-level mortality hotspots were identified by exceedance probabilities. FINDINGS: The COVID-19 mortality rates per 100,000 were 65.43 for the urban and 50.78 for the rural counties. Percent of Blacks, HIV, and diabetes rates were significantly associated with higher mortality in rural and urban counties, whereas the unemployment rate (adjusted RR = 1.479, CrI = 1.171, 1.867) and residential segregation (adjusted RR = 1.034, CrI = 1.019, 1.050) were associated with increased mortality in urban counties. Counties with a higher percentage of college or associate degrees had lower COVID-19 mortality rates. CONCLUSIONS: SDoH plays an important role in explaining differential COVID-19 mortality rates and should be considered for resource allocations and policy decisions on operational needs for businesses and schools at county levels. Twit Text FOAVip The Association of Social Determinants of Health With COVID-19 Mortality in Rural and Urban Counties ????J Rural Health http://www.kidney.de/pget.php?&tw=1&pmid=33619746 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33619746 #FOAvip English Wikipedia <ref>{{Cite pmid|33619746}}</ref> The Association of Social Determinants of Health With COVID-19 Mortality in Rural and Urban Counties #MMPMID33619746 Paul R; Arif A; Pokhrel K; Ghosh S J Rural Health 2021[Mar]; 37 (2): 278-286 PMID33619746show ga PURPOSE: To identify the county-level effects of social determinants of health (SDoH) on COVID-19 (corona virus disease 2019) mortality rates by rural-urban residence and estimate county-level exceedance probabilities for detecting clusters. METHODS: The county-level data on COVID-19 death counts as of October 23, 2020, were obtained from the Johns Hopkins University. SDoH data were collected from the County Health Ranking and Roadmaps, the US Department of Agriculture, and the Bureau of Labor Statistics. Semiparametric negative binomial regressions with expected counts based on standardized mortality rates as offset variables were fitted using integrated Laplace approximation. Bayesian significance was assessed by 95% credible intervals (CrI) of risk ratios (RR). County-level mortality hotspots were identified by exceedance probabilities. FINDINGS: The COVID-19 mortality rates per 100,000 were 65.43 for the urban and 50.78 for the rural counties. Percent of Blacks, HIV, and diabetes rates were significantly associated with higher mortality in rural and urban counties, whereas the unemployment rate (adjusted RR = 1.479, CrI = 1.171, 1.867) and residential segregation (adjusted RR = 1.034, CrI = 1.019, 1.050) were associated with increased mortality in urban counties. Counties with a higher percentage of college or associate degrees had lower COVID-19 mortality rates. CONCLUSIONS: SDoH plays an important role in explaining differential COVID-19 mortality rates and should be considered for resource allocations and policy decisions on operational needs for businesses and schools at county levels. |*Social Determinants of Health[MESH] |Black People/statistics & numerical data[MESH] |COVID-19/*mortality[MESH] |Diabetes Mellitus/epidemiology[MESH] |Female[MESH] |HIV Infections/epidemiology[MESH] |Humans[MESH] |Male[MESH] |Rural Population/*statistics & numerical data[MESH] |Social Segregation[MESH] |Unemployment/statistics & numerical data[MESH] |United States/epidemiology[MESH]The Association of Social Determinants of Health With COVID-19 Mortali(epmc).pdf DeepDyve Pubget Overpricing