County Reclassifications and Rural–Urban Mortality Disparities in the United States (1970–2018)

2020 ◽  
Vol 110 (12) ◽  
pp. 1814-1816
Author(s):  
Matthew M. Brooks ◽  
J. Tom Mueller ◽  
Brian C. Thiede
Keyword(s):  
United States ◽  
Health Disparities ◽  
Longitudinal Research ◽  
The United States ◽  
Mortality Rates ◽  
Policy Interventions ◽  
Rural And Urban ◽  
Urban Classification ◽  
Mortality Disparities ◽  
Over Time

Objectives. To demonstrate how inferences about rural–urban disparities in age-adjusted mortality are affected by the reclassification of rural and urban counties in the United States from 1970 to 2018. Methods. We compared estimates of rural–urban mortality disparities over time, produced through a time-varying classification of rural and urban counties, with counterfactual estimates of rural–urban disparities, assuming no changes in rural–urban classification since 1970. We evaluated mortality rates by decade of reclassification to assess selectivity in reclassification. Results. We found that reclassification amplified rural–urban mortality disparities and accounted for more than 25% of the rural disadvantage observed from 1970 to 2018. Mortality rates were lower in counties that reclassified from rural to urban than in counties that remained rural. Conclusions. Estimates of changing rural–urban mortality differentials are significantly influenced by rural–urban reclassification. On average, counties that have remained classified as rural over time have elevated mortality. Longitudinal research on rural–urban health disparities must consider the methodological and substantive implications of reclassification. Public Health Implications. Attention to rural–urban reclassification is necessary when evaluating or justifying policy interventions focusing on geographic health disparities.

scholarly journals The Enduring Association between Education and Mortality

2011 ◽  
Vol 76 (6) ◽  
pp. 913-934 ◽  
Author(s):  
Richard Miech ◽  
Fred Pampel ◽  
Jinyoung Kim ◽  
Richard G. Rogers
Keyword(s):  
United States ◽  
Health Disparities ◽  
Causes Of Death ◽  
The United States ◽  
Mortality Rates ◽  
Social Forces ◽  
Educational Disparities ◽  
Fundamental Cause ◽  
Almost All ◽  
Over Time

This article examines how educational disparities in mortality emerge, grow, decline, and disappear across causes of death in the United States, and how these changes contribute to the enduring association between education and mortality over time. Focusing on adults age 40 to 64 years, we first examine the extent to which educational disparities in mortality persisted from 1989 to 2007. We then test the fundamental cause prediction that educational disparities in mortality persist, in part, by shifting to new health outcomes over time. We focus on the period from 1999 to 2007, when all causes of death were coded to the same classification system. Results indicate (1) substantial widening and narrowing of educational disparities in mortality across causes of death, (2) almost all causes of death with increasing mortality rates also had widening educational disparities, and (3) the total educational disparity in mortality would be about 25 percent smaller today if not for newly emergent and growing educational disparities since 1999. These results point to the theoretical and policy importance of identifying social forces that cause health disparities to widen over time.

scholarly journals The evolution of infant mortality inequality in the United States, 1960–2016

2020 ◽  
Vol 6 (29) ◽  
pp. eaba5908
Author(s):  
Nick Turner ◽  
Kaveh Danesh ◽  
Kelsey Moran
Keyword(s):  
United States ◽  
Infant Mortality ◽  
The United States ◽  
Mortality Rates ◽  
County Level ◽  
Level Data ◽  
Antipoverty Programs ◽  
The Relationship ◽  
Over Time ◽  
Mortality Inequality

What is the relationship between infant mortality and poverty in the United States and how has it changed over time? We address this question by analyzing county-level data between 1960 and 2016. Our estimates suggest that level differences in mortality rates between the poorest and least poor counties decreased meaningfully between 1960 and 2000. Nearly three-quarters of the decrease occurred between 1960 and 1980, coincident with the introduction of antipoverty programs and improvements in medical care for infants. We estimate that declining inequality accounts for 18% of the national reduction in infant mortality between 1960 and 2000. However, we also find that level differences between the poorest and least poor counties remained constant between 2000 and 2016, suggesting an important role for policies that improve the health of infants in poor areas.

scholarly journals Trends in heart failure-related cardiovascular mortality in rural versus urban United States counties, 2011–2018: A cross-sectional study

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0246813
Author(s):  
Jacob B. Pierce ◽  
Nilay S. Shah ◽  
Lucia C. Petito ◽  
Lindsay Pool ◽  
Donald M. Lloyd-Jones ◽  
...  
Keyword(s):  
United States ◽  
Heart Failure ◽  
Cause Of Death ◽  
Negative Binomial ◽  
The United States ◽  
Mortality Rates ◽  
County Level ◽  
Physician Density ◽  
Rural And Urban ◽  
Related Mortality

Background Adults in rural counties in the United States (US) experience higher rates broadly of cardiovascular disease (CVD) compared with adults in urban counties. Mortality rates specifically due to heart failure (HF) have increased since 2011, but estimates of heterogeneity at the county-level in HF-related mortality have not been produced. The objectives of this study were 1) to quantify nationwide trends by rural-urban designation and 2) examine county-level factors associated with rural-urban differences in HF-related mortality rates. Methods and findings We queried CDC WONDER to identify HF deaths between 2011–2018 defined as CVD (I00-78) as the underlying cause of death and HF (I50) as a contributing cause of death. First, we calculated national age-adjusted mortality rates (AAMR) and examined trends stratified by rural-urban status (defined using 2013 NCHS Urban-Rural Classification Scheme), age (35–64 and 65–84 years), and race-sex subgroups per year. Second, we combined all deaths from 2011–2018 and estimated incidence rate ratios (IRR) in HF-related mortality for rural versus urban counties using multivariable negative binomial regression models with adjustment for demographic and socioeconomic characteristics, risk factor prevalence, and physician density. Between 2011–2018, 162,314 and 580,305 HF-related deaths occurred in rural and urban counties, respectively. AAMRs were consistently higher for residents in rural compared with urban counties (73.2 [95% CI: 72.2–74.2] vs. 57.2 [56.8–57.6] in 2018, respectively). The highest AAMR was observed in rural Black men (131.1 [123.3–138.9] in 2018) with greatest increases in HF-related mortality in those 35–64 years (+6.1%/year). The rural-urban IRR persisted among both younger (1.10 [1.04–1.16]) and older adults (1.04 [1.02–1.07]) after adjustment for county-level factors. Main limitations included lack of individual-level data and county dropout due to low event rates (<20). Conclusions Differences in county-level factors may account for a significant amount of the observed variation in HF-related mortality between rural and urban counties. Efforts to reduce the rural-urban disparity in HF-related mortality rates will likely require diverse public health and clinical interventions targeting the underlying causes of this disparity.

scholarly journals COVID-19 mortality rates for persons with intellectual and developmental disabilities

2021 ◽  
Vol 2 (1) ◽  
pp. 179-183
Author(s):  
Mark D. Davis ◽  
Scott Spreat ◽  
Ryan Cox ◽  
Matthew Holder ◽  
Kathryn M. Burke ◽  
...  
Keyword(s):  
United States ◽  
Developmental Disabilities ◽  
General Population ◽  
General Public ◽  
The United States ◽  
Mortality Rates ◽  
Intellectual And Developmental Disabilities ◽  
Time Points ◽  
Probability Of Death ◽  
Over Time

People with intellectual and developmental disabilities (IDD) appear to have an increased probability of death from COVID-19 once infected. We report infection and mortality rates for people with IDD compared to the general population of eight states at two time points during the COVID-19 pandemic. Note that these eight states contain approximately 1/3 of the population of the United States. These data suggest individuals with IDD are less likely to be infected with the COVID-19 virus (5.62%) than the general public (7.57%). However, while mortality rates for both groups have declined over time, people with IDD are over twice as likely (2.29) to die from the infection as members of the general public.

scholarly journals Combating COVID-19 with Charisma: Evidence on Governor Speeches and Physical Distancing in the United States

2021 ◽  
Author(s):  
Ulrich Jensen ◽  
Dominic Rohner ◽  
Olivier Bornet ◽  
Daniel Carron ◽  
Phillip Garner ◽  
...  
Keyword(s):  
United States ◽  
Laboratory Experiment ◽  
The United States ◽  
Individual Behavior ◽  
Smart Phones ◽  
Policy Interventions ◽  
Anonymized Data ◽  
Over Time

We show that governor charisma can affect individual behavior to help mitigate COVID-related outcomes. We provide evidence in the field using deep neural ratings of charisma of governor speeches over time to explain physical distancing based on anonymized data from smart phones. We also show in an incentivized laboratory experiment that individuals who are conservative are more responsive to charismatic appeals of a governor, which drives their beliefs on whether their co-citizens will physically distance; these beliefs in turn appear to affect their behavior too. Interestingly, liberals are unaffected by charisma, as a result of their preference to physically distance regardless. These findings are important because they show that a learnable skill—or at least one that can be honed—can give leaders an additional weapon to complement policy interventions for pandemics, especially with certain populations who may need a “nudge,” and hence save lives.

scholarly journals Trends in Mortality Due to Cancer in the United States by Age and County-Level Income, 1999–2015

2019 ◽  
Vol 111 (8) ◽  
pp. 863-866 ◽  
Author(s):  
Diana R Withrow ◽  
Amy Berrington de González ◽  
Susan Spillane ◽  
Neal D Freedman ◽  
Ana F Best ◽  
...  
Keyword(s):  
United States ◽  
Cancer Mortality ◽  
Death Certificate ◽  
The United States ◽  
Mortality Rates ◽  
Income Quintile ◽  
County Level ◽  
Younger Adults ◽  
Rate Ratios ◽  
Over Time

Abstract Disparities in cancer mortality by county-level income have increased. It is unclear whether these widening disparities have affected older and younger adults equally. National death certificate data were utilized to ascertain cancer deaths during 1999–2015. Average annual percent changes in mortality rates and mortality rate ratios (RRs) were estimated by county-level income quintile and age (25–64 vs ≥65 years). Among 25- to 64-year-olds, cancer mortality rates were 30% higher (RR = 1.30, 95% confidence interval [CI] = 1.29 to 1.31) in the lowest-vs the highest-income counties in 1999–2001 and 56% higher (RR = 1.56, 95% CI = 1.55 to 1.57) in 2013–2015; the disparities among those 65 years and older were smaller but also widened over time (RR1999–2001 = 1.04, 95% CI = 1.03 to 1.05; RR2013–2015 = 1.14, 95% CI = 1.13 to 1.14). Widening disparities occurred across cancer sites. If all counties had the mortality rates of the highest-income counties, 21.5% of cancer deaths among 25- to 64-year-olds and 7.3% of cancer deaths in those 65 years and older would have been avoided in 2015. These results highlight an ongoing need for equity-focused interventions, particularly among younger adults.

scholarly journals How differential privacy will affect our understanding of health disparities in the United States

2020 ◽  
Vol 117 (24) ◽  
pp. 13405-13412 ◽  
Author(s):  
Alexis R. Santos-Lozada ◽  
Jeffrey T. Howard ◽  
Ashton M. Verdery
Keyword(s):  
United States ◽  
Health Disparities ◽  
Ethnic Groups ◽  
Census Data ◽  
Differential Privacy ◽  
The United States ◽  
Mortality Rates ◽  
Vital Rates ◽  
Data Products ◽  
Racial Ethnic

The application of a currently proposed differential privacy algorithm to the 2020 United States Census data and additional data products may affect the usefulness of these data, the accuracy of estimates and rates derived from them, and critical knowledge about social phenomena such as health disparities. We test the ramifications of applying differential privacy to released data by studying estimates of US mortality rates for the overall population and three major racial/ethnic groups. We ask how changes in the denominators of these vital rates due to the implementation of differential privacy can lead to biased estimates. We situate where these changes are most likely to matter by disaggregating biases by population size, degree of urbanization, and adjacency to a metropolitan area. Our results suggest that differential privacy will more strongly affect mortality rate estimates for non-Hispanic blacks and Hispanics than estimates for non-Hispanic whites. We also find significant changes in estimated mortality rates for less populous areas, with more pronounced changes when stratified by race/ethnicity. We find larger changes in estimated mortality rates for areas with lower levels of urbanization or adjacency to metropolitan areas, with these changes being greater for non-Hispanic blacks and Hispanics. These findings highlight the consequences of implementing differential privacy, as proposed, for research examining population composition, particularly mortality disparities across racial/ethnic groups and along the urban/rural continuum. Overall, they demonstrate the challenges in using the data products derived from the proposed disclosure avoidance methods, while highlighting critical instances where scientific understandings may be negatively impacted.

Obesity and Income Inequality in OECD Countries

2015 ◽  
pp. 484-500
Author(s):  
Dejun Su
Keyword(s):  
United States ◽  
Income Inequality ◽  
Social Cohesion ◽  
The United States ◽  
Oecd Countries ◽  
Economic Cooperation ◽  
Obesity Prevalence ◽  
Absolute Income ◽  
Policy Interventions ◽  
Over Time

Countries of the Organization for Economic Cooperation and Development (OECD) exhibit substantial increases in both income inequality and obesity prevalence since the 1970s. Income inequality may affect obesity through increased psychosocial distress, concentrated poverty, erosion of social cohesion, and inadequate policy interventions. Substantial variations appear in estimated obesity prevalence across OECD countries in 2010. Particularly important are the United States and Mexico, which lead OECD countries in current obesity rates, income inequality, and the pace of increases in obesity prevalence over time. When both countries are included in the analysis, differences in obesity prevalence are more related to differences in income inequality than to differences in absolute income across these countries. This association between income inequality and obesity prevalence virtually disappears when both countries are excluded from analysis. So far, limited research exploring the association between income inequality and obesity has not yielded conclusive, unequivocal findings.

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