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

Am J Public Health

Matthew M. Brooks and Brian C. Thiede are with the Department of Agricultural Economics, Sociology, and Education, Pennsylvania State University, University Park. Tom Mueller is with the Department of Sociology, Social Work, and Anthropology, Utah State University, Logan.

Published: December 2020

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. 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. 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. 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. Attention to rural-urban reclassification is necessary when evaluating or justifying policy interventions focusing on geographic health disparities.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662006PMC
http://dx.doi.org/10.2105/AJPH.2020.305895DOI Listing

Publication Analysis

Top Keywords

rural-urban mortality
16
mortality disparities
12
rural urban
12
urban counties
12
rural-urban
10
mortality
8
united states
8
rural-urban disparities
8
1970 2018
8
estimates rural-urban
8

Similar Publications

Enteropathogens are major contributors to mortality and morbidity, particularly in settings with limited access to water, sanitation, and hygiene infrastructure. To assess transmission pathways associated with enteropathogen infection, we measured household environmental conditions and assayed 22 enteropathogens using TaqMan Array Cards in stool samples from 276 six-month-old children living in communities along a rural-urban gradient in Northern Ecuador. We utilized multivariable models, risk factor importance, and distance-based statistical methods to test factors associated with infection.

View Article and Find Full Text PDF

Purpose: Lung cancer mortality rates for American Indians (AIs) are the highest among US race groups. End-of-life (EOL) care presents opportunities to limit aggressive and potentially unnecessary treatment. We evaluated differences in EOL quality of care between AI and White (WH) decedents with lung cancer.

View Article and Find Full Text PDF

Background: The development of ST-segment elevation myocardial infarction (STEMI) in patients hospitalized for non-cardiac indications carries a high mortality rate.

Objectives: Determine the impact of rural vs. urban hospital location and hospital percutaneous coronary intervention (PCI) volumes on clinical outcomes.

View Article and Find Full Text PDF

Objective: To examine how rural residence interacts with SES and race/ethnicity relative to Head and neck squamous cell carcinoma (HNSCC) treatment delay and outcomes.

Methods: The SEER database was queried for patients aged ≥18 with HNSCC. Out of 164,337 cases, 126,052 remained after exclusions for missing data.

View Article and Find Full Text PDF

Estimates of life expectancy and premature mortality among multidimensional poor and non-poor in India.

BMC Public Health

December 2024

Department of Population and Development, International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai, Maharashtra, 400088, India.

Article Synopsis
  • In Low and Middle Income Countries (LMICs), there's a connection between reducing multidimensional poverty and improving life expectancy, but studies on this link, especially in India, are limited.
  • Using data from over 2.8 million individuals in India, researchers assessed multidimensional poverty through education, health, and living standards, revealing that approximately 26% of the population is multidimensionally poor.
  • The study found that multidimensionally poor individuals have a life expectancy 4 years shorter than those who are non-poor, with urban poor experiencing a greater life expectancy gap than rural poor, and premature mortality rates being higher among the multidimensionally poor.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!