Dataset Information

Decomposing Mortality Disparities in Urban and Rural U.S. Counties.

ABSTRACT: OBJECTIVE:To understand the role of county characteristics in the growing divide between rural and urban mortality from 1980 to 2010. DATA SOURCE:Age-adjusted mortality rates for all U.S. counties from 1980 to 2010 were obtained from the CDC Compressed Mortality File and combined with county characteristics from the U.S. Census Bureau, the Area Health Resources File, and the Inter-University Consortium for Political and Social research. STUDY DESIGN:We used Oaxaca-Blinder decomposition to assess the extent to which rural-urban mortality disparities are explained by observed county characteristics at each decade. PRINCIPAL FINDINGS:Decomposition shows that, at each decade, differences in rural/urban characteristics are sufficient to explain differences in mortality. Furthermore, starting in 1990, rural counties have significantly lower predicted mortality than urban counties when given identical county characteristics. We find changes in the effect of characteristics on mortality, not the characteristics themselves, drive the growing mortality divide. CONCLUSIONS:Differences in economic and demographic characteristics between rural and urban counties largely explain the differences in age-adjusted mortality in any given year. Over time, the role these characteristics play in improving mortality has increased differentially for urban counties. As characteristics continue changing in importance as determinants of health, this divide may continue to widen.

SUBMITTER: Spencer JC

PROVIDER: S-EPMC6232410 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Decomposing Mortality Disparities in Urban and Rural U.S. Counties.

Spencer Jennifer C JC Wheeler Stephanie B SB Rotter Jason S JS Holmes George M GM

Health services research 20180530 6

<h4>Objective</h4>To understand the role of county characteristics in the growing divide between rural and urban mortality from 1980 to 2010.<h4>Data source</h4>Age-adjusted mortality rates for all U.S. counties from 1980 to 2010 were obtained from the CDC Compressed Mortality File and combined with county characteristics from the U.S. Census Bureau, the Area Health Resources File, and the Inter-University Consortium for Political and Social research.<h4>Study design</h4>We used Oaxaca-Blinder d ...[more]

PMID: 29845634

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Project description:ImportanceUS rural vs nonrural populations have striking disparities in diabetes care. Whether rurality contributes to disparities in diabetes mortality is unknown.ObjectiveTo examine rates and trends in diabetes mortality based on county urbanization.Design, setting, and participantsIn this observational, cross-sectional study, the US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database was searched from January 1, 1999, to December 31, 2018, for diabetes as a multiple cause and the underlying cause of death among residents aged 25 years or older in US counties. County urbanization was categorized as metro, medium-small, and rural. Weighted multiple linear regression models and jackknife resampling, with a 3-segment time component, were used. The models included exposures with up to 3-way interactions and were age standardized to the 2009-2010 population. The analyses were conducted from July 1, 2020, to February 1, 2022.ExposuresCounty urbanization (metro, medium-small, or rural), gender (men or women), age group (25-54, 55-74, or ≥75 years), and region (Midwest, Northeast, South, or West).Main outcomes and measuresAnnual diabetes mortality rate per 100 000 people.ResultsFrom 1999-2018, based on 4 022 238 309 person-years, diabetes was a multiple cause of death for 4 735 849 adults aged 25 years or older. As a multiple cause, diabetes mortality rates in 2017-2018 vs 1999-2000 were highest and unchanged in rural counties (157.2 [95% CI, 150.7-163.7] vs 154.1 [95% CI, 148.2-160.1]; P = .49) but lower in medium-small counties (123.6 [95% CI, 119.6-127.6] vs 133.6 [95% CI, 128.4-138.8]; P = .003) and urban counties (92.9 [95% CI, 90.5-95.3] vs 109.7 [95% CI, 105.2-114.1]; P < .001). In 2017-2018 vs 1999-2000, mortality rates were higher in rural men (+18.2; 95% CI, 14.3-22.1) but lower in rural women (-14.0; 95% CI, -17.7 to -10.3) (P < .001 for both). In the 25- to 54-year age group, mortality rates in 2017-2018 vs 1999-2000 showed a greater increase in rural counties (+9.4; 95% CI, 8.6-10.2) compared with medium-small counties (+4.5; 95% CI, 4.0-5.0) and metro counties (+0.9; 95% CI, 0.4-1.4) (P < .001 for all). Of all regions and urbanization levels, the mortality rate in 2017-2018 vs 1999-2000 was higher only in the rural South (+13.8; 95% CI, 7.6-20.0; P < .001).Conclusions and relevanceIn this cross-sectional study, US rural counties had the highest overall diabetes mortality rate. The determinants of persistent rural disparities, in particular for rural men and for adults in the rural South, require investigation.

Project description:After decades of lower or comparable mortality rates in rural than in urban areas of the U.S., numerous studies have documented a rural mortality penalty that started in the 1990s and has grown since the mid-2000s. The widening of the gap appears to be especially pronounced among non-Hispanic (NH) whites. However, the rural U.S. is not monolithic, and some rural places have experienced much larger mortality rate increases than others over the past 30 years. Drawing on restricted mortality files from the National Vital Statistics System (NVSS), I examine metro versus nonmetro and intra-nonmetro (divisional and economic dependency) all-cause and cause-specific mortality trends among working-age (25-64) NH white males and females, 1990-2018. Results show that the nonmetro mortality penalty is wide and growing and is pervasive across multiple disease and injury categories. Trends for females are particularly concerning. Smaller nonmetro declines in mortality from cancers and cardiovascular disease (throughout the 1990s and 2000s) and larger increases in metabolic and respiratory diseases, suicide, alcohol-related, and mental/behavioral disorders (throughout the 2010s) collectively drove the growth in the nonmetro disadvantage. There are also large divisional disparities (which are growing for females), with particularly poor trends in New England, South Atlantic, ES Central, WS Central, and Appalachia and more favorable trends in the Mid-Atlantic, Mountain, and Pacific. Mining-dependent counties have diverged from the other economic dependency types since the mid-2000s due to multiple causes of death, whereas farming counties have comparatively lower mortality rates. High and rising mortality rates across a variety of causes and rural places, some of which have been occurring since the 1990s and others that emerged more recently, suggest that there is not one underlying explanation. Instead, systemic failures across a variety of institutions and policies have contributed to rural America's troubling mortality trends generally and within-rural disparities more specifically.

Project description:IntroductionInfant mortality rates are higher in nonmetropolitan areas versus large metropolitan areas. Variation by race/ethnicity and cause of death has not been assessed. Urban-rural infant mortality rate differences were quantified by race/ethnicity and cause of death.MethodsNational Vital Statistics System linked birth/infant death data (2014-2016) were analyzed in 2019 by 3 urban-rural county classifications: large metropolitan, medium/small metropolitan, and nonmetropolitan. Excess infant mortality rates (rate differences) by urban-rural classification were calculated relative to large metropolitan areas overall and for each racial/ethnic group. The number of excess deaths, population attributable fraction, and proportion of excess deaths attributable to underlying causes of death was calculated.ResultsNonmetropolitan areas had the highest excess infant mortality rate overall. Excess infant mortality rates were substantially lower for Hispanic infants than other races/ethnicities. Overall, 7.4% of infant deaths would be prevented if all areas had the infant mortality rate of large metropolitan areas. With more than half of births occurring outside of large metropolitan areas, the population attributable fraction was highest for American Indian/Alaska Natives (20.3%) and whites, non-Hispanic (14.3%). Excess infant mortality rates in both nonmetropolitan and medium/small metropolitan areas were primarily attributable to sudden unexpected infant deaths (42.3% and 31.9%) and congenital anomalies (30.1% and 26.8%). This pattern was consistent for all racial/ethnic groups except black, non-Hispanic infants, for whom preterm-related and sudden unexpected infant deaths accounted for the largest share of excess infant mortality rates.ConclusionsInfant mortality increases with rurality, and excess infant mortality rates are predominantly attributable to sudden unexpected infant deaths and congenital anomalies, with differences by race/ethnicity regarding magnitude and cause of death.

Dataset Information

Decomposing Mortality Disparities in Urban and Rural U.S. Counties.

Publications

Decomposing Mortality Disparities in Urban and Rural U.S. Counties.

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