Large Central Metropolitan Counties Research Articles

Preventable Premature Deaths from the Five Leading Causes of Death in Nonmetropolitan and Metropolitan Counties, United States, 2010-2022.

A 2019 report quantified the higher percentage of potentially excess (preventable) deaths in U.S. nonmetropolitan areas compared with metropolitan areas during 2010-2017. In that report, CDC compared national, regional, and state estimates of preventable premature deaths from the five leading causes of death in nonmetropolitan and metropolitan counties during 2010-2017. This report provides estimates of preventable premature deaths for additional years (2010-2022). 2010-2022. Mortality data for U.S. residents from the National Vital Statistics System were used to calculate preventable premature deaths from the five leading causes of death among persons aged <80 years. CDC's National Center for Health Statistics urban-rural classification scheme for counties was used to categorize the deaths according to the urban-rural county classification level of the decedent's county of residence (1: large central metropolitan [most urban], 2: large fringe metropolitan, 3: medium metropolitan, 4: small metropolitan, 5: micropolitan, and 6: noncore [most rural]). Preventable premature deaths were defined as deaths among persons aged <80 years that exceeded the number expected if the death rates for each cause in all states were equivalent to those in the benchmark states (i.e., the three states with the lowest rates). Preventable premature deaths were calculated separately for the six urban-rural county categories nationally, the 10 U.S. Department of Health and Human Services public health regions, and the 50 states and the District of Columbia. During 2010-2022, the percentage of preventable premature deaths among persons aged <80 years in the United States increased for unintentional injury (e.g., unintentional poisoning including drug overdose, unintentional motor vehicle traffic crash, unintentional drowning, and unintentional fall) and stroke, decreased for cancer and chronic lower respiratory disease (CLRD), and remained stable for heart disease. The percentages of preventable premature deaths from the five leading causes of death were higher in rural counties in all years during 2010-2022. When assessed by the six urban-rural county classifications, percentages of preventable premature deaths in the most rural counties (noncore) were consistently higher than in the most urban counties (large central metropolitan and fringe metropolitan) for the five leading causes of death during the study period.During 2010-2022, preventable premature deaths from heart disease increased most in noncore (+9.5%) and micropolitan counties (+9.1%) and decreased most in large central metropolitan counties (-10.2%). Preventable premature deaths from cancer decreased in all county categories, with the largest decreases in large central metropolitan and large fringe metropolitan counties (-100.0%; benchmark achieved in both county categories in 2019). In all county categories, preventable premature deaths from unintentional injury increased, with the largest increases occurring in large central metropolitan (+147.5%) and large fringe metropolitan (+97.5%) counties. Preventable premature deaths from CLRD decreased most in large central metropolitan counties where the benchmark was achieved in 2019 and increased slightly in noncore counties (+0.8%). In all county categories, preventable premature deaths from stroke decreased from 2010 to 2013, remained constant from 2013 to 2019, and then increased in 2020 at the start of the COVID-19 pandemic. Percentages of preventable premature deaths varied across states by urban-rural county classification during 2010-2022. During 2010-2022, nonmetropolitan counties had higher percentages of preventable premature deaths from the five leading causes of death than did metropolitan counties nationwide, across public health regions, and in most states. The gap between the most rural and most urban counties for preventable premature deaths increased during 2010-2022 for four causes of death (cancer, heart disease, CLRD, and stroke) and decreased for unintentional injury. Urban and suburban counties (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) experienced increases in preventable premature deaths from unintentional injury during 2010-2022, leading to a narrower gap between the already high (approximately 69% in 2022) percentage of preventable premature deaths in noncore and micropolitan counties. Sharp increases in preventable premature deaths from unintentional injury, heart disease, and stroke were observed in 2020, whereas preventable premature deaths from CLRD and cancer continued to decline. CLRD deaths decreased during 2017-2020 but increased in 2022. An increase in the percentage of preventable premature deaths for multiple leading causes of death was observed in 2020 and was likely associated with COVID-19-related conditions that contributed to increased mortality from heart disease and stroke. Routine tracking of preventable premature deaths based on urban-rural county classification might enable public health departments to identify and monitor geographic disparities in health outcomes. These disparities might be related to different levels of access to health care, social determinants of health, and other risk factors. Identifying areas with a high prevalence of potentially preventable mortality might be informative for interventions.

Comparison of Demographic Characteristics and Social Determinants of Health Between Adults With Diagnosed HIV and All Adults in the U.S.

Quantifying disparities in social determinants of health between people with HIV and the total population could help address health inequities, and ensure health and well-being among people with HIV in the U.S., but estimates are lacking. Several representative data sources were used to assess differences in social determinants of health between adults with diagnosed HIV (Centers for Disease Control and Prevention Medical Monitoring Project) and the total adult population (U.S. Census Bureau's decennial census, American Community Survey, Household Pulse Survey, the Current Population Survey Annual Social and Economic Supplements; the Department of Housing and Urban Development's point-in-time estimates of homelessness; and the Bureau of Justice Statistics). The differences were quantified using standardized prevalence differences and standardized prevalence ratios, adjusting for differences in age, race/ethnicity, and birth sex between people with HIV and the total U.S. population. Overall, 35.6% of people with HIV were living in a household with an income at or below the federal poverty level, and 8.1% recently experienced homelessness. Additionally, 42.9% had Medicaid and 27.6% had Medicare; 39.7% were living with a disability. Over half (52.3%) lived in large central metropolitan counties and 20.6% spoke English less than very well based on survey responses. After adjustment, poverty (standardized prevalence difference=25.1%, standardized prevalence ratio=3.5), homelessness (standardized prevalence difference=8.5%, standardized prevalence ratio=43.5), coverage through Medicaid (standardized prevalence difference=29.5%, standardized prevalence ratio=3.0) or Medicare (standardized prevalence difference=7.8%), and disability (standardized prevalence difference=30.3%, standardized prevalence ratio=3.0) were higher among people with HIV than the total U.S. population. The percentage of people with HIV living in large central metropolitan counties (standardized prevalence difference=13.4%) or who were recently incarcerated (standardized prevalence ratio=5.9) was higher than the total U.S. population. These findings provide a baseline for assessing national-level disparities in social determinants of health between people with HIV and the total U.S. population, and it can be used as a model to assess local disparities. Addressing social determinants of health is essential for achieving health equity, requiring a multipronged approach with interventions at the provider, facility, and policy levels.

U.S. State Preemption Laws and Working-Age Mortality

The goal of this study was to estimate how state preemption laws that prohibit local authority to raise the minimum wage or mandate paid sick leave have contributed to working-age mortality from suicide, homicide, drug overdose, alcohol poisoning, and transport accidents. County-by-quarter death counts by cause and sex for 1999-2019 were regressed on minimum wage levels and hours of paid sick-leave requirements, controlling for time-varying covariates and place- and time-specific fixed effects. The model coefficients were then used to predict expected reductions in mortality if the preemption laws were repealed. Analyses were conducted during January 2022-April 2022. Paid sick-leave requirements were associated with lower mortality. These associations were statistically significant for suicide and homicide deaths among men and for homicide and alcohol-related deaths among women. Mortality may decline by more than 5% in large central metropolitan counties currently constrained by preemption laws if they were able to mandate a 40-hour annual paid sick-leave requirement. State legislatures' preemption of local authority to enact health-promoting legislation may be contributing to the worrisome trends in external causes of death.

Trends in Assault Mortalities Among Asian Americans, 2009-2018.

As of yet, few studies have described the prevalence or rates of assault mortalities involving Asian victims on a national level. This study aimed to describe yearly trends and regional differences in assault mortalities among Asians. This repeat cross-sectional study from 2009 to 2018 used data from the Mortality Multiple Cause-of-Death Public Use Record from the National Center for Health Statistics and the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research. Total and proportion of assault mortalities involving Asians or Pacific Islanders were calculated by year. Total and rates (per 100,000 Asians or Pacific Islanders) of assault mortalities among Asians or Pacific Islanders were stratified by state and county classification where deaths occurred. In 2009, 344 assault mortalities among Asians or Pacific Islanders accounted for 2.07% of assault-related deaths. In 2018, 366 assault mortalities among Asians or Pacific Islanders accounted for 1.96% of assault-related deaths. Furthermore, there were more assault mortalities from 2009 to 2018 among Asians or Pacific Islanders in California (n=1116) and large central metropolitan counties (n=1707). However, the highest rates of assault mortalities were in Alaska and Mississippi (7.1 and 6.8 per 100,000, respectively) and noncore nonmetropolitan counties (2.9 per 100,000). These findings emphasize the importance of studying and addressing violence toward Asians in rural regions and Southern states. Future studies should use these results as a baseline to analyze mortality data from 2019 to 2021, when available, to examine the coronavirus disease 2019 pandemic's impact on assault mortalities among Asian.

Rural–Urban Residence and Maternal Hepatitis C Infection, U.S.: 2010–2018

The prevalence of hepatitis C virus infection among women delivering live births in the U.S. may be higher in rural areas where county-level estimates may be unreliable. The aim of this study is to model county-level maternal hepatitis C virus infection among deliveries in the U.S. In 2020, U.S. natality files (2010-2018) with county-level maternal residence information were used from states that had adopted the 2003 revised U.S. birth certificate, which included a field for hepatitis C virus infection present during pregnancy. Hierarchical Bayesian spatial models with spatiotemporal random effects were applied to produce stable annual county-level estimates of maternal hepatitis C virus infection for years when all states had adopted the revised birth certificate (2016-2018). Models included a 6-Level Urban-Rural County Classification Scheme along with the birth year and county-specific covariates to improve posterior predictions. Among approximately 32 million live births, the overall prevalence of maternal hepatitis C virus infection was 3.5 per 1,000 births (increased from 2.0 in 2010 to 5.0 in 2018). During 2016-2018, posterior predicted median county-level maternal hepatitis C virus infection rates showed that nonurban counties had 3.5-3.8 times higher rates of hepatitis C virus than large central metropolitan counties. The counties in the top 10th percentile for maternal hepatitis C virus rates in 2018 were generally located in Appalachia, in Northern New England, along the northern border in the Upper Midwest, and in New Mexico. Further implementation of community-level interventions that are effective in reducing maternal hepatitis C virus infection and its subsequent morbidity may help to reduce geographic and rural disparities.

Road Traffic Accidents and Disparities in Child Mortality.

Road traffic accidents are a leading cause of child deaths in the United States. Although this has been examined at the national and state levels, there is more value in acquiring information at the county level to guide local policies. We aimed to estimate county-specific child mortality from road traffic accidents in the United States. We queried the Fatality Analysis Reporting System database, 2010-2017, for road traffic accidents that resulted in a death within 30 days of the auto crash. We included all children <15 years old who were fatally injured. We estimated county-specific age- and sex-standardized mortality. We evaluated the impact of the availability of trauma centers and urban-rural classification of counties on mortality. We included 9271 child deaths. Among those, 45% died at the scene. The median age was 7 years. The overall mortality was 1.87 deaths per 100 000 children. County-specific mortality ranged between 0.25 and 21.91 deaths per 100 000 children. The availability of a trauma center in a county was associated with decreased mortality (adult trauma center [odds ratio (OR): 0.59; 95% credibility interval (CI), 0.52-0.66]; pediatric trauma center [OR: 0.56; 95% CI, 0.46-0.67]). Less urbanized counties were associated with higher mortality, compared with large central metropolitan counties (noncore counties [OR: 2.33; 95% CI, 1.85-2.91]). There are marked differences in child mortality from road traffic accidents among US counties. Our findings can guide targeted public health interventions in high-risk counties with excessive child mortality and limited access to trauma care.

Heat-Related Deaths - United States, 2004-2018.

Deaths attributable to natural heat exposure, although generally considered preventable (1), represent a continuing public health concern in the United States. During 2004-2018, an average of 702 heat-related deaths occurred in the United States annually. To study patterns in heat-related deaths by age group, sex, race/ethnicity, and level of urbanization, and to explore comorbid conditions associated with deaths resulting from heat exposure, CDC analyzed nationally comprehensive mortality data from the National Vital Statistics System (NVSS).* The rate of heat-related mortality tended to be higher among males, persons aged ≥65 years, non-Hispanic American Indian/Alaska Natives, and persons living in noncore nonmetropolitan and large central metropolitan counties. Natural heat exposure was a contributing cause of deaths attributed to certain chronic medical conditions and other external causes. Preparedness and response initiatives directed toward extreme heat events, currently underway at local, state, and national levels, can contribute to reducing morbidity and mortality associated with natural heat exposure. Successful public health interventions† to mitigate heat-related deaths include conducting outreach to vulnerable communities to increase awareness of heat-related symptoms and provide guidance for staying cool and hydrated, particularly for susceptible groups at risk such as young athletes and persons who are older or socially isolated (2). Improved coordination across various health care sectors could inform local activities to protect health during periods of high heat. For instance, jurisdictions can monitor weather conditions and syndromic surveillance data to guide timing of risk communication and other measures (e.g., developing and implementing heat response plans, facilitating communication and education activities) to prevent heat-related mortality in the United States. CDC also recommends that federal, state, local, and tribal jurisdictions open cooling centers or provide access to public locations with air conditioning for persons in need of a safe, cool, environment during hot weather conditions. In light of the coronavirus disease 2019 (COVID-19) pandemic, CDC updated its guidance on the use of cooling centers to provide best practices (e.g., potential changes to staffing procedures, separate areas for persons with symptoms of COVID-19, and physical distancing) to reduce the risk for introducing and transmitting SARS COV-2, the virus that causes COVID-19, into cooling centers.§.

Potentially Excess Deaths from the Five Leading Causes of Death in Metropolitan and Nonmetropolitan Counties - United States, 2010-2017.

A 2017 report quantified the higher percentage of potentially excess (or preventable) deaths in nonmetropolitan areas (often referred to as rural areas) compared with metropolitan areas. In that report, CDC compared national, regional, and state estimates of potentially excess deaths among the five leading causes of death in nonmetropolitan and metropolitan counties for 2010 and 2014. This report enhances the geographic detail by using the six levels of the 2013 National Center for Health Statistics (NCHS) urban-rural classification scheme for counties and extending estimates of potentially excess deaths by annual percent change (APC) and for additional years (2010-2017). Trends were tested both with linear and quadratic terms. 2010-2017. Mortality data for U.S. residents from the National Vital Statistics System were used to calculate potentially excess deaths from the five leading causes of death among persons aged <80 years. CDC's NCHS urban-rural classification scheme for counties was used to categorize the deaths according to the urban-rural county classification level of the decedent's county of residence (1: large central metropolitan [most urban], 2: large fringe metropolitan, 3: medium metropolitan, 4: small metropolitan, 5: micropolitan, and 6: noncore [most rural]). Potentially excess deaths were defined as deaths among persons aged <80 years that exceeded the number expected if the death rates for each cause in all states were equivalent to those in the benchmark states (i.e., the three states with the lowest rates). Potentially excess deaths were calculated separately for the six urban-rural county categories nationally, the 10 U.S. Department of Health and Human Services public health regions, and the 50 states and District of Columbia. The number of potentially excess deaths among persons aged <80 years in the United States increased during 2010-2017 for unintentional injuries (APC: 11.2%), decreased for cancer (APC: -9.1%), and remained stable for heart disease (APC: 1.1%), chronic lower respiratory disease (CLRD) (APC: 1.7%), and stroke (APC: 0.3). Across the United States, percentages of potentially excess deaths from the five leading causes were higher in nonmetropolitan counties in all years during 2010-2017. When assessed by the six urban-rural county classifications, percentages of potentially excess deaths in the most rural counties (noncore) were consistently higher than in the most urban counties (large central metropolitan) for the study period. Potentially excess deaths from heart disease increased most in micropolitan counties (APC: 2.5%) and decreased most in large fringe metropolitan counties (APC: -1.1%). Potentially excess deaths from cancer decreased in all county categories, with the largest decreases in large central metropolitan (APC: -16.1%) and large fringe metropolitan (APC: -15.1%) counties. In all county categories, potentially excess deaths from the five leading causes increased, with the largest increases occurring in large central metropolitan (APC: 18.3%), large fringe metropolitan (APC: 17.1%), and medium metropolitan (APC: 11.1%) counties. Potentially excess deaths from CLRD decreased most in large central metropolitan counties (APC: -5.6%) and increased most in micropolitan (APC: 3.7%) and noncore (APC: 3.6%) counties. In all county categories, potentially excess deaths from stroke exhibited a quadratic trend (i.e., decreased then increased), except in micropolitan counties, where no change occurred. Percentages of potentially excess deaths also differed among and within public health regions and across states by urban-rural county classification during 2010-2017. Nonmetropolitan counties had higher percentages of potentially excess deaths from the five leading causes than metropolitan counties during 2010-2017 nationwide, across public health regions, and in the majority of states. The gap between the most rural and most urban counties for potentially excess deaths increased during 2010-2017 for three causes of death (cancer, heart disease, and CLRD), decreased for unintentional injury, and remained relatively stable for stroke. Urban and suburban counties (large central metropolitan and large fringe metropolitan, medium metropolitan, and small metropolitan) experienced increases in potentially excess deaths from unintentional injury during 2010-2017, leading to a narrower gap between the already high (approximately 55%) percentage of excess deaths in noncore and micropolitan counties. Routine tracking of potentially excess deaths by urban-rural county classification might help public health departments and decision-makers identify and monitor public health problems and focus interventions to reduce potentially excess deaths in these areas.

Opioid Prescribing Rates in Nonmetropolitan and Metropolitan Counties Among Primary Care Providers Using an Electronic Health Record System - United States, 2014-2017.

Drug overdose is the leading cause of unintentional injury-associated death in the United States. Among 70,237 fatal drug overdoses in 2017, prescription opioids were involved in 17,029 (24.2%) (1). Higher rates of opioid-related deaths have been recorded in nonmetropolitan (rural) areas (2). In 2017, 14 rural counties were among the 15 counties with the highest opioid prescribing rates.* Higher opioid prescribing rates put patients at risk for addiction and overdose (3). Using deidentified data from the Athenahealth electronic health record (EHR) system, opioid prescribing rates among 31,422 primary care providers† in the United States were analyzed to evaluate trends from January 2014 to March 2017. This analysis assessed how prescribing practices varied among six urban-rural classification categories of counties, before and after the March 2016 release of CDC's Guideline for Prescribing Opioids for Chronic Pain (Guideline) (4). Patients in noncore (the most rural) counties had an 87% higher chance of receiving an opioid prescription compared with persons in large central metropolitan counties during the study period. Across all six county groups, the odds of receiving an opioid prescription decreased significantly after March 2016. This decrease followed a flat trend during the preceding period in micropolitan and large central metropolitan county groups; in contrast, the decrease continued previous downward trends in the other four county groups. Data from EHRs can effectively supplement traditional surveillance methods for monitoring trends in opioid prescribing and other areas of public health importance, with minimal lag time under ideal conditions. As less densely populated areas appear to indicate both substantial progress in decreasing opioid prescribing and ongoing need for reduction, community health care practices and intervention programs must continue to be tailored to community characteristics.

Mortality, Ethnicity, and Urbanization Among Children Aged 1-4 Years on the US-Mexico Border.

Little is known about the mortality of children along the US-Mexico border. The objective of our study was to determine whether mortality rates among Hispanic children along the border ("border Hispanic children") exceeded mortality rates among non-Hispanic white children along the border. We examined mortality rates from 2001-2015 for children aged 1-4 years in US-Mexico border counties and in the United States overall. We compared mortality rates among Hispanic and non-Hispanic white children by county urbanization level (large central, medium, and small metropolitan; micropolitan nonmetropolitan; and noncore nonmetropolitan). During 2001-2015, 1811 children aged 1-4 years died in the border region. The mortality rate per 100 000 children among border Hispanic children (28.3; 95% confidence interval [CI], 26.8-29.9) exceeded the mortality rate of US Hispanic children (24.7; 95% CI, 24.3-25.1) and border non-Hispanic white children (23.2; 95% CI, 20.8-25.6). When stratified by county urbanization level, however, mortality rates of border Hispanic children were not significantly different from mortality rates of US Hispanic or border non-Hispanic white children. Mortality rates in noncore nonmetropolitan counties were twice those in large central metropolitan counties, with injury mortality accounting for most of the excess. Mortality rates increased in nonmetropolitan border counties after 2010. Increased risk for injury and disease in noncore nonmetropolitan counties might be related to poverty, reduced access to care, or poorer quality of care. Future research should identify the remediable risk factors in such communities as the next step in preventing deaths among children aged 1-4 years.

Rural and Urban Differences in Air Quality, 2008-2012, and Community Drinking Water Quality, 2010-2015 - United States.

Problem/ConditionThe places in which persons live, work, and play can contribute to the development of adverse health outcomes. Understanding the differences in risk factors in various environments can help to explain differences in the occurrence of these outcomes and can be used to develop public health programs, interventions, and policies. Efforts to characterize urban and rural differences have largely focused on social and demographic characteristics. A paucity of national standardized environmental data has hindered efforts to characterize differences in the physical aspects of urban and rural areas, such as air and water quality.Reporting Period2008–2012 for air quality and 2010–2015 for water quality.Description of SystemSince 2002, CDC’s National Environmental Public Health Tracking Program has collaborated with federal, state, and local partners to gather standardized environmental data by creating national data standards, collecting available data, and disseminating data to be used in developing public health actions. The National Environmental Public Health Tracking Network (i.e., the tracking network) collects data provided by national, state, and local partners and includes 21 health outcomes, exposures, and environmental hazards. To assess environmental factors that affect health, CDC analyzed three air-quality measures from the tracking network for all counties in the contiguous United States during 2008–2012 and one water-quality measure for 26 states during 2010–2015. The three air-quality measures include 1) total number of days with fine particulate matter (PM2.5) levels greater than the U.S. Environmental Protection Agency’s (EPA’s) National Ambient Air Quality Standards (NAAQS) for 24-hour average PM2.5 (PM2.5 days); 2) mean annual average ambient concentrations of PM2.5 in micrograms per cubic meter (mean PM2.5); and 3) total number of days with maximum 8-hour average ozone concentrations greater than the NAAQS (ozone days). The water-quality measure compared the annual mean concentration for a community water system (CWS) to the maximum contaminant level (MCL) defined by EPA for 10 contaminants: arsenic, atrazine, di(2-ethylhexyl) phthalate (DEHP), haloacetic acids (HAA5), nitrate, perchloroethene (PCE), radium, trichloroethene (TCE), total trihalomethanes (TTHM), and uranium. Findings are presented by urban-rural classification scheme: four metropolitan (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) and two nonmetropolitan (micropolitan and noncore) categories. Regression modeling was used to determine whether differences in the measures by urban-rural categories were statistically significant.ResultsPatterns for all three air-quality measures suggest that air quality improves as areas become more rural (or less urban). The mean total number of ozone days decreased from 47.54 days in large central metropolitan counties to 3.81 days in noncore counties, whereas the mean total number of PM2.5 days decreased from 11.21 in large central metropolitan counties to 0.95 in noncore counties. The mean average annual PM2.5 concentration decreased from 11.15 μg/m3 in large central metropolitan counties to 8.87 μg/m3 in noncore counties. Patterns for the water-quality measure suggest that water quality improves as areas become more urban (or less rural). Overall, 7% of CWSs reported at least one annual mean concentration greater than the MCL for all 10 contaminants combined. The percentage increased from 5.4% in large central metropolitan counties to 10% in noncore counties, a difference that was significant, adjusting for U.S. region, CWS size, water source, and potential spatial correlation. Similar results were found for two disinfection by-products, HAA5 and TTHM. Arsenic was the only other contaminant with a significant result. Medium metropolitan counties had 3.1% of CWSs reporting at least one annual mean greater than the MCL, compared with 2.4% in large central counties.InterpretationNoncore (rural) counties experienced fewer unhealthy air-quality days than large central metropolitan counties, likely because of fewer air pollution sources in the noncore counties. All categories of counties had a mean annual average PM2.5 concentration lower than the EPA standard. Among all CWSs analyzed, the number reporting one or more annual mean contaminant concentrations greater the MCL was small. The water-quality measure suggests that water quality worsens as counties become more rural, in regards to all contaminants combined and for the two disinfection by-products individually. Although significant differences were found for the water-quality measure, the odds ratios were very small, making it difficult to determine whether these differences have a meaningful effect on public health. These differences might be a result of variations in water treatment practices in rural versus urban counties.Public Health ActionUnderstanding the differences between rural and urban areas in air and water quality can help public health departments to identify, monitor, and prioritize potential environmental public health concerns and opportunities for action. These findings suggest a continued need to develop more geographically targeted, evidence-based interventions to prevent morbidity and mortality associated with poor air and water quality.

QuickStats: Age-Adjusted Rate* of Motor Vehicle Traffic Deaths,by Urbanization of County of Residence— 2005 and 2015

The overall age-adjusted rate of motor vehicle traffic deaths in the United States decreased 25% from 14.6 deaths per 100,000 population in 2005 to 10.9 in 2015. During this period, the rate declined in each of the county groupings, with the largest decline of 26% in the large fringe metropolitan and micropolitan counties and the smallest decline of 20% in rural counties. For both years, the rates for motor vehicle traffic deaths were higher in nonmetropolitan areas than in metropolitan areas. In 2015, the age-adjusted rate in rural counties was nearly three times the rate for large central metropolitan counties (23.0 compared with 7.9 per 100,000).

Trends and Geographic Patterns in Drug-Poisoning Death Rates in the U.S., 1999–2009

Drug poisoning mortality has increased substantially in the U.S. over the past 3 decades. Previous studies have described state-level variation and urban-rural differences in drug-poisoning deaths, but variation at the county level has largely not been explored in part because crude county-level death rates are often highly unstable. The goal of the study was to use small-area estimation techniques to produce stable county-level estimates of age-adjusted death rates (AADR) associated with drug poisoning for the U.S., 1999-2009, in order to examine geographic and temporal variation. Population-based observational study using data on 304,087 drug-poisoning deaths in the U.S. from the 1999-2009 National Vital Statistics Multiple Cause of Death Files (analyzed in 2012). Because of the zero-inflated and right-skewed distribution of drug-poisoning death rates, a two-stage modeling procedure was used in which the first stage modeled the probability of observing a death for a given county and year, and the second stage modeled the log-transformed drug-poisoning death rate given that a death occurred. Empirical Bayes estimates of county-level drug-poisoning death rates were mapped to explore temporal and geographic variation. Only 3% of counties had drug-poisoning AADRs greater than ten per 100,000 per year in 1999-2000, compared to 54% in 2008-2009. Drug-poisoning AADRs grew by 394% in rural areas compared to 279% for large central metropolitan counties, but the highest drug-poisoning AADRs were observed in central metropolitan areas from 1999 to 2009. There was substantial geographic variation in drug-poisoning mortality across the U.S.