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1.
MMWR Surveill Summ ; 73(2): 1-11, 2024 May 02.
Article in English | MEDLINE | ID: mdl-38687830

ABSTRACT

Problem/Condition: 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). Period Covered: 2010-2022. Description of System: 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. Results: 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. Interpretation: 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. Public Health Action: 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.


Subject(s)
Cause of Death , Mortality, Premature , Rural Population , Urban Population , Humans , United States/epidemiology , Aged , Middle Aged , Adult , Adolescent , Urban Population/statistics & numerical data , Rural Population/statistics & numerical data , Young Adult , Infant , Child, Preschool , Child , Female , Male , Aged, 80 and over , Infant, Newborn , Neoplasms/mortality
2.
Ann Epidemiol ; 91: 37-43, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38309641

ABSTRACT

PURPOSE: To examine changes in death rates by demographic group and by the leading causes of death in U.S. persons 1 to 24 years of age during the COVID-19 pandemic. METHODS: A retrospective cross-sectional study using mortality data from the National Vital Statistics System from April 2017 to March 2023. Pre-pandemic death rates were compared with death rates during the pandemic overall, by race/ethnicity, age, sex, and cause group. RESULTS: Age-adjusted death rates in young persons 1-24 years of age increased by 14.3% during the pandemic. Injury-related causes accounted for 78.2% of the increase, driven mainly by increases in homicides and unintentional injuries related to drug overdose, firearms, and motor-vehicle traffic crashes. Non-Hispanic Black and Hispanic teens and young adults experienced the largest increases in deaths overall and across the leading causes of death. CONCLUSIONS: During the COVID-19 pandemic, injury-related causes accounted for the majority of the increases in deaths in children and young adults, driven mainly by firearms, drug overdoses, and motor vehicle traffic crashes. Findings highlight the importance of understanding the drivers of these marked increases in injury-related mortality and the need for injury prevention efforts among children even in the context of an infectious disease pandemic.


Subject(s)
COVID-19 , Pandemics , Child , Adolescent , Young Adult , Humans , United States/epidemiology , Infant , Child, Preschool , Adult , Cause of Death , Cross-Sectional Studies , Retrospective Studies
3.
J Rural Health ; 2023 Dec 11.
Article in English | MEDLINE | ID: mdl-38082546

ABSTRACT

PURPOSE: To estimate percent excess deaths during the COVID-19 pandemic by rural-urban residence in the United States and to describe rural-urban disparities by age, sex, and race/ethnicity. METHODS: Using US mortality data, we used overdispersed Poisson regression models to estimate monthly expected death counts by rurality of residence, age group, sex, and race/ethnicity, and compared expected death counts with observed deaths. We then summarized excess deaths over 6 6-month time periods. FINDINGS: There were 16.9% (95% confidence interval [CI]: 16.8, 17.0) more deaths than expected between March 2020 and February 2023. The percent excess varied by rurality (large central metro: 18.2% [18.1, 18.4], large fringe metro: 15.6% [15.5, 15.8], medium metro: 18.1% [18.0, 18.3], small metro: 15.5% [15.3, 15.7], micropolitan rural: 16.3% [16.1, 16.5], and noncore rural: 15.8% [15.6, 16.1]). The percent excess deaths were 20.2% (20.1, 20.3) for males and 13.6% (13.5, 13.7) for females, and highest for Hispanic persons (49% [49.0, 49.6]), followed by non-Hispanic Black persons (28% [27.5, 27.9]) and non-Hispanic White persons (12% [11.6, 11.8]). The 6-month time periods with the highest percent excess deaths for large central metro areas were March 2020-August 2020 and September 2020-February 2021; for all other areas, these time periods were September 2020-February 2021 and September 2021-February 2022. CONCLUSION: Percent excess deaths varied by rurality, age group, sex, race/ethnicity, and time period. Monitoring excess deaths by rurality may be useful in assessing the impact of the pandemic over time, as rural-urban patterns appear to differ.

5.
Prev Chronic Dis ; 20: E111, 2023 Nov 30.
Article in English | MEDLINE | ID: mdl-38033271

ABSTRACT

Introduction: Housing insecurity is associated with poor health outcomes. Characterization of chronic disease outcomes among adults with and without housing assistance would enable housing programs to better understand their population's health care needs. Methods: We used National Health and Nutrition Examination Survey (NHANES) data from 2005 through 2018 linked to US Department of Housing and Urban Development (HUD) administrative records to estimate the prevalence of obesity, diabetes, and hypertension and to assess the independent associations between housing assistance and chronic conditions among adults receiving HUD assistance and HUD-assistance-eligible adults not receiving HUD assistance at the time of their NHANES examination. We estimated propensity scores to adjust for potential confounders among linkage-eligible adults who had an income-to-poverty ratio less than 2 and were not receiving HUD assistance. Sensitivity analysis used 2013-2018 NHANES cycles to account for disability status. Results: Adults not receiving HUD assistance had a significantly lower adjusted prevalence of obesity (42.1%; 95% CI, 40.4%-43.8%) compared with adults receiving HUD assistance (47.5%; 95% CI, 44.8%-50.3%), but we found no differences for diabetes and hypertension. We found significant associations between housing assistance and obesity (adjusted odds ratio = 1.29; 95% CI, 1.12-1.47), but these were not significant in the sensitivity analysis with and without controlling for disability status. We found no significant associations between housing assistance and diabetes or hypertension. Conclusion: Based on data from a cross-sectional survey, we observed a higher prevalence of obesity among adults with HUD assistance compared with HUD-assistance-eligible adults without HUD assistance. Results from this study can help inform research on understanding the prevalence of chronic disease among adults with HUD assistance.


Subject(s)
Diabetes Mellitus , Hypertension , Humans , Adult , United States/epidemiology , Housing , Nutrition Surveys , Public Housing , Cross-Sectional Studies , Obesity/epidemiology , Chronic Disease , Diabetes Mellitus/epidemiology , Hypertension/epidemiology
6.
Clin Infect Dis ; 76(3): e255-e262, 2023 02 08.
Article in English | MEDLINE | ID: mdl-35717660

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19)-associated fungal infections cause severe illness, but comprehensive data on disease burden are lacking. We analyzed US National Vital Statistics System (NVSS) data to characterize disease burden, temporal trends, and demographic characteristics of persons dying of fungal infections during the COVID-19 pandemic. METHODS: Using NVSS's January 2018-December 2021 Multiple Cause of Death Database, we examined numbers and age-adjusted rates (per 100 000 population) of deaths due to fungal infection by fungal pathogen, COVID-19 association, demographic characteristics, and year. RESULTS: Numbers and age-adjusted rates of deaths due to fungal infection increased from 2019 (n = 4833; rate, 1.2 [95% confidence interval, 1.2-1.3]) to 2021 (n = 7199; rate, 1.8 [1.8-1.8] per 100 000); of 13 121 such deaths during 2020-2021, 2868 (21.9%) were COVID-19 associated. Compared with non-COVID-19-associated deaths (n = 10 253), COVID-19-associated deaths more frequently involved Candida (n = 776 [27.1%] vs n = 2432 [23.7%], respectively) and Aspergillus (n = 668 [23.3%] vs n = 1486 [14.5%]) and less frequently involved other specific fungal pathogens. Rates of death due to fungal infection were generally highest in nonwhite and non-Asian populations. Death rates from Aspergillus infections were approximately 2 times higher in the Pacific US census division compared with most other divisions. CONCLUSIONS: Deaths from fungal infection increased during 2020-2021 compared with previous years, primarily driven by COVID-19-associated deaths, particularly those involving Aspergillus and Candida. Our findings may inform efforts to prevent, identify, and treat severe fungal infections in patients with COVID-19, especially in certain racial/ethnic groups and geographic areas.


Subject(s)
COVID-19 , Mycoses , Vital Statistics , Humans , United States/epidemiology , Pandemics , Mycoses/epidemiology , Racial Groups
7.
Paediatr Perinat Epidemiol ; 37(2): 134-142, 2023 02.
Article in English | MEDLINE | ID: mdl-36372984

ABSTRACT

BACKGROUND: Trends in the prevalence of hepatitis C virus (HCV) infection among women delivering live births may differ in rural vs. urban areas of the United States, but estimation of trends based on observed counts may lead to unstable estimates in rural counties due to small numbers. OBJECTIVES: The objective of the study was to use small area estimation methods to provide updated county-level prevalence estimates and, for the first time, trends in maternal HCV infection among live births by county-level rurality. METHODS: Cross-sectional natality data from 2016 to 2020 were used to estimate maternal hepatitis C prevalence using hierarchical Bayesian models with spatiotemporal random effects to produce annual county-level estimates of maternal HCV infection and trends over time. Models included a 6-level rural-urban county classification, year, maternal characteristics and county-specific covariates. Data were analysed in 2022. RESULTS: There were 90,764/18,905,314 live births (4.8 per 1000) with HCV infection reported on the birth certificate. Hepatitis C prevalence was higher among rural counties as compared to urban counties. Rural counties had the largest annual increases in maternal hepatitis C prevalence (per 1000 births) from 2016 to 2020 (micropolitan: 0.39; noncore: 0.40), with smaller increases among less densely populated urban counties (medium metro: 0.28; small metro: 0.28) and urban counties (large central metro:0.11; large fringe metro: 0.14). CONCLUSIONS: The prevalence of maternal HCV infection was the highest in rural counties, and rural counties saw the greatest average prevalence increase during 2016-2020. County-level data can help in monitoring rural-urban trends in maternal HCV infection to reduce geographic disparities.


Subject(s)
Hepacivirus , Hepatitis C , Humans , United States/epidemiology , Female , Prevalence , Cross-Sectional Studies , Bayes Theorem , Urban Population , Hepatitis C/epidemiology , Rural Population
8.
Sci Rep ; 12(1): 18559, 2022 11 03.
Article in English | MEDLINE | ID: mdl-36329082

ABSTRACT

Both the USA and Europe experienced substantial excess mortality in 2020 and 2021 related to the COVID-19 pandemic. Methods used to estimate excess mortality vary, making comparisons difficult. This retrospective observational study included data on deaths from all causes occurring in the USA and 25 European countries or subnational areas participating in the network for European monitoring of excess mortality for public health action (EuroMOMO). We applied the EuroMOMO algorithm to estimate excess all-cause mortality in the USA and Europe during the first two years of the COVID-19 pandemic, 2020-2021, and compared excess mortality by age group and time periods reflecting three primary waves. During 2020-2021, the USA experienced 154.5 (95% Uncertainty Interval [UI]: 154.2-154.9) cumulative age-standardized excess all-cause deaths per 100,000 person years, compared with 110.4 (95% UI: 109.9-111.0) for the European countries. Excess all-cause mortality in the USA was higher than in Europe for nearly all age groups, with an additional 44.1 excess deaths per 100,000 person years overall from 2020-2021. If the USA had experienced an excess mortality rate similar to Europe, there would have been approximately 391 thousand (36%) fewer excess deaths in the USA.


Subject(s)
COVID-19 , Humans , United States/epidemiology , COVID-19/epidemiology , Pandemics , Europe/epidemiology , Public Health , Algorithms , Mortality
9.
Influenza Other Respir Viruses ; 16(3): 411-416, 2022 05.
Article in English | MEDLINE | ID: mdl-35044097

ABSTRACT

BACKGROUND: In the United States, infection with SARS-CoV-2 caused 380,000 reported deaths from March to December 2020. METHODS: We adapted the Moving Epidemic Method to all-cause mortality data from the United States to assess the severity of the COVID-19 pandemic across age groups and all 50 states. By comparing all-cause mortality during the pandemic with intensity thresholds derived from recent, historical all-cause mortality, we categorized each week from March to December 2020 as either low severity, moderate severity, high severity, or very high severity. RESULTS: Nationally for all ages combined, all-cause mortality was in the very high severity category for 9 weeks. Among people 18 to 49 years of age, there were 29 weeks of consecutive very high severity mortality. Forty-seven states, the District of Columbia, and New York City each experienced at least 1 week of very high severity mortality for all ages combined. CONCLUSIONS: These periods of very high severity of mortality during March through December 2020 are likely directly or indirectly attributable to the COVID-19 pandemic. This method for standardized comparison of severity over time across different geographies and demographic groups provides valuable information to understand the impact of the COVID-19 pandemic and to identify specific locations or subgroups for deeper investigations into differences in severity.


Subject(s)
COVID-19 , Pandemics , COVID-19/epidemiology , Geography , Humans , Infant , Research Design , SARS-CoV-2 , United States/epidemiology
10.
Am J Epidemiol ; 191(6): 1030-1039, 2022 05 20.
Article in English | MEDLINE | ID: mdl-35020799

ABSTRACT

It has been difficult to measure rural-urban differences in maternal mortality ratios (MMRs) in the United States in recent years because of the incremental adoption of a pregnancy status checkbox on the standard US death certificate. Using 1999-2017 mortality and birth data, we examined the impact of the pregnancy checkbox on MMRs according to urbanicity of residence (large urban area, medium/small urban area, or rural area), using log-binomial regression models to predict trends that would have been observed if all states had adopted the checkbox as of 1999. Implementation of the checkbox resulted in an average estimated increase of 7.5 maternal deaths per 100,000 live births (95% confidence interval (CI): 6.3, 8.8) in large urban areas (a 76% increase), 11.6 (95% CI: 9.6, 13.6) in medium/small urban areas (a 113% increase), and 16.6 (95% CI: 12.9, 20.3) in rural areas (a 107% increase), compared with MMRs prior to the checkbox. Assuming that all states had the checkbox as of 1999, demographic-factor-adjusted predicted MMRs increased in rural areas, declined in large urban areas, and did not change in medium/small urban areas. However, trends and urban-rural differences were substantially attenuated when analyses were limited to direct/specific causes of maternal death, which are probably subject to less misclassification. Accurate ascertainment of maternal deaths, particularly in rural areas, is important for reducing disparities in maternal mortality.


Subject(s)
Maternal Death , Maternal Mortality , Death Certificates , Female , Humans , Live Birth , Pregnancy , Rural Population , United States/epidemiology
11.
Am J Public Health ; 111(12): 2133-2140, 2021 12.
Article in English | MEDLINE | ID: mdl-34878853

ABSTRACT

The National Center for Health Statistics' (NCHS's) National Vital Statistics System (NVSS) collects, processes, codes, and reviews death certificate data and disseminates the data in annual data files and reports. With the global rise of COVID-19 in early 2020, the NCHS mobilized to rapidly respond to the growing need for reliable, accurate, and complete real-time data on COVID-19 deaths. Within weeks of the first reported US cases, NCHS developed certification guidance, adjusted internal data processing systems, and stood up a surveillance system to release daily updates of COVID-19 deaths to track the impact of the COVID-19 pandemic on US mortality. This report describes the processes that NCHS took to produce timely mortality data in response to the COVID-19 pandemic. (Am J Public Health. 2021;111(12):2133-2140. https://doi.org/10.2105/AJPH.2021.306519).


Subject(s)
COVID-19/mortality , Data Collection/standards , Public Health Surveillance/methods , Vital Statistics , Cause of Death , Clinical Coding/standards , Ethnic and Racial Minorities , Guidelines as Topic , Health Status Disparities , Humans , SARS-CoV-2 , Sociodemographic Factors , Time Factors , United States/epidemiology
12.
MMWR Morb Mortal Wkly Rep ; 70(33): 1114-1119, 2021 Aug 20.
Article in English | MEDLINE | ID: mdl-34411075

ABSTRACT

The COVID-19 pandemic has disproportionately affected Hispanic or Latino, non-Hispanic Black (Black), non-Hispanic American Indian or Alaska Native (AI/AN), and non-Hispanic Native Hawaiian or Other Pacific Islander (NH/PI) populations in the United States. These populations have experienced higher rates of infection and mortality compared with the non-Hispanic White (White) population (1-5) and greater excess mortality (i.e., the percentage increase in the number of persons who have died relative to the expected number of deaths for a given place and time) (6). A limitation of existing research on excess mortality among racial/ethnic minority groups has been the lack of adjustment for age and population change over time. This study assessed excess mortality incidence rates (IRs) (e.g., the number of excess deaths per 100,000 person-years) in the United States during December 29, 2019-January 2, 2021, by race/ethnicity and age group using data from the National Vital Statistics System. Among all assessed racial/ethnic groups (non-Hispanic Asian [Asian], AI/AN, Black, Hispanic, NH/PI, and White populations), excess mortality IRs were higher among persons aged ≥65 years (426.4 to 1033.5 excess deaths per 100,000 person-years) than among those aged 25-64 years (30.2 to 221.1) and those aged <25 years (-2.9 to 14.1). Among persons aged <65 years, Black and AI/AN populations had the highest excess mortality IRs. Among adults aged ≥65 years, Black and Hispanic persons experienced the highest excess mortality IRs of >1,000 excess deaths per 100,000 person-years. These findings could help guide more tailored public health messaging and mitigation efforts to reduce disparities in mortality associated with the COVID-19 pandemic in the United States,* by identifying the racial/ethnic groups and age groups with the highest excess mortality rates.


Subject(s)
COVID-19/mortality , Health Status Disparities , Mortality/trends , Adult , Age Distribution , Aged , COVID-19/ethnology , Ethnicity/statistics & numerical data , Humans , Middle Aged , Racial Groups/statistics & numerical data , United States/epidemiology , Young Adult
13.
Natl Vital Stat Rep ; 70(7): 1-12, 2021 Jun.
Article in English | MEDLINE | ID: mdl-34132635

ABSTRACT

This report describes drug-involved infant deaths in the United States for 2015-2017 by type of drug involved and selected maternal and infant characteristics. Deaths are grouped according to whether drugs were the underlying or a contributing cause of death.


Subject(s)
Infant Death , Poisoning/mortality , Cause of Death/trends , Humans , Infant , United States/epidemiology , Vital Statistics
16.
Am J Prev Med ; 60(6): 820-830, 2021 06.
Article in English | MEDLINE | ID: mdl-33640230

ABSTRACT

INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.


Subject(s)
Hepatitis C , Rural Population , Appalachian Region , Bayes Theorem , Female , Hepatitis C/epidemiology , Humans , New England , New Mexico , Pregnancy , United States/epidemiology
17.
MMWR Morb Mortal Wkly Rep ; 69(42): 1522-1527, 2020 Oct 23.
Article in English | MEDLINE | ID: mdl-33090978

ABSTRACT

As of October 15, 216,025 deaths from coronavirus disease 2019 (COVID-19) have been reported in the United States*; however, this number might underestimate the total impact of the pandemic on mortality. Measures of excess deaths have been used to estimate the impact of public health pandemics or disasters, particularly when there are questions about underascertainment of deaths directly attributable to a given event or cause (1-6).† Excess deaths are defined as the number of persons who have died from all causes, in excess of the expected number of deaths for a given place and time. This report describes trends and demographic patterns in excess deaths during January 26-October 3, 2020. Expected numbers of deaths were estimated using overdispersed Poisson regression models with spline terms to account for seasonal patterns, using provisional mortality data from CDC's National Vital Statistics System (NVSS) (7). Weekly numbers of deaths by age group and race/ethnicity were assessed to examine the difference between the weekly number of deaths occurring in 2020 and the average number occurring in the same week during 2015-2019 and the percentage change in 2020. Overall, an estimated 299,028 excess deaths have occurred in the United States from late January through October 3, 2020, with two thirds of these attributed to COVID-19. The largest percentage increases were seen among adults aged 25-44 years and among Hispanic or Latino (Hispanic) persons. These results provide information about the degree to which COVID-19 deaths might be underascertained and inform efforts to prevent mortality directly or indirectly associated with the COVID-19 pandemic, such as efforts to minimize disruptions to health care.


Subject(s)
Coronavirus Infections/ethnology , Coronavirus Infections/mortality , Ethnicity/statistics & numerical data , Pandemics , Pneumonia, Viral/ethnology , Pneumonia, Viral/mortality , Racial Groups/statistics & numerical data , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , COVID-19 , Child , Child, Preschool , Health Status Disparities , Humans , Infant , Infant, Newborn , Middle Aged , United States/epidemiology , Vital Statistics , Young Adult
18.
MMWR Morb Mortal Wkly Rep ; 69(42): 1517-1521, 2020 Oct 23.
Article in English | MEDLINE | ID: mdl-33090984

ABSTRACT

During February 12-October 15, 2020, the coronavirus disease 2019 (COVID-19) pandemic resulted in approximately 7,900,000 aggregated reported cases and approximately 216,000 deaths in the United States.* Among COVID-19-associated deaths reported to national case surveillance during February 12-May 18, persons aged ≥65 years and members of racial and ethnic minority groups were disproportionately represented (1). This report describes demographic and geographic trends in COVID-19-associated deaths reported to the National Vital Statistics System† (NVSS) during May 1-August 31, 2020, by 50 states and the District of Columbia. During this period, 114,411 COVID-19-associated deaths were reported. Overall, 78.2% of decedents were aged ≥65 years, and 53.3% were male; 51.3% were non-Hispanic White (White), 24.2% were Hispanic or Latino (Hispanic), and 18.7% were non-Hispanic Black (Black). The number of COVID-19-associated deaths decreased from 37,940 in May to 17,718 in June; subsequently, counts increased to 30,401 in July and declined to 28,352 in August. From May to August, the percentage distribution of COVID-19-associated deaths by U.S. Census region increased from 23.4% to 62.7% in the South and from 10.6% to 21.4% in the West. Over the same period, the percentage distribution of decedents who were Hispanic increased from 16.3% to 26.4%. COVID-19 remains a major public health threat regardless of age or race and ethnicity. Deaths continued to occur disproportionately among older persons and certain racial and ethnic minorities, particularly among Hispanic persons. These results can inform public health messaging and mitigation efforts focused on prevention and early detection of infection among disproportionately affected groups.


Subject(s)
Coronavirus Infections/ethnology , Coronavirus Infections/mortality , Ethnicity/statistics & numerical data , Health Status Disparities , Minority Groups/statistics & numerical data , Pandemics , Pneumonia, Viral/ethnology , Pneumonia, Viral/mortality , Racial Groups/statistics & numerical data , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , COVID-19 , Child , Child, Preschool , Female , Humans , Infant , Male , Middle Aged , United States/epidemiology , Vital Statistics , Young Adult
19.
Vital Health Stat 3 ; (44): 1-61, 2020 Jan.
Article in English | MEDLINE | ID: mdl-32510309

ABSTRACT

Maternal mortality is a critical indicator of population health in both the United States and internationally (1-3). Monitoring maternal mortality over time is important to evaluate progress in improving maternal health in the United States, to make international comparisons, and to examine differences and inequities by demographic subgroup (3). Substantial disparities in maternal mortality exist by race and Hispanic origin and age in the United States (4-6). Maternal and pregnancy-related mortality rates for non-Hispanic black women are approximately three times the rates for non-Hispanic white women, while women aged 40 and over have the highest maternal mortality rates compared with other age groups (4,6,7).


Subject(s)
Maternal Mortality/ethnology , Maternal Mortality/trends , Surveys and Questionnaires/statistics & numerical data , Surveys and Questionnaires/standards , Adolescent , Adult , Age Factors , Cause of Death/trends , Ethnicity/statistics & numerical data , Female , Humans , Middle Aged , Pregnancy , Pregnancy Complications/epidemiology , Racial Groups/statistics & numerical data , United States/epidemiology , Vital Statistics , Young Adult
20.
Am J Prev Med ; 58(2): 254-260, 2020 02.
Article in English | MEDLINE | ID: mdl-31735480

ABSTRACT

INTRODUCTION: Infant 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. METHODS: National 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. RESULTS: Nonmetropolitan 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. CONCLUSIONS: Infant 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.


Subject(s)
Cause of Death/trends , Ethnicity/statistics & numerical data , Infant Mortality , Racial Groups/statistics & numerical data , Rural Population/statistics & numerical data , Urban Population/statistics & numerical data , Black or African American/statistics & numerical data , Female , Humans , Indians, North American/statistics & numerical data , Infant , Infant Mortality/ethnology , Infant Mortality/trends , Infant, Newborn , Male , United States , Vital Statistics , White People/statistics & numerical data
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