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The dataset presents life expectancy at birth estimates based on annual complete period life tables for each of the 50 states and the District of Columbia (D.C.)
in 2018 for the total, male and female populations.
Tags deaths life expectancy mortality nchs state and 3 more
Updated
July 25 2023
Views
300

External Link
This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning from 1999 to 2015.
Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent).
Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2015 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published.
Estimate does not meet standards of reliability or precision. Death rates are flagged as “Unreliable” in the chart when the rate is calculated with a numerator of 20 or less.
Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Estimates should be interpreted with caution.
Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year during 1999–2015. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates are unavailable for Broomfield County, Colo., and Denali County, Alaska, before 2003 (6,7). Additionally, Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. County boundaries are consistent with the vintage 2005-2007 bridged-race population file geographies (6).
Tags deaths drug poisoning mortality national state and 2 more
Updated
July 25 2023
Views
156

External Link
Effective September 27, 2023, this dataset will no longer be updated. Similar data are accessible from wonder.cdc.gov.
This visualization provides weekly data on the number of deaths from all causes by jurisdiction of occurrence and age group. Counts of deaths in more recent weeks can be compared with counts from earlier years to determine if the number is higher than expected.
Tags age age group all causes deaths state and 7 more
Updated
September 28 2023
Views
1,249

External Link
This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning.
Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent).
Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published.
Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances.
REFERENCES
1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm.
2. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.
Tags deaths drug poisoning mortality national state and 2 more
Updated
July 26 2023
Views
188

External Link

The United States Cancer Statistics (USCS) online databases in WONDER provide cancer incidence and mortality data for the United States for the years since 1999, by year, state and metropolitan areas (MSA), age group, race, ethnicity, gender, childhood cancer classifications and cancer site. Report case counts, deaths, crude and age-adjusted incidence and death rates, and 95% confidence intervals for rates. The USCS data are the official federal statistics on cancer incidence from registries having high-quality data and cancer mortality statistics for 50 states and the District of Columbia. USCS are produced by the Centers for Disease Control and Prevention (CDC) and the National Cancer Institute (NCI), in collaboration with the North American Association of Central Cancer Registries (NAACCR). Mortality data are provided by the Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), National Vital Statistics System (NVSS).

Tags age cancer epidemiology ethnicity state and 9 more
Updated
July 26 2023
Views
2,515

External Link
This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning.
Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent).
Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2016 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published.
Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances.
REFERENCES
1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm.
2. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.
Tags deaths drug poisoning mortality national state and 2 more
Updated
July 25 2023
Views
136

External Link
Data on active dentists in the United States by state. Data are from Health, United States. SOURCE: American Dental Association, Health Policy Institute.
Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.
Tags dentists health us state
Updated
September 7 2024
Views
36

External Link

The Population online databases contain data from the US Census Bureau. The Census Estimates online database contains contains county-level population counts for years 1970 - 2000. The data comprise the April 1st Census counts for years 1970, 1980, 1990 and 2000, the July 1st intercensal estimates for years 1971-1979 and 1981-1989, and the July 1st postcensal estimates for years 1991-1999. The Census Projections online database contains population projections for years 2004-2030 by year, state, age, race and sex, prodyced by teh Cenus Bureau in 2005. The data are produced by the United States Department of Commerce, U.S. Census Bureau, Population Division.

Tags age county population statistics race state and 2 more
Updated
July 25 2023
Views
162

External Link
2005-2016. This dataset includes data from the retired BRFSS Vision Module. From 2005-2011 the BRFSS employed a ten question vision module regarding vision impairment, access and utilization of eye care, and self-reported eye diseases. In 2013 and subsequently, one question in the core of BRFSS asks about vision: “Are you blind or do you have serious difficulty seeing, even when wearing glasses?” The latest data for this core question can be found in the Vision and Eye Health Surveillance System (VEHSS). VEHSS is intended to provide population estimates of vision loss function, eye diseases, health disparities, as well as barriers and facilitators to access to vision and eye care. This information can be used for designing, implementing, and evaluating vision and eye health prevention programs. To access the latest BRFSS data, (2013-2017) view the Behavioral Risk Factors – Vision and Eye Health Surveillance dataset (https://chronicdata.cdc.gov/Vision-Eye-Health/Behavioral-Risk-Factors-Vision-and-Eye-Health-Surv/vkwg-yswv).
Tags diabetes eye diseases heart diseases hypertension state and 5 more
Updated
September 22 2023
Views
525

External Link
Effective September 27, 2023, this dataset will no longer be updated. Similar data are accessible from wonder.cdc.gov.
Estimates of excess deaths can provide information about the burden of mortality potentially related to COVID-19, beyond the number of deaths that are directly attributed to COVID-19. Excess deaths are typically defined as the difference between observed numbers of deaths and expected numbers. This visualization provides weekly data on excess deaths by jurisdiction of occurrence. Counts of deaths in more recent weeks are compared with historical trends to determine whether the number of deaths is significantly higher than expected.
Estimates of excess deaths can be calculated in a variety of ways, and will vary depending on the methodology and assumptions about how many deaths are expected to occur. Estimates of excess deaths presented in this webpage were calculated using Farrington surveillance algorithms (1). For each jurisdiction, a model is used to generate a set of expected counts, and the upper bound of the 95% Confidence Intervals (95% CI) of these expected counts is used as a threshold to estimate excess deaths. Observed counts are compared to these upper bound estimates to determine whether a significant increase in deaths has occurred. Provisional counts are weighted to account for potential underreporting in the most recent weeks. However, data for the most recent week(s) are still likely to be incomplete. Only about 60% of deaths are reported within 10 days of the date of death, and there is considerable variation by jurisdiction. More detail about the methods, weighting, data, and limitations can be found in the Technical Notes.
Tags all causes coronavirus covid-19 deaths state and 8 more
Updated
September 28 2023
Views
1,029