This dataset contains model-based county estimates for drug-poisoning mortality.

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.

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. 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 for 1999-2015 have been updated, and may differ slightly from previously published estimates. Differences are expected to be minimal, and may result from different county boundaries used in this release (see below) and from the inclusion of an additional year of data. Previously published estimates can be found here for comparison.(6) Estimates are unavailable for Broomfield County, Colorado, and Denali County, Alaska, before 2003 (7,8). Additionally, Clifton Forge County, Virginia only appears on the mortality files prior to 2003, while Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. These counties were therefore merged with adjacent counties where necessary to create a consistent set of geographic units across the time period. County boundaries are largely consistent with the vintage 2005-2007 bridged-race population file geographies, with the modifications noted previously (7,8).

REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm.

1. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.

2. Rossen LM, Khan D, Warner M. Trends and geographic patterns in drug-poisoning death rates in the U.S., 1999–2009. Am J Prev Med 45(6):e19–25. 2013.

3. Rossen LM, Khan D, Warner M. Hot spots in mortality from drug poisoning in the United States, 2007–2009. Health Place 26:14–20. 2014.

4. Rossen LM, Khan D, Hamilton B, Warner M. Spatiotemporal variation in selected health outcomes from the National Vital Statistics System. Presented at: 2015 National Conference on Health Statistics, August 25, 2015, Bethesda, MD. Available from: http://www.cdc.gov/nchs/ppt/nchs2015/Rossen_Tuesday_WhiteOak_BB3.pdf.

5. Rossen LM, Bastian B, Warner M, and Khan D. NCHS – Drug Poisoning Mortality by County: United States, 1999-2015. Available from: https://data.cdc.gov/NCHS/NCHS-Drug-Poisoning-Mortality-by-County-United-Sta/pbkm-d27e.

6. National Center for Health Statistics. County geography changes: 1990–2012. Available from: http://www.cdc.gov/nchs/data/nvss/bridged_race/County_Geography_Changes.pdf.

7. National Center for Health Statistics. County geography changes: 1990–2015. Available from: https://www.cdc.gov/nchs/nvss/bridged_race/county_geography-_changes2015.pdf.

This dataset describes drug poisoning deaths at the county 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).

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.

1. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.

NCHS - Infant and neonatal mortality rates: United States, 1915-2013

  Description

Rates are infants (under 1 year) and neonatal (under 28 days) deaths per 1,000 live births. https://www.cdc.gov/nchs/data-visualization/mortality-trends/

  Dataset Details

Publisher: Centers for Disease Control and Prevention Temporal Coverage: 1915/2013 Geographic Coverage: United States Last Modified: 2025-04-21 Contact: National Center for Health Statistics (cdcinfo@cdc.gov)… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/nchs-infant-and-neonatal-mortality-rates-united-st.

NCHS - VSRR Quarterly provisional estimates for selected indicators of mortality

  Description

Provisional estimates of death rates. Estimates are presented for each of the 15 leading causes of death plus estimates for deaths attributed to drug overdose, falls (for persons aged 65 and over), human immunodeficiency virus (HIV) disease, homicide, and firearms-related deaths.

  Dataset Details

Publisher: Centers for Disease Control and Prevention Temporal Coverage:… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/nchs-vsrr-quarterly-provisional-estimates-for-sele.

The mortality data in this table have been derived from death certificates in participation with the National Vital Statistics System, and are maintained and provided by the Utah Department of Health, Office of Vital Records. They include virtually all deaths of Utah residents, regardless of where the death occurred. The causes of death were coded using International Classification of Diseases (ICD) codes. The population estimates for years 1980-1999 were produced by the Utah Governor's Office of Planning and Budget (GOPB). For years 2000 and later the population estimates are provided by the National Center for Health Statistics (NCHS) through a collaborative agreement with the U.S. Census Bureau. The leading causes of death is defined by NCHS 50 leading causes.

Analysis of ‘NCHS - Drug Poisoning Mortality by County: United States’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/3452f1d5-5a52-4f78-8ff8-02a7f7bff7fc on 12 February 2022.

--- Dataset description provided by original source is as follows ---

This dataset contains model-based county estimates for drug-poisoning mortality.

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.

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. 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 for 1999-2015 have been updated, and may differ slightly from previously published estimates. Differences are expected to be minimal, and may result from different county boundaries used in this release (see below) and from the inclusion of an additional year of data. Previously published estimates can be found here for comparison.(6) Estimates are unavailable for Broomfield County, Colorado, and Denali County, Alaska, before 2003 (7,8). Additionally, Clifton Forge County, Virginia only appears on the mortality files prior to 2003, while Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. These counties were therefore merged with adjacent counties where necessary to create a consistent set of geographic units across the time period. County boundaries are largely consistent with the vintage 2005-2007 bridged-race population file geographies, with the modifications noted previously (7,8).

REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm.

1. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.

2. Rossen LM, Khan D, Warner M. Trends and geographic patterns in drug-poisoning death rates in the U.S., 1999–2009. Am J Prev Med 45(6):e19–25. 2013.

3. Rossen LM, Khan D, Warner M. Hot spots in mortality from drug poisoning in the United States, 2007–2009. Health Place 26:14–20. 2014.

4. Rossen LM, Khan D, Hamilton B, Warner M. Spatiotemporal variation in selected health outcomes from the National Vital Statistics System. Presented at: 2015 National Conference on Health Statistics, August 25, 2015, Bethesda, MD. Available from: http://www.cdc.gov/nchs/ppt/nchs2015/Rossen_Tuesday_WhiteOak_BB3.pdf.

5. Rossen LM, Bastian B, Warner M, and Khan D. NCHS – Drug Poisoning Mortality by County: United States, 1999-2015. Available from: https://data.cdc.gov/NCHS/NCHS-Drug-Poisoning-Mortality-by-County-United-Sta/pbkm-d27e.

6. National Center for Health Statistics. County geog

--- Original source retains full ownership of the source dataset ---

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).

NCHS released maternal mortality statistics for 2018, an extensive review of data quality, and new coding procedures for death certificates based on this review.

NCHS - Age-adjusted Death Rates for Selected Major Causes of Death

  Description

This dataset of U.S. mortality trends since 1900 highlights trends in age-adjusted death rates for five selected major causes of death. Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/nchs-age-adjusted-death-rates-for-selected-major-c.

Analysis of ‘NCHS - Drug Poisoning Mortality by State: United States’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/e469e38a-aa81-4bf9-9218-7fbed56cb5a5 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

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).

--- Original source retains full ownership of the source dataset ---

NCHS - Injury Mortality: United States

  Description

This dataset describes injury mortality in the United States beginning in 1999. Two concepts are included in the circumstances of an injury death: intent of injury and mechanism of injury. Intent of injury describes whether the injury was inflicted purposefully (intentional injury) and, if purposeful, whether the injury was self-inflicted (suicide or self-harm) or inflicted by another person (homicide). Injuries that were… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/nchs-injury-mortality-united-states.

National provisional drug overdose deaths by month and 2013 NCHS Urban–Rural Classification Scheme for Counties. Drug overdose deaths are identified using underlying cause-of-death codes from the Tenth Revision of ICD (ICD–10): X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), and Y10–Y14 (undetermined). Deaths are based on the county of residence in the United States. Death counts provided are for “12-month ending periods,” defined as the number of deaths occurring in the 12-month period ending in the month indicated. Estimates for 2020 are based on provisional data. Estimates for 2018 and 2019 are based on final data. For more information on NCHS urban-rural classification, see: https://www.cdc.gov/nchs/data/series/sr_02/sr02_166.pdf

NCHS - Percent Distribution of Births to Unmarried Women by Age Group: United States

  Description

This dataset includes percent distribution of births to unmarried women by age group in the United States since 1970. Methods for collecting information on marital status changed over the reporting period and have been documented in: • Ventura SJ, Bachrach CA. Nonmarital childbearing in the United States, 1940–99. National vital statistics reports; vol 48 no 16. Hyattsville… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/nchs-percent-distribution-of-births-to-unmarried-w.

NCHS - Nonmarital Birth Rates, by Age Group for All Women Age 15-44: United States, 1970-2013

  Description

https://www.cdc.gov/nchs/data-visualization/births-to-unmarried-women/index.htm

  Dataset Details

Publisher: Centers for Disease Control and Prevention Temporal Coverage: 1970/2013 Last Modified: 2025-04-21 Contact: National Center for Health Statistics (births@cdc.gov)

  Source

Original data can be found at:… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/nchs-nonmarital-birth-rates-by-age-group-for-all-w.

NCHS - VSRR Quarterly provisional estimates for infant mortality

  Description

Provisional estimates of infant mortality (deaths of infants under 1 year per 1,000 live births), neonatal mortality (deaths of infants aged 0-27 days per 1,000 live births), postneonatal mortality (deaths of infants aged 28 days through 11 months per 1,000 live births), and death rates for the five leading causes of infant death.

  Dataset Details

Publisher: Centers for Disease Control… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/nchs-vsrr-quarterly-provisional-estimates-for-infa.

NCHS - Births and General Fertility Rates: United States

  Description

This dataset includes crude birth rates and general fertility rates in the United States since 1909. The number of states in the reporting area differ historically. In 1915 (when the birth registration area was established), 10 states and the District of Columbia reported births; by 1933, 48 states and the District of Columbia were reporting births, with the last two states, Alaska and Hawaii, added to… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/nchs-births-and-general-fertility-rates-united-sta.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Divorce estimates may vary from the divorce data released by the National Center for Health Statistics (NCHS) because of differences in methodology and data collection. NCHS uses information collected on divorce decrees from states providing them. From these administrative records, NCHS then publishes information about couples who divorced in a calendar year. In contrast, the ACS collects survey-based reports from individuals as to whether or not they divorced in the last 12 months. We recommend using caution when comparing the NCHS estimates to the ACS estimates of divorces..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Information on the fetal death data tape file was abstracted from the Report of Fetal Death forms received in all the States and the District of Columbia, with a record on the data file for each report of a fetal death received. The data is provided to the National Center for Health Statistics (NCHS) through the Vital Statistics Cooperative Program by the registration offices of all States, the District of Columbia, and New York City. Data from New York, excluding New York City, were submitte d in machine readable form. All other 1992 data were coded and keyed by the U.S. Bureau of the Census. Fetal death data are limited to deaths occurring within the United States to U.S. residents and nonresidents. Fetal deaths occurring to U.S. citizens outside the United States are not included in this data file. In NCHS tabulations by place of residence, fetal deaths to nonresidents of the United States are excluded. The foreign resident records can be identified by code 4 in tape location 7 of the data tape. In addition, the majority of fetal death tables published by NCHS include only those fetal deaths with stated or presumed gestation of 20 weeks or more (see the Technical Appendix). Those records identified with a 2 in tape location 5 are included in these tabulations. All other records are excluded. Effective January 1, 1989, a revised U-S. Standard Report of Fetal Death replaced the 1978 revision. The 1989 revision provides a wide variety of new information on maternal and fetal health characteristics. Questions on complications of labor and delivery and congenital anomalies of fetus were changed from an open-ended question to a checkbox format to improve reporting of information. Several new items were added that improve the data files value for monitoring and research of factors affecting fetal mortality. The Office of Management and Budget revised its designation of metropolitan statistical areas based on figures from the 1990 Census. Effective with the 1990 data file, NCHS has been using these new definitions and codes as indicated in the listing of 320 Metropolitan Statistical Areas (MSAS), Primary Metropolitan Statistical Areas (PMSAS), and New England County Metropolitan Ar eas (NEaSS) included in this documentation. There are also 20 Consolidated Metropolitan Statistical Areas (mSAS), which are made up of PMSAS. Other geographic changes based on the 1990 Census will be implemented later. NCHS has adopted a new policy on release of vital statistics unit record data files. This new policy was implemented with the 1989 vital event files to prevent the inadvertent disclosure of individuals and institutions. As a result, this file does not contain the actual day of the death. The geographic detail is also restricted-only counties and cities of 100,000 or more population based on the 1980 Census as well as metropolitan areas of 100,000 or more population based on the 1990 Census, are identified. NOSB = Note to Users: This CD is part of a collection located in the Data Archive at the Odum Institute for Research in Social Science, University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check out the CDs, subscribing to the honor system. Items may be checked out for a period of two weeks. Loan forms are located adjacent to the collection.

This data visualization presents county-level provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. County-level provisional counts include deaths occurring within the 50 states and the District of Columbia, as of the date specified and may not include all deaths that occurred during a given time period. Provisional counts are often incomplete and causes of death may be pending investigation resulting in an underestimate relative to final counts (see Technical Notes).

The provisional data presented on the dashboard below include reported 12 month-ending provisional counts of death due to drug overdose by the decedent’s county of residence and the month in which death occurred.

Percentages of deaths with a cause of death pending further investigation and a note on historical completeness (e.g. if the percent completeness was under 90% after 6 months) are included to aid in interpretation of provisional data as these measures are related to the accuracy of provisional counts (see Technical Notes). Counts between 1-9 are suppressed in accordance with NCHS confidentiality standards. Provisional data presented on this page will be updated on a quarterly basis as additional records are received.

Technical Notes

Nature and Sources of Data

Provisional drug overdose death counts are based on death records received and processed by the National Center for Health Statistics (NCHS) as of a specified cutoff date. The cutoff date is generally the first Sunday of each month. National provisional estimates include deaths occurring within the 50 states and the District of Columbia. NCHS receives the death records from the state vital registration offices through the Vital Statistics Cooperative Program (VSCP).

The timeliness of provisional mortality surveillance data in the National Vital Statistics System (NVSS) database varies by cause of death and jurisdiction in which the death occurred. The lag time (i.e., the time between when the death occurred and when the data are available for analysis) is longer for drug overdose deaths compared with other causes of death due to the time often needed to investigate these deaths (1). Thus, provisional estimates of drug overdose deaths are reported 6 months after the date of death.

Provisional death counts presented in this data visualization are for “12 month-ending periods,” defined as the number of deaths occurring in the 12 month period ending in the month indicated. For example, the 12 month-ending period in June 2020 would include deaths occurring from July 1, 2019 through June 30, 2020. The 12 month-ending period counts include all seasons of the year and are insensitive to reporting variations by seasonality. These provisional counts of drug overdose deaths and related data quality metrics are provided for public health surveillance and monitoring of emerging trends. Provisional drug overdose death data are often incomplete, and the degree of completeness varies by jurisdiction and 12 month-ending period. Consequently, the numbers of drug overdose deaths are underestimated based on provisional data relative to final data and are subject to random variation.

Cause of Death Classification and Definition of Drug Deaths

Mortality statistics are compiled in accordance with the World Health Organizations (WHO) regulations specifying that WHO member nations classify and code causes of death with the current revision of the International Statistical Classification of Diseases and Related Health Problems (ICD). ICD provides the basic guidance used in virtually all countries to code and classify causes of death. It provides not only disease, injury, and poisoning categories but also the rules used to select the single underlying cause of death for tabulation from the several diagnoses that may be reported on a single death certificate, as well as definitions, tabulation lists, the format of the death certificate, and regulations on use of the classification. Causes of death for data presented on this report were coded according to ICD guidelines described in annual issues of Part 2a of the NCHS Instruction Manual (2). Drug overdose deaths are identified using underlying cause-of-death codes from the Tenth Revision of ICD (ICD–10): X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), and Y10–Y14 (undetermined).

Selection of Specific Jurisdictions to Report

Provisional counts are presented by the jurisdiction where the decedent resides (e.g. county of residence). Data quality and timeliness for drug overdose deaths vary by reporting jurisdiction. Provisional counts are presented, along with measures of data quality: the percentage of records where the manner of death is listed as “pending investigation”, and a note for specific jurisdictions with historically lower levels of data completeness (where provisional 2019 data were less than 90% complete after 6 months).

Percentage of Records Pending Investigation

Drug overdose deaths often require lengthy investigations, and death certificates may be initially filed with a manner of death “pending investigation” and/or with a preliminary or unknown cause of death. When the percentage of records reported as “pending investigation” is high for a given jurisdiction, the number of drug overdose deaths is likely to be underestimated. Counts of drug overdose deaths may be underestimated to a greater extent in jurisdictions or counties where more records in NVSS are reported as “pending investigation” for the six most recent 12 month-ending periods.

Historical Completeness

The historical percent completeness of provisional data is obtained by dividing the number of death records in the NVSS database for each jurisdiction and county after a 6-month lag for deaths occurring in 2019 by the number of deaths eventually included in the final data files. Counties with historically lower levels of provisional data completeness are flagged with a note to indicate that the data may be incomplete in these areas. However, the completeness of provisional data may change over time, and therefore the degree of underestimation will not be known until data are finalized (typically 11-12 months after the end of the data year).

Differences between Final and Provisional Data

There may be differences between provisional and final data for a given data year (e.g., 2020). Final drug overdose death data published annually through NCHS statistical reports (3) and CDC WONDER undergo additional data quality checks and processing. Provisional counts reported here are subject to change as additional data are received.

Source

NCHS, National Vital Statistics System. Estimates for 2020 and 2021 are based on provisional data. Estimates for 2019 are based on final data (available from: https://www.cdc.gov/nchs/nvss/mortality_public_use_data.htm).

References

1. Spencer MR, Ahmad F. Timeliness of death certificate data for mortality surveillance and provisional estimates. National Center for Health Statistics. 2016. Available from: https://www.cdc.gov/nchs/data/vsrr/report001.pdf
2. National Vital Statistics System. Instructions for classifying the underlying cause of death. In: NCHS instruction manual; Part 2a. Published annually.
3. Hedegaard H, Miniño AM, Warner M. Drug overdose deaths in the United States, 1999–2018. NCHS Data Brief, no 356. Hyattsville, MD: National Center for Health Statistics. 2020. Available from: https://www.cdc.gov/nchs/products/databriefs/db356.htm

Suggested Citation

Ahmad FB, Anderson RN, Cisewski JA, Rossen LM, Warner M, Sutton P. County-level provisional drug overdose death counts. National Center for Health Statistics. 2021.

Designed by MirLogic Solutions Corp: National Center for Health Statistics.