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NCHS - Drug Poisoning Mortality by County: United States
healthdata.gov | Last Updated 2023-07-25T17:57:16.000ZThis 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. 2. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html. 3. 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. 4. 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. 5. 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. 6. 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. 7. National Center for Health Statistics. County geog
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Animal Contact Exhibits_Legal Epidemiology Research Procedure and Code Book_2016
healthdata.gov | Last Updated 2023-07-26T01:28:18.000ZAnimals at petting zoos and agricultural fairs can be carriers of pathogens, such as Escherichia coli. Disease outbreaks at animal contact exhibits can be prevented by handwashing after contact with animals and keeping food and beverage away from exhibits. This research procedure and code book accompanies the data set, Animal Contact Exhibits_Legal Epidemiology Dataset_2016, which catalogs and analyzes a collection of state hand sanitation laws for the following categories of animal contact exhibits: a. Petting zoos b. Agricultural fairs c. County or state fairs d. Exotic animal exhibits e. Circuses f. Zoos
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Assisted Reproductive Technology (ART) Surveillance
healthdata.gov | Last Updated 2023-07-25T17:53:28.000Z<p>In 1992, Congress enacted the Fertility Clinic Success Rate and Certification Act (FCSRCA). The act requires CDC to collect data from clinics and submit an annual report to Congress on Assisted Reproductive Technology (ART) success rates. In 1996, CDC initiated the ART Surveillance System to collect cycle specific and clinic specific data from all medical clinics practicing ART in the United States and its territories. The data collected include patient's diagnosis, type of ART, clinical information pertaining to the ART procedure, and information on pregnancy outcomes.</p>
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Approved Animal Drug Products (Green Book)
healthdata.gov | Last Updated 2023-07-25T18:40:13.000ZOn November 16, 1988, the President of the United States signed into law the Generic Animal Drug and Patent Restoration Act (GADPTRA). Among its major provisions, the Act extends eligibility for submission of Abbreviated New Animal Drug Applications (ANADAs) to all animal drug products approved for safety and effectiveness under the Federal Food, Drug, and Cosmetic Act. The Act also requires that each sponsor of an approved animal drug product submit to the FDA certain information regarding patents held for the animal drug or its method of use. The Act requires that this information, as well as a list of all animal drug products approved for safety and effectiveness, be made available to the public. This list must be updated monthly under the provisions of the Act. This publication, which is known as the �Green Book�, was first published in January of 1989. Updates have been added monthly since then. The list is published in its entirety each January.
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Youth Tobacco Survey (YTS) Data
healthdata.gov | Last Updated 2023-08-26T04:00:22.000Z1999-2017. Centers for Disease Control and Prevention (CDC). State Tobacco Activities Tracking and Evaluation (STATE) System. YTS Data. The YTS was developed to provide states with comprehensive data on both middle school and high school students regarding tobacco use, exposure to environmental tobacco smoke, smoking cessation, school curriculum, minors' ability to purchase or otherwise obtain tobacco products, knowledge and attitudes about tobacco, and familiarity with pro-tobacco and anti-tobacco media messages. The YTS uses a two-stage cluster sample design to produce representative samples of students in middle schools (grades 6–8) and high schools (grades 9–12). The data for the STATE System were extracted from Youth Tobacco Surveys from participating states. Tobacco topics included are cigarette smoking prevalence, cigarette smoking frequency, smokeless tobacco products prevalence and quit attempts.
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DASH - Global School-based Student Health Survey (GSHS)
healthdata.gov | Last Updated 2023-08-26T04:00:50.000Z2003-2015. Global School dataset. The Global School-based Student Health Survey (GSHS) was developed by the World Health Organization (WHO) in collaboration with the United Nations' UNICEF, UNESCO, and UNAIDS; and with technical assistance from CDC. The GSHS is a school-based survey conducted primarily among students aged 13-17 years in countries around the world. It uses core questionnaire modules that address the leading causes of morbidity and mortality among children and adults worldwide: 1) Alcohol use, 2) dietary behaviors, 3) drug use, 4) hygiene, 5) mental health, 6) physical activity, 7) protective factors, 8) sexual behaviors that contribute to HIV infection, other sexually-transmitted infections, and unintended pregnancy, 9) tobacco use, and 10) violence and unintentional injury. This dataset contains global data from 2003 – 2015. Additional information about the GSHS can be found at https://www.cdc.gov/gshs/index.htm.
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NCHS - Childhood Mortality Rates
healthdata.gov | Last Updated 2023-07-25T20:41:19.000ZThis dataset of U.S. mortality trends since 1900 highlights childhood mortality rates by age group for age at 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 for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below). Age groups for childhood death rates are based on age at death. SOURCES CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES 1. National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm. 2. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. 3. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf. 4. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf. 5. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.
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PubMed total records by publication year
healthdata.gov | Last Updated 2024-09-04T04:01:53.000ZYearly citation totals from each year of the MEDLINE/PubMed Baseline referencing citations back to year 1781. These totals may increase over time for a particular year as new citations are added. For example, 25 citations were listed for the year 1800 in the 2018 MEDLINE/PubMed Baseline, while the 2019 Baseline includes 387 citations for that year.
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Office of Head Start (OHS) Head Start Center Locations Search Tool
healthdata.gov | Last Updated 2023-07-26T01:28:28.000Z<p>Office of Head Start (OHS) web based search tool for finding Head Start program office contact information. Searchable by location, grant number or center type. Results are downloadable in CSV format.</p>
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Botswana Combination Prevention Project (BCPP) - Public Release Data
healthdata.gov | Last Updated 2023-07-26T12:10:32.000ZThe Botswana Combination Prevention Project (BCPP) was a research project conducted by the Botswana Ministry of Health (MOH), Harvard School of Public Health/Botswana Harvard AIDS Institute Partnership (BHP), and the U.S. Centers for Disease Control and Prevention (CDC). BCPP was a community randomized trial that examined the impact of prevention interventions on HIV incidence in 15 intervention and 15 control communities. The interventions included extensive HIV testing, linkage to care, and universal treatment services. To reduce HIV incidence in the intervention communities, the UNAIDS 90-90-90 goals were used: 90% of HIV-positive persons know their status; 90% of persons who know status are to be on ART; 90% of persons on ART are to be virally suppressed. The BCPP study is composed of 2 interlocking protocols: Evaluation Protocol and Intervention Protocol. The Evaluation Protocol of the BCPP evaluated the primary endpoint (HIV incidence), as well as some key related secondary endpoints. This protocol focused on the Baseline Household Survey; the HIV Incidence Cohort; and an End of Study Survey. The Intervention Protocol of the BCPP implemented the combination prevention (CP) intervention package in CPCs and measures the uptake of these interventions (expanded HIV testing and counselling, strengthened male circumcision, and expanded HIV Care and Treatment).