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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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Department of Human Services(DHS): Child Support Enforcement Administration Performance Measures
healthdata.gov | Last Updated 2023-11-21T04:02:09.000ZCHILD SUPPORT ENFORCEMENT ADMINISTRATION The performance measures are used to evaluate each State's performance and measure results in the Child Support Enforcement program. These measures emphasize paternity establishment, support order establishment, collection of current support, collection of arrearages, and cost effectiveness. The performance measures, except cost effectiveness which can only be measured annually, are calculated from data which is reported on federal form OCSE 157. CASES WITH SUPPORT ORDERS This metric measures the proportion of IV-D cases with support orders established. Equation: Number of IV-D Cases with Support Orders divided by Total Number of IV-D Cases IV-D Paternity Establishment Percentage: This metric measures the proportion of children in the IV-D caseload as of the end of the preceding FFY who were born out of wedlock is the total number of children in the IV-D caseload in the federal fiscal year born out of wedlock with paternity established or acknowledged divided by the total number of children in the IV-D caseload as of the end of the preceding FFY who were born out of wedlock. . Equation: Total # of Children in IV-D Caseload in the Federal Fiscal Year or, as of the end of the Fiscal Year who were born out of wedlock with Paternity Established or Acknowledged divided by Total # of Children in IV-D Caseload as of the end of the preceding Federal Fiscal Year who were Born Out of Wedlock COLLECTIONS ON CURRENT SUPPORT This measure focuses on the proportion of current support due that is collected on IV-D cases. Equation: Total Dollars Collected for Current Support in IV-D Cases during the Federal Fiscal Year divided by Total Dollars Owed for Current Support in IV-D Cases during the Federal Fiscal Year COLLECTIONS ON ARREARS The measure assesses efforts to collect money from those cases with an arrearage due. The measure specifically counts paying cases, and not total arrears dollars collected. Equation: Total number of IV-D cases paying toward arrears during the Federal Fiscal Year divided by Total number of IV-D cases with arrears due
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Road Traffic Injuries
healthdata.gov | Last Updated 2023-07-26T12:08:09.000ZThis table contains data on the annual number of fatal and severe road traffic injuries per population and per miles traveled by transport mode, for California, its regions, counties, county divisions, cities/towns, and census tracts. Injury data is from the Statewide Integrated Traffic Records System (SWITRS), California Highway Patrol (CHP), 2002-2010 data from the Transportation Injury Mapping System (TIMS) . The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity]. Transportation accidents are the second leading cause of death in California for people under the age of 45 and account for an average of 4,018 deaths per year (2006-2010). Risks of injury in traffic collisions are greatest for motorcyclists, pedestrians, and bicyclists and lowest for bus and rail passengers. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience 4 times the death rate as Whites or Asians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.
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Children by Disposition
healthdata.gov | Last Updated 2023-07-25T18:18:16.000ZThe numbers of children (duplicate count) are counted once for each investigation response or alternative response that reached a disposition (finding) for the most recent federal fiscal year for which data are available. *11/29/2021: Added column including year in which data was collected. To view more National Child Abuse and Neglect Data System (NCANDS) findings, click link to summary page below: https://healthdata.gov/stories/s/kaeg-w7jc
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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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Annual Miles Traveled
healthdata.gov | Last Updated 2023-07-26T12:25:17.000ZThis table contains data on the annual miles traveled by place of occurrence and by mode of transportation (vehicle, pedestrian, bicycle), for California, its regions, counties, and cities/towns. The ratio uses data from the California Department of Transportation, the U.S. Department of Transportation, and the U.S. Census Bureau. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Miles traveled by individuals and their choice of mode – car, truck, public transit, walking or bicycling – have a major impact on mobility and population health. Miles traveled by automobile offers extraordinary personal mobility and independence, but it is also associated with air pollution, greenhouse gas emissions linked to global warming, road traffic injuries, and sedentary lifestyles. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which has many documented health benefits. More information about the data table and a data dictionary can be found in the About/Attachments section.
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Transportation to Work
healthdata.gov | Last Updated 2023-07-25T20:47:11.000ZThis table contains data on the percent of residents aged 16 years and older mode of transportation to work for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Commute trips to work represent 19% of travel miles in the United States. The predominant mode – the automobile - offers extraordinary personal mobility and independence, but it is also associated with health hazards, such as air pollution, motor vehicle crashes, pedestrian injuries and fatalities, and sedentary lifestyles. Automobile commuting has been linked to stress-related health problems. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which is associated with lowering rates of heart disease and stroke, diabetes, colon and breast cancer, dementia and depression. Risk of injury and death in collisions are higher in urban areas with more concentrated vehicle and pedestrian activity. Bus and rail passengers have a lower risk of injury in collisions than motorcyclists, pedestrians, and bicyclists. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience four times the death rate Whites or Asian pedestrians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.
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Evergreen Heights Elementary update
healthdata.gov | Last Updated 2023-07-25T20:35:59.000ZLead in Drinking Water in Schools Test Results – Evergreen Heights Elementary
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HIV Ambulatory Care Quality of Care Performance Results: Beginning 2011
healthdata.gov | Last Updated 2023-07-25T20:37:30.000ZThis dataset represents self‐reported performance data by HIV ambulatory care programs. All HIV ambulatory programs throughout New York State with a significant HIV caseload (a total caseload of at least 30 HIV‐infected patients receiving ambulatory HIV care at one or more sites) are expected to self‐report their annual quality of care performance data using standardized submission tools and methodologies. With the assistance of the online eHIVQUAL application, performance data results are instantly available to HIV programs, allowing them to immediately utilize their data findings to prioritize upcoming quality activities, and are available for generating benchmarking reports across New York State. See Limitations regarding redaction of small‐population data.