The adult obesity rate of Jefferson County, AL was 32.90% in 2015.

Health Behaviors

The Robert Wood Johnson Foundation produces health rankings for states and counties. They explore many aspects of health including quality of life, health behaviors, access to clinical care, socioeconomic factors, and environmental factors.

Above charts are based on data from the Robert Wood Johnson Foundation | Data Source | ODN Dataset | API - Notes:

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Health and Health Behaviors Datasets Involving Jefferson County, AL

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    San Diego County Smoking Attributable Mortality

    data.sandiegocounty.gov | Last Updated 2019-03-29T18:49:10.000Z

    This dataset presents smoking attributable deaths for San Diego County by condition and overall categories for those 35 years of age and older. 2014-2016. For data by HHSA Region or archived years, please visit www.sdhealthstatistics.com Methods: Fractions by the Centers for Disease Control, Smoking‐Attributable Mortality, Morbidity, and Economic Costs (SAMMEC) System. http://www.ncbi.nlm.nih.gov/books/NBK294316/table/ch12.t4/?report=objectonly Note: Deaths with unknown age or sex were not included in the analysis. Deaths were pulled using 2016 ICD 10 codes. Source: California Department of Public Health, Center for Health Statistics, Office of Health Information and Research, Vital Records Business Intelligence System (2016). Prepared by County of San Diego, Health & Human Services Agency, Public Health Services, Community Health Statistics Unit, 2019. Note: COPD = chronic obstructive pulmonary disease. a - Other cancers consist of cancers of the lip, pharynx and oral cavity, esophagus, stomach, pancreas, larynx, cervix uteri (women), kidney and renal pelvis, bladder, liver, colon and rectum, and acute myeloid leukemia. b - Other heart disease comprised of rheumatic heart disease, pulmonary heart disease, and other forms of heart disease. c - Cerebrovascular diseases ICD-10 Codes: I60-I69 d - Other vascular diseases are comprised of atherosclerosis, aortic aneurysm, and other arterial diseases. e - Pulmonary diseases consists of pneumonia, influenza, emphysema, bronchitis, and chronic airways obstruction. f - Prenatal conditions (All Ages) comprised of ICD-10 codes: K55.0, P00.0, P01.0, P01.1, P01.5, P02.0, P02.1, P02.7, P07.0–P07.3, P10.2, P22.0–P22.9, P25.0–P27.9, P28.0, P28.1, P36.0–P36.9, P52.0–P52.3, and P77 (Dietz et al. 2010). g - Sudden Infant Death Syndrome ((All Ages) ICD-10 code R95

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    Percent Of Adults Who Ever Smoked All States All Years

    opendata.utah.gov | Last Updated 2019-04-19T08:27:20.000Z

    Percent Of Adults Who Ever Smoked All States All Years

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    Fire Dispatches: 2012 - 2017

    opendata.howardcountymd.gov | Last Updated 2019-04-23T05:20:50.000Z

    Emergency incidents created by HCPD's 911 Dispatch Center and classified as Fire, Rescue or Emergency Medical Service (EMS) calls. Not all of these incidents are created as cases, and thus not all of these incidents have a matching record in the Howard County Fire & Rescue Incidents table.

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    Number Of Adults Who Ever Smoked All States All Years

    opendata.utah.gov | Last Updated 2019-04-19T02:27:44.000Z

    Number Of Adults Who Ever Smoked All States All Years

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    Family Health Home Visit Expansion

    datahub.smcgov.org | Last Updated 2018-09-11T20:50:05.000Z

    FHHVE Measure K Performance

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    Family Health Home Visit Expansion

    performance.smcgov.org | Last Updated 2018-06-12T21:29:39.000Z

    FHHVE Measure K Performance

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    Number Of People Without Health Insurance All States 2005-2012

    opendata.utah.gov | Last Updated 2019-04-19T06:44:33.000Z

    Number Of People Without Health Insurance All States 2005-2012

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    Potentially Avoidable Antibiotic Prescribing Rates for Acute Respiratory Infection by Provider County, Adults Age 18-64 Years, NYS Medicaid: Beginning 2010

    health.data.ny.gov | Last Updated 2018-11-01T18:02:22.000Z

    This dataset contains Potentially Avoidable Antibiotic Prescribing observed and risk-adjusted rates for adult Medicaid enrollees by provider county beginning in 2010. Potentially Avoidable Antibiotic Prescriptions are antibiotic prescriptions filled for the treatment of acute respiratory infections for which antibiotics are not indicated, contributing to bacterial drug resistance. Index visits for acute respiratory infections and corresponding prescription fills were identified through the use of previously published methods. The rates were calculated using Medicaid outpatient claims and encounters, and prescription drug data. The observed and risk adjusted rates are presented by provider county (including a statewide total).

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    Potentially Avoidable Antibiotic Prescribing Rates for Acute Respiratory Infection by Provider County, Children Age 3 Months-17 Years, NYS Medicaid: Beginning 2010

    health.data.ny.gov | Last Updated 2018-12-13T18:34:12.000Z

    This dataset contains Potentially Avoidable Antibiotic Prescribing observed and risk-adjusted rates for child Medicaid enrollees by provider county beginning in 2010. Potentially Avoidable Antibiotic Prescriptions are antibiotic prescriptions filled for the treatment of acute respiratory infections for which antibiotics are not indicated, contributing to bacterial drug resistance. Index visits for acute respiratory infections and corresponding prescription fills were identified through the use of previously published methods. The rates were calculated using Medicaid outpatient claims and encounters, and prescription drug data. The observed and risk adjusted rates are presented by provider county (including a statewide total).

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    Ambulance Patient Offload Delay Data, 2012 to Present

    data.countyofriverside.us | Last Updated 2017-06-01T16:08:43.000Z

    This data is collected from the dispatch data of Riverside County's primary contracted 9-1-1 medical response provider, American Medical Response (AMR). It is the interval that ambulance crews and patients are retained past the initial 30 minutes after arrival to the Emergency Department. This data is used to evaluate hospital Emergency Department compliance with the offload standard and evaluate how the impact of offload delays may be affecting the 9-1-1 response system.