| 6488 |
Centers for Disease Control and Prevention |
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Promoting active communities in a culture of distracted driving |
Efforts to improve health outcomes through behavioral modification are often complicated by external factors that may thwart success and introduce potential harm. Factors associated with traffic safety present a contemporary challenge to efforts to promote physical activity. One example is the difficulty of encouraging pedestrian-based physical activity because of the growing prevalence of distracted driving. |
| pedestrian-based physical activity | 0.60409 |
| communications technology sector | 0.514475 |
| active communities | 0.531982 |
| Texas A&M University | 0.53029 |
| environmental modifications | 0.528527 |
| monthly text messages | 0.529517 |
| Matthew Lee Smith | 0.512769 |
| Rural Public Health | 0.639553 |
| reduced collision claims | 0.522761 |
| commercial automotive industry | 0.519177 |
| portable technology device | 0.527996 |
| College Station | 0.560722 |
| Mark E. Benden | 0.521829 |
| Science Center School | 0.617911 |
| health outcomes | 0.515245 |
| bicycle lanes | 0.550293 |
| Traffic Safety Association | 0.552938 |
| active transportation | 0.551606 |
| roadway design accounts | 0.546953 |
| Healthy People | 0.525273 |
| markedly increased injuries | 0.520261 |
| public health | 0.732922 |
| street-scale environmental policies | 0.543782 |
| distracted driving | 0.628849 |
|
| overall roadway safety | 0.554407 |
| bicyclists | 0.547642 |
| mobile communication technology | 0.532008 |
| automobile-pedestrian interactions | 0.530585 |
| pedestrians | 0.620233 |
| street design features | 0.537398 |
| A&M Health Science | 0.63285 |
| road users | 0.545912 |
| Texas A&M Health | 0.632675 |
| traffic safety | 0.617277 |
| physical activity | 0.995746 |
| promotes physical activity | 0.58713 |
| public health movement | 0.573079 |
| Complete Streets initiative | 0.655312 |
| proper technological solutions | 0.512361 |
| Health Science Center | 0.63436 |
| hand-held cellular telephone | 0.533732 |
| Public Health Service | 0.566616 |
| physical activity opportunities | 0.586768 |
| unsafe street environments | 0.532751 |
| independently rising growth | 0.518548 |
| specifies active transportation | 0.547873 |
| modifiable public infrastructures | 0.56629 |
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| 6603 |
Centers for Disease Control and Prevention |
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Prevalence and risk of homelessness among US veterans. |
Understanding the prevalence of and risk for homelessness among veterans is prerequisite to preventing and ending homelessness among this population. Homeless veterans are at higher risk for chronic disease; understanding the dynamics of homelessness among veterans can contribute to our understanding of their health needs. |
| additional homeless people | 0.411016 |
| data | 0.516153 |
| homeless assessment report | 0.440857 |
| homeless people | 0.434811 |
| homeless status | 0.416076 |
| Veterans Affairs records | 0.426861 |
| black male veterans | 0.411157 |
| homeless services | 0.417295 |
| HMIS data | 0.503831 |
| Homelessness Among Veterans | 0.473099 |
| homeless veterans | 0.563221 |
| risk ratios | 0.51341 |
| homeless populations | 0.438997 |
| poverty populations | 0.409185 |
| poverty | 0.541436 |
| service-using homeless population | 0.444353 |
| End Homelessness | 0.412655 |
| black female veterans | 0.410051 |
| male veterans | 0.477297 |
| highest risk | 0.415325 |
| CoC | 0.408096 |
| black race | 0.424472 |
| Homelessness status | 0.445474 |
| homelessness services | 0.555039 |
| federal poverty threshold | 0.492806 |
|
| women | 0.42905 |
| veterans | 0.803558 |
| study | 0.407969 |
| Urban Development | 0.415526 |
| United States | 0.45043 |
| age group | 0.486551 |
| National Center | 0.406514 |
| 54-year-old age group | 0.485448 |
| general population | 0.531321 |
| Annual Homelessness Assessment | 0.436098 |
| poverty population | 0.505363 |
| female veterans | 0.43495 |
| American Community Survey | 0.543893 |
| New York | 0.492006 |
| homelessness series | 0.412789 |
| veteran status | 0.957401 |
| Homeless Management Information | 0.51699 |
| ACS | 0.443507 |
| annual homeless assessment | 0.440861 |
| Veterans Affairs | 0.498674 |
| homeless population | 0.713158 |
| veteran homelessness | 0.4435 |
| risk | 0.54657 |
| ACS data | 0.421639 |
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| 7992 |
Centers for Disease Control and Prevention |
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Preventing Chronic Disease - CDC: Volume 10, 2013: 12_0088 |
Volumen 10 — el 10 de enero de 2013. |
| Enfoques Alimentarios | 0.956592 |
| Dietary Approaches | 0.61862 |
| Leng I | 0.622559 |
| mm hg | 0.591024 |
| Foy CG | 0.63017 |
| Hunter JC | 0.590463 |
| largo plazo | 0.52644 |
|
| Quandt SA | 0.629556 |
| Vitolins MZ | 0.625988 |
| Whitt-Glover MC | 0.593949 |
| pequeña muestra | 0.518417 |
| estudio piloto | 0.812556 |
| bajos recursos | 0.813051 |
| Stop Hypertension | 0.625834 |
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| 9132 |
Centers for Disease Control and Prevention |
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Asthma - State Data Profiles |
National Asthma Control Program State Profiles |
| CDC National Asthma | 0.704331 |
| Technical Notes | 0.244398 |
| Puerto Rico | 0.274055 |
| State Contacts | 0.253009 |
| visit https://www.cdc.gov/asthma/nacp.htm | 0.266751 |
| asthma patient education | 0.651413 |
| state partners | 0.253563 |
| Select state profiles | 0.380136 |
|
| previous funding cycle | 0.433435 |
| current information | 0.2607 |
| U.S. Statistical data | 0.383744 |
| Asthma Control Program | 0.924017 |
| Asthma State Profiles | 0.857316 |
| Program grantee states | 0.419611 |
| National Asthma Control | 0.924709 |
| asthma prevalence | 0.550177 |
|
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| 11519 |
Centers for Disease Control and Prevention |
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NCIRD | DBD Bulletin Fall 2011 | Meetings and Epi-AIDs | CDC |
Division of Bacterial Diseases Bulletin Fall |
| pneumococcal conjugate vaccines | 0.505724 |
| infant pertussis | 0.345698 |
| Respiratory Infections | 0.343875 |
| vaccine schedules | 0.363197 |
| Smart Program | 0.301048 |
| Laboratory diagnostics | 0.302447 |
| Invasive group | 0.317077 |
| Respiratory Surveillance sites | 0.406749 |
| Severe Pertussis | 0.365133 |
| streptococcal disease | 0.366108 |
| Infectious Diseases Society | 0.36329 |
| pneumococcal conjugate vaccine | 0.507283 |
| Southern Africa meeting | 0.38999 |
| historical reasons | 0.303972 |
| 49th Annual Meeting | 0.377416 |
| Asian countries | 0.306518 |
| Chris Van Beneden | 0.980895 |
| meningococcal disease | 0.346227 |
| acute care hospital | 0.353494 |
| invasive pneumococcal infections | 0.460966 |
| streptococcal infections | 0.33724 |
| South Africa | 0.366314 |
| Infectious Disease Societies | 0.410856 |
| Vaccines Surveillance Meeting | 0.406154 |
| Faso meningitis surveillance | 0.384173 |
|
| United States | 0.399195 |
| invasive disease | 0.356681 |
| invasive pneumococcal disease | 0.440958 |
| International Emerging Infections | 0.403921 |
| U.S. overview | 0.367621 |
| Legionellosis outbreak | 0.30905 |
| disease outbreak | 0.401314 |
| Hib disease | 0.362802 |
| Tom Clark | 0.380256 |
| streptococcal strain | 0.324113 |
| DBD/RDB | 0.351229 |
| Meningococcal conjugate vaccine | 0.498257 |
| Antimicrobial Agents | 0.299476 |
| National Pertussis Workshop | 0.452298 |
| Bob Pinner | 0.3033 |
| conjugate vaccine | 0.529271 |
| term care facility | 0.363725 |
| XVIII Lancefield International | 0.394725 |
| International Symposium | 0.395393 |
| California pertussis vaccine | 0.484464 |
| Vaccine efficacy | 0.36319 |
| Fabiana Pimenta | 0.429026 |
| Hubei Province | 0.306002 |
| universal vaccine introduction | 0.465866 |
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Centers for Disease Control and Prevention |
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Autism Spectrum Disorder (ASD) - Screening and Diagnosis |
Autism Spectrum Disorders (ASDs) are a group of developmental disabilities that can cause significant social, communication and behavioral challenges. CDC is working to find out how many children have ASDs, discover the risk factors, and raise awareness of the signs. |
| final diagnosis | 0.263272 |
| developmental screening test | 0.592039 |
| developmental screening | 0.748382 |
| family member | 0.236567 |
| developmental problems | 0.558539 |
| experienced professional | 0.271883 |
| ASD | 0.904698 |
| basic skills | 0.265396 |
| children | 0.368225 |
| Additional screening | 0.528238 |
| well-child doctor visits | 0.869253 |
| autism spectrum disorder | 0.518818 |
| neurological testing | 0.218582 |
| thorough review | 0.233317 |
| higher risk | 0.227138 |
|
| developmental delays | 0.594324 |
| regular well-child doctor | 0.863691 |
| comprehensive diagnostic evaluation | 0.404084 |
| blood test | 0.281057 |
| short test | 0.255964 |
| diagnostic tools | 0.23036 |
| primary care doctor | 0.414939 |
| medical test | 0.27071 |
| comprehensive evaluation | 0.219362 |
| vision screening | 0.295228 |
| genetic testing | 0.222203 |
| high risk | 0.472205 |
| medical testing | 0.213329 |
| low birth weight | 0.848976 |
|
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Centers for Disease Control and Prevention |
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Employment and Activity Limitations Among Adults with Chronic Obstructive Pulmonary Disease - United States, 2013 |
Anne G. Wheaton, PhD1, Timothy J. Cunningham, PhD1, Earl S. |
| COPD patients | 0.761916 |
| Opinion Research Response | 0.47204 |
| limitation measures | 0.521085 |
| health care provider | 0.478594 |
| Janet B. Croft | 0.474034 |
| various activity limitations | 0.52461 |
| current smokers | 0.58667 |
| smoking status | 0.501995 |
| state health departments | 0.482105 |
| health care providers | 0.526524 |
| current smoking | 0.507534 |
| progressive respiratory conditions | 0.476515 |
| response rate | 0.490345 |
| activity limitation characteristics | 0.511354 |
| noninstitutionalized civilian adults | 0.486069 |
| special equipment | 0.559794 |
| health problems | 0.526243 |
| physician-diagnosed COPD | 0.725489 |
| smoking cessation | 0.487584 |
| pulmonary rehabilitation program | 0.476408 |
| chronic bronchitis | 0.476256 |
| Earl S. Ford | 0.472972 |
| Behavioral Risk Factor | 0.471639 |
| physical activity status | 0.536079 |
| obstructive pulmonary disease | 0.482224 |
|
| United States | 0.611391 |
| adults | 0.56228 |
| Timothy J. Cunningham | 0.473581 |
| respiratory symptoms | 0.468311 |
| Anne G. Wheaton | 0.534585 |
| activity limitations | 0.829415 |
| Data Quality Report | 0.476081 |
| greater educational level | 0.468047 |
| random-digit–dialed telephone survey | 0.470969 |
| activity limitation | 0.573155 |
| COPD prevalence | 0.74081 |
| important contributor | 0.477083 |
| U.S. adults | 0.54653 |
| age-adjusted prevalence | 0.503906 |
| response rates | 0.472357 |
| health | 0.531899 |
| physical activity | 0.666019 |
| median survey response | 0.474341 |
| current smoking status | 0.488865 |
| COPD diagnosis | 0.639241 |
| public health efforts | 0.469257 |
| American Indian/Alaska Native | 0.467485 |
| pulmonary rehabilitation | 0.565368 |
| COPD status | 0.674639 |
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Community Knowledge, Attitudes, and Practices RegardingEbola Virus Disease - Five Counties, Liberia, September-October,2014 |
Miwako Kobayashi, MD1,2; Karlyn D. Beer, PhD1,3; Adam Bjork, PhD4; Kevin Chatham-Stephens, MD1,5; Cara C. Cherry, DVM1,6; Sampson Arzoaquoi, MD7; Wilmot Frank, MD8; Odell Kumeh, MD9; Joseph Sieka, MD10; Adolphus Yeiah, MD11; Julia E. |
| Ebola treatment unit | 0.658494 |
| Ebola treatment | 0.706453 |
| Ebola virus transmission | 0.553738 |
| Ebola symptoms | 0.661072 |
| Ebola survivors | 0.551669 |
| Ebola virus | 0.620556 |
| 8Sinoe County Health | 0.369505 |
| Ebola outbreak | 0.560479 |
| Gee County Health | 0.375275 |
| Ebola transmission-free status | 0.609827 |
| Ebola transmission | 0.746043 |
| Survey respondents | 0.401054 |
| survey areas | 0.386127 |
| local health messages | 0.370112 |
| field team | 0.42193 |
| Ebola knowledge questions | 0.570784 |
| current Ebola awareness | 0.545 |
| timely health messages | 0.375152 |
| initial Ebola messaging | 0.541127 |
| low cumulative incidence | 0.369664 |
| Ebola patients | 0.740025 |
| CDC Liberia Ebola | 0.591676 |
| counties | 0.441827 |
| county health office | 0.521325 |
|
| Ebola | 0.92633 |
| lower Ebola incidence | 0.593591 |
| 9Maryland County Health | 0.369487 |
| Ebola virus disease | 0.608813 |
| Ebola epidemic | 0.529736 |
| Ebola attitudes | 0.546714 |
| low-incidence counties | 0.394323 |
| median correct responses | 0.410108 |
| Sierra Leone | 0.379323 |
| Ebola cases | 0.770321 |
| Ebola health messages | 0.566221 |
| cultural practices | 0.388164 |
| Ebola incident cases | 0.588033 |
| high cumulative incidence | 0.372609 |
| health office staff | 0.369548 |
| Ebola awareness | 0.564109 |
| new Ebola cases | 0.6407 |
| Ebola knowledge | 0.584101 |
| River Gee | 0.43596 |
| Ebola practices | 0.551868 |
| 7Bong County Health | 0.369523 |
| Ebola KAP survey | 0.615832 |
| Ebola incidence | 0.62953 |
| Ebola treatment units | 0.678185 |
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| 14317 |
Centers for Disease Control and Prevention |
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How Potassium Iodide (KI) Works| Infographic |
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| 16156 |
Centers for Disease Control and Prevention |
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Todos pueden ayudar a detener el hostigamiento de los niños que tienen el síndrome de Gilles de la Tourette - Especiales CDC - CDC en Español |
Del 15 de mayo al 15 de junio es el Mes de Concientización sobre el Síndrome de Tourette. El tema de este año es un desafío para aumentar la concientización y la aceptación del síndrome de Gilles de la Tourette (#DesafíoST). Conozca la información sobre los tics y el síndrome de Gilles de la Tourette (también llamado síndrome de Tourette o TS, por sus siglas en inglés) y sepa cómo puede aumentar la aceptación al ayudar a detener el hostigamiento de los niños con este síndrome. |
| Archivo Apple Quicktime | 0.831324 |
| malas palabras | 0.773977 |
| Archivo Zip Comprimido | 0.827813 |
| Archivo Microsoft PowerPoint | 0.844402 |
| Archivo Adobe PDF | 0.828397 |
| Archivo Microsoft Excel | 0.823898 |
|
| pequeña cantidad | 0.771885 |
| boy scouts | 0.742085 |
| Archivo Microsoft | 0.982742 |
| Embajadores Juveniles | 0.752186 |
| Archivo Microsoft Word | 0.842044 |
|
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