| 6844 |
Centers for Disease Control and Prevention |
Html |
en |
CDC - Preventing Chronic Disease: Volume 9, 2012: 11_0166 |
The purpose of this study was to use the Community Readiness Model to assess readiness for adopting a physical activity program for people with arthritis in 8 counties in West Virginia. |
| C. Physical activity | 0.474171 |
| Nonoccupational physical activity | 0.474992 |
| leisure-time activity | 0.458071 |
| key informants | 0.681577 |
| Arthritis information | 0.458849 |
| technique whereby informants | 0.488863 |
| readiness score | 0.516561 |
| median rating | 0.459238 |
| Disease Control | 0.471843 |
| physical activity programs | 0.558223 |
| arthritis exercise programs | 0.492114 |
| community efforts | 0.467612 |
| readiness assessment | 0.484407 |
| community | 0.578842 |
| 14-member community advisory | 0.459727 |
| time physical activity | 0.471632 |
| physical activity interventions | 0.472808 |
| community advisory board | 0.479445 |
| arthritis | 0.583765 |
| Fam Community Health | 0.464822 |
| community ownership | 0.459666 |
| West Virginia University | 0.514367 |
| community members | 0.519867 |
| potential informants | 0.490468 |
| informants mentioned groups | 0.498487 |
|
| West Virginia Bureau | 0.490057 |
| community leaders | 0.474382 |
| Epidemiol Community Health | 0.48002 |
| physical activity program | 0.49524 |
| PRC-HAN Physical Activity | 0.473248 |
| West Virginia | 0.766861 |
| physical activity benefits | 0.480379 |
| Physical Activity Guidelines | 0.474301 |
| senior centers | 0.487753 |
| public health | 0.56946 |
| physical activity programming | 0.510373 |
| health care | 0.477531 |
| physical activity campaign | 0.48037 |
| community readiness model | 0.565186 |
| L. Community readiness | 0.491369 |
| Arthritis Foundation | 0.47286 |
| aerobic leisure activity | 0.462446 |
| people | 0.493234 |
| physical activity | 0.964272 |
| leisure-time physical activity | 0.479081 |
| older adults | 0.567853 |
| public health priority | 0.47536 |
| readiness scores | 0.462051 |
| physical activity levels | 0.543308 |
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| 7795 |
Centers for Disease Control and Prevention |
Html |
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Genomics and Disease - Health Communication |
Genomics and Disease - Gateway to Health Communication - CDC |
| cardiovascular disease | 0.205066 |
| risk factors | 0.328087 |
| disease | 0.73421 |
| chemical exposures | 0.201161 |
| genes | 0.320116 |
| high blood pressure—both | 0.271029 |
| 38-year-old insurance salesmen | 0.270609 |
| disease progression | 0.236678 |
| various genes | 0.203562 |
| genetic factors | 0.254126 |
| modifiable environmental factors | 0.40988 |
| different genetic variations | 0.311691 |
|
| lifestyle factors | 0.21814 |
| African American couple | 0.2633 |
| family history | 0.763644 |
| heart disease | 0.489916 |
| key genetic component | 0.314992 |
| risk | 0.371383 |
| African American newborns | 0.264377 |
| single genes | 0.235352 |
| rare-single gene disorders | 0.280874 |
| behavioral factors | 0.351631 |
| sickle cell anemia | 0.905361 |
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| 10507 |
Centers for Disease Control and Prevention |
Html |
en |
Conference Call June 13, 2013'Clinicians Outreach and Communication Activity (COCA) |
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| MPEG | 0.378858 |
| search | 0.263099 |
| PDF | 0.261307 |
| PPT | 0.446092 |
|
| DOC | 0.368812 |
| information | 0.262482 |
| different file formats | 0.938484 |
| page | 0.276773 |
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| 10975 |
Centers for Disease Control and Prevention |
Html |
en |
Pandemic Flu Storybook: Clifton and Nellie Taliaferro |
I Survived, The staggering statistics associated with pandemics sometimes makes it difficult to remember that each number represents a single, human life. In this section, survivors share their intimate recollections of either their own illness or that of a loved one. All these storytellers are 90-plus years of age and they have carried with them for a lifetime their memories of the 1918 flu pandemic. |
| necessities | 0.463779 |
| streets | 0.530685 |
| bodies | 0.447416 |
| Nellie Taliaferro | 0.740875 |
| father | 0.443337 |
| Linda Palmer | 0.675595 |
| navigation Skip | 0.824664 |
| Washington | 0.489952 |
| gatherings | 0.451846 |
| children | 0.481744 |
| Storyteller | 0.460375 |
| supplier | 0.441114 |
| runner | 0.450515 |
| list Skip | 0.822619 |
|
| stories | 0.483809 |
| railroad | 0.441658 |
| influenza pandemic | 0.67284 |
| page options Skip | 0.935315 |
| Clifton | 0.524914 |
| D.C. | 0.443473 |
| paternal grandparents | 0.686436 |
| undertaker | 0.471417 |
| deliveries | 0.456385 |
| boarding house | 0.619559 |
| funeral | 0.441148 |
| household | 0.446678 |
| ones | 0.444306 |
| Location | 0.445758 |
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| 11641 |
Centers for Disease Control and Prevention |
Html |
en |
Vaccination with Tetanus, Diphtheria, and AcellularPertussis Vaccine of Pregnant Women Enrolled in Medicaid -Michigan, 2011-2013 |
Michelle Housey, MPH1,2, Fan Zhang, PhD3, Corinne Miller, DDS, PhD1, Sarah Lyon-Callo, MA, MS1, Jevon McFadden, MD1,4, Erika Garcia, MS1, Rachel Potter, DVM1 (Author affiliations at end of text). |
| Medicaid administrative claims | 0.664605 |
| pregnancy status | 0.379923 |
| maternal age | 0.745893 |
| prenatal vaccination | 0.402921 |
| information system data | 0.368757 |
| significant difference | 0.421024 |
| vaccination coverage | 0.561289 |
| pregnant women | 0.713089 |
| Hispanic women | 0.460066 |
| maternal race/ethnicity | 0.437054 |
| Tdap | 0.816842 |
| gestational age | 0.525344 |
| privately insured population | 0.369776 |
| pregnancy | 0.61323 |
| Kotelchuck index | 0.364157 |
| publicly insured population | 0.369716 |
| prenatal care | 0.537671 |
| white women | 0.661047 |
| complete vaccination histories | 0.479846 |
| particularly vulnerable population | 0.383485 |
| optimal vaccination time | 0.511701 |
| women | 0.944241 |
| vaccination | 0.851344 |
| maternal vaccination | 0.50267 |
|
| median maternal age | 0.451358 |
| Michelle Housey | 0.363775 |
| administrative claims data | 0.490571 |
| privately insured women | 0.413232 |
| Native American women | 0.637955 |
| vaccination administration | 0.412919 |
| publicly insured Medicaid | 0.392304 |
| Tdap vaccination history | 0.512872 |
| privately insured infants.* | 0.383527 |
| entire study population | 0.374812 |
| ACIP recommendation | 0.396126 |
| maternal Medicaid | 0.454773 |
| publicly insured women | 0.424124 |
| Tdap dose | 0.397948 |
| maternal antibodies | 0.377978 |
| study population | 0.545449 |
| maternal race | 0.510735 |
| Tdap coverage | 0.422354 |
| influenza vaccination | 0.392108 |
| publicly funded insurance | 0.364057 |
| ACIP recommendations | 0.38861 |
| significant predictors | 0.448816 |
| statewide immunization information | 0.676392 |
| Tdap vaccination | 0.682051 |
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| 11763 |
Centers for Disease Control and Prevention |
Html |
en |
Ebola Virus Disease Distribution Map |
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| Ebola Virus Infection | 0.625676 |
| Congo Isiro Health | 0.469232 |
| Interim U.S. Guidance | 0.467438 |
| Ebola Questions | 0.590973 |
| Sudan ebolavirus | 0.518481 |
| Africa Ebola Outbreak | 0.637276 |
| Confirmed Ebola Patients | 0.614855 |
| Dem. Rep. | 0.52073 |
| Previous Outbreak Updates | 0.469614 |
| Potential Ebola Virus | 0.642632 |
| Sierra Leone Vaccine | 0.474705 |
| Public Health Resources | 0.527269 |
| Ebola Treatment Centers | 0.647948 |
| Ebola Patients | 0.637229 |
| Specific Groups | 0.469088 |
| South Sudan Nzara | 0.493426 |
| Ebola Epidemic | 0.584674 |
| Ebola Assessment Hospitals | 0.594358 |
| Virus Exposure Influenza | 0.47095 |
| Ebola Diagnosed | 0.584643 |
| Ebola PPE | 0.59457 |
| U.S. Healthcare Workers | 0.531248 |
| Distribution Map | 0.503841 |
| Uganda Luwero District | 0.475026 |
|
| Current Ebola Treatment | 0.598181 |
| Sierra Leone | 0.483647 |
| Search Form Controls | 0.50003 |
| Patient Handoff SOP | 0.479049 |
| Zaire ebolavirus | 0.663442 |
| Confirmed Ebola Virus | 0.624536 |
| West Africa Outbreak | 0.482021 |
| Ebola Hemorrhagic Fever | 0.62219 |
| Ebola Virus Disease | 0.942533 |
| Suspected Ebola Patients | 0.597567 |
| Personal Protective Equipment | 0.481114 |
| Disease Distribution Map | 0.498679 |
| Ebola Survivors Questions | 0.605074 |
| Virus Disease Distribution | 0.522404 |
| Pediatric Healthcare Professionals | 0.527123 |
| Healthcare Settings Guidance | 0.478028 |
| Outbreak Distribution Map | 0.47377 |
| Handling Untreated Sewage | 0.477827 |
| Ebola Transmission | 0.572305 |
| Ebola Virus Exposure | 0.641235 |
| Ebola Response Planning | 0.602682 |
| Ebola Virus | 0.963059 |
| West Africa | 0.490692 |
| Congo Outbreak | 0.473969 |
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| 12583 |
Centers for Disease Control and Prevention |
Video |
en |
Rose: Three Keys to Recovery | Tips From Former Smokers |
Rose had lung cancer from smoking cigarettes, and she needed very difficult medical treatments. This video explains three keys that helped her get through treatments: family support, faith, and quitting smoking.
Comments on this video are allowed in accordance with our comment policy: http://www.cdc.gov/SocialMedia/Tools/CommentPolicy.html
This video can also be viewed at http://streaming.cdc.gov/vod.php?id=68424ecf2f978c46d57a4fe0c4cd41d120140925164127140 |
| Smokers | 0.915255 |
| CDC | 0.901732 |
| Keys | 0.794495 |
|
| Recovery | 0.431111 |
| YouTube | 0.85455 |
|
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| 14335 |
Centers for Disease Control and Prevention |
Html |
en |
Surveillance Systems to Track Progress Toward PolioEradication - Worldwide, 2014-2015 | MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| paralysis onset | 0.451213 |
| poliovirus transmission | 0.343871 |
| environmental surveillance | 0.418098 |
| stool specimens | 0.365497 |
| environmental surveillance findings | 0.300754 |
| AFP cases | 0.767268 |
| true AFP cases | 0.393856 |
| AFP surveillance indicators | 0.536175 |
| adequate stool specimen | 0.321603 |
| stool specimen collection | 0.321501 |
| AFP case samples | 0.389889 |
| poliovirus surveillance data | 0.329347 |
| surveillance activities | 0.309072 |
| WPV1 cases | 0.305474 |
| World Health Organization | 0.420007 |
| national AFP surveillance | 0.464788 |
| surveillance quality indicators | 0.317226 |
| surveillance quality indicators.* | 0.315429 |
| nonpolio AFP | 0.457217 |
| AFP surveillance quality | 0.537428 |
| african region | 0.483794 |
| adequate stool specimens | 0.328029 |
| AFP surveillance | 0.832068 |
| Ebola virus disease | 0.438902 |
|
| timely polio-free certification | 0.310223 |
| polio eradication | 0.339431 |
| cVDPV cases | 0.386772 |
| Polio Laboratory Network | 0.386623 |
| wild poliovirus | 0.30038 |
| Mediterranean Region countries | 0.485209 |
| Eastern Mediterranean Region | 0.930608 |
| nonpolio AFP cases | 0.38947 |
| high nonpolio AFP | 0.351568 |
| sensitive AFP surveillance | 0.396841 |
| stool specimen | 0.359158 |
| stool specimen adequacy | 0.32747 |
| African continent | 0.295563 |
| African Region countries | 0.448172 |
| national-level surveillance indicators | 0.324939 |
| nucleotide sequence difference | 0.30261 |
| acute flaccid paralysis | 0.313984 |
| surveillance performance | 0.331819 |
| nonpolio AFP rate | 0.418628 |
| Environmental surveillance collection | 0.313444 |
| intratypic differentiation results | 0.348497 |
| surveillance gaps | 0.318998 |
| nonpolio AFP rates | 0.405055 |
| Global Polio Laboratory | 0.383757 |
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| 15365 |
Centers for Disease Control and Prevention |
Html |
en |
The Cleveland-Cuyahoga County Food Policy Coalition:"We Have Evolved" |
Preventing Chronic Disease (PCD) is a peer-reviewed electronic journal established by the National Center for Chronic Disease Prevention and Health Promotion. PCD provides an open exchange of information and knowledge among researchers, practitioners, policy makers, and others who strive to improve the health of the public through chronic disease prevention. |
| Cleveland City Planning | 0.557979 |
| community food systems | 0.554412 |
| food policy initiatives | 0.604553 |
| urban food policy | 0.613168 |
| Urban Garden District | 0.85712 |
| key informants | 0.636607 |
| Food Policy Coalition | 0.663648 |
| city planning official | 0.563657 |
| nutritious food | 0.630883 |
| garden preservation strategy | 0.568686 |
| Garden Zoning policy | 0.57132 |
| Cleveland City Council | 0.561176 |
| community | 0.57404 |
| case study | 0.657585 |
| policy gains | 0.553509 |
| city’s food | 0.551754 |
| nutritious food access | 0.583666 |
| District Zoning policy | 0.572938 |
| Food access inequities | 0.546163 |
| local food policies | 0.558742 |
| city | 0.594154 |
| policies | 0.586556 |
| State University Extension | 0.574469 |
| Cleveland | 0.692597 |
| Prevention Research Center | 0.607316 |
|
| CCCFPC | 0.696373 |
| zoning policy | 0.577411 |
| urban agriculture ordinances | 0.556964 |
| food policy innovations | 0.577291 |
| food policy councils | 0.868499 |
| Garden District Zoning | 0.856913 |
| participants | 0.630897 |
| urban agriculture | 0.97207 |
| food environment | 0.637061 |
| District Zoning legislation | 0.603799 |
| urban agriculture legislation | 0.557907 |
| local policy makers | 0.554496 |
| Ohio State University | 0.574013 |
| health | 0.546417 |
| urban agriculture initiatives | 0.667624 |
| food access | 0.623544 |
| case study methods | 0.600977 |
| food policy change | 0.582987 |
| Western Reserve University | 0.634791 |
| policy development process | 0.590554 |
| policy makers | 0.729969 |
| Cleveland–Cuyahoga County Food | 0.618159 |
| County Food Policy | 0.66936 |
| food policy | 0.932594 |
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| 15872 |
Centers for Disease Control and Prevention |
Html |
null |
CDC Wins Hermes Gold Award for Mobile Game Targeting Health Disparate Populations |
CDC Wins Hermes Gold Award for Mobile Game Targeting Health Disparate Populations - CDC
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