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Media ID	Source Name	Media Type	Language	Media Name	Media Description	Keywords	Keywords	Link to Article
917	Centers for Disease Control and Prevention	Html	en	Declines in Student Obesity Prevalence Associated with aPrevention Initiative - King County, Washington, 2012	Eli Kern, MPH1, Nadine L. Chan, PhD1, David W. Fleming, MD1, James W.	reduced price lunch 0.378563 obesity rates 0.4329 youth obesity 0.68081 CPPW schools 0.352296 biennially administered Washington 0.358484 baseline obesity prevalence 0.466802 significant difference 0.347863 low-income school districts 0.435779 school districts obesity 0.440892 non-CPPW students 0.360987 Youth Risk Behavior 0.353432 obesity prevention 0.514594 obesity prevalence 0.896697 school districts 0.557129 school-based CPPW interventions 0.362298 CPPW students 0.356014 documents recent trends 0.350965 robust obesity prevention 0.459832 healthy eating 0.358698 Washington State Department 0.396554 obesity prevention initiatives 0.473804 youth obesity prevalence 0.619835 King County students 0.399036 baseline prevalence 0.357293 non-CPPW school districts 0.439057	Washington State 0.430846 population-wide obesity trends 0.422697 statistically significant decrease 0.471288 school-based policy 0.347335 baseТЌline obesity prevalence 0.448926 County youth obesity 0.468922 logistic regression analysis 0.383515 obesity trends 0.480287 State Healthy Youth 0.386542 obesity prevention initiative 0.446918 obesity prevention strategy 0.419945 non-CPPW districts 0.370309 statistically significant decline 0.396403 rest 0.364193 Washington State Healthy 0.387993 CPPW school district 0.362667 CPPW initiative 0.351325 CPPW districts 0.350979 Healthy Youth Survey 0.387275 school cafeteria staff 0.348285 self-reported youth obesity 0.47037 CPPW school districts 0.4618 Survey response rates 0.347498 King County 0.969447	CLICK HERE
6488	Centers for Disease Control and Prevention	Html	en	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	CLICK HERE
6603	Centers for Disease Control and Prevention	Html	en	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	CLICK HERE
8269	Centers for Disease Control and Prevention	Html	en	Notes from the Field: Outbreak of Infections Caused byShigella sonnei with Decreased Susceptibility to Azithromycin - LosAngeles, California, 2012	Persons using assistive technology might not be able to fully access information in this file. For assistance, please send e-mail to: mmwrq@cdc.gov.	underwent pulsed-field gel 0.668515 mmwrq@cdc.gov. 0.607105 multidrug-resistant Shigella 0.684218 Los Angeles County 0.703164 stool specimens 0.611373 Human Services 0.662652 outbreak PFGE pattern 0.706336 club members 0.615789 public health authorities 0.675853 U.S. Department 0.659746 MMWR HTML versions 0.655572 Anna Bowen 0.652322 electronic PDF version 0.656267 parenteral antimicrobial medications 0.661802 Zoonotic Infectious Diseases 0.65896 Environmental Health 0.621897 general U.S. population 0.662857 Acute Communicable Disease 0.844173 National Antimicrobial Resistance 0.674792 original paper copy 0.649779 Infectious Diseases 0.661777 azithromycin susceptibility testing 0.772793 Shigella strains 0.689895 Thirty-nine cases 0.606971	additional isolates 0.661807 United States 0.778239 original MMWR paper 0.662175 U.S. Government Printing 0.660107 Elk Grove Village 0.648263 Disease Control Unit 0.842674 azithromycin treatment failure 0.754301 Shigella species 0.683065 elevated azithromycin minimum 0.763924 Shigella infections 0.692875 plasmid-encoded macrolide resistance 0.673593 bridge club 0.924571 indistinguishable patterns 0.609792 public health 0.773783 Shigella sonnei 0.779029 Antimicrob Agents Chemother 0.655335 stool specimen 0.612132 shigellosis patients 0.622795 azithromycin MICs 0.707932 Communicable Disease Control 0.849374 Maria Sjolund Karlsson 0.661666 private bridge club 0.717821 health facility 0.612799 Los Angeles 0.848294	CLICK HERE
9921	Centers for Disease Control and Prevention	Html	en	NIOSH Program Portfolio : Total Worker Health : r2p	The TWH™ Program includes an intramural component and an extramural component, comprised of four Centers of Excellence to Promote a Healthier Workforce. Both of these components conduct research on the integration of health protection and health promotion; communication of current knowledge, successful approaches, and challenges, and advocacy of the concepts and practices of total worker health to our partners and stakeholders.	extensive investigator experience 0.59469 worker involvement 0.542147 Harvard School 0.58958 New England Research 0.676699 mental health 0.59469 Healthier Workforce Center 0.841518 Total Worker Health® 0.656368 Cancer Institute Center 0.654868 research findings 0.949281 Public health Center 0.746606 NIOSH Center 0.648127 Partners Health Care 0.684012 occupational ergonomic interventions 0.662833 reduced job stress 0.589312 safer work practices 0.602151 occupational health 0.757129 worker health promotion 0.753729 new research 0.578007 Boston University School 0.631957 cardiovascular health 0.590589 workplace solutions 0.590514 New England Workplace 0.852729 effective prevention practices 0.654635 national WorkLife Centers 0.630171	musculoskeletal health 0.593116 healthy workforce center 0.792305 oregon healthy workforce 0.767044 personal health risk 0.702271 employee health programs 0.671156 Iowa Healthier Workforce 0.816246 collaborative research-to-practice initiative 0.601634 NIOSH-funded research findings 0.740257 technology-based interventions 0.53854 NIOSH initiative 0.631401 Science University 0.533523 psychosocial stress hazard 0.608432 Community-Based Research 0.565483 worker protection 0.554593 Education Research Center 0.705056 Portland State University 0.62411 improved lifestyle choices 0.586369 physical health 0.583296 health promotion interventions 0.897406 research goal 0.575456 effective products 0.531178 Occupational Health Psychology 0.700652 effective NIOSH 0.642944	CLICK HERE
12606	Centers for Disease Control and Prevention	Video	en	Video: CDC Responds to Meningitis in Burkina Faso	Epidemics of bacterial meningitis in Africa can affect hundreds of thousands of people and kill many thousands. CDC's Dr. Rana Hajjeh describes how CDC has contributed to development of an inexpensive vaccine and is now working with partners to ensure it is used where needed most and evaluated for effectiveness. 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://www.cdc.gov/globalhealth/video/meningitis/meningitis.htm	Burkina Faso 0.948699 CDC Responds 0.871575	Meningitis 0.638184	CLICK HERE
13704	Centers for Disease Control and Prevention	Html	en	Ebola Virus Disease in Health Care Workers - Guinea,2014	Please note: An erratum has been published for this article. To view the erratum, please click here.	total Ebola cases 0.422642 Ebola treatment unit 0.415797 Ebola infections 0.693026 symptom onset 0.236618 comprehensive infection prevention 0.208509 Ebola case notifications 0.406789 Ebola infection 0.770393 HCW patients 0.202245 Ebola cases 0.689166 Ebola outbreak 0.36162 continuous infection prevention 0.205754 probable Ebola infections 0.43542 non-HCW Ebola patients 0.404168 intense Ebola transmission 0.384213 Ebola case investigation 0.38076 HCWs 0.464165 Guinea Ebola Response 0.41884 HCW infections 0.222586	health care 0.309707 Ebola surveillance purposes 0.368426 inadequate infection control 0.229718 health care workforce 0.226901 surveillance data 0.20096 probable Ebola cases 0.593477 specific HCW groups 0.217596 Ebola exposures 0.478743 infection prevention 0.313776 HCW denominators 0.208871 HCW case counts 0.230693 potential Ebola exposures 0.439391 HCW risks factors 0.214373 HCW cases 0.252316 infection control training 0.20711 Ebola patients 0.439562 Guinea MOH 0.24833 Ebola 0.927307	CLICK HERE
13917	Centers for Disease Control and Prevention	Html	en	Healthy Living | Thalassemia | Blood Disorders | NCBDDD | CDC	null	Haemophilus influenzae type 0.57495 possible organ damage 0.560414 special vaccination schedule 0.561442 chelation therapy 0.614983 Pneumococcal vaccines 0.507423 healthy choices 0.604736 nutritious meals 0.493895 healthy lifestyle 0.765185 family members 0.477363 iron overload 0.496356 thalassemia 0.911029 blood transfusions 0.596992 certain infections 0.486121 essential nutrients 0.483015 treatable disorder 0.499741 special instructions 0.485284 Pay special attention 0.551836 severe anemia 0.489727 daily life 0.47687 nutritious foods 0.489698 sexually transmitted diseases 0.547011 medical specialist 0.490447 positive relationships 0.489037 Romantic relationships 0.479057 thalassemia trait 0.732012	healthy decisions 0.5042 high risk 0.485999 vigorous forms 0.483894 romantic relationship 0.478759 great way 0.490715 orange juice 0.482235 better health outcomes 0.54986 following vaccines 0.50174 supportive relationships 0.479749 up-to-date vaccination schedules 0.557311 extra iron 0.485417 overall healthy lifestyle 0.577679 genetic counseling 0.480589 regular basis 0.488804 moderate physical activities 0.547858 chelation schedule 0.503995 flu vaccination.  People 0.566572 transfusion center 0.484935 important thing 0.493515 medical care 0.490625 Meningococcal vaccines 0.513222 water aerobics 0.481884 gentle reminders 0.477559 low-impact activities 0.482681	CLICK HERE
14317	Centers for Disease Control and Prevention	Image	null	How Potassium Iodide (KI) Works| Infographic	null			CLICK HERE
15628	Centers for Disease Control and Prevention	Html	en	US States' Childhood Obesity Surveillance Practices andRecommendations for Improving Them, 2014-2015	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.	BMI surveillance programs 0.44805 school-based BMI measurement 0.46716 BMI surveillance program 0.456058 conduct BMI surveillance 0.448621 childhood obesity epidemic 0.431021 Pediatric Nutrition Surveillance 0.32893 childhood obesity interventions 0.324886 BMI surveillance laws 0.457452 high BMI 0.34092 public health surveillance 0.400308 school-based BMI surveillance 0.468195 obesity surveillance practices 0.364933 state surveillance 0.365614 BMI data collection 0.391418 body mass index 0.396834 state BMI measurement 0.39291 statewide school-based BMI 0.377459 population-level BMI 0.338517 child health surveillance 0.359794 BMI records 0.341877 BMI surveillance systems 0.532169 child BMI measurement 0.376167 childhood obesity surveillance 0.429269 controversial school-based BMI 0.389315 representative child BMI 0.372487	state surveillance legislation 0.349082 school-based BMI 0.49457 child bmi surveillance 0.922319 state-level child BMI 0.434585 states 0.438826 exemplary surveillance programs 0.322696 BMI screening programs 0.403881 BMI surveillance practices 0.512871 EHR-based child BMI 0.41922 child BMI data 0.613188 public health 0.530264 surveillance purposes 0.322096 state BMI surveillance 0.456109 BMI surveillance 0.949965 BMI measurement program 0.409462 school-based BMI screening 0.407749 states operating surveillance 0.342898 BMI surveillance data 0.527044 childhood obesity 0.611718 weight surveillance data 0.387939 Risk Behavior Surveillance 0.329241 cost-efficient surveillance approach 0.318093 BMI data 0.618271 local child BMI 0.374222	CLICK HERE