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Media ID	Source Name	Media Type	Language	Media Name	Media Description	Keywords	Keywords	Link to Article
6395	Centers for Disease Control and Prevention	Html	en	Unhealthy Air Quality --- United States, 2006--2009	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.	fine particulate matter 0.580868 high school education 0.531821 ambient air quality 0.580662 Dockery DW 0.557604 multi-hour ozone exposure 0.587408 24-hour PM2.5 standard 0.652409 medium metropolitan counties 0.533124 Dominici F. Ozone 0.579818 highest income population 0.539782 Health Effects Institute 0.6155 ozone-related health effects 0.53559 air quality 0.665767 Pope CA 0.612496 8-hour ozone nonattainment 0.75509 ozone concentration 0.560244 24-hour PM2.5 concentrations 0.612403 air quality standards 0.569035 ozone production 0.608423 particulate air pollution 0.546072 small metropolitan counties 0.53236 nonattainment areas 0.543411 health effects 0.820242 maximum 8-hour ozone 0.617149 air pollutants 0.567152 ppm ozone 0.54879	United States 0.55326 well-characterized air pollutants 0.533155 ozone exposure 0.634055 particulate matter 0.60979 adverse health effects 0.561168 ozone nonattainment county 0.666535 8-hour ozone standard 0.664359 gaseous air pollutants 0.5314 PM2.5 nonattainment county 0.632208 ozone nonattainment counties 0.946966 Low-level ozone exposure 0.584796 fringe metropolitan counties 0.531201 Ground-level ozone 0.581332 ozone levels 0.56836 ambient ozone 0.544249 urban areas 0.591239 U.S. population 0.545504 PM2.5 nonattainment counties 0.700601 Environ Health Perspect 0.618552 Environmental ozone effects 0.597914 et al 0.794489 greatest percentage 0.539335 metropolitan counties 0.548956 air pollution 0.727588	CLICK HERE
7085	Centers for Disease Control and Prevention	Html	en	Global Health - Czech Republic	null	Content source 0.422709 HHS 0.297574 list Skip 0.74332 endorsement 0.291872 CDC 0.271556 non-federal site 0.4688	Notice 0.270187 sponsors 0.241885 page options Skip 0.947337 information 0.241652 employees 0.242118	CLICK HERE
7130	Centers for Disease Control and Prevention	Html	en	QuickStats: Age-Adjusted Homicide Rates,* by Sex and Type of Locality - United States, 2007-2009	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.	mmwrq@cdc.gov. 0.309065 localities 0.245593 endorsement 0.24418 Alternate Text 0.297668 Human Services 0.371156 assistive technology 0.316916 MMWR HTML versions 0.366706 U.S. Department 0.366497 medium metropolitan counties 0.546922 homicide rates 0.389298 identification 0.216885 electronic PDF version 0.364239 e-mail 0.239377 homicide rate 0.867319 Contact GPO 0.308462 locality 0.243405 commercial sources 0.298247 males 0.376348 population 0.260687 current prices 0.292317 original paper copy 0.358914 United States 0.301783 original MMWR paper 0.363319 100,000 0.2572	Superintendent 0.217895 assistance 0.219763 title 0.218612 MMWR readers 0.296258 character translation 0.293179 file 0.219876 Persons 0.21994 fringe metropolitan counties 0.405504 format errors 0.291828 females 0.310925 subject line 0.308046 Health 0.230908 age-adjusted homicide rate 0.686902 typeset documents 0.295384 trade names 0.298319 paper copy 0.360422 official text 0.289723 females. 0.217738 non-CDC sites 0.294797 report 0.218599 information 0.21989 Accommodation 0.218625 electronic conversions 0.289977 central metropolitan counties 0.953003	CLICK HERE
7837	Centers for Disease Control and Prevention	Html	en	Health Marketing Basics	Health Marketing Basics - Gateway to Health Communication - CDC	diverse populations 0.558384 successful marketing mix 0.641698 health information 0.577622 new drink 0.599672 marketing plans 0.587461 clear target market 0.673982 major grocery store 0.605308 social needs 0.563742 end user 0.563406 current tests 0.558091 state health departments 0.613159 traditional marketing 0.678826 non-monetary price 0.559916 customer needs 0.558693 new testing kits 0.611546 marketing plan 0.673368 diabetes example 0.569786 marketing mix elements 0.645518 fundamental aspects 0.615823 new product 0.601453 public health service 0.629704 effective target market 0.68156 exchange 0.566004 marketing resources 0.584661 marketing process 0.633112	commercial product 0.572937 traditional marketing theories 0.654111 target markets 0.677627 target market 0.945916 target health issue 0.664891 ‘target market 0.584267 example 0.610519 effective marketing plan 0.633374 science based strategies 0.616933 testing kits 0.611749 local health departments 0.612113 product 0.61472 marketing mix 0.662531 medical journals 0.557891 different markets 0.602942 specific market 0.583853 people 0.563886 fundamental marketing elements 0.642312 marketing 0.813673 larger market 0.578029 health marketing 0.781687 HIV testing kit 0.606039 marketing efforts 0.579444 effective ‘marketing mix 0.616967	CLICK HERE
9064	Centers for Disease Control and Prevention	Html	en	Climate Change and Transportation - Health Communication	Climate Change and Transportation - Gateway to Health Communication - CDC	global concentrations 0.482932 atmosphere 0.444614 motor vehicle travel 0.564754 land use patterns 0.482338 streets 0.437024 Carbon dioxide 0.482804 couple times 0.474271 transportation choices 0.494289 vehicle miles 0.483145 atmospheric concentrations 0.481344 land development techniques 0.534113 fewer GHGs 0.478959 climate change 0.704016 public transportation systems 0.567301 sport utility vehicles 0.564716 necessary component 0.478049 building developer 0.469928 large-scale emitters 0.483397 fuel intensive forms 0.53185 private vehicles 0.529506 public transportation 0.785196 office buildings 0.471584 harmful climate change 0.558814 elementary school 0.47058 largest sources 0.488798	transportation emissions 0.588901 rate GHG emissions 0.671313 best ways 0.474802 transportation infrastructure 0.496515 unique community 0.476257 United States 0.568806 GHG emissions 0.944286 largest transportation systems 0.565404 new developments 0.473343 community’s residents 0.477028 pickup trucks 0.488551 travel mode 0.476358 greenhouse gas 0.572364 available transit services 0.530254 severe impacts 0.478762 walking 0.431537 primary greenhouse gas 0.549827 transportation sector 0.503416 passenger cars 0.486881 urban areas 0.47329 people 0.456002 smart growth 0.527767 particular area 0.482849 transportation-related GHG emissions 0.667666	CLICK HERE
10290	Centers for Disease Control and Prevention	Html	en	Before a Storm'Winter Weather	Taking preventive action is your best defense against having to deal with extreme cold-weather conditions. By preparing your home and car in advance for winter emergencies, and by observing safety precautions during times of extremely cold weather, you can reduce the risk of weather-related health problems.	temperatures 0.458116 winter storms 0.788413 stages 0.371516	challenge 0.397336 winter storm 0.722421	CLICK HERE
11278	Centers for Disease Control and Prevention	Html	en	Young Worker Safety and Health: Selected Charts on Young Worker Employment, Injuries and Illnesses: Rates of Work-related Injuries and Illnesses Treated in Hospital Emergency Departments by Year, 15-17 Year-Olds, United States	Young Worker Safety and Health: Selected Charts on Young Worker Employment, Injuries and Illnesses: Rates of Work-related Injuries and Illnesses Treated in Hospital Emergency Departments by Year, 15-17 Year-Olds, United States	NIOSH Work Supplement 0.593993 highest rate 0.465671 CDC 0.339661 Download data 0.450021 United States 0.788558 Health 0.332095 Illnesses Treated 0.821976 rates 0.423192 Charts 0.36089 work-related nonfatal injuries 0.824693 fulltime equivalents 0.642245 graph 0.331447	Hospital Emergency Departments 0.923754 time period 0.463544 Young Worker Employment 0.951672 Excel 0.326796 Young Worker Safety 0.681002 olds 0.336319 Year-Olds 0.429788 Download image file 0.577824 Work-related Injuries 0.835497 lowest rate 0.470663 Electronic Injury Surveillance 0.576584	CLICK HERE
11348	Centers for Disease Control and Prevention	Html	en	Preventing Chronic Disease GIS Snapshot | Comparing Apples to Oranges: Comparative Case Study of 2 Produce Carts in Chicago - CDC	In June 2012, the Chicago Department of Public Health passed ordinances to legalize mobile produce vending throughout the city, provided at least 50% of produce carts operate in designated underserved areas. In response, the Neighbor Carts program emerged to promote the opportunity for economic success and healthful food access through an unconventional retail structure.	underserved zones 0.744767 Northwestern University 0.756667 larger evaluation 0.691334 underserved zone 0.907086 local business support 0.669196 Lake Shore Dr 0.657761 Future evaluation 0.606672 centrally located Streeterville 0.712435 Chicago Department 0.628238 Bessie Feinberg Foundation 0.66745 customer intercept survey 0.713991 0.5-mile walking radius 0.670826 Neighbor Carts program 0.851085 customer volume 0.612176 produce carts 0.887466 unique consumer trends 0.665328 produce vending programs 0.692644 code data 0.609032 broad service area 0.682861 customer age 0.617372 geo-demographic information 0.60793 over-arching program goals 0.686265 Neighbor Capital 0.60662 individual cart sustainability 0.732153 closer proximity 0.606431	mobile produce carts 0.863758 Public Health 0.689453 geographic information systems 0.682708 unconventional retail structure 0.69007 University institutional review 0.683703 L. M. Anderson 0.675872 Chicago neighborhoods 0.638161 different evaluation metrics 0.680402 public transportation lines 0.672633 customer surveys 0.623345 Nutrition Assistance Program 0.697335 program effectiveness 0.803753 city ordinances 0.610403 recording self-reported customer 0.737965 poor nutritional intake 0.66124 program improvement 0.615984 maps highlight customer 0.712193 service area 0.905189 Maps. Customer utilization 0.731522 economic success 0.607404 cart success 0.663269 Public Health Service 0.684984 healthful food access 0.86896 North Lawndale neighborhood 0.714858	CLICK HERE
12833	Centers for Disease Control and Prevention	Html	en	Outbreak of Salmonella Newport Infections Linked toCucumbers - United States, 2014	Kristina M. Angelo, DO1,2, Alvina Chu, MHS3, Madhu Anand, MPH4, Thai-An Nguyen, MPH2, Lyndsay Bottichio, MPH2, Matthew Wise, PhD2, Ian Williams, PhD2, Sharon Seelman, MS, MBA5, Rebecca Bell, PhD5, Marianne Fatica, PhD5, Susan Lance, DVM, PhD5, Deanna Baldwin6, Kyle Shannon3, Hannah Lee, MPH3, Eija Trees, PhD2, Errol Strain, PhD5, Laura Gieraltowski, PhD2 (Author affiliations at end of text).	characterize PFGE pattern 0.536388 single nucleotide polymorphism 0.60865 leafy greens 0.568383 York State Department 0.586233 Kristina M. Angelo 0.618377 outbreak investigation 0.538274 produce items 0.531286 Agriculture foodborne outbreak 0.60528 outbreak 0.674845 Zoonotic Infectious Diseases 0.575171 ill persons 0.625959 PFGE pattern 0.754119 nucleotide polymorphism distance 0.609842 Illness onset dates 0.537926 Delmarva region 0.964039 highly related isolates 0.530676 Salmonella Newport outbreaks 0.574385 Salmonella Newport PFGE 0.572869 Maryland Department 0.560791 Salmonella Newport 0.861619 different distribution chain 0.605066 supplemental questionnaire 0.632809 illness subclusters 0.702855 distinct illness subclusters 0.536932 illness onset 0.621643	PFGE pattern JJPX01.0061 0.632796 novel outbreak vehicle 0.615057 multistate outbreak 0.537795 consuming cucumbers 0.564656 Delmarva region tomatoes 0.572278 XbaI PFGE pattern 0.537671 outbreak investigations 0.532943 New York subcluster 0.529014 local health 0.530715 informational traceback 0.603091 outbreak strain 0.59487 Salmonella Saintpaul infections 0.558433 New York 0.808183 unrelated ill persons 0.535205 FoodNet Population Survey 0.745812 Eastern Shore 0.579483 additional suspected outbreak 0.587826 Salmonella enterica serotype 0.592583 cucumbers 0.760584 national molecular subtyping 0.531782 cucumber consumption 0.557511 recommendations.** Cucumbers 0.551965 product traceback evidence 0.543277 Maryland rapid response 0.525874	CLICK HERE
13412	Centers for Disease Control and Prevention	Html	es	Epidemia de heroína - Signos Vitales	CDC Vital Signs links science, policy, and communications with the intent of communicating a call-to-action for the public. CDC Vital Signs provides the most recent, comprehensive data on key indicators of important health topics.	Bajo Precio 0.317848 Archivo Apple Quicktime 0.324635 Archivo RealPlayer 0.314838 adultos jóvenes 0.317605 hepatitis b 0.316721 Archivo Microsoft PowerPoint 0.326076 Archivo Adobe PDF 0.324208 Archivo Microsoft 0.371168 Archivo Microsoft Word 0.325845	analgésicos opioides 0.992896 Crear directrices 0.316717 largo plazo 0.315786 mayores aumentos 0.320921 Archivo Zip Comprimido 0.32438 Archivo Microsoft Excel 0.323942 pacientes adictos 0.314739 creciente epidemia 0.319643	CLICK HERE