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Media ID	Source Name	Media Type	Language	Media Name	Media Description	Keywords	Keywords	Link to Article
1199	Centers for Disease Control and Prevention	Html	en	Notes from the Field: Increase in Fentanyl-Related OverdoseDeaths - Rhode Island, November 2013-March 2014	Melissa C. Mercado-Crespo, PhD1, Steven A. Sumner, MD1, M.	time-limited active surveillance 0.367989 Acetyl fentanyl 0.459937 CDC 0.377252 Melissa C. Mercado-Crespo 0.617751 unintentional overdose deaths 0.689876 illegally produced fentanyl 0.58412 fentanyl-related overdose deaths 0.788992 overdose deaths 0.98534 synthetic opioid 0.275807 injection-drug users 0.246739 Preliminary analyses 0.230667 National Center 0.228914 program records 0.235543 risk factors 0.232119 detection limit 0.231703 drug overdose patients 0.541404 active fentanyl prescriptions 0.547164 Unintentional Injury Prevention 0.363439 fentanyl-related deaths 0.394947 nonfatal opioid overdose 0.562136 fentanyl levels 0.442833 northern Rhode Island 0.424978 Steven A. Sumner 0.385704 additional data analyses 0.334451	fentanyl-related overdose death 0.782597 prescription monitoring program 0.588323 local staff members 0.351776 Rhode Island Department 0.608473 M. Bridget Spelke 0.40874 drug overdose deaths 0.772832 prescription drug 0.256662 Rhode Island 0.89142 Christina Stanley 0.24962 Rhode Island emergency 0.39148 Author affiliations 0.255671 Drug Enforcement Administration 0.37177 urban areas 0.229319 illicit fentanyl 0.481638 illicit sources 0.246928 New Jersey 0.242799 official cause 0.230674 Vital Records 0.239665 toxicology reports 0.232953 enzyme-linked immunosorbent assay 0.348234 David E. Sugerman 0.405704 medical records 0.238672 State Medical Examiners 0.584034 large percentage 0.246853	CLICK HERE
4415	Centers for Disease Control and Prevention	Html	en	Diseases & Conditions A-Z Index - D	CDC Diseases and Conditions A-Z Index	Error processing SSI 0.968415 Microsoft PowerPoint file 0.472728 ePub file 0.388096 Audio/Video file 0.375696 Dengue Hemorrhagic Fever 0.728753 Hymenolepis Infection 0.395291 Workforce Development 0.644468 Microsoft Word file 0.47615 Dengue Fever 0.602329 Corynebacterium diphtheriae Infection 0.512 Disease Control 0.42408 Public Health Systems 0.957903 Microsoft Excel file 0.470219 [Trisomy 21] 0.330865 Contact CDC 0.478314 list Skip 0.384095 page options Skip 0.505178 Form Controls TOPIC 0.460415 different file formats 0.474838 Mortality Data 0.332655 Public Affairs 0.325558 Cat Flea 0.459136 Dermatophyte Infection 0.400441 Apple Quicktime file 0.467474 Dog Bites 0.347602	CDC A-Z 0.648492 RealPlayer file 0.377893 Adobe PDF file 0.468107 Guinea Worm Disease 0.422168 Diphtheria Vaccination 0.348252 Developmental Disabilities 0.328797 Deep Vein Thrombosis 0.671772 processing SSI file 0.934422 Search Form Controls 0.695156 Dog Heartworm 0.562463 new entry 0.32733 Diphyllobothrium Infection 0.504283 A-Z Index 0.952079 Conditions A-Z Index 0.789537 CDC Topics 0.59372 Search The CDC 0.527585 Search Controls 0.374158 Clifton Road Atlanta 0.412255 Dog Flea Tapeworm 0.535687 Text file 0.379815 Antimicrobial Resistance 0.32345 (Dog Heartworm) 0.526402 RIS file 0.386044 SAS file 0.376842	CLICK HERE
6474	Centers for Disease Control and Prevention	Html	en	Prevalence of asthma among adults in metropolitan versus nonmetropolitan areas in Montana, 2008	The objective of this study was to compare the prevalence of asthma among adults living in metropolitan versus nonmetropolitan counties in Montana.	potential respondents 0.32404 United States 0.48823 current asthma prevalence 0.463037 logistic regression analyses 0.354863 NMNA counties 0.352648 NMNA respondents 0.326313 Human Services 0.316175 Risk Factor Surveillance 0.355343 health insurance status 0.434816 Metro counties 0.316587 younger respondents 0.351386 nonwhite respondents 0.332844 rural areas 0.436078 asthma prevalence 0.7063 current asthma 0.618241 prevalence estimates 0.375534 public health 0.356965 Rural-Urban Continuum Codes 0.365209 lower annual household 0.343032 similar prevalence rates 0.342682 Montana 0.439779 metropolitan versus 0.327131 self-reported asthma 0.875559	multivariable logistic regression 0.36183 Asthma Call-back Survey 0.390825 versus nonmetropolitan counties 0.368869 self-reported current asthma 0.507405 metropolitan areas 0.319628 body mass index 0.366684 Obese respondents 0.35949 nonmetropolitan counties 0.518498 annual household income 0.704797 asthma 0.976911 urban areas 0.350002 potential geographic variation 0.342566 population 0.320873 respondents 0.590842 demographic risk factors 0.338256 Asthma Control Program 0.427773 current self-reported asthma 0.696858 sociodemographic characteristics 0.337352 metropolitan area 0.326743 American Indian/Alaska Native 0.34302 metropolitan county 0.435397 Behavioral Risk Factor 0.359453 self-reported asthma status 0.425227	CLICK HERE
7075	Centers for Disease Control and Prevention	Html	en	Notifiable Diseases and Mortality Tables - May 25, 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.	H. influenzae 0.376572 National Center 0.293729 cases 0.354859 CDC 0.287887 novel influenza 0.635704 Total case counts 0.443245 pandemic influenza 0.93758 measles cases 0.335474 ** Data 0.337913	Cumulative total E. 0.463016 Influenza Division 0.441593 case reports 0.281924 2009 pandemic 0.744245 probable cases 0.321713 Respiratory Diseases 0.300603 rubella cases 0.304484 human infection 0.323499 influenza A virus 0.480032	CLICK HERE
9023	Centers for Disease Control and Prevention	Video	en	Cancer in the Family	A news segment about individuals with a family member whose cigarette smoking led to a cancer diagnosis. 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/tobacco/basic_information/health_effects/cancer/index.htm	Family 0.365045	YouTube 0.930567	CLICK HERE
10567	Centers for Disease Control and Prevention	Html	en	Preventing Chronic Disease | Models for Count Data With an Application to Healthy Days Measures: Are You Driving in Screws With a Hammer? - CDC	Volume 11 — March 27, 2014.	logistic regression model 0.599977 data 0.693577 data distribution 0.562542 mental health 0.597178 relevant financial relationships 0.593676 Healthy Days data 0.568421 Risk Factor Surveillance 0.703971 Poisson regression model 0.624847 Prev Chronic Dis 0.617334 AMA PRA 0.574025 unhealthy day count 0.571416 homeownership question 0.565906 number 0.590643 Disease Control 0.639293 multivariate regression models 0.618718 alternative regression models 0.595912 William W. Thompson 0.594605 logistic regression 0.615487 health-related quality 0.686096 Paul Z. Siegel 0.597397 Poisson regression models 0.646249 Poisson data 0.562441 chronic disease 0.599278 linear regression models 0.621163	Behavioral Risk Factor 0.70647 regression models 0.707003 logistic regression analysis 0.580074 AMA PRA Category 0.563022 homeownership 0.607374 logistic regression analyses 0.570452 Epidemiol Community Health 0.561264 exact Poisson distribution 0.562603 Hong Zhou 0.567031 negative binomial models 0.633667 unhealthy days questions 0.572365 Charles P. Vega 0.56568 count data 0.621902 negative binomial model 0.833214 Rashid S. Njai 0.598107 binomial regression model 0.644886 negative binomial regression 0.936392 simplest regression model 0.595946 negative binomial component 0.603142 Poisson distribution 0.571208 observed percentage distribution 0.563263 Poisson regression 0.687421 Chronic Disease Prevention 0.571757 percentage distribution 0.584319	CLICK HERE
11573	Centers for Disease Control and Prevention	Html	en	NER - Peer-Reviewed Biomonitoring Articles | Environmental Phenols: Triclosan	null	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	CLICK HERE
12295	Centers for Disease Control and Prevention	Html	en	Non-Polio Enterovirus | Transmission Non-Polio Enterovirus Infection | Picornavirus | CDC	You can get infected with non-polio enteroviruses by having close contact with an infected person. Also spread by touching objects or surfaces that have the virus on them and then touching your mouth, nose, or eyes.	stool 0.418736 hands 0.447013 objects 0.334489 sputum 0.335759 babies 0.335386 eyes 0.383484 Mothers 0.336983 navigation Skip 0.615467 coughing 0.344144 sneezing 0.350418 diapers 0.345993 mouth secretions 0.551455 close contact 0.491626 Infected people 0.593088 nasal mucus 0.535609 nose 0.464758 delivery 0.332956	non-polio enteroviruses 0.720976 list Skip 0.616861 pass 0.337555 page options Skip 0.781747 blister fluid 0.5119 Non-Polio Enterovirus Infection 0.684831 water 0.335221 infected person 0.912067 saliva 0.352754 eye 0.336001 doctor 0.33318 Pregnancy 0.332548 Pregnant women 0.48825 respiratory tract 0.479622 non-polio enteroviruses infection 0.680301 information 0.332592 feces 0.36251	CLICK HERE
13351	Centers for Disease Control and Prevention	Html	en	Progress Toward Measles Elimination - South-East AsiaRegion, 2003-2013	Arun Thapa, MD1; Sudhir Khanal, MPH1; Umid Sharapov, MD2; Virginia Swezy, MPH1; Tika Sedai, MA1; Alya Dabbagh, PhD3; Paul Rota, PhD4; James L. Goodson, MPH2; Jeffrey McFarland, MD1 (Author affiliations at end of text).	measles elimination platform 0.469388 endemic measles virus 0.440691 measles elimination 0.837069 measles incidence 0.584168 measles laboratory network 0.50276 aggregate measles surveillance 0.474146 measles genotypes 0.406827 routine immunization 0.340674 measles outbreaks 0.561745 MCV1 coverage 0.308762 timely case-based measles 0.498258 routine immunization services 0.30856 measles control 0.415283 World Health Organization 0.4085 measles virus genotypes 0.446291 Rubella Laboratory Network 0.318499 countries 0.372906 measles elimination activities 0.461883 Rubella Strategic Plan 0.303569 laboratory-confirmed measles outbreaks 0.543037 measles epidemiology 0.411126 congenital rubella syndrome 0.466683 rubella syndrome control 0.459724 measles case-based surveillance 0.507425 MCV2 coverage 0.335589	laboratory-confirmed measles cases 0.453367 Global Measles 0.463257 south-east asia region 0.771863 regional measles mortality 0.451228 laboratory-confirmed rubella outbreaks 0.325887 South-East Asia Region* 0.31777 laboratory-confirmed mixed measles 0.457113 measles elimination goal 0.576663 measles cases 0.461191 Asia Regional Office 0.347612 measles SIAs 0.457287 Regional Committee 0.324839 rubella/congenital rubella syndrome 0.303718 coverage 0.351446 South-East Asia Regional 0.361093 measles surveillance data 0.506908 target population 0.312665 Sri Lanka 0.324549 annual measles incidence 0.461823 rubella outbreaks 0.343385 case-based measles surveillance 0.574895 periodic high-quality SIAs 0.307003 routine immunization program 0.301291 measles deaths 0.482338	CLICK HERE
13680	Centers for Disease Control and Prevention	Html	en	A Sex-Specific Analysis of Nutrition Label Use and Health, Douglas County, Nebraska, 2013	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.	higher probability 0.35517 Douglas County 0.394203 higher odds 0.418943 nutrition education 0.376667 body weight 0.367686 high cholesterol 0.41242 weight change 0.390214 self-rated health 0.393706 health behaviors 0.366252 health care access 0.420425 health insurance coverage 0.381059 selected health variables 0.361967 sex-specific nutrition education 0.35902 nutrition education efforts 0.35623 self-reported health status 0.353918 health status 0.385629 respondents 0.349877 self-rated health categories 0.351469 Reducing Health Disparities 0.347546 various health needs 0.354458 women 0.535545 highest nutrition label 0.382106 Nebraska Medical Center 0.461686 nutrition facts 0.353111	food choices 0.37276 association 0.452009 heart disease 0.428957 men 0.565929 health behavior 0.367547 targeted nutrition education 0.356202 Nutrition Labeling 0.347776 standardized nutrition information 0.366092 Health status variables 0.356818 weight reported nutrition 0.370252 Similar findings 0.350147 nutrition label 0.964844 label reading 0.362497 Community Health Survey 0.35902 nutrition labels 0.633835 men vs women 0.364788 health 0.536328 U-shaped relationship 0.412291 total sample 0.378189 chronic conditions 0.453836 random sample survey 0.348749 leisure-time physical activity 0.438073 close association 0.3607 personal doctor 0.414013	CLICK HERE