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Media ID	Source Name	Media Type	Language	Media Name	Media Description	Keywords	Keywords	Link to Article
1209	Centers for Disease Control and Prevention	Html	en	Tobacco Product Use Among Adults - United States,2012-2013	Please note: An erratum has been published for this article. To view the erratum, please click here.	tobacco ingredient 0.42895 electronic cigarettes 0.376032 additional tobacco products 0.463247 tobacco product type 0.489304 tobacco control programs 0.483288 т‰Ѕ1 combustible tobacco 0.481939 specific tobacco products 0.471963 little cigars 0.588375 comprehensive tobacco control 0.460037 comprehensive state tobacco 0.440623 tobacco product prices 0.463172 water pipes/hookahs 0.412812 following tobacco product 0.514949 regular pipes 0.475303 tobacco products 0.992298 mass media campaigns 0.384184 cigarettes 0.410579 combustible tobacco product 0.533889 Smokeless tobacco users 0.444658 current tobacco 0.441248 United States 0.382421 tobacco price increases 0.470535 comprehensive smoke-free laws 0.385094 tobacco use measures 0.424121	cigars/cigarillos/filtered little cigars 0.365858 prevalence estimates 0.365864 cigarette smoking 0.417254 occasional tobacco 0.456858 т‰Ѕ1 tobacco products 0.48983 self-reported tobacco 0.42571 Adult Tobacco Survey 0.500042 tobacco taxes 0.421884 tobacco product types 0.575051 tobacco product 0.875652 different tobacco product 0.477066 dissolvable tobacco products 0.727136 tobacco product type.* 0.474066 U.S. adults 0.434817 annual household income 0.378012 water pipes/hookah 0.431154 dissolvable tobacco product 0.462996 smokeless tobacco products 0.483039 tobacco use definitions 0.421491 Tobacco use prevalence 0.459518 smokeless tobacco 0.570627 National Adult Tobacco 0.499727 respective tobacco product 0.458922 combustible tobacco products 0.492443	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
5129	Centers for Disease Control and Prevention	Html	en	Highest Rates of Leisure-Time Physical Inactivity in Appalachia and South - Press Release: February 16, 2011	Highest Rates of Leisure-Time Physical Inactivity in Appalachia and South	CDC 0.543885 mental health 0.347853 Risk Factor Surveillance 0.453806 transportation policies 0.340782 West Coast 0.351874 moderate physical activity 0.487807 Community organizations 0.338569 Disease Control 0.364556 obesity 0.510368 obese people 0.334501 leisure time 0.506237 lowest levels 0.347574 Obesity program 0.417855 Moderate intensity activities 0.465557 physical inactivity rates 0.582337 U.S. counties 0.489753 free time 0.492765 high risk 0.464927 highest levels 0.343111 HUMAN SERVICES 0.334705 county level 0.343416 CDC survey 0.441575 environmental change 0.333902 leisure-time physical inactivity 0.929758 percent 0.422635	physical inactivity estimates 0.589449 self-reported data 0.34936 heart disease 0.348146 U.S. DEPARTMENT 0.335891 CDC funds 0.4188 health care 0.340884 multiple partners 0.332866 census information 0.340412 county-level estimates 0.536763 chronic diseases 0.46328 U.S. adults 0.3499 estimated levels 0.349099 state-based adult telephone 0.479628 physical activity 0.952842 brisk walking 0.342287 lifestyle intervention programs 0.434266 state-based Nutrition 0.35137 regular job 0.503594 Ann Albright 0.346086 diabetes 0.647459 Janet E. Fulton 0.449416 physical activities 0.37465 Diabetes Translation 0.464367 health-promoting urban design 0.458013	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
7608	Centers for Disease Control and Prevention	Html	en	Tuberculosis (TB) Treatment	null	result 0.227239 latent TB infection 0.987967 TB disease. 0.491314 following populations 0.302982	TB disease 0.76078 TB-related conditions 0.300505 TB bacteria 0.566294 additional considerations 0.298824	CLICK HERE
8051	Centers for Disease Control and Prevention	Html	en	Announcement: New Recommendations from the CommunityPreventive Services Task Force Available Online	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. 0.598854 Task Force 0.919612 prevention experts 0.590416 CDC 0.608153 endorsement 0.546771 Human Services 0.746888 assistive technology 0.603123 U.S. Department 0.750455 MMWR HTML versions 0.654836 electronic PDF version 0.649671 new information 0.596978 e-mail 0.530945 Preventive 0.515181 population health 0.5925 Contact GPO 0.602777 commercial sources 0.586941 decision makers 0.586318 current prices 0.58218 Electronic Screening 0.59074 original paper copy 0.645607 programs 0.527871 Excessive Alcohol Consumption 0.668942 wide range 0.589413 original MMWR paper 0.651207	U.S. Government Printing 0.649609 Superintendent 0.516193 unpaid panel 0.592366 assistance 0.516137 title 0.515177 MMWR readers 0.589301 character translation 0.581781 technical support 0.588236 file 0.516241 Persons 0.516304 public health 0.597149 format errors 0.583929 Brief Intervention 0.591629 http://www.thecommunityguide.org/alcohol/esbi.html 0.515593 subject line 0.593907 typeset documents 0.587352 trade names 0.587017 Services Task Force 0.73237 official text 0.580557 non-CDC sites 0.58544 report 0.515165 Accommodation 0.51519 electronic conversions 0.582577 printable versions 0.578314	CLICK HERE
8059	Centers for Disease Control and Prevention	Html	en	Preconception Care, Show Your Love Campaign	null	pregnancies 0.524866 healthy behaviors 0.97861 new resources 0.760518 posters 0.488125 dreams 0.490871 babies 0.514081 healthcare 0.496517 number 0.489078 preconception health 0.949095	main goal 0.818207 Love 0.497962 future 0.485179 Buttons 0.491457 national campaign 0.803561 page 0.484437 family 0.485457 women 0.810552	CLICK HERE
8809	Centers for Disease Control and Prevention	Html	en	Naegleria fowleri - Organ Transplantation - Info for Health Professionals	Information for health professionals about Naegleria fowleri. Education and information about the brain eating ameba Naegleria fowleri that causes encephalitis and death including frequently asked questions, biology, sources of infection, diagnosis, treatment, prevention and control, and other publications and pertinent information for the public and medical professionals.	tissue cross-contamination 0.650288 Trans R Soc 0.679433 generalized amoebiasis 0.677607 Engl J Med 0.651407 shipping instructions 0.648017 CDC Emergency Operations 0.692967 CDC Free-Living Ameba 0.697448 organ transplantation 0.808426 da Silva AJ 0.672207 solid organ transplantation 0.796203 primary amoebic meningoencephalitis 0.877887 specimen collection guidance 0.683891 Morb Mortal Wkly 0.746019 CDC. Balamuthia 0.668577 B. Diagnostic review 0.670854 free-living ameba 0.698663 historical case 0.651788 Visvesvara GS 0.728969 Tuppeny M. Primary 0.684381 Public Health 0.686108 primary meningoencephalitis 0.684738 Duma RJ 0.686934 individual organ 0.683419 extra-CNS organs 0.654355 donor organs 0.653768	MMWR Morb Mortal 0.74604 suitable organ 0.679978 experimental pathological changes 0.675391 organ recipient serology 0.716055 Naegleria fowleri 0.996022 organ transplantation—Mississippi 0.680204 Mortal Wkly Rep. 0.73665 blood-brain barrier 0.647835 Transplant-transmitted Balamuthia mandrillaris—Arizona 0.702388 Soc Trop Med 0.768134 organ recipients 0.689078 Trop Med Public 0.701363 Crit Rev Clin 0.679978 Primary amebic meningoencephalitis 0.712562 guide clinical management 0.676219 Clin Microbiol. 0.651517 potentially greater risk 0.682091 subsequent organ procurement 0.713096 deceased PAM cases 0.686603 Annu Rev Microbiol 0.675549 Trop Med Hyg 0.764552 diagnostic assistance 0.648926 Roy SL 0.676483 Naegleria sp. 0.786321	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