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Media ID	Source Name	Media Type	Language	Media Name	Media Description	Keywords	Keywords	Link to Article
6464	Centers for Disease Control and Prevention	Html	en	Diabetes-related services and programs in small local public health departments.	The objectives of this study were to describe various diabetes-related patient care and primary prevention services offered by small LHDs (those serving a population of less than 150,000) and explore factors associated with the diversity of these services.	diabetes prevention 0.366144 obesity prevention program 0.304404 diabetes public health 0.358145 obesity prevention programs 0.348589 large metropolitan LHDs 0.347384 diabetes-related services 0.375006 public health departments 0.298918 National Diabetes Prevention 0.313372 frequently mentioned diabetes 0.293353 state health departments 0.316878 obesity prevention 0.428062 small LHDs function 0.309324 patient care services 0.505585 public health services 0.333613 health care services 0.303569 local diabetes care 0.392356 patient care 0.509556 public health performance 0.304259 patient care service 0.343173 population 0.30929 City Health Officials 0.320427 diabetes awareness activities 0.296979 chronic disease 0.314006 state public health 0.312256 diabetes care specialists 0.342593	diabetes prevention program 0.343999 diabetes care services 0.344337 United States 0.37032 diabetes primary prevention 0.337024 certified diabetes educator 0.339498 primary prevention programs 0.605523 Health Manag Pract 0.349779 diabetes-related patient care 0.43713 diabetes patient care 0.337796 primary prevention program 0.300474 state health department 0.415248 primary prevention 0.73737 health departments 0.394834 diabetes surveillance capacity 0.326062 local health departments 0.350261 primary prevention services 0.348153 public health 0.660572 local diabetes burden 0.318553 small LHDs 0.916812 Public Health Manag 0.350726 diabetes surveillance 0.367798 local public health 0.350377 Fifty-eight small LHDs 0.309257 local diabetes surveillance 0.303388	CLICK HERE
7128	Centers for Disease Control and Prevention	Html	en	CDC - Preventing Chronic Disease: Volume 9, 2012: 11_0313	Diabetes-related health improvements achieved from self-management education interventions are not sustained long-term. We examined the health effects at 1 year follow-up of a 2-year, empowerment-based, diabetes self-management support intervention designed for African Americans.	Lifelong Diabetes Self-Management 0.620175 glycemic control 0.587953 ongoing DSMS intervention 0.473491 follow-up period 0.482131 Effective diabetes self-management 0.58865 12-month diabetes intervention 0.595094 diabetes-specific quality 0.51585 diabetes self-management 0.908416 diabetes empowerment measure 0.493772 diabetes self-management support 0.750418 2-year diabetes self-management 0.701074 diabetes treatment 0.46885 Michigan Diabetes Research 0.488424 blood pressure 0.479198 lifelong self-management efforts 0.489167 empowerment-based diabetes self-management 0.650574 diabetes education intervention 0.614476 diabetes self-management intervention 0.741604 self-management education interventions 0.550571 ongoing diabetes self-management 0.642163 group-based self-management support 0.510103 DSMS intervention 0.56047 participant-identified self-management priorities 0.496752 diabetes empowerment 0.51583	study 0.512622 diabetes education program 0.503963 diabetes-related health benefits 0.510818 self-management efforts 0.509666 diabetes self-management education 0.744988 certified diabetes educator 0.500587 self-management support control 0.515582 diabetes care 0.595488 self-management support intervention 0.685363 diabetes care intervention 0.557598 individual self-management 0.469114 participants 0.524719 Internet-based diabetes self-management 0.592147 empowerment-based DSMS intervention 0.530458 2-year DSMS intervention 0.51386 diabetes education programme 0.491353 intervention follow-up period 0.476902 Diabetes Empowerment Scale 0.511015 randomized controlled trial 0.477512 diabetes self-management interventions 0.752031 Diabetes Distress Scale 0.540633 diabetes self-care interventions 0.525481 diabetes self-care activities 0.573433 group-based self-management intervention 0.565021	CLICK HERE
8598	Centers for Disease Control and Prevention	Html	en	Advanced Molecular Detection (AMD) - Questions and Answers	AMD Questions and Answers will help answer questions like what is AMD, why AMD and why now, what does AMD look like when you put it to work against disease threats, and many more	disease detectives 0.532372 CDC 0.909003 bioinformatics CDC 0.575471 health care treatment 0.460257 infectious disease threats 0.499594 drug-resistant microbes 0.565747 good disease detective 0.456656 similar disease threats 0.477601 rapidly evolving field 0.458312 resistant microbe sweeps 0.477714 infectious disease outbreaks 0.522441 complex infectious disease 0.516974 World Health Organization 0.463395 deadly microbes 0.459997 massive amounts 0.532142 food supply 0.446334 public health response 0.482319 genomic sequencing 0.461305 public health laboratories 0.456759 interrupt disease transmission 0.449663 national health security 0.6963 generation sequencing tools 0.497524 adequate AMD capacity 0.47769 New molecular tools 0.504192 United States 0.49719	health security needs 0.47738 infectious disease control 0.502825 pulse-field gel electrophoresis 0.450746 advanced computing 0.5388 important disease threats 0.484524 outbreak detection systems 0.457353 point-of-care molecular tests 0.455694 deadly health threats 0.51372 molecular detection tools 0.497642 characterize drug-resistant microbes 0.506462 killer microbes 0.482506 disease transmission 0.458354 public health 0.754723 disease threats 0.512255 polymerase chain reaction 0.451787 CDC scientists 0.527528 infectious disease laboratory 0.495573 bioinformatics experts 0.543548 shoe leather epidemiology 0.462459 infectious disease 0.695543 public health efforts 0.482804 new technologies 0.450416 public health science 0.472584 world-class microbe library 0.460692	CLICK HERE
8612	Centers for Disease Control and Prevention	Html	en	PanFlu Storybook - In Memorial, Marcella Bobzien	In Memorial, To date, October 1918 remains the deadliest month in U.S. history when approximately 200,000 Americans died of the flu. Healthy, young adults (average age 35 years) began coughing in the morning and were dead by the evening. The family stories described in this section define true courage amid unbearable loss.	1918 flu pandemic 0.831942 urban America 0.420165 brothers 0.271262 arrangement 0.238189 Carmen Garske Bobzien 0.696732 toddler 0.244613 community′s capacity 0.403409 Robert 0.312156 rural North Dakota 0.960055 sister′s children 0.402576 young children 0.406766 Leon 0.238229 Marilynn Sutherland 0.479123 saddened listening 0.451394 grandmother Carmen 0.502497 siblings Millie 0.449186 outskirts 0.239438 Marcella Bobzien 0.512074 adult 0.236965 Bismarck 0.239291 second-hand knowledge 0.409664 pandemic flu 0.840436 Stella Garske Bobzien 0.604021 Dolores 0.248085 close–knit farming community 0.582038	epidemic′s dependent survivors 0.576819 duration 0.239408 mother′s stories 0.423821 Storyteller 0.244065 orphanage 0.23989 Otto′s diary 0.407305 Jack 0.237371 Otto John Bobzien 0.634523 public health 0.402595 Bea 0.247028 sod farmhouse 0.416584 flu deaths 0.542349 maternal grandparents 0.445172 Carmen′s younger sister 0.584438 recollections 0.243008 Dick 0.236716 inevitable next flu 0.545216 Vernon 0.34896 Jim 0.237393 Ferd 0.335858 time 0.237618 family 0.339136 pandemics 0.252807 isolated farming families 0.61478	CLICK HERE
9159	Centers for Disease Control and Prevention	Html	en	NIOSH A-Z Index - O	null	MPEG 0.741242 site 0.541063 PDF 0.544429	PPT 0.837268 DOC 0.733754	CLICK HERE
10861	Centers for Disease Control and Prevention	Html	en	Preventing Chronic Disease | Smoking in Top-Grossing US Movies, 2011 - CDC	We reviewed the number of incidents of tobacco use (almost exclusively smoking) depicted in movies in the United States in 2011 to compare that with previously reported trends.	tobacco appearances 0.271862 United States 0.210493 top-grossing movies 0.727157 policies 0.23103 Human Services 0.205497 smoking causes youth 0.238583 movies 0.762188 movie subsidy programs 0.201236 Tobacco Control Research 0.28717 companies 0.212776 long-term trends 0.203021 Motion Picture Association 0.385641 tobacco brands 0.286119 tobacco 0.903074 new youth-rated movies 0.225765 earlier report 0.247121 tobacco product 0.456 in-theater tobacco impressions 0.287711 figure 0.232513	box office 0.209869 Historical data 0.251909 tabular version 0.256941 tobacco-free youth-rated movies 0.234557 Total tobacco incidents 0.390767 tobacco use incident 0.271744 R-rated movie 0.225733 fewer incidents 0.200811 tobacco depictions 0.287536 youth smoking 0.21933 onscreen tobacco imagery 0.298575 support youth-rated movies 0.228047 top-grossing US movie 0.204643 youth-rated movies 0.566251 tobacco incidents 0.768655 tobacco imagery 0.433027 onscreen smoking 0.270858 Sacramento-Emigrant Trails 0.202166	CLICK HERE
11800	Centers for Disease Control and Prevention	Html	null	Preventing Chronic Disease | Measurement of Compliance WithNew York City's Regulations on Beverages, Physical Activity, andScreen Time in Early Child Care Centers - CDC	Policy interventions designed to change the nutrition environment and increase physical activity in child care centers are becoming more common, but an understanding of the implementation of these interventions is yet to be developed. The objective of this study was to explore the extent and consistency of compliance with a policy intervention designed to promote nutrition and physical activity among licensed child care centers in New York City.			CLICK HERE
12809	Centers for Disease Control and Prevention	Html	en	HEADS UP to Youth Sports: Parents | HEADS UP | CDC Injury Center	null	proper helmet fit 0.976161 brain injury 0.375183 CDC 0.204375	3D helmet fit 0.942728 Helmet Safety app 0.989449 HEADS UP Concussion 0.848434	CLICK HERE
13522	Centers for Disease Control and Prevention	Html	en	Germs & Infections | Contact Lenses | CDC	CDC - Protect Your Eyes: Healthy and Safe Contact Lens Cleaning and Use. Millions of people use contact lenses every day but lens cleaning practices can lead to eye infections. Hands should be washed before handling contact lenses and contacts should be properly cleaned, disinfected, and stored to ensure eye health and safety. Following your eye doctor’s recommendations and a few simple steps can lead to healthy daily contact lens use.	benefits 0.222734 treatment 0.221868 contact lens wearers 0.940048 eye problems 0.306071 bacteria 0.221157 clear dome 0.314817 eye infection 0.299747 type 0.242138 eyes 0.241389 tips 0.220161 glasses 0.254034 daily activities 0.330831 inflammation 0.225767 vital aspect 0.330436 supplies 0.27051 patient 0.221897 sight 0.225832 infections 0.222745 contact lenses 0.873684 proper care 0.302552	higher risk 0.308659 germs 0.226631 viruses 0.220914 complications 0.222584 blindness 0.222446 eye surgery 0.32165 patients 0.22235 Worldwide 0.22433 corneal transplant 0.30943 people 0.250812 severe cases 0.305582 pair 0.221688 microbial keratitis 0.480055 eye 0.334027 eye doctor 0.311816 fungi 0.220602 permanent vision loss 0.412181 parasites 0.222306 practice healthy habits 0.420185 Contact lens wear 0.439269	CLICK HERE
14490	Centers for Disease Control and Prevention	Html	en	Who Would Pay for State Alcohol Tax Increases in the UnitedStates?	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.	capita alcohol consumption 0.30075 alcohol tax increase 0.296011 binge drinkers 0.229577 net cost 0.29351 binge drinking 0.365435 hypothetical tax increases 0.333861 tax increases 0.788391 alcohol prices 0.237541 hypothetical tax increase 0.31302 Alcohol Abuse 0.225825 higher alcohol taxes 0.283553 alcohol taxes 0.45171 alcohol 0.791816 aggregate costs 0.290183 adult excessive drinkers 0.290387 state alcohol tax 0.464782 BRFSS core alcohol 0.230523 heavy drinker 0.254124 daily average 0.255015 alcohol tax increases 0.746898 state alcohol taxes 0.34449 sociodemographic characteristics 0.234235 alcohol policy interventions 0.233863 capita costs 0.345711	State-specific tax increases 0.249169 United States 0.387976 drinks 0.467223 current alcohol taxes 0.253209 average annual increase 0.230942 non-Hispanic white drinkers 0.274355 alcohol consumption 0.607549 Average daily alcohol 0.264005 Alcohol Epidemiologic Data 0.232708 excessive drinkers 0.841684 Excessive alcohol consumption 0.347454 excessive drinking 0.243269 hypothetical state alcohol 0.373777 non-Hispanic whites 0.284088 public health 0.250963 nonexcessive drinkers 0.909314 costs 0.35543 Alcohol Policy Information 0.282279 value-based alcohol taxes 0.253549 annual alcohol consumption 0.244944 hypothetical alcohol tax 0.299364 evidence-based public health 0.239268 alcohol spectrum disorders 0.239775 current drinkers 0.239986	CLICK HERE