| 5175 |
Centers for Disease Control and Prevention |
Html |
en |
South Carolina Activities to Prevent HAIs |
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| MPEG | 0.249823 |
| funding | 0.580785 |
| prevention activities | 0.424039 |
| monthly update | 0.669138 |
| email address | 0.956601 |
| different file formats | 0.600395 |
| Affordable Care Act | 0.620202 |
| Epidemiology | 0.417475 |
| South Carolina | 0.426747 |
| recent work | 0.647979 |
|
| HAI infrastructure | 0.442443 |
| conduct surveillance | 0.429469 |
| infectious disease | 0.710812 |
| PPT | 0.262794 |
| Laboratory Capacity | 0.84554 |
| Infectious Diseases | 0.864414 |
| DOC | 0.247626 |
| page | 0.296577 |
| ELC | 0.479386 |
|
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| 5521 |
Centers for Disease Control and Prevention |
Html |
en |
2,6-Di-tert-butyl-p-cresol - NIOSH Pocket Guide to Chemical Hazards |
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 |
| 5714 |
Centers for Disease Control and Prevention |
Html |
en |
Chlorodiphenyl (42% chlorine) - NIOSH Pocket Guide to Chemical Hazards |
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 |
| 6922 |
Centers for Disease Control and Prevention |
Html |
en |
Short Sleep Duration Among Workers - United States, 2010 |
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. |
| Insufficient sleep | 0.271429 |
| regular night shift | 0.263431 |
| Non-Hispanic black workers | 0.243794 |
| report short sleep | 0.278179 |
| highest prevalence | 0.228552 |
| higher prevalence | 0.253016 |
| average sleep duration | 0.387606 |
| National Health Interview | 0.250438 |
| non-Hispanic white workers | 0.243723 |
| National Sleep Foundation | 0.284629 |
| sleep opportunities | 0.258872 |
| non-Hispanic Asian workers | 0.243756 |
| night shift | 0.429997 |
| evidence-based training programs | 0.27246 |
| significantly higher rate | 0.235505 |
| 4-digit industry codes | 0.230945 |
| shorter sleep episodes | 0.268909 |
| Health Interview Survey | 0.250681 |
| broad industry categories | 0.243 |
| self-reported short sleep | 0.277228 |
| U.S. workers | 0.237607 |
| usual shift | 0.315558 |
| NHIS public dataset | 0.227924 |
| simple 2-digit industry | 0.230782 |
| NHIS | 0.228455 |
|
| individual workers | 0.229131 |
| manufacturing workers | 0.229214 |
| overall prevalence | 0.228525 |
| social assistance | 0.242145 |
| industry | 0.258895 |
| shift factors | 0.241703 |
| warehousing workers | 0.228242 |
| sufficient sleep | 0.256152 |
| adverse health effects | 0.245182 |
| fatigued workers | 0.234254 |
| regular daytime shift | 0.257279 |
| Sara E. Luckhaupt | 0.24356 |
| workers | 0.407516 |
| shift system designs | 0.247903 |
| various adverse health | 0.245684 |
| short sleep duration | 0.943065 |
| civilian employed U.S. | 0.232274 |
| U.S. adults | 0.228296 |
| Hispanic workers | 0.229654 |
| manufacturing industry sector | 0.228734 |
| shift.†Workers | 0.230569 |
| night shift workers | 0.340375 |
| adequate sleep | 0.260758 |
| especially high prevalence | 0.304853 |
|
CLICK HERE |
| 7131 |
Centers for Disease Control and Prevention |
Html |
en |
Notifiable Diseases and Mortality Tables - June 1, 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 |
| 9337 |
Centers for Disease Control and Prevention |
Html |
es |
Factores de riesgo de depresión, diabetes y enfermedades crónicas en mujeres estadounidenses en edad de procrear |
null |
| breve lapso | 0.991871 |
| Bansil P | 0.741714 |
| Dietz PM | 0.762339 |
| Hayes DK | 0.767674 |
|
| futuros embarazos | 0.983652 |
| Bitsko RH | 0.748104 |
| Farr SL | 0.768547 |
| factores riesgo | 0.799511 |
|
CLICK HERE |
| 11860 |
Centers for Disease Control and Prevention |
Html |
en |
Pertussis | Whooping Cough | Pertactin-Negative Strains | CDC |
Pertactin-Negative Pertussis Strains |
| CDC | 0.354022 |
| pre-vaccine era | 0.367319 |
| Page | 0.313842 |
| specific strains | 0.417807 |
| pertactin-negative pertussis strains | 0.666859 |
| pertussis outbreaks | 0.568852 |
| number | 0.31354 |
| flu vaccines | 0.46044 |
| pertussis cases | 0.573363 |
| protein | 0.331759 |
| new strains | 0.39597 |
| effective tool | 0.365546 |
| new strain | 0.370116 |
| pertussis bacteria | 0.687332 |
| pertussis vaccines | 0.982739 |
| conclusions | 0.314569 |
| countries | 0.314374 |
| severe cases | 0.366765 |
| better diagnostics | 0.368012 |
| pertactin deficiency | 0.368629 |
| pertussis strains | 0.688073 |
| scientists | 0.315736 |
| letter | 0.314655 |
| vaccination | 0.313796 |
| pertactin-deficient strains | 0.405215 |
|
| components | 0.370146 |
| study | 0.326287 |
| United States | 0.521757 |
| vaccine protection | 0.365782 |
| airways | 0.337061 |
| current evidence | 0.372139 |
| pertactin-deficient strain | 0.372549 |
| prevalence | 0.315985 |
| paper | 0.314492 |
| situation | 0.31334 |
| pertactin-negative strains | 0.40425 |
| resurgence | 0.315201 |
| disease | 0.328854 |
| Clinical Vaccine Immunology | 0.440011 |
| suggestion | 0.314796 |
| available scientific evidence | 0.427862 |
| increase | 0.329414 |
| Medicine | 0.314666 |
| childhood pertussis vaccines | 0.690393 |
| epidemics | 0.316121 |
| appearance | 0.313249 |
| Antibiotics | 0.315154 |
| lining | 0.334465 |
| New England Journal | 0.437523 |
|
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| 11933 |
Centers for Disease Control and Prevention |
Html |
en |
Keyfinding-Using Diagnostic Intruments | Autism | NCBDDD | CDC |
null |
| parent interview | 0.491463 |
| complex causes | 0.478264 |
| standardized diagnostic tools | 0.577649 |
| different subgroups | 0.487601 |
| children | 0.791611 |
| child psychologists | 0.492768 |
| young children | 0.512615 |
| diverse range | 0.483843 |
| Developmental Disorders. | 0.477809 |
| autism spectrum disorder | 0.586094 |
| treatment decisions | 0.483898 |
| parent report | 0.559663 |
| parent-reported ASD symptoms | 0.821497 |
| largest research study | 0.544521 |
| Autism Diagnostic Observation | 0.573222 |
| associated symptoms | 0.4795 |
| experienced clinicians | 0.495367 |
| SEED method | 0.633443 |
| standardized tools | 0.508883 |
| Levy SE | 0.477882 |
| developmental pediatricians | 0.497402 |
| Early Development | 0.679463 |
| United States | 0.479699 |
| Lee LC | 0.479074 |
|
| research design | 0.479065 |
| best diagnostic tools | 0.550627 |
| gold standard | 0.57593 |
| uniform way | 0.492769 |
| treatment process | 0.478853 |
| ASD | 0.995319 |
| effective ways | 0.485176 |
| well-defined groups | 0.580048 |
| new published analysis | 0.556752 |
| clinical observation | 0.647243 |
| low mental age | 0.549207 |
| research designs | 0.486729 |
| Developmental Disorders | 0.49615 |
| standardized diagnostic instruments | 0.656415 |
| thorough review | 0.590283 |
| CDC’s Study | 0.594698 |
| SEED classification method | 0.575259 |
| ASD classification | 0.761461 |
| Autism Diagnostic Interview-Revised | 0.565988 |
| CDC researchers | 0.655045 |
| new analysis | 0.492662 |
| certain ASD symptoms | 0.778385 |
| Moody EJ | 0.480923 |
| clinic visit | 0.480309 |
|
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Centers for Disease Control and Prevention |
Html |
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State-Specific Prevalence of Current Cigarette Smoking andSmokeless Tobacco Use Among Adults Aged ?18 Years - United States,2011-2013 |
Please note: An erratum has been published for this article. To view the erratum, please click here. |
| tobacco-control programs | 0.377739 |
| smoking decreases | 0.354724 |
| noninstitutionalized U.S. adults | 0.354428 |
| smokeless tobacco use.†| 0.488 |
| varied prevalence | 0.360131 |
| current cigarette smokers | 0.389828 |
| Kimberly Nguyen | 0.35706 |
| State-specific point prevalence | 0.389951 |
| tobacco use prevalence | 0.4263 |
| tobacco users | 0.3866 |
| self-reported smoking | 0.354439 |
| current cigarette smoking | 0.698281 |
| lower prevalence estimates | 0.383864 |
| comprehensive tobacco control | 0.412872 |
| current cigarette smoking* | 0.395032 |
| tobacco industry | 0.390764 |
| tobacco products | 0.563013 |
| mass media campaigns | 0.396757 |
| state-based telephone survey | 0.353488 |
| Behavioral Risk Factor | 0.354255 |
| median state response | 0.397095 |
| overall prevalence | 0.363459 |
| comprehensive smoke-free laws | 0.400418 |
| tobacco advertising | 0.418686 |
| South Carolina | 0.385533 |
|
| states | 0.499062 |
| cigarette smoking | 0.8698 |
| West Virginia | 0.577395 |
| comprehensive state tobacco-control | 0.360127 |
| statistically significant decline | 0.357294 |
| tobacco-related disease | 0.361063 |
| cell phone samples | 0.403434 |
| state response rates | 0.394527 |
| tobacco taxes | 0.384967 |
| tobacco control prevention | 0.41415 |
| overall cigarette smoking | 0.454255 |
| U.S. adults | 0.384076 |
| cigarette smoking prevalence | 0.533048 |
| recent state-based estimates | 0.354272 |
| cigarette smokers | 0.416212 |
| smokeless tobacco products | 0.477606 |
| relative percent change | 0.405406 |
| u.s. states | 0.365746 |
| smokeless tobacco | 0.992707 |
| concurrent cigarette smoking | 0.446111 |
| New Mexico | 0.385579 |
| statistically significant change | 0.353421 |
| cessation assistance | 0.353701 |
| current smokeless tobacco | 0.604331 |
|
CLICK HERE |
| 14302 |
Centers for Disease Control and Prevention |
Html |
en |
National Public Health Week | CDC Features |
April 4-10, 2016 is National Public Health Week. Read more about this year's p |
| new honors | 0.4763 |
| CDC’s fun | 0.511165 |
| unlock level | 0.481096 |
| Random mix | 0.472951 |
| agent | 0.413757 |
| Easy | 0.412613 |
| fictional outbreaks | 0.489591 |
| health skills | 0.487152 |
| points | 0.413184 |
| Trainee | 0.418521 |
| safety | 0.414293 |
| free mobile apps | 0.555485 |
| clue | 0.416583 |
| rank | 0.413542 |
| harmful rays | 0.479701 |
| germs | 0.419134 |
| Epidemic Intelligence Service | 0.554269 |
| tough decisions | 0.483003 |
| lives | 0.413004 |
| word scrambles | 0.481638 |
| Smarter | 0.417468 |
| game show scientists | 0.476629 |
| difficulty | 0.4133 |
| Public Health Nerd | 0.985877 |
|
| cases. | 0.412856 |
| 24/7 | 0.415314 |
| role | 0.413784 |
| Disease Detective | 0.477234 |
| challenging scenarios | 0.476718 |
| National Public Health | 0.682851 |
| trivia questions | 0.476356 |
| higher your score | 0.476981 |
| village | 0.413581 |
| hand | 0.412781 |
| exciting selection | 0.477202 |
| Health Nerd graphics | 0.627425 |
| better your answers | 0.478279 |
| public health workers | 0.583551 |
| Talk | 0.414215 |
| people | 0.414205 |
| badges | 0.412714 |
| lab results | 0.48257 |
| NPHW | 0.429858 |
| minimum SPF | 0.482642 |
| real-life cases | 0.482 |
| Health IQ | 0.530836 |
| public health agency | 0.596014 |
| levels | 0.412631 |
|
CLICK HERE |