| 6462 |
Centers for Disease Control and Prevention |
Html |
en |
Obesity in K-8 Students - New York City, 2006-07 to 2010-11 School Years |
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. |
| school neighborhood poverty | 0.58273 |
| grade children | 0.549821 |
| public health interventions | 0.620418 |
| neighborhood poverty level | 0.561983 |
| Asian/Pacific Islander children | 0.608985 |
| obesity prevention programs | 0.564438 |
| postal code area | 0.562182 |
| public health office | 0.591633 |
| City public school | 0.585763 |
| education public schools | 0.550968 |
| obesity prevalence trends | 0.594882 |
| New York City | 0.96021 |
| public school students | 0.59091 |
| children | 0.67889 |
| school | 0.652973 |
| shows obesity prevalence | 0.599487 |
| school postal code | 0.60941 |
| obesity prevalence | 0.691896 |
| child obesity | 0.548554 |
| poverty level | 0.585933 |
| obesity reduction | 0.549943 |
| body mass index | 0.569503 |
| York City Dept | 0.613604 |
| age groups | 0.577588 |
| pediatric obesity | 0.563653 |
|
| public school children | 0.60315 |
| York City fitness | 0.557308 |
| federal poverty level | 0.567968 |
| K–8 public school | 0.575406 |
| United States | 0.559483 |
| age group | 0.582415 |
| public school data | 0.56175 |
| obese children | 0.553035 |
| school type | 0.548094 |
| group child care | 0.557457 |
| public school | 0.648072 |
| public school population | 0.571083 |
| Asian/Pacific Islander | 0.678625 |
| white children | 0.557586 |
| school postal codes | 0.550181 |
| district public health | 0.549462 |
| Obesity prevalence estimates | 0.58522 |
| largest decrease | 0.553839 |
| school borough | 0.581458 |
| physical education teachers | 0.570859 |
| physical activity | 0.574964 |
| York City Department | 0.60924 |
| childhood obesity | 0.585227 |
| free lunch status | 0.65201 |
|
CLICK HERE |
| 8015 |
Centers for Disease Control and Prevention |
Html |
en |
Why Our Global Work Matters - CDC Global Health |
null |
| Global Work Matters | 0.628451 |
|
|
CLICK HERE |
| 9451 |
Centers for Disease Control and Prevention |
Html |
es |
Mejora del rendimiento del sistema de salud pública por medio de asociaciones multiorganizacionales. |
null |
| Scutchfield FD | 0.359078 |
| múltiples organizaciones | 0.347442 |
| salud pública | 0.933435 |
|
| Mays GP | 0.360711 |
| Estados Unidos | 0.420296 |
| altos costos | 0.347513 |
|
CLICK HERE |
| 10969 |
Centers for Disease Control and Prevention |
Html |
en |
MERS-Laboratory Testing for MERS-CoV |
CDC Coronavirus: Coronaviruses are common throughout the world. They can infect people and animals. Five different coronaviruses can infect people and make them sick. They usually cause mild to moderate upper-respiratory illness. |
| investigational purposes | 0.661456 |
| active infection | 0.726152 |
| circumstances additional specimens | 0.662152 |
| CDC | 0.843775 |
| FDA-cleared/approved tests | 0.560801 |
| additional confirmatory testing | 0.616652 |
| stool specimens | 0.561091 |
| public health investigators | 0.632961 |
| current case definition | 0.644236 |
| MERS-CoV outbreak | 0.560701 |
| MERS symptoms | 0.575269 |
| rRT-PCR assay | 0.715309 |
| travel industry partners | 0.67345 |
| secondary antibody | 0.640045 |
| Serology testing | 0.582449 |
| CDC investigators | 0.604616 |
| serology tests | 0.801317 |
| specific confirmatory test | 0.629213 |
| ELISA results | 0.569197 |
| IFA results | 0.576045 |
| single negative result | 0.653775 |
| active MERS-CoV infection | 0.874032 |
| virus-infected cells | 0.658375 |
| Real-time reverse-transcription polymerase | 0.653533 |
| IFA assay | 0.636395 |
|
| MERS-CoV serology tests | 0.734997 |
| specific antibodies | 0.826761 |
| MERS disease | 0.578686 |
| single positive target | 0.645902 |
| positive rRT-PCR result | 0.664331 |
| ELISA | 0.584465 |
| different laboratory tests | 0.704199 |
| negative rRT-PCR tests | 0.691043 |
| United States | 0.642599 |
| public health scientists | 0.832736 |
| diagnostic purposes | 0.650633 |
| lab tests | 0.578256 |
| immunofluorescence assay | 0.592508 |
| public health | 0.898539 |
| specific genomic targets | 0.64778 |
| microneutralization assay | 0.776213 |
| molecular tests | 0.77192 |
| negative rRT-PCR test | 0.678434 |
| MERS-CoV serology results | 0.707824 |
| MERS-CoV infection | 0.99837 |
| local public health | 0.67812 |
| previous infection | 0.725597 |
| enzyme-linked immunosorbent assay | 0.696018 |
| clinical sample | 0.727559 |
|
CLICK HERE |
| 11710 |
Centers for Disease Control and Prevention |
Html |
en |
Alcohol Involvement in Opioid Pain Reliever andBenzodiazepine Drug Abuse-Related Emergency Department Visits andDrug-Related Deaths - United States, 2010 |
Christopher M. Jones, PharmD1, Leonard J. Paulozzi, MD2, Karin A. |
| DAWN ME data | 0.547161 |
| benzodiazepine deaths | 0.57232 |
| OPR drug | 0.545762 |
| abuse–related ED visits | 0.787552 |
| United States | 0.623523 |
| OPR abuse–related ED | 0.591904 |
| Drug Administration | 0.544138 |
| ED visits | 0.991544 |
| alcohol consumption | 0.603555 |
| benzodiazepine ED visits | 0.655949 |
| national ED visits | 0.621294 |
| benzodiazepine visits | 0.57281 |
| prescription drug abuse | 0.579913 |
| alcohol involvement | 0.702533 |
| prescription drugs | 0.548071 |
| single-drug class deaths | 0.602889 |
| drug abuse-related ED | 0.620951 |
| Excessive alcohol consumption | 0.601837 |
| alcohol overdose | 0.569821 |
| OPR ED visits | 0.633684 |
| benzodiazepine drug-related deaths | 0.61956 |
| benzodiazepine single-drug class | 0.548036 |
| Drug Abuse Warning | 0.552709 |
| alcohol | 0.85075 |
|
| single-drug class ED | 0.590821 |
| alcohol-related visits | 0.561645 |
| illicit drugs | 0.544487 |
| hospital ED visits | 0.622648 |
| benzodiazepines | 0.668043 |
| drugs | 0.610099 |
| OPRs | 0.610711 |
| alcohol increases | 0.584314 |
| Christopher M. Jones | 0.573296 |
| class ED visits | 0.623767 |
| DAWN ED | 0.615133 |
| problematic alcohol | 0.569219 |
| drug related deaths | 0.580656 |
| single drug-class deaths | 0.571183 |
| abuse-related ED visits | 0.656696 |
| alcohol consumption level | 0.584622 |
| pharmaceutical overdose deaths | 0.571044 |
| drug abuse–related ED | 0.687137 |
| OPR deaths | 0.593359 |
| OPR visits | 0.578234 |
| drug-related deaths | 0.783779 |
| ED visit data | 0.579513 |
| benzodiazepine-related deaths | 0.556675 |
|
CLICK HERE |
| 11878 |
Centers for Disease Control and Prevention |
Html |
en |
Influenza Outbreak in a Vaccinated Population - USS Ardent,February 2014 |
Theodore L. Aquino, DO1, Gary T. Brice, PhD2, Sherry Hayes, MPH3, Christopher A. |
| Center San Diego | 0.358092 |
| Preventive Medicine Unit | 0.432131 |
| Ardent crew member | 0.406064 |
| influenza vaccination policy | 0.525361 |
| San Diego County | 0.346564 |
| nasal swab specimens | 0.999545 |
| seasonal influenza vaccination | 0.517233 |
| San Diego | 0.849812 |
| independent duty corpsman | 0.436884 |
| ILI cases | 0.442786 |
| influenza A. Ultimately | 0.563326 |
| ILI case | 0.426458 |
| influenza vaccine | 0.627407 |
| ILI symptoms | 0.758156 |
| outbreak response | 0.361913 |
| Public Health Services | 0.439824 |
| rapid influenza testing | 0.776649 |
| U.S. Navy minesweeper | 0.380544 |
| local naval health | 0.342019 |
| immediate influenza testing | 0.538563 |
| U.S. Navy | 0.485998 |
| Health Research Center | 0.667209 |
| ship outbreak | 0.361256 |
| hemisphere influenza season | 0.518432 |
|
| influenza | 0.781739 |
| Diego Public Health | 0.447259 |
| Naval Health Research | 0.545673 |
| influenza outbreaks | 0.447659 |
| USS Ardent sailor | 0.374397 |
| H3N2 influenza outbreak | 0.644008 |
| shipboard medical provider | 0.339197 |
| Theodore L. Aquino | 0.444398 |
| crew members | 0.985698 |
| USS Ardent | 0.79934 |
| ILI patients | 0.565675 |
| higher-level Navy authorities | 0.351446 |
| initial rapid influenza | 0.561949 |
| influenza season | 0.55381 |
| USS Ardent crew | 0.505646 |
| San Diego Public | 0.447276 |
| ILI patient | 0.504075 |
| rapid influenza tests | 0.533109 |
| outbreak isolate | 0.371021 |
| influenza epidemics | 0.450791 |
| Ardent crew members | 0.51484 |
| Influenza A virus | 0.463483 |
| outbreak information | 0.361849 |
| Base San Diego | 0.340838 |
|
CLICK HERE |
| 12545 |
Centers for Disease Control and Prevention |
Video |
en |
CDC: Theresa's Story, Let's Stop HIV Together |
In this digital story, Theresa discusses learning about her HIV diagnosis and how her diagnosis has changed her life. Her daughter, Crystal, discusses the importance of supporting friends and family who are HIV positive.
Let's Stop HIV Together is a national HIV awareness and anti-stigma campaign produced by the Centers for Disease Control and Prevention (CDC). It features stories of individuals living with HIV and the people who support them. Join the conversation on Facebook at www.facebook.com/ActAgainstAIDS.
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://streaming.cdc.gov/vod.php?id=3fee3ed417ee28e72d10704798ef7c3420131125085910390 |
| CDC | 0.701155 |
| Theresa | 0.718023 |
|
|
CLICK HERE |
| 13527 |
Centers for Disease Control and Prevention |
Html |
en |
Publications, Data, & Statistics | 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. |
| pediatric contact lens | 0.356152 |
| Lam DY | 0.312681 |
| wear contact lens | 0.341539 |
| contact lens users | 0.337717 |
| contact lens risk | 0.337329 |
| Chalmers RL | 0.472701 |
| Cont Lens Anterior | 0.733085 |
| extended-wear contact lens | 0.334071 |
| Kinoshita BT | 0.28361 |
| Stapleton F. Contact | 0.352929 |
| lens materials | 0.306259 |
| Beach MJ | 0.291389 |
| Acanthamoeba keratitis | 0.351261 |
| Lens Anterior Eye. | 0.733067 |
| Study Group | 0.28165 |
| contact lenses | 0.417087 |
| contact lens case | 0.34969 |
| risk factors | 0.342736 |
| F. Contact lens | 0.350097 |
| Stapleton F. | 0.391309 |
| Contact lens wearer | 0.333375 |
| microbial keratitis | 0.312297 |
| contact lens storage | 0.335809 |
| multiple contact lens | 0.331789 |
| contact lens hygiene | 0.310353 |
|
| soft contact lens | 0.381679 |
| contact lens wearers | 0.385076 |
| contact lens postmarket | 0.323913 |
| disposable contact lens | 0.321349 |
| United States | 0.288696 |
| cosmetic contact lenses | 0.296543 |
| Eye Contact Lens. | 0.810076 |
| lens replacement | 0.292958 |
| contact lens wear | 0.510764 |
| safe lens wear | 0.298044 |
| silicone hydrogel | 0.317271 |
| contact lens assessment | 0.347294 |
| silicone hydrogel lenses | 0.298831 |
| corneal infiltrative events | 0.294927 |
| disposable contact lenses | 0.305594 |
| lens storage cases | 0.289235 |
| lens case biofilm | 0.287012 |
| lens storage case | 0.328768 |
| contact lens compliance | 0.354469 |
| contact lens solution | 0.409927 |
| lens case contamination | 0.328777 |
| contact lens cases | 0.340368 |
| contact lens solutions | 0.331318 |
| Optom Vis Sci. | 0.900611 |
|
CLICK HERE |
| 13693 |
Centers for Disease Control and Prevention |
Html |
en |
Seven Things You May Not Know about Women's Health | CDC Features |
Learn about lesser-known women's health diseases and conditions and what to do. |
| opioid abuse | 0.464883 |
| prescription opioid overdose | 0.594535 |
| menstrual period | 0.467319 |
| Basic prevention steps | 0.535211 |
| heavy menstrual bleeding | 0.899159 |
| possible causes | 0.445648 |
| married women ages | 0.611932 |
| health issues | 0.47057 |
| Bacterial vaginosis | 0.436965 |
| additional care | 0.439851 |
| chronic health outcomes | 0.531837 |
| Trafficking Victims Protection | 0.562203 |
| overdose deaths | 0.450581 |
| common vaginal infection | 0.539007 |
| women ages | 0.700508 |
| opioid pain relievers | 0.573546 |
| Pap test | 0.442296 |
| tobacco smoke | 0.436838 |
| American women | 0.511136 |
| reproductive technology | 0.540381 |
| fertility treatments | 0.431858 |
| sexually transmitted diseases | 0.551836 |
| specific needs | 0.44226 |
| certain activities | 0.438272 |
| long term | 0.4257 |
|
| commercial sex act | 0.540565 |
| unprotected sex | 0.455513 |
| women | 0.92629 |
| sexually active women | 0.597783 |
| sex partners | 0.438214 |
| ART treatment | 0.434864 |
| African Americans | 0.453093 |
| asthma triggers | 0.608232 |
| regular health screenings | 0.565305 |
| longer time periods | 0.532679 |
| BV | 0.448495 |
| excessive alcohol | 0.434406 |
| marital status | 0.438417 |
| infertility treatment | 0.448703 |
| sex trafficking | 0.548349 |
| health resources | 0.446396 |
| common cause | 0.435475 |
| asthma action plan | 0.623618 |
| Older adults | 0.450749 |
| public health problem | 0.545777 |
| certain bacteria | 0.425363 |
| general health care | 0.566623 |
| relationship problems | 0.425576 |
| air pollution | 0.443678 |
|
CLICK HERE |
| 15893 |
Centers for Disease Control and Prevention |
Html |
en |
Polypharmacy and Health-Related Quality of Life Among USAdults With Arthritis, Medical Expenditure Panel Survey,2010-2012 |
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. |
| MEPS prescription medications | 0.305266 |
| poverty status | 0.295206 |
| PCS scores | 0.709941 |
| MCS scores | 0.391954 |
| significantly lower PCS | 0.399223 |
| short-form health survey | 0.288139 |
| federal poverty line | 0.306023 |
| physical component summary | 0.289442 |
| prescription drugs | 0.987506 |
| chronic physical conditions | 0.363259 |
| health care providers | 0.327886 |
| mental component summary | 0.285963 |
| health insurance coverage | 0.354339 |
| health-related quality | 0.39783 |
| fewer drug classes | 0.397609 |
| polypharmacy group | 0.326688 |
| 12-item short-form health | 0.287604 |
| HRQoL measures | 0.345485 |
| rheumatoid arthritis | 0.436628 |
| lower PCS scores | 0.559797 |
| prescription drug classes | 0.325721 |
| multiple prescription medications | 0.292173 |
| arthritis | 0.52711 |
| significantly lower MCS | 0.318773 |
| disease-modifying antirheumatic drugs | 0.325409 |
|
| mean PCS scores | 0.284485 |
| polypharmacy | 0.603038 |
| obstructive pulmonary disease | 0.32234 |
| baseline MCS | 0.33919 |
| adults | 0.47967 |
| anti-inflammatory drugs | 0.285682 |
| polypharmacy groups | 0.321119 |
| prescription medications | 0.314467 |
| retrospective cohort study | 0.299653 |
| early rheumatoid arthritis | 0.298498 |
| prescription drug coverage | 0.451957 |
| low PCS scores | 0.31279 |
| Arthritis Care Res | 0.294781 |
| multiple drugs | 0.303931 |
| explanatory variables | 0.329851 |
| geographic area | 0.283938 |
| chronic conditions | 0.375418 |
| mean MCS scores | 0.289133 |
| lower MCS scores | 0.291609 |
| Health Qual Life | 0.284597 |
| average MCS scores | 0.284691 |
| et al | 0.286712 |
| drug classes | 0.896419 |
| older American Indians | 0.309774 |
|
CLICK HERE |