| 5393 |
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CDC Report Finds Gay, Lesbian and Bisexual Students At Greater Risk for Unhealthy, Unsafe Behaviors - Press Release: June 6, 2011 |
CDC Report Finds Gay, Lesbian and Bisexual Students At Greater Risk for Unhealthy, Unsafe Behaviors |
| health education | 0.255435 |
| Evaluation Research Branch | 0.329324 |
| suicidal behaviors | 0.473861 |
| Mortality Weekly Report | 0.353224 |
| sexual orientation | 0.291493 |
| risk behaviors | 0.906664 |
| higher prevalence rates | 0.568887 |
| health risk behaviors | 0.738625 |
| New York City | 0.351046 |
| unintentional injuries | 0.357722 |
| San Diego | 0.235026 |
| Risk Behavior Survey | 0.350083 |
| Disease Control | 0.251983 |
| health risk categories | 0.564815 |
| urban school districts | 0.560968 |
| sexual contact | 0.483664 |
| federal government | 0.239003 |
| Youth Risk Behavior | 0.559166 |
| bisexual students | 0.267499 |
| heterosexual students | 0.299578 |
| sexual identity | 0.568768 |
| opposite sex | 0.385865 |
| better job | 0.25064 |
| weight management | 0.353063 |
| youth experience | 0.256337 |
|
| unhealthy risk behaviors | 0.646902 |
| sexually transmitted diseases | 0.318618 |
| dramatic disparities | 0.24001 |
| unhealthy dietary behaviors | 0.507494 |
| different health risks | 0.401983 |
| higher rates | 0.343555 |
| sexual risk behaviors | 0.675098 |
| large urban school | 0.755455 |
| additional stressors | 0.254507 |
| United States | 0.345613 |
| adolescent health | 0.288281 |
| sexual behaviors | 0.628359 |
| urban school districts—Boston | 0.36143 |
| young people | 0.371206 |
| health services | 0.253717 |
| Selected Sites—Youth Risk | 0.369487 |
| high school students | 0.562771 |
| wide array | 0.233045 |
| San Francisco | 0.234938 |
| sexual contacts | 0.448363 |
| School Health | 0.297858 |
| Howell Wechsler | 0.254874 |
| health risks | 0.581569 |
| lesbian students | 0.354654 |
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| 6670 |
Centers for Disease Control and Prevention |
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Investigation of the Disparity Between New York City and National Prevalence of Nonspecific Psychological Distress Among Hispanics |
In New York City, the age-adjusted prevalence of nonspecific psychological distress (NPD) among Hispanics is twice that of non-Hispanic whites; nationally, there is little Hispanic-white disparity. We aimed to explain the pattern of disparity in New York City. |
| NPD prevalence | 0.386342 |
| mental health | 0.361035 |
| significantly higher NPD | 0.346053 |
| mental health disorders | 0.329583 |
| National Health Interview | 0.351047 |
| York City Hispanics | 0.459554 |
| Puerto Ricans | 0.370368 |
| high NPD odds | 0.332207 |
| CHS | 0.330375 |
| New York City | 0.90228 |
| York City population | 0.329806 |
| NPD gradient | 0.326328 |
| K6 scale | 0.332971 |
| federal poverty threshold | 0.332292 |
| broader United States | 0.327689 |
| mental health interventions | 0.326432 |
| socioeconomic status | 0.325644 |
| York City Department | 0.347559 |
| racial/ethnic groups | 0.338795 |
| risk factors | 0.345203 |
| Central/South Americans | 0.330795 |
| nonspecific psychological distress | 0.365988 |
| elevated NPD risk | 0.33594 |
| Health Interview Survey | 0.351541 |
| adverse mental health | 0.335743 |
|
| higher overall prevalence | 0.33142 |
| York City whites | 0.361302 |
| NPD prevalence estimates | 0.341986 |
| Hispanic ancestry groups | 0.332908 |
| NPD risk factors | 0.332773 |
| different NPD prevalence | 0.343401 |
| higher NPD prevalence | 0.349999 |
| NPD | 0.415345 |
| United States | 0.58143 |
| differences | 0.324791 |
| Elevated NPD prevalence | 0.346926 |
| City non-Hispanic whites | 0.330578 |
| York City Epi | 0.326907 |
| Hispanic-white disparity | 0.350734 |
| non-Hispanic whites | 0.354856 |
| mental health outcomes | 0.338793 |
| Community Health Survey | 0.374704 |
| age-adjusted prevalence | 0.326991 |
| City racial/ethnic group | 0.330003 |
| marital disruption | 0.32675 |
| Katharine H. McVeigh | 0.324682 |
| York City populations | 0.329736 |
| York City adults | 0.331044 |
| higher prevalence | 0.326937 |
|
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| 7526 |
Centers for Disease Control and Prevention |
Html |
en |
Fotonovela Gives Tips to Prevent Type 2 Diabetes | CDC Features |
Read this fotonovela to learn simple steps to prevent or delay type 2 diabetes. |
| United States | 0.293486 |
| ¡Hazlo por ellos | 0.508992 |
| Puerto Ricans | 0.312155 |
| type | 0.202567 |
| CDC-NDEP Deputy Director | 0.44109 |
| print copy | 0.280845 |
| Hispanic adults | 0.316508 |
| South Americans | 0.292594 |
| Hispanic men | 0.315879 |
| age-adjusted rate | 0.286592 |
| email Betsy RodrÃguez | 0.459749 |
| 200-pound person | 0.276056 |
| visit CDC-Info | 0.279388 |
| additional risk factors | 0.439156 |
| healthier foods | 0.298632 |
| Mexican Americans | 0.288266 |
|
| Raquel | 0.21336 |
| National Diabetes Education | 0.99885 |
| U.S. adults | 0.286988 |
| diagnosed diabetes | 0.514947 |
| hard work—and encounters | 0.479094 |
| physical activity | 0.291008 |
| Diabetes Education Program | 0.998637 |
| Hispanic/Latino families | 0.315509 |
| simple steps | 0.317187 |
| Pero por ti | 0.531759 |
| brisk walking | 0.283613 |
| family history | 0.323767 |
| Hispanic Heritage | 0.323452 |
| fotonovela | 0.312331 |
| major study | 0.289739 |
| dry cleaning store | 0.494254 |
|
CLICK HERE |
| 7945 |
Centers for Disease Control and Prevention |
Html |
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Preventing Chronic Disease | Ten Years of Preventing ChronicDisease - CDC |
Ten years are a blink. Ten years are a lifetime. It has been 10 years since the first issue of Preventing Chronic Disease: Public Health Research, Practice, and Policy (PCD). |
| research journals | 0.524144 |
| research findings | 0.517637 |
| social determinants | 0.602877 |
| Creek Rd Atlanta | 0.566744 |
| multiple health topics | 0.668457 |
| inaugural issue | 0.677639 |
| classic life-cycle metaphor | 0.565005 |
| public health surveillance | 0.696837 |
| Border Health ¡SI | 0.655347 |
| Spanish-language articles | 0.513975 |
| breast health | 0.570597 |
| health informatics | 0.566461 |
| new media opportunities | 0.571186 |
| population health | 0.59433 |
| online journal | 0.521807 |
| PCD app | 0.65791 |
| cervical cancer screening | 0.753028 |
| African American Health | 0.658329 |
| Border Health Strategic | 0.655522 |
| Public health researchers | 0.719904 |
| PCD | 0.798869 |
| prevention research | 0.532102 |
| chronic disease prevention | 0.770644 |
| ongoing public health | 0.679289 |
| PCD’s premise | 0.67123 |
|
| Public Health Research | 0.759891 |
| public health policy | 0.712341 |
| racial/ethnic minority populations | 0.578727 |
| journal content | 0.517453 |
| school-based health education | 0.66107 |
| International health | 0.571451 |
| health practitioners | 0.608387 |
| Service health series | 0.658894 |
| health financing | 0.571204 |
| community-based participatory research | 0.6015 |
| public health | 0.935208 |
| Georgia State University | 0.567799 |
| research methods | 0.519997 |
| international journal | 0.524612 |
| public health law | 0.698887 |
| PCD articles | 0.68088 |
| medical education credits | 0.570593 |
| chronic diseases | 0.671072 |
| annual student paper | 0.568176 |
| chronic conditions | 0.553677 |
| multisectorial approaches | 0.50664 |
| qualitative semistructured interviews | 0.5851 |
| Public Health Service | 0.673594 |
| policy makers | 0.507457 |
|
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| 10981 |
Centers for Disease Control and Prevention |
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CDC Global Health - Importance of Communication in OutbreakResponse: Ebola |
null |
| potentially disruptive element | 0.550748 |
| health communication specialist | 0.600258 |
| media questions | 0.50674 |
| CDC | 0.576936 |
| Emergency Communications Network | 0.573352 |
| Global Disease Detection | 0.55837 |
| time Rollin | 0.636231 |
| EIS Officer Leisha | 0.575563 |
| local media outlets | 0.560516 |
| Ebola outbreak | 0.881244 |
| Dr. Rollin | 0.669378 |
| epidemiologists Joel Montgomery | 0.552707 |
| new information | 0.507129 |
| accurate information | 0.50319 |
| proactive U.S. Embassy | 0.577247 |
| epidemiologist James Zingesser | 0.559677 |
| Dr. Pierre Rollin | 0.907496 |
| Epidemic Intelligence Service | 0.558916 |
| World Health Organization | 0.588647 |
| CDC responders | 0.541999 |
| public health emergencies | 0.602409 |
| emergency communications experts | 0.576454 |
| ongoing Ebola outbreak | 0.755933 |
| important role | 0.502839 |
| CDC’s team | 0.574723 |
|
| U.S. Ambassador | 0.504056 |
| Viral Special Pathogens | 0.914649 |
| clear health messages | 0.596288 |
| outbreak cases | 0.606306 |
| Alexander Mark Laskaris | 0.587722 |
| Embassy staff | 0.520213 |
| Guinea | 0.640445 |
| Special Pathogens Branch | 0.907275 |
| early messaging | 0.559014 |
| perfect convergence—an English | 0.566885 |
| EIS Officers Meredith | 0.573785 |
| local media colleagues | 0.579317 |
| public health emergency | 0.60016 |
| CDC team | 0.54658 |
| information technology specialist | 0.575625 |
| CDC staff | 0.548694 |
| local radio stations | 0.578976 |
| effective outbreak response | 0.663926 |
| Rollin’s presentation | 0.642197 |
| Mary Joung Choi | 0.563058 |
| complex information | 0.511063 |
| Guinea’s Ministry | 0.627739 |
| U.S. Embassy | 0.598613 |
| global health outbreaks | 0.61428 |
|
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| 12177 |
Centers for Disease Control and Prevention |
Html |
en |
Incidence of Sickle Cell Trait - United States, 2010 |
Jelili Ojodu, MPH1, Mary M. Hulihan, MPH2, Shammara N. Pope, MPH2, Althea M. |
| red blood cells | 0.484709 |
| Screening 10-Year Incidence | 0.532604 |
| overall incidence | 0.548376 |
| data | 0.547707 |
| SCT | 0.939905 |
| sickle cell trait | 0.493321 |
| newborn screening results | 0.51273 |
| state nbs programs | 0.661269 |
| potential health effects | 0.482084 |
| sickle cell disease | 0.64218 |
| primary care providers | 0.480356 |
| Newborn Screening Report | 0.508479 |
| Mary M. Hulihan | 0.557948 |
| Hispanic newborns | 0.499689 |
| universal newborn screening | 0.507122 |
| care providers | 0.482564 |
| lowest incidence | 0.489523 |
| total U.S. incidence | 0.520111 |
| different races | 0.481929 |
| infants | 0.558342 |
| NBS results | 0.494786 |
| universal sickle cell | 0.493289 |
| positive SCT test | 0.622791 |
| positive SCT screening | 0.641641 |
|
| abnormal УŸ-globin gene | 0.484153 |
| Shammara N. Pope | 0.488371 |
| standardized methods | 0.480604 |
| newborn screening | 0.733047 |
| potential health | 0.522325 |
| positive SCT | 0.842082 |
| newborn screening programs | 0.514024 |
| SCT incidence | 0.616126 |
| United States | 0.527545 |
| positive SCT results | 0.725303 |
| states | 0.632769 |
| family planning | 0.481 |
| state newborn screening | 0.537174 |
| positive SCT result | 0.701432 |
| total number | 0.516052 |
| National Newborn Screening | 0.567119 |
| newborn Hispanic infant | 0.503712 |
| white infants | 0.504623 |
| SCD | 0.490796 |
| Pacific Islander infants | 0.507986 |
| highest incidence | 0.488166 |
| primary care | 0.484684 |
| abnormal hemoglobin | 0.490136 |
| Althea M. Grant | 0.485812 |
|
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| 12421 |
Centers for Disease Control and Prevention |
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Update on the Epidemiology of Middle East RespiratorySyndrome Coronavirus MERS-CoV Infection, and Guidance for thePublic, Clinicians, and Public Health Authorities - January2015 |
Brian Rha, MD1, Jessica Rudd, MPH1, Daniel Feikin, MD1, John Watson, MD1, Aaron T. Curns, MPH1, David L. Swerdlow, MD2, Mark A. |
| nationwide surveillance | 0.556044 |
| CDC | 0.529819 |
| appropriate isolation measures | 0.664418 |
| health care provider | 0.698514 |
| recent travel | 0.700562 |
| David L. Swerdlow | 0.759033 |
| Oman | 0.465782 |
| laboratory-confirmed†cases | 0.600968 |
| Susan I. Gerber | 0.738553 |
| health care providers | 0.970092 |
| residence | 0.460847 |
| National Center | 0.662985 |
| Immunization | 0.45742 |
| World Health Organization | 0.761776 |
| patients | 0.455605 |
| Mark A. Pallansch | 0.744097 |
| countries | 0.510834 |
| public health officials | 0.729005 |
| travel-associated cases | 0.58676 |
| persons | 0.537089 |
| Jessica Rudd | 0.591153 |
| Corresponding author | 0.54925 |
| Saudi Arabia.§ | 0.592529 |
| MERS cases | 0.775045 |
| health care settings | 0.692938 |
|
| Arabian Peninsula | 0.844128 |
| United States | 0.969379 |
| respiratory illness | 0.628982 |
| Viral Diseases | 0.553664 |
| fever | 0.487757 |
| Saudi Arabia | 0.93503 |
| U.S. travelers | 0.55463 |
| John Watson | 0.584236 |
| respiratory symptoms | 0.775515 |
| Aaron T. Curns | 0.739285 |
| Qatar | 0.471763 |
| brief update | 0.567755 |
| health departments | 0.567257 |
| respiratory diseases | 0.808587 |
| Daniel Feikin | 0.588538 |
| public health | 0.741519 |
| Author affiliations | 0.582103 |
| MPH1 | 0.456325 |
| United Arab Emirates | 0.707271 |
| Brian Rha | 0.767282 |
| medical care | 0.557543 |
| MERS-CoV infection | 0.88101 |
| respiratory syndrome coronavirus | 0.851952 |
| MERS-CoV epidemiology | 0.587161 |
|
CLICK HERE |
| 12708 |
Centers for Disease Control and Prevention |
Video |
en |
The Immunization Baby Book |
For parents there's no greater joy than watching your child grow up happy and healthy. That's why most parents choose the safe, proven protection of vaccines. Flipping through this baby book, you can learn what vaccines babies need, when they're needed, and why it's so important to follow CDC's recommended immunization schedule. Immunization gives you the power to protect your baby from 14 serious childhood diseases by age 2. For more information about vaccines, visit http://www.cdc.gov/vaccines/parents.
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/cdctv/Babybook/ |
| Immunization Baby Book | 0.969546 |
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CLICK HERE |
| 13717 |
Centers for Disease Control and Prevention |
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Comparing the Maryland Comprehensive Cancer Control Plan With Federal Cancer Prevention and Control Recommendations |
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. |
| up-to-date evidence-based recommendations | 0.49433 |
| MCCCP’s goals | 0.620822 |
| cancer detection screening | 0.477639 |
| USPSTF | 0.906937 |
| CDC evidence-based recommendations | 0.525765 |
| American Cancer Society | 0.582051 |
| pregnant women | 0.48569 |
| National Comprehensive Cancer | 0.524105 |
| prevention-related recommendations | 0.478646 |
| evidence-based recommendations | 0.796817 |
| MCCCP recommendations | 0.565398 |
| Hopkins Bloomberg School | 0.515091 |
| cancer-related evidence-based recommendations | 0.540441 |
| cancer-related USPSTF recommendations | 0.698717 |
| MCCCP’s publication | 0.475901 |
| state cancer plans | 0.68344 |
| Cancer Control Program | 0.482385 |
| cancer control plans | 0.593579 |
| federal cancer-related recommendations | 0.571219 |
| screening recommendations | 0.481632 |
| additional national recommendations | 0.491678 |
| state cancer plan | 0.53159 |
| USPSTF recommendations | 0.714525 |
| federal evidence-based recommendations | 0.665124 |
| cancer prevention | 0.822014 |
|
| Johns Hopkins Bloomberg | 0.508324 |
| MCCCP | 0.848 |
| secondary cancer prevention | 0.50802 |
| Cancer Control Plan | 0.619528 |
| cancer-related federal recommendations | 0.569447 |
| comprehensive cancer control | 0.936415 |
| alcohol misuse | 0.474295 |
| federal recommendations | 0.94931 |
| ACIP’s recommendations | 0.512811 |
| National Cancer Institute | 0.548384 |
| national cancer plan | 0.479692 |
| CDC recommendations | 0.477288 |
| current cancer-related USPSTF | 0.564727 |
| national recommendations | 0.493639 |
| cancer prevention recommendations | 0.565066 |
| Maryland Comprehensive Cancer | 0.611818 |
| strategies | 0.514123 |
| cancer control planning | 0.470654 |
| CDC guidelines | 0.501578 |
| Comprehensive Cancer Center | 0.473678 |
| Kimmel Comprehensive Cancer | 0.473029 |
| ACIP recommendations | 0.559816 |
| partial correspondence | 0.630597 |
| USPSTF Grade | 0.903032 |
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| 16112 |
Centers for Disease Control and Prevention |
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Help Prevent Type 2 Diabetes | NDPP | Diabetes |
National Diabetes Prevention Program |
| increased physical activity | 0.457472 |
| Page | 0.330114 |
| type | 0.361752 |
| Engl J Med | 0.39106 |
| diabetes prevention lifestyle | 0.689291 |
| body weight | 0.388085 |
| National Diabetes Prevention | 0.61079 |
| fact sheet | 0.380923 |
| online CDC-recognized lifestyle | 0.544962 |
| CDC-recognized lifestyle change | 0.806692 |
| certain standards | 0.386724 |
| Sepah SC | 0.379966 |
| program progress | 0.408345 |
| Diabetes Educator | 0.482128 |
| meaningful engagement | 0.389586 |
| portion sizes | 0.381883 |
| average weight loss | 0.461484 |
| impact | 0.326057 |
| weight loss | 0.519509 |
| lifestyle change program | 0.789123 |
| lifestyle coaches | 0.459578 |
| similar range | 0.38407 |
| high risk | 0.387845 |
| group support | 0.386318 |
| Unlimited Support | 0.380592 |
|
| national effort | 0.401155 |
| employees | 0.329404 |
| et al. | 0.377466 |
| DPP—a nationwide effort | 0.480212 |
| Diabetes Prevention Study | 0.549179 |
| Program Details | 0.402568 |
| lifestyle change programs | 0.818865 |
| lifestyle change intervention | 0.576297 |
| United States | 0.397357 |
| approved curriculum | 0.386274 |
| impaired glucose tolerance | 0.447479 |
| diabetes mellitus | 0.478434 |
| National DPP | 0.412492 |
| CDC standards | 0.394835 |
| high-quality experience | 0.389382 |
| weight loss programs | 0.473331 |
| online lifestyle change | 0.534599 |
| year-long program | 0.419476 |
| online social network | 0.450637 |
| participants | 0.364445 |
| prediabetes | 0.32855 |
| lifestyle change | 0.943132 |
| Diabetes Prevention Program | 0.831141 |
| visit Lifestyle Change | 0.530688 |
|
CLICK HERE |