| 1079 |
Centers for Disease Control and Prevention |
Html |
en |
Foreword - April 18, 2014 | MMWR |
Thomas R. Frieden, MD, MPH. |
| performance management component | 0.356479 |
| program implementation | 0.607077 |
| Communication. Effective communication | 0.388471 |
| motor vehicle–related death | 0.346587 |
| public health interventions | 0.447822 |
| Inequalities Report—United States | 0.3968 |
| original MMWR paper | 0.354844 |
| U.S. Government Printing | 0.342491 |
| health program implementation | 0.569401 |
| Rigorous real-time monitoring | 0.35609 |
| effective program implementation | 0.433425 |
| cdc health disparities | 0.800144 |
| American Indian tribes | 0.346897 |
| decrease alcohol-impaired driving | 0.353081 |
| MMWR HTML versions | 0.35624 |
| health issues | 0.348419 |
| technical package | 0.369443 |
| diphtheria-tetanus-pertussis/diphtheria-tetanus-acellular pertussis vaccine | 0.343766 |
| successful public health | 0.431298 |
| effective communication strategies | 0.388725 |
| CDC. CDC health | 0.556111 |
| key public health | 0.438313 |
| continuous program improvement | 0.383531 |
| Winnable Battles initiative | 0.346614 |
|
| public health | 0.970667 |
| public health program | 0.587172 |
| health disparity reports | 0.446117 |
| American Indians/Alaska Natives | 0.494419 |
| non-Hispanic American Indian/Alaska | 0.400519 |
| public health programs | 0.57174 |
| randomized clinical trial | 0.352147 |
| childhood vaccination rates | 0.353681 |
| large-scale health effects | 0.398536 |
| health determinants | 0.365382 |
| Effective communication—through billboards | 0.371521 |
| legally mandated program | 0.384344 |
| political commitment | 0.455022 |
| non-Hispanic Asian children | 0.398435 |
| human immunodeficiency virus | 0.350497 |
| effective public health | 0.704251 |
| Ongoing political commitment | 0.350341 |
| non-Hispanic white children | 0.3983 |
| successful program implementation | 0.400823 |
| performance management | 0.367128 |
| evidence-based technical package | 0.354846 |
| long-term behavior change | 0.351862 |
| public health action | 0.56836 |
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| 5416 |
Centers for Disease Control and Prevention |
Html |
en |
Using small-area estimation method to calculate county-level prevalence of obesity in Mississippi, 2007-2009. |
null |
| county obesity rates | 0.554959 |
| adult obesity prevalence | 0.628246 |
| obesity rates | 0.630334 |
| state-level obesity rate | 0.547968 |
| obesity control programs | 0.563209 |
| Risk Factor Surveillance | 0.491375 |
| fixed-effect parameter estimates | 0.499932 |
| state-level model estimates | 0.500368 |
| design-based direct estimates | 0.497369 |
| public health problems | 0.500648 |
| obesity map | 0.529855 |
| county-level estimates | 0.569973 |
| highest obesity rates | 0.564445 |
| direct estimates | 0.592612 |
| BRFSS data | 0.515668 |
| small-area estimates | 0.49401 |
| education level | 0.491039 |
| obesity prevalence | 0.921383 |
| estimates | 0.603126 |
| obesity prevention policies | 0.564234 |
| Mississippi counties | 0.523634 |
| respective direct estimates | 0.495827 |
| county-level obesity prevalence | 0.735228 |
| obesity estimates | 0.576501 |
|
| Mississippi | 0.564774 |
| Mississippi BRFSS data | 0.509211 |
| Mississippi State Department | 0.558524 |
| lower obesity rates | 0.546149 |
| higher obesity rates | 0.553229 |
| model-generated parameter estimates | 0.496378 |
| Behavioral Risk Factor | 0.492709 |
| county-level prevalence | 0.506324 |
| state obesity prevalence | 0.600585 |
| reliable county-level estimates | 0.526598 |
| Introduction
Obesity | 0.553804 |
| model estimates | 0.519951 |
| small-area county-level estimates | 0.519717 |
| random-effect parameter estimates | 0.533966 |
| county prevalence | 0.500516 |
| reliable prevalence estimates | 0.54662 |
| child obesity crisis | 0.539917 |
| obesity status | 0.527945 |
| obesity epidemic | 0.618814 |
| obesity prevention campaigns | 0.542819 |
| employment status | 0.498534 |
| small-area estimation | 0.57477 |
| small-area estimation method | 0.553213 |
| linear mixed model | 0.523482 |
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| 5755 |
Centers for Disease Control and Prevention |
Html |
en |
Hexachloronaphthalene - 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 |
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| 6586 |
Centers for Disease Control and Prevention |
Html |
en |
Surveillance of Demographic Characteristics and Health Behaviors Among Adult Cancer Survivors - Behavioral Risk Factor Surveillance System, United States, 2009 |
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. |
| cancer treatment | 0.324966 |
| commonly reported cancer | 0.283169 |
| prostate cancer survivors | 0.316876 |
| insurance coverage | 0.343664 |
| optional cancer survivorship | 0.297705 |
| cancer survivor population | 0.271531 |
| male cancer survivors | 0.381822 |
| cancer prevalence | 0.279713 |
| obese cancer survivors | 0.319382 |
| colorectal cancer screening | 0.277622 |
| health behaviors | 0.307778 |
| BRFSS | 0.273723 |
| health insurance coverage | 0.294316 |
| colorectal cancer | 0.293007 |
| cancer diagnosis | 0.350504 |
| cancer types | 0.277547 |
| cancer survivorship questions | 0.276405 |
| breast cancer survivors | 0.32624 |
| cervical cancer | 0.287575 |
| cancer diagnoses | 0.271319 |
| regular physical activity | 0.275203 |
| cancer survivors | 0.911796 |
| cancer survivorship module | 0.308177 |
| female cancer survivors | 0.406858 |
| cancer treatments | 0.274972 |
|
| cancer screening | 0.301037 |
| United States | 0.306201 |
| cancer registry data | 0.276727 |
| supplemental cancer survivorship | 0.271783 |
| primary cancer types | 0.270886 |
| comprehensive cancer control | 0.292981 |
| previous cancer diagnosis | 0.28593 |
| U.S. Virgin Islands | 0.30827 |
| National Cancer Institute | 0.279725 |
| health care | 0.295588 |
| public health | 0.269885 |
| white cancer survivors | 0.316086 |
| cancer survivor health | 0.279928 |
| previous cancer | 0.286414 |
| preventive health care | 0.28307 |
| counsel cancer survivors | 0.312889 |
| health | 0.334825 |
| common primary cancer | 0.270967 |
| New Jersey | 0.300206 |
| prostate cancer screening | 0.292314 |
| physical activity | 0.39351 |
| leisure-time physical activity | 0.314833 |
| nonmelanoma skin cancer | 0.323878 |
| cancer treatment history | 0.292788 |
|
CLICK HERE |
| 6977 |
Centers for Disease Control and Prevention |
Html |
en |
Global Health - Ghana |
The Centers for Disease Control and Prevention (CDC) has collaborated with the Ghana Health Service (GHS), Ghana AIDS Commission (GAC), and other agencies since 2009 through the US President’s Emergency Program for AIDS Relief (PEPFAR) to support HIV/AIDS prevention, care, and treatment. |
| HIV/AIDS prevention | 0.607881 |
| CDC | 0.640755 |
| endorsement | 0.261675 |
| flu surveillance | 0.611013 |
| Laboratory Training Program | 0.851738 |
| U.S. President | 0.544155 |
| PMI | 0.25555 |
|
| Ghana Field Epidemiology | 0.992439 |
| Content source | 0.496296 |
| HHS | 0.27547 |
| non-federal site | 0.615813 |
| Notice | 0.208935 |
| Malaria Initiative | 0.621667 |
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| 7181 |
Centers for Disease Control and Prevention |
Html |
en |
Pandemic Flu Preparedness Tools |
Resources to help hospital administrators and state and local health officials prepare for the next influenza pandemic - CDC |
| template | 0.228253 |
| practice | 0.228588 |
| laboratory directors | 0.354853 |
| infectious diseases | 0.370536 |
| CommunityFlu | 0.231566 |
| students | 0.229521 |
| potential number | 0.349825 |
| navigation Skip | 0.481819 |
| response plans | 0.353023 |
| basic instructions | 0.347505 |
| KB | 0.23588 |
| specimen | 0.23167 |
| spreadsheet-based program | 0.405054 |
| state | 0.261287 |
| Spreadsheet-based model | 0.411492 |
| estimates | 0.275547 |
| hospital administrators | 0.543382 |
|
| list Skip | 0.483761 |
| draft report | 0.351729 |
| influenza pandemic | 0.784918 |
| surge | 0.283403 |
| page options Skip | 0.63574 |
| local health officials | 0.558788 |
| public health officials | 0.971112 |
| community | 0.229332 |
| demand | 0.306491 |
| local public health | 0.481206 |
| software programs FluAid | 0.468287 |
| FluLabSurge | 0.229469 |
| policy makers | 0.369269 |
| Resources | 0.232072 |
| hospital-based services | 0.373868 |
| flu pandemic | 0.662941 |
|
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| 7909 |
Centers for Disease Control and Prevention |
Html |
en |
African Countries Gain Ground in Fight Against Influenza |
New data on the burden and epidemiology of seasonal flu in Africa - CDC |
| recent large-scale improvements | 0.543119 |
| Influenza Lead | 0.663315 |
| pathogenic avian influenza | 0.685389 |
| influenza-related epidemiologic | 0.480219 |
| new preparedness plans | 0.560722 |
| response systems | 0.478389 |
| influenza vaccine | 0.655008 |
| World Health Organization | 0.675183 |
| laboratory networks | 0.487224 |
| International Epidemiology | 0.509121 |
| seasonal flu | 0.501493 |
| control policies | 0.478142 |
| Influenza Division | 0.820626 |
| new data | 0.495416 |
| influenza surveillance | 0.840728 |
| African Network | 0.53931 |
| H1N1 pandemic | 0.503276 |
| influenza surveillance methods | 0.728088 |
| Institut Pasteur | 0.568764 |
| Epidemic-Prone Diseases | 0.479573 |
| pandemic preparedness | 0.483217 |
| in-country resources | 0.479922 |
| influenza | 0.918542 |
| Influenza Division International | 0.694916 |
|
| CDC’s Haiti | 0.522956 |
| Dr. Marc-Alain Widdowson | 0.557813 |
| sheds light | 0.48703 |
| CDC office | 0.522593 |
| flu vaccine | 0.498981 |
| important policy decisions | 0.540038 |
| epidemiology | 0.513256 |
| Team Lead | 0.478036 |
| CDC’s Influenza | 0.747892 |
| African countries | 0.711912 |
| Medical Epidemiologist | 0.485897 |
| solid data | 0.48397 |
| surveillance systems | 0.508207 |
| pandemic influenza prevention | 0.734017 |
| influenza data | 0.640911 |
| impacted populations | 0.479751 |
| various cooperative agreements | 0.530745 |
| regional level | 0.478054 |
| flu viruses | 0.489893 |
| grantee countries | 0.485705 |
| vaccine policy | 0.482675 |
| Infectious Diseases supplement | 0.581111 |
| epidemiologic support | 0.482414 |
| Dr. Mark Katz | 0.558679 |
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| 8128 |
Centers for Disease Control and Prevention |
Html |
en |
CDC - Sodium Reduction Resources for Everyone -DHDSP |
null |
| list Skip | 0.625394 |
| sodium intake | 0.94477 |
| health e-card | 0.378843 |
| page options Skip | 0.884253 |
| resources | 0.213579 |
| steps | 0.253112 |
|
| navigation Skip | 0.630528 |
| excess sodium | 0.951254 |
| diet | 0.207591 |
| sodium reduction tools | 0.889688 |
| health effects | 0.560248 |
| public health | 0.347697 |
|
CLICK HERE |
| 9222 |
Centers for Disease Control and Prevention |
Html |
en |
Preventing Chronic Disease | Adult Caregivers in the United States: Characteristics and Differences in Well-being, by Caregiver Age and Caregiving Status - CDC |
We examined the characteristics of adults providing regular care or assistance to friends or family members who have health problems, long-term illnesses, or disabilities (ie, caregivers). |
| frequent physical distress | 0.688733 |
| long-term illnesses | 0.434779 |
| Ronda C. Talley | 0.428348 |
| health problem | 0.466555 |
| mental health | 0.462572 |
| Risk Factor Surveillance | 0.681883 |
| higher prevalence | 0.446295 |
| complex sample design | 0.437877 |
| family member | 0.546899 |
| caregiving status | 0.457754 |
| high school education | 0.434841 |
| mental distress | 0.694707 |
| Disease Control | 0.506362 |
| BRFSS | 0.454816 |
| median cooperation rate | 0.430334 |
| health-related quality | 0.515006 |
| family members | 0.513911 |
| R. Family caregiving | 0.495208 |
| following question | 0.427855 |
| respondents | 0.473843 |
| poor self-rated health | 0.46556 |
| health problems | 0.472416 |
| state-based telephone survey | 0.447828 |
| Survey Research Organizations | 0.441757 |
| caregiving question | 0.448739 |
|
| state-based population estimates | 0.433872 |
| Behavioral Risk Factor | 0.685349 |
| younger caregivers | 0.79002 |
| public health issue | 0.49922 |
| SPSS software version | 0.436226 |
| regular care | 0.593039 |
| Andresen E. Caregiving | 0.483986 |
| caregivers | 0.927865 |
| daily activities | 0.432187 |
| Population Health | 0.437116 |
| public health | 0.65283 |
| 50 states | 0.441025 |
| Native adult caregivers | 0.5835 |
| emotional support | 0.437289 |
| CI | 0.484279 |
| older caregivers | 0.707268 |
| health | 0.664985 |
| lower mental distress | 0.493615 |
| frequent mental distress | 0.687127 |
| adult caregivers | 0.625693 |
| Western Kentucky University | 0.423663 |
| Public Health Service | 0.461303 |
| long-term illness | 0.430772 |
| percent confidence intervals | 0.430974 |
|
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| 11648 |
Centers for Disease Control and Prevention |
Html |
en |
Preventing Chronic Disease | Using a Participatory Research Approach in a School-Based Physical Activity Intervention to Prevent Diabetes in the Hualapai Indian Community, Arizona, 2002"2006 - CDC |
In the United States, type 2 diabetes has reached epidemic proportions among indigenous people. Community-based participatory research offers American Indian communities and university partners an opportunity to integrate skills in community action and systematic inquiry to develop locally acceptable primary prevention interventions to combat diabetes risk factors. The Hualapai Tribe and the University of Arizona designed, implemented, and assessed a school-based physical activity intervention to reduce diabetes risk factors among youth. |
| fitness measures | 0.523431 |
| organized physical activity | 0.423825 |
| outcome measures | 0.416079 |
| youth | 0.555449 |
| female participants | 0.443992 |
| Hualapai Tribal members | 0.43638 |
| research team | 0.478496 |
| Lite blood glucose | 0.418858 |
| blood glucose meter | 0.462517 |
| local physical activity | 0.434698 |
| Hualapai Tribal Diabetes | 0.42539 |
| DM risk factors | 0.576856 |
| physical activity classes | 0.546879 |
| Hualapai Health Department | 0.440594 |
| risk factors | 0.633168 |
| body mass index | 0.48879 |
| Hualapai Tribal census | 0.422872 |
| elementary school | 0.430647 |
| American Indian youth | 0.43405 |
| twice-per-week physical activity | 0.422408 |
| American Indian communities | 0.535672 |
| blood glucose level | 0.664622 |
| physical activity intervention | 0.461232 |
| physical activity sessions | 0.418486 |
| blood glucose | 0.781912 |
|
| community members | 0.443468 |
| blood samples | 0.419686 |
| blood glucose levels | 0.494909 |
| physical fitness measures | 0.472561 |
| high fasting blood | 0.423818 |
| lay physical activity | 0.476562 |
| physical activity program | 0.511659 |
| community-based participatory research | 0.500573 |
| public health | 0.475449 |
| Hualapai Tribe | 0.433009 |
| School Health Index | 0.422613 |
| Hualapai Tribal | 0.522899 |
| Tribal Health Department | 0.521169 |
| physical activity leaders | 0.436333 |
| fasting blood glucose | 0.550947 |
| Hualapai Tribal Council | 0.519954 |
| Indian Health Service | 0.448995 |
| physical activity leader | 0.423094 |
| physical activity | 0.914476 |
| school-based physical activity | 0.483382 |
| data collection sessions | 0.424886 |
| Youth Wellness Program | 0.549073 |
| diabetes risk factors | 0.534199 |
| tribe–university research team | 0.440614 |
|
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