| 640 |
Centers for Disease Control and Prevention |
Html |
en |
Smoke-Free Policies Improve Health - Smoking & Tobacco Use |
Secondhand Smoke Fact Sheets. |
| smokefree laws | 0.885425 |
| Comprehensive Smoke-Free Legislation | 0.395549 |
| Smoking Ban | 0.414755 |
| A. Hospital Admissions | 0.361925 |
| Human Services | 0.344758 |
| Comprehensive Smoke-Free Laws | 0.415013 |
| U.S. Department | 0.342432 |
| health outcomes | 0.378098 |
| Health Promotion | 0.343437 |
| workplaces | 0.340016 |
| Irish Smoking Ban | 0.375404 |
| Comprehensive Smoking Bans | 0.401131 |
| medicare beneficiaries | 0.340113 |
| rating scale | 0.350593 |
| local smokefree laws | 0.515966 |
| Pell JP | 0.394321 |
| Legislative Smoking Bans | 0.37649 |
| medicare enrollees | 0.345666 |
| county smokefree laws | 0.516653 |
| smokefree legislation | 0.507828 |
| Comprehensive Statewide Smoking | 0.39442 |
| American Journal | 0.510291 |
| monthly hospital admissions | 0.381875 |
| highest level | 0.343147 |
| nonsmoking bar workers | 0.694997 |
|
| indoor areas | 0.672484 |
| International Agency | 0.42055 |
| Secondhand Smoke Exposure | 0.415759 |
| heart attacks | 0.421278 |
| Public Health | 0.413834 |
| Comprehensive Smoking Ban | 0.396912 |
| respiratory health | 0.487293 |
| respiratory symptoms | 0.439393 |
| acute coronary syndrome | 0.478661 |
| hospital admissions | 0.983719 |
| public places | 0.349722 |
| population Substantial health | 0.362353 |
| heart disease morbidity | 0.36522 |
| New York | 0.340463 |
| acute coronary events | 0.709172 |
| throat irritations | 0.341545 |
| heart attack admissions | 0.364769 |
| health | 0.500998 |
| national smokefree law | 0.97677 |
| smoke-free legislation | 0.58956 |
| comprehensive smokefree laws | 0.669386 |
| state smokefree law | 0.713321 |
| New England Journal | 0.414647 |
| acute myocardial infarction | 0.726204 |
|
CLICK HERE |
| 4575 |
Centers for Disease Control and Prevention |
Html |
en |
November 09, 2009: States Where Persons Infected with the Outbreak Strain of E. coli O157:H7 Live, United States, by State | E. coli CDC |
Get the latest CDC information on the recent infections from ground beef, and find out what you can do to protect yourself and your family. |
| O157 | 0.415243 |
| cluster | 0.350488 |
| CDC | 0.326019 |
| United States | 0.616271 |
| Maine | 0.319414 |
| ongoing case finding | 0.491683 |
| advanced secondary DNA | 0.486648 |
| strains | 0.32509 |
| human isolates | 0.413858 |
| number | 0.33564 |
| Massachusetts | 0.319504 |
| ill persons | 0.406793 |
| Beef | 0.322224 |
| E. coli | 0.92108 |
| outbreak strain | 0.748083 |
|
| secondary tests | 0.402763 |
| H7 Live | 0.545352 |
| Outbreak Investigations | 0.483445 |
| genetic associations | 0.404089 |
| New York | 0.401489 |
| California | 0.319614 |
| New Jersey | 0.401805 |
| Fairbank Farms | 0.435125 |
| persons | 0.442845 |
| New Hampshire | 0.402122 |
| Connecticut | 0.319554 |
| H7 Infections Associated | 0.632985 |
| Maryland | 0.319464 |
| Multistate Outbreak | 0.493577 |
| laboratory testing | 0.40601 |
|
CLICK HERE |
| 4684 |
Centers for Disease Control and Prevention |
Html |
en |
Residence in a distressed county in Appalachia as a risk factor for diabetes, Behavioral Risk Factor Surveillance System, 2006-2007 |
null |
| nondistressed Appalachian counties | 0.460635 |
| high rates | 0.437471 |
| tool kit | 0.378416 |
| Risk Factor Surveillance | 0.419109 |
| self-reported diabetes | 0.465323 |
| competitive counties | 0.367941 |
| Appalachian county | 0.444877 |
| Disease Control | 0.375172 |
| undiagnosed diabetes | 0.401619 |
| Self-reported diabetes status | 0.456866 |
| obesity | 0.403083 |
| risk factors | 0.47803 |
| diabetes risks | 0.401605 |
| Appalachian people | 0.3854 |
| distressed Appalachian counties | 0.775934 |
| Appalachian participants | 0.378571 |
| physical activity level | 0.382507 |
| residents | 0.433393 |
| Behavioral Risk Factor | 0.417557 |
| United States | 0.389138 |
| distressed counties | 0.760114 |
| culturally sensitive programs | 0.405877 |
| Appalachian Mountains | 0.394957 |
| cigarette smoking | 0.380781 |
| diabetes cases | 0.403018 |
|
| unadjusted prevalence | 0.384107 |
| diabetes prevalence | 0.44123 |
| Family Matter program | 0.387032 |
| isolated counties | 0.370969 |
| 3-year unemployment rate | 0.412172 |
| rural Appalachian society | 0.401109 |
| self-reported diagnosed diabetes | 0.504628 |
| health care | 0.408596 |
| higher risk | 0.407971 |
| New York | 0.367512 |
| classifies Appalachian counties | 0.451965 |
| national median prevalence | 0.370917 |
| Appalachian Regional Commission | 0.414375 |
| Appalachian traditions | 0.377703 |
| Appalachian Diabetes Control | 0.501321 |
| Appalachian population | 0.379878 |
| physical activity | 0.675532 |
| leisure-time physical activity | 0.375243 |
| non-Appalachian counties | 0.546401 |
| attainment counties | 0.382323 |
| diabetes | 0.78391 |
| diabetes educator | 0.401513 |
| Diabetes Translation | 0.403338 |
| physical inactivity | 0.382868 |
|
CLICK HERE |
| 6945 |
Centers for Disease Control and Prevention |
Html |
en |
CDC - Preventing Chronic Disease: Volume 9, 2012:11_0331 |
HIV infection, a communicable disease, and noncommunicable diseases (NCDs) are among the major health concerns worldwide. An estimated 33 million people live with HIV, two-thirds of them in sub-Saharan Africa, where three-fourths of all AIDS-related deaths occur. |
| NCDs | 0.495412 |
| major risk factor | 0.394423 |
| major risk factors | 0.393478 |
| sexually transmitted infection | 0.420044 |
| HIV programs | 0.538434 |
| noncommunicable diseases | 0.367489 |
| Integrated health systems | 0.428279 |
| integrated programs | 0.413055 |
| major health concerns | 0.42705 |
| chronic infectious diseases | 0.415028 |
| limited human resources | 0.382783 |
| positive health behaviors | 0.414324 |
| insufficient physical activity | 0.392306 |
| health management | 0.384652 |
| integrated approaches | 0.400883 |
| middle-income countries | 0.794991 |
| health systems | 0.501247 |
| World Health Organization | 0.41936 |
| similar vertical programs | 0.417996 |
| HIV infection increase | 0.523869 |
| Unsafe sexual behavior | 0.391529 |
| disease management programs | 0.42776 |
| chronic disease | 0.435867 |
| vertical approaches | 0.367818 |
| high-profile vertical program | 0.392749 |
|
| health workers | 0.372131 |
| weak health systems | 0.45966 |
| health care programs | 0.426298 |
| health needs | 0.394687 |
| different clinical interrelationships | 0.393945 |
| public health concern | 0.416166 |
| vertical programs | 0.431914 |
| HIV-family planning integration | 0.38511 |
| health care | 0.442146 |
| Different chronic diseases | 0.420271 |
| health care systems | 0.413409 |
| integrated HIV–NCD management | 0.413406 |
| dynamic health systems | 0.412829 |
| chronic diseases | 0.469425 |
| Different health | 0.368103 |
| health | 0.566009 |
| people | 0.390894 |
| management | 0.454722 |
| Public Health Service | 0.402573 |
| major chronic diseases | 0.419869 |
| antiretroviral treatments | 0.39413 |
| HIV infection | 0.973626 |
| chronic care programs | 0.424326 |
| NCD burden | 0.373723 |
|
CLICK HERE |
| 7263 |
Centers for Disease Control and Prevention |
Html |
en |
Lexicon, Definitions, and Conceptual Framework for PublicHealth Surveillance |
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. |
| data | 0.401547 |
| public health interventions | 0.278487 |
| specific health events | 0.272801 |
| Risk Factor Surveillance | 0.278074 |
| health information | 0.328757 |
| health surveillance activities | 0.351545 |
| health policy information | 0.261439 |
| public health decision | 0.272588 |
| sentinel surveillance systems | 0.282359 |
| public health inquiry | 0.272945 |
| public health surveillance | 0.994115 |
| surveillance program | 0.271442 |
| disease surveillance | 0.288227 |
| health events | 0.275718 |
| public health decisions | 0.265998 |
| data sources | 0.282958 |
| surveillance data | 0.313745 |
| population health assessment | 0.299727 |
| traditional public health | 0.271075 |
| public health practice | 0.324145 |
| Surveillance Consultation | 0.283541 |
| health surveillance systems | 0.359259 |
| effective public health | 0.268408 |
| chronic disease surveillance | 0.288111 |
| health surveillance concepts | 0.317292 |
|
| public health threat | 0.274805 |
| valuable surveillance data | 0.295355 |
| public heath surveillance | 0.301138 |
| public health community | 0.292284 |
| specific public health | 0.268793 |
| 21st century | 0.265716 |
| surveillance systems | 0.38019 |
| complex health events | 0.263812 |
| public health knowledge | 0.275288 |
| public health program | 0.296523 |
| surveillance purposes | 0.272498 |
| health information needs | 0.269297 |
| public health concerns | 0.27261 |
| health data | 0.286029 |
| Notifiable Diseases Surveillance | 0.28594 |
| appropriate health information | 0.265551 |
| public health programs | 0.342195 |
| national surveillance systems | 0.282333 |
| sentinel surveillance | 0.283393 |
| electronic health records | 0.266348 |
| data collection | 0.390501 |
| Electronic Disease Surveillance | 0.2857 |
| public health problem | 0.290543 |
| data collection activities | 0.262182 |
|
CLICK HERE |
| 7834 |
Centers for Disease Control and Prevention |
Html |
en |
CDCynergy Lite - Interventions |
Gateway to Health Communication and Social Marketing Practice - CDCynergy Lite, interventions |
| local service providers | 0.8658 |
| common goals | 0.726347 |
| marketing—like commercial marketing—is | 0.845818 |
| ultimate behavioral objective | 0.85192 |
| walking clubs | 0.74995 |
| Product interventions | 0.846233 |
| certain costs | 0.76025 |
| behavior change | 0.983454 |
| drug-free activities | 0.764329 |
| indirect costs | 0.755961 |
| organizational rulings | 0.731864 |
| time frame | 0.736794 |
| line items | 0.72922 |
| program priorities | 0.726909 |
| city funding | 0.728888 |
| target segment | 0.73716 |
| program plan | 0.730891 |
| Gantt chart | 0.731403 |
| male sex partners | 0.848229 |
| barber shops | 0.730835 |
| training classes | 0.75732 |
| Include key deadlines | 0.848059 |
| nicotine replacement device | 0.837837 |
| Policy interventions | 0.844447 |
| primary sections | 0.725076 |
|
| separate funding streams | 0.818197 |
| similar items | 0.728914 |
| strongest planning team | 0.88701 |
| creative contributions | 0.747726 |
| common understanding | 0.727543 |
| Service interventions | 0.849015 |
| Budget narratives | 0.746873 |
| screening clinic services | 0.849555 |
| specific activities | 0.731572 |
| bike lanes | 0.733618 |
| intervention activities | 0.73838 |
| community decisions | 0.730383 |
| long time | 0.742364 |
| influence individual | 0.728954 |
| enhances health | 0.739998 |
| specific population | 0.736439 |
| radio soap opera | 0.842452 |
| HIV testing | 0.750827 |
| Social Marketing interventions | 0.968537 |
| Communication interventions inform | 0.951689 |
| African-American men | 0.735696 |
| Include launch schedules | 0.840119 |
| ethical requirements | 0.722147 |
| outcome objective | 0.759308 |
|
CLICK HERE |
| 8675 |
Centers for Disease Control and Prevention |
Html |
en |
Triple A's of Healthy Swimming - Healthy Swimming & Recreational Water |
null |
|
|
CLICK HERE |
| 8961 |
Centers for Disease Control and Prevention |
Html |
en |
Emergency Preparedness - Publications by Topic - Public Health Law |
null |
| caregiver preparedness | 0.465306 |
| public health practitioners | 0.511397 |
| health officials | 0.544715 |
| emergency declarations | 0.484926 |
| Radiological Emergency Preparedness | 0.514398 |
| Court House Preparedness | 0.48456 |
| mid-tier public health | 0.506223 |
| Healthcare Emergency Preparedness | 0.500697 |
| legal issues | 0.480492 |
| public health emergencies | 0.582627 |
| Emergency Preparedness Law | 0.517169 |
| health emergency response | 0.488935 |
| public health officials | 0.542446 |
| legal preparedness | 0.586112 |
| public health investigations | 0.487215 |
| emergency preparedness practice | 0.514191 |
| emergency preparedness | 0.578454 |
| City Health Officials | 0.519387 |
| health emergency training | 0.486657 |
| Emergency Preparedness Training | 0.504881 |
| Hospital Legal Preparedness | 0.528724 |
| public health workforce | 0.489794 |
| all-hazards preparedness | 0.466066 |
| Center Environmental Health | 0.46569 |
| Educational Facilities Preparedness | 0.49004 |
|
| radiation legal preparedness | 0.505315 |
| Health Emergency Law | 0.53143 |
| Zika Preparedness | 0.46486 |
| Emergency Preparedness Web | 0.499144 |
| public health professionals | 0.504269 |
| public health emergency | 0.607144 |
| health legal preparedness | 0.524519 |
| law enforcement | 0.472029 |
| public health | 0.904754 |
| public health law | 0.727248 |
| Public Health Association | 0.492042 |
| Health Law Program | 0.594603 |
| competency-based preparedness | 0.46806 |
| Territorial Health Officials | 0.490196 |
| Health Lawyers Association | 0.481152 |
| Disaster Preparedness | 0.465189 |
| public health workers | 0.491279 |
| local public health | 0.507463 |
| Public Health Preparedness | 0.605659 |
| health law bench | 0.493746 |
| tribal emergency preparedness | 0.514736 |
| public health problem | 0.48495 |
| American Health Lawyers | 0.477769 |
| federal public health | 0.5028 |
|
CLICK HERE |
| 9133 |
Centers for Disease Control and Prevention |
Html |
en |
Preventing Chronic Disease | Improving Quality of Cause-of-Death Reporting in New York City - CDC |
Letter to the Editor |
| Electronic Death Registration | 0.53516 |
| NYC hospitals | 0.505814 |
| hospital staff | 0.516996 |
| hospital staff training | 0.503798 |
| self-reported beliefs | 0.475443 |
| examiner’s office | 0.502345 |
| medical examiner | 0.571785 |
| cause-of-death reporting | 0.811298 |
| York City Resident | 0.547959 |
| New York City | 0.956774 |
| excessive reporting | 0.481559 |
| medical residents | 0.469453 |
| resident physicians | 0.582084 |
| resident respondents | 0.470299 |
| Survey authors | 0.471862 |
| intermediate cause | 0.476784 |
| Wexelman et | 0.469913 |
| public health statistics | 0.616867 |
| similar successful results | 0.503959 |
| poor cause-of-death reporting | 0.548426 |
| data check | 0.516247 |
| additional case examples | 0.51775 |
| Survey | 0.47432 |
| cause-of-death screening | 0.469062 |
| septic shock | 0.572505 |
|
| cause-of-death data | 0.471986 |
| conference calls | 0.520803 |
| correct cause | 0.492219 |
| Luke’s–Roosevelt hospitals | 0.515292 |
| previous US-wide | 0.470461 |
| inadvertent negative effect | 0.505317 |
| heart disease | 0.473947 |
| in-service trainings | 0.53567 |
| NYC | 0.606222 |
| poor cause-of death | 0.527676 |
| cardiovascular disease death | 0.546826 |
| City Health Information | 0.531546 |
| inaccurate cause | 0.543494 |
| health department | 0.523131 |
| poor quality cause-of-death | 0.543348 |
| cause-of-death messaging | 0.469351 |
| York City Department | 0.710343 |
| teaching hospitals | 0.473767 |
| Public Health Service | 0.516672 |
| cause-of-death reporting practices | 0.538831 |
| successful quality-improvement efforts | 0.514068 |
| initial conference calls | 0.5061 |
| additional explanatory condition | 0.509196 |
| urinary tract infection | 0.506392 |
|
CLICK HERE |
| 9848 |
Centers for Disease Control and Prevention |
Html |
en |
Preventing Chronic Disease | Look Local: The Value of Cancer Surveillance and Reporting by American Indian Clinics - CDC |
Cancer incidence and mortality rates for American Indians in the Northern Plains region of the United States are among the highest in the nation. Reliable cancer surveillance data are essential to help reduce this burden; however, racial data in state cancer registries are often misclassified, and cases are often underreported. |
| Health Problems cancer | 0.399517 |
| Indian Cancer Surveillance | 0.421129 |
| American Indian cases | 0.466271 |
| Comprehensive Cancer Control | 0.403764 |
| Great Lakes | 0.43327 |
| Wisconsin Carbone Cancer | 0.542759 |
| new cancer cases | 0.403594 |
| state-level cancer registry | 0.395714 |
| AI/AN cancer data | 0.536738 |
| AI/AN cancer burden | 0.393922 |
| urban Indian clinics | 0.597786 |
| high-quality cancer data | 0.409763 |
| AI/AN cancer | 0.629617 |
| cancer registry capture | 0.422263 |
| AI/AN cancer case | 0.421117 |
| comprehensive cancer center | 0.443318 |
| AI/AN cancer cases | 0.605166 |
| cancer surveillance | 0.48176 |
| Great Lakes Inter-Tribal | 0.420254 |
| state registry | 0.652533 |
| cancer case records | 0.407018 |
| cancer health disparities | 0.398904 |
| cancer prevention | 0.401464 |
| Washington State Cancer | 0.393549 |
| cancer registry data | 0.513012 |
|
| Indian cancer data | 0.439239 |
| local cancer data | 0.479848 |
| state cancer surveillance | 0.409329 |
| quality cancer data | 0.410402 |
| Carbone Cancer Center | 0.597629 |
| Indian cancer conference | 0.393698 |
| Wisconsin AI/AN cancer | 0.424311 |
| local cancer registry | 0.418027 |
| AI/AN cancer patients | 0.403475 |
| cancer cases | 0.783065 |
| cancer data | 0.606714 |
| cancer burden | 0.420145 |
| cancer surveillance data | 0.468302 |
| community-based participatory research | 0.413093 |
| american indian cancer | 0.522179 |
| Indian Health Service | 0.660978 |
| cancer case misclassification | 0.394122 |
| cancer disparities | 0.433497 |
| state registry data | 0.456747 |
| Wisconsin Comprehensive Cancer | 0.415328 |
| prematched AI/AN cancer | 0.393283 |
| Native cancer data | 0.411206 |
| state cancer registries | 0.524725 |
| Wisconsin Cancer Reporting | 0.913532 |
|
CLICK HERE |