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Barriers to colorectal cancer screening: physician and general population perspectives, New Mexico, 2006 |
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| CRC testing | 0.487735 |
| electronic medical records | 0.483249 |
| New Mexico BRFSS | 0.501863 |
| upper age limit | 0.502456 |
| primary care providers | 0.588708 |
| CRC screening decision | 0.587979 |
| New Mexico VA | 0.49121 |
| physician respondents | 0.519209 |
| barium enema | 0.500531 |
| CRC screening | 0.894644 |
| Prevention Initiative CRC | 0.496478 |
| Clinical Prevention Initiative | 0.511819 |
| patients | 0.55038 |
| Cancer Screening Practices | 0.560214 |
| markedly different perspectives | 0.48288 |
| CRC incidence | 0.499643 |
| primary care physicians | 0.635761 |
| new CRC cases | 0.525478 |
| respondents | 0.584176 |
| BRFSS respondents | 0.492092 |
| New Mexico Cancer | 0.491576 |
| fecal occult blood | 0.485411 |
| average-risk patients | 0.51859 |
| cancer screening beliefs | 0.56773 |
|
| screening barriers | 0.578602 |
| cancer screening | 0.585632 |
| screening tests | 0.526552 |
| home FOBT | 0.492296 |
| lower endoscopy | 0.548546 |
| general population | 0.505856 |
| flexible sigmoidoscopy | 0.525799 |
| screening practices | 0.668128 |
| CRC screening practices | 0.65687 |
| state-specific CRC screening | 0.632645 |
| effective screening | 0.549411 |
| colonoscopy | 0.483917 |
| health care | 0.483544 |
| New Mexico School | 0.492657 |
| health | 0.485736 |
| barriers | 0.602525 |
| New Mexico | 0.984575 |
| screening procedures | 0.533417 |
| primary care | 0.72679 |
| low screening proportions | 0.573358 |
| screening rates | 0.55476 |
| physician survey | 0.516656 |
| higher screening rates | 0.538624 |
| New Mexico Department | 0.611365 |
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Radiation Emergencies - Protecting Yourself and Your Family |
Information on terrorism and public health. Provided by the Centers for Disease Control and Prevention (CDC). |
| pets | 0.402189 |
| disaster situations | 0.907171 |
| local officials | 0.849797 |
| radiation emergency | 0.851651 |
|
| specific actions | 0.888701 |
| ones | 0.469126 |
| people | 0.471712 |
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Information for Educators - FASD |
FASDs are 100% preventable if a woman does not drink alcohol during pregnancy. There is no known safe amount of alcohol to drink while pregnant. There is also no safe time during pregnancy to drink and no safe kind of alcohol. |
| Maternal Substance Abuse | 0.233973 |
| effective parenting techniques | 0.223648 |
| Science Ambassador Program | 0.227293 |
| child development | 0.328038 |
| Tribal Justice Systems | 0.222781 |
| Substance Abuse | 0.249018 |
| Provider Resource Kit | 0.372145 |
| Childcare Provider Resource | 0.3819 |
| middle school children | 0.459826 |
| related conditions | 0.244065 |
| K-12 FASD Education | 0.306535 |
| various child development | 0.2254 |
| fetal alcohol | 0.91109 |
|
| FASDs | 0.252508 |
| Fetal Alcohol Syndrome | 0.775828 |
| Double ARC | 0.342026 |
| separate training curricula | 0.222972 |
| Healthy Path curriculum | 0.233521 |
| high school students | 0.222905 |
| alcohol spectrum disorders | 0.715229 |
| FASD Toolbox | 0.208725 |
| Mental Health Services | 0.231535 |
| Alcohol Syndrome Awareness | 0.28583 |
| Child Development Center | 0.244887 |
| fetal alcohol spectrum | 0.764746 |
| future science teachers | 0.241539 |
|
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Centers for Disease Control and Prevention |
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New Million Hearts tools announced by partners - Press Release: November 3, 2011 |
New Million Hearts tools announced by partners |
| quality improvement organizations | 0.471399 |
| heart attacks | 0.658837 |
| Heart Stroke Recognition | 0.484593 |
| hearts partnerships | 0.577086 |
| major risk factors | 0.473914 |
| Hearts initiative visit | 0.545299 |
| Blood pressure control | 0.47763 |
| health care disparities | 0.505662 |
| cardiovascular preventive care | 0.495595 |
| National Care Initiative | 0.49015 |
| American College | 0.529389 |
| ethnically diverse populations | 0.467025 |
| Million Hearts campaign | 0.643614 |
| Million Hearts effort | 0.647861 |
| heart disease | 0.489481 |
| pharmacy faculty members | 0.467715 |
| Million Hearts goals | 0.787429 |
| cardiovascular disease measures | 0.488157 |
| Hearts visit http://millionhearts.hhs.gov | 0.550824 |
| health care providers | 0.501817 |
| ACC CEO Jack | 0.489624 |
| additional community outreach | 0.470612 |
| American Heart Association | 0.644033 |
| health care | 0.551408 |
|
| health care systems | 0.519429 |
| public health organizations | 0.513845 |
| TheNational Consumers League | 0.469781 |
| cardiovascular disease | 0.490986 |
| Million Hearts initiative | 0.733832 |
| Private sector commitments | 0.476216 |
| Cardiovascular health care | 0.522736 |
| Black Cardiologistswill work | 0.474302 |
| Future Medication Adherence | 0.470504 |
| public health partners | 0.501278 |
| human services | 0.508044 |
| care delivery. AHA | 0.498753 |
| best evidence-based strategies | 0.473675 |
| cardiovascular diseases | 0.464708 |
| National Consumers League | 0.473878 |
| Million Hearts | 0.979629 |
| community health centers | 0.494078 |
| u.s. department | 0.509308 |
| Hearts Executive Director | 0.5657 |
| better align health | 0.492493 |
| trans fat consumption | 0.471653 |
| cardiac care team | 0.48285 |
| patient education activities | 0.46859 |
|
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Preventing Chronic Disease | Use of Practice-Based Research Network Data to Measure Neighborhood Smoking Prevalence - CDC |
Practice-Based Research Networks (PBRNs) and health systems may provide timely, reliable data to guide the development and distribution of public health resources to promote healthy behaviors, such as quitting smoking. The objective of this study was to determine if PBRN data could be used to make neighborhood-level estimates of smoking prevalence. |
| logistic regression model | 0.63639 |
| data | 0.700094 |
| overall smoking prevalence | 0.641904 |
| Patient smoking status | 0.599791 |
| Risk Factor Surveillance | 0.596099 |
| community-level smoking prevalence | 0.653606 |
| Harvard Medical School | 0.594824 |
| smoking status | 0.762497 |
| market share | 0.610593 |
| state health departments | 0.601173 |
| BRFSS population-based estimates | 0.616031 |
| BRFSS prevalence | 0.597404 |
| behavioral risk factors | 0.64142 |
| health systems | 0.640306 |
| population smoking data | 0.605777 |
| annual population-based data | 0.597134 |
| undocumented smoking status | 0.59468 |
| smoking status documentation | 0.609056 |
| Massachusetts General Hospital | 0.593822 |
| population-based estimates | 0.640062 |
| Care PBRN practices | 0.617491 |
| practice-based research networks | 0.605088 |
| health system data | 0.605215 |
| Behavioral Risk Factor | 0.597609 |
|
| PBRN prevalence | 0.60287 |
| smoking prevalence | 0.923288 |
| health record data | 0.607147 |
| multiple health systems | 0.612663 |
| Partners Primary Care | 0.766963 |
| EHR data | 0.608178 |
| percentage points | 0.610302 |
| smoking prevalence estimates | 0.675449 |
| national smoking prevalence | 0.632061 |
| routine clinical care | 0.633211 |
| public health | 0.654463 |
| health care | 0.63255 |
| population smoking prevalence | 0.645179 |
| PBRN data | 0.685057 |
| health | 0.712323 |
| neighborhood-level smoking prevalence | 0.738452 |
| neighborhood smoking prevalence | 0.656878 |
| practice-based smoking prevalence | 0.653992 |
| public health data | 0.611454 |
| PBRN estimates | 0.599589 |
| regional smoking prevalence | 0.62891 |
| primary care | 0.78436 |
| population-based smoking prevalence | 0.697837 |
| neighborhood smoking status | 0.614368 |
|
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Centers for Disease Control and Prevention |
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Stephanie Sansom, Conversations with the CDC Director |
The CDC Director’s webpage offers information on Dr. Thomas Frieden, who became the agency’s 16th director in June 2009. The pages features information on Dr. Frieden’s Weekly Focus, the Latest from Dr. Frieden (his RSS feed), and links to his bio, statements, videos, press releases, media appearances, photos, presentations, and speeches. |
| 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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Preventing Chronic Disease | Developing Theoretically Based and Culturally Appropriate Interventions to Promote Hepatitis B Testing in 4 Asian American Populations, 2006"2011 - CDC |
Hepatitis B infection is 5 to 12 times more common among Asian Americans than in the general US population and is the leading cause of liver disease and liver cancer among Asians. The purpose of this article is to describe the step-by-step approach that we followed in community-based participatory research projects in 4 Asian American groups, conducted from 2006 through 2011 in California and Washington state to develop theoretically based and culturally appropriate interventions to promote hepatitis B testing. We provide examples to illustrate how intervention messages addressing identical theoretical constructs of the Health Behavior Framework were modified to be culturally appropriate for each community. |
| Taylor VM | 0.493171 |
| hepatitis B transmission | 0.487375 |
| hepatitis B virus | 0.594569 |
| hepatitis B booklets | 0.470776 |
| hepatitis B. | 0.549685 |
| self-reported hepatitis | 0.486605 |
| hepatitis b screening | 0.482212 |
| hepatitis b knowledge | 0.522956 |
| hepatitis B blood | 0.553091 |
| intervention development | 0.479528 |
| hepatitis B. Hmong | 0.536597 |
| Hepatitis B Information | 0.476853 |
| guide listing hepatitis | 0.490458 |
| Asian American groups | 0.503112 |
| hepatitis B vaccination | 0.492629 |
| liver disease | 0.498919 |
| hepatitis B infectioncMany | 0.467695 |
| cervical cancer screening | 0.471903 |
| hepatitis B testeThe | 0.466769 |
| community | 0.55447 |
| Asian American populations | 0.490079 |
| cervical cancer | 0.478708 |
| hepatitis B surface | 0.471775 |
| hepatitis B pamphlet | 0.473469 |
| hepatitis BaHepatitis | 0.468942 |
|
| health promotion interventions | 0.508288 |
| Chen MS Jr | 0.475603 |
| intervention | 0.638828 |
| intervention approach | 0.478394 |
| Hepatitis B Internet | 0.47206 |
| cancer screening | 0.521928 |
| print materials | 0.472168 |
| pilot testing | 0.471123 |
| hepatitis b infection | 0.661555 |
| intervention messages | 0.496608 |
| hepatitis B info-cards | 0.471967 |
| Introduction
Hepatitis | 0.512343 |
| health behavior | 0.770886 |
| community-based participatory research | 0.466221 |
| hepatitis B vaccinations | 0.474322 |
| hepatitis B vaccine | 0.468725 |
| hepatitis B infections | 0.487487 |
| hepatitis | 0.92811 |
| lay health workers | 0.692048 |
| chronic hepatitis | 0.594489 |
| hepatitis b testing | 0.920868 |
| et al | 0.681898 |
| high school diploma | 0.515437 |
| liver cancer | 0.607726 |
|
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Surveillance and Preparedness for Ebola Virus Disease - NewYork City, 2014 |
On October 14, 2014, this report was posted as an MMWR Early Release on the MMWR website (http://www.cdc.gov/mmwr). |
| clear reporting criteria | 0.427993 |
| Ebola surveillance | 0.560902 |
| Jennifer C. Baumgartner | 0.447418 |
| New York City | 0.46414 |
| MMWR Early Release | 0.453649 |
| infection control guidance | 0.431619 |
| health care providers | 0.698071 |
| laboratory studies | 0.433873 |
| citywide conference calls | 0.430647 |
| West African immigrants | 0.455142 |
| health care community | 0.48425 |
| F. Kennedy International | 0.43349 |
| Isaac Benowitz | 0.444424 |
| health care facilities | 0.496085 |
| low-risk exposure | 0.44037 |
| health care settings | 0.49989 |
| electronic health | 0.469059 |
| Ebola patients | 0.737469 |
| Ebola | 0.824322 |
| Jay K. Varma | 0.446069 |
| Ebola virus disease | 0.654863 |
| alternate diagnoses | 0.436204 |
| affected area | 0.429403 |
| infection control | 0.443698 |
| Ebola cases | 0.570302 |
|
| recent travel history | 0.445553 |
| emergency medical services | 0.442733 |
| Ebola case | 0.569331 |
| Sharon E. Balter | 0.452081 |
| infection control precautions | 0.433143 |
| viral hemorrhagic fever | 0.43475 |
| health care workers | 0.637277 |
| Scott A. Harper | 0.448699 |
| local hospitals | 0.442358 |
| health care | 0.99183 |
| travel history | 0.487191 |
| electronic health alert | 0.46415 |
| Ebola-affected country | 0.446089 |
| New York | 0.540533 |
| Lucretia E. Jones | 0.453748 |
| American health care | 0.522303 |
| Public Health Preparedness | 0.472418 |
| Ellen H. Lee | 0.44708 |
| local health care | 0.48883 |
| Ebola testing | 0.61777 |
| West Africa | 0.57623 |
| DOHMH medical epidemiologists | 0.457572 |
| Ebola-specific data collection | 0.435022 |
| MD2 | 0.444716 |
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Hunger and Behavioral Risk Factors for NoncommunicableDiseases in School-Going Adolescents in Bolivia, 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. |
| significantly greater odds | 0.457993 |
| public health interventions | 0.455356 |
| United Nations | 0.489144 |
| vegetable consumption | 0.932331 |
| complex sample design | 0.455651 |
| SAS Institute Inc. | 0.452719 |
| nondaily fruit | 0.830884 |
| odds ratio | 0.480919 |
| daily sugar-sweetened soda | 0.585344 |
| Urban Public Health | 0.450668 |
| fully conditional specification | 0.451923 |
| lowest hunger prevalence | 0.601621 |
| global school-based student | 0.644886 |
| sugar-sweetened soda consumption | 0.740797 |
| overall survey response | 0.462516 |
| school-going adolescents | 0.489156 |
| greater odds | 0.466348 |
| behavioral risk factors | 0.778553 |
| risk factors | 0.823792 |
| World Health Organization | 0.597194 |
| body mass index | 0.459364 |
| response rate | 0.50305 |
| current tobacco users | 0.481115 |
| current alcohol | 0.513523 |
|
| various risk factors | 0.461705 |
| highest hunger prevalence | 0.59786 |
| hunger | 0.987769 |
| traditional behavioral risk | 0.483494 |
| school response rate | 0.455376 |
| household food insecurity | 0.930803 |
| communicable disease burden | 0.468721 |
| current tobacco | 0.889143 |
| hunger contributes | 0.532655 |
| adequate physical activity | 0.477893 |
| Bolivia | 0.580603 |
| nationally representative survey | 0.469468 |
| school-based student health | 0.644662 |
| public health | 0.455414 |
| multivariable logistic regression | 0.612557 |
| AOR | 0.54175 |
| Student Health Survey | 0.640592 |
| sample design | 0.472783 |
| hunger status | 0.542236 |
| growth reference data | 0.465214 |
| physical activity | 0.516516 |
| Health Organization child | 0.472352 |
| school meal programs | 0.545536 |
| poorer general health | 0.459541 |
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Type 2 Diabetes: All in the Family? |
null |
| family members | 0.716599 |
| risk factors | 0.431036 |
| certain habits | 0.471154 |
| lifestyle coach | 0.431206 |
| share experiences | 0.411363 |
| Diabetes Program | 0.719725 |
| type | 0.365761 |
| mm Hg | 0.491318 |
| Family history | 0.4361 |
|
| healthy lifestyle—including | 0.436429 |
| good news | 0.438084 |
| physical activity | 0.435476 |
| National Diabetes Prevention | 0.931271 |
| lifestyle changes | 0.435169 |
| better checkups | 0.462223 |
| high blood pressure | 0.727292 |
| CDC Diabetes | 0.809017 |
| diabetes | 0.972951 |
|
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