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Centers for Disease Control and Prevention |
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Vital Signs: Risk for Overdose from Methadone Used for Pain Relief - United States, 1999-2010 |
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. |
| synthetic opioid methadone | 0.802105 |
| chronic noncancer pain | 0.671241 |
| Opioid distribution data | 0.554987 |
| appropriate opioid prescribing | 0.600628 |
| medical examiner | 0.496734 |
| methadone prescriptions | 0.807627 |
| Pain Relief | 0.499035 |
| fatal methadone overdoses | 0.732658 |
| OPR-related overdose deaths | 0.562261 |
| Methadone Used | 0.705324 |
| long-term pain reduction | 0.500554 |
| overdose deaths | 0.707945 |
| pain treatment | 0.517733 |
| pain reliever overdoses | 0.573425 |
| major opioids | 0.544511 |
| methadone | 0.98372 |
| Methadone-related deaths | 0.4923 |
| opioid pain relievers | 0.757193 |
| severe respiratory depression | 0.50247 |
| opioid treatment programs | 0.599413 |
| methadone overdoses | 0.737755 |
| methadone mortality rates | 0.684968 |
| national death rates | 0.472115 |
| single-drug OPR deaths | 0.546393 |
| drug-related deaths | 0.537814 |
|
| Leonard J. Paulozzi | 0.495283 |
| single-drug deaths | 0.591993 |
| United States | 0.530757 |
| low back pain | 0.479711 |
| health-care providers | 0.485518 |
| methadone death rate | 0.690413 |
| methadone mortality rate | 0.683903 |
| methadone mortality | 0.71122 |
| mild pain | 0.513503 |
| extended-release opioids | 0.550558 |
| overdose death rate | 0.50422 |
| public health | 0.492701 |
| opioid prescriptions | 0.564779 |
| drug overdose deaths | 0.555487 |
| acute pain | 0.512249 |
| medical examiners | 0.508379 |
| methadone poisoning | 0.668216 |
| opioid analgesics | 0.515035 |
| opioid-related deaths | 0.494028 |
| pain specialists | 0.483109 |
| opioid addiction treatment | 0.559939 |
| vital statistics | 0.496046 |
| opioid pain reliever | 0.696037 |
| opioids | 0.600105 |
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| 7650 |
Centers for Disease Control and Prevention |
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Vital Signs: Racial Disparities in Breast Cancer Severity -United States, 2005-2009 |
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. |
| female breast cancer | 0.436807 |
| Breast cancer prognosis | 0.453267 |
| receptor–negative breast cancer | 0.440495 |
| timely breast cancer | 0.452626 |
| higher breast cancer | 0.474341 |
| breast cancer deaths | 0.624601 |
| abnormal breast cancer | 0.454803 |
| complex breast cancer | 0.456171 |
| cancer incidence rates | 0.408371 |
| white breast cancer | 0.46072 |
| Cancer Early Detection | 0.403724 |
| breast cancer patients | 0.439688 |
| cervical cancer screening | 0.397344 |
| breast cancer care | 0.523618 |
| aggressive breast cancers | 0.413538 |
| cancer incidence data | 0.398351 |
| screen-detected breast carcinoma | 0.398388 |
| United States Cancer | 0.402114 |
| breast cancer death | 0.519957 |
| white women | 0.695729 |
| breast cancer characteristics | 0.454351 |
| invasive breast cancer | 0.47906 |
| black women | 0.723906 |
| treatment | 0.402452 |
| breast cancer detection | 0.474682 |
|
| cancer mortality rates | 0.441991 |
| United States | 0.500647 |
| breast cancer diagnosis | 0.447836 |
| black women experience | 0.443879 |
| Cancer Epidemiol Biomarkers | 0.421799 |
| shows breast cancer | 0.441974 |
| breast cancers | 0.549394 |
| National Cancer Institute | 0.435145 |
| Cancer Res Treat | 0.398154 |
| Annual breast cancer | 0.45927 |
| National Breast | 0.408774 |
| cancer mortality statistics | 0.399936 |
| adequate breast cancer | 0.454266 |
| breast cancer screening | 0.584818 |
| abnormal screening test | 0.410568 |
| breast cancer | 0.949964 |
| PR+ breast cancers | 0.419257 |
| breast cancer mortality | 0.63073 |
| breast cancer cases | 0.44623 |
| et al | 0.409746 |
| breast cancer incidence | 0.572402 |
| cancer death rates | 0.430528 |
| Breast Cancer Res | 0.469944 |
| mortality rates | 0.466531 |
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| 10058 |
Centers for Disease Control and Prevention |
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CDC Telebriefing on infectious disease threats and global health security | Transcript | CDC Newsroom | CDC |
CDC public health news, press releases, government public health news, medical and disease news, story ideas, photos. |
| high-quality standardized laboratory | 0.313236 |
| infectious disease threats | 0.937275 |
| emergency operations center | 0.318676 |
| mobile applications | 0.319726 |
| global health capacity | 0.370534 |
| smart mobile phone | 0.308512 |
| press star | 0.364866 |
| remote rural areas | 0.319036 |
| carbapenem-resistant Enterobacteriaceae spreading | 0.318653 |
| long prolonged contact | 0.308111 |
| early infant diagnosis | 0.319128 |
| World Health Organization | 0.368096 |
| presidents emergency plan | 0.307481 |
| emergency operations procedures | 0.320298 |
| tom frieden | 0.74337 |
| countries | 0.396895 |
| text message | 0.323583 |
| Crimean-Congo hemorrhagic fever | 0.314559 |
| public health experts | 0.341683 |
| Lunar New | 0.324531 |
| high case fatality | 0.30679 |
| International Health Regulations | 0.352468 |
| michael smith | 0.369416 |
| mobile smartphone application | 0.313602 |
| global health security | 0.688095 |
|
| newer technology systems | 0.308844 |
| real-time information systems | 0.327266 |
| TOM SKINNER | 0.393433 |
| travel health kit | 0.338431 |
| tremendously powerful tool | 0.305227 |
| infectious disease risks | 0.32412 |
| CDC press office | 0.312844 |
| health care workers | 0.354291 |
| Dr. Tom Frieden | 0.412361 |
| health information specific | 0.345401 |
| drug resistant infections | 0.316853 |
| question | 0.319153 |
| michelle castillo | 0.36217 |
| electronic health records | 0.341362 |
| health protection | 0.302422 |
| H7N9 avian influenza | 0.320194 |
| drug-resistant tuberculosis | 0.337426 |
| up-to-date health information | 0.35362 |
| China public health | 0.35372 |
| viral hemorrhagic fevers | 0.314725 |
| Uganda | 0.311861 |
| travel health insurance | 0.3384 |
| Dr. Frieden | 0.449519 |
| rural remote areas | 0.318816 |
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| 11025 |
Centers for Disease Control and Prevention |
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Preventing Chronic Disease | State-Based Medicaid Costs for Pediatric Asthma Emergency Department Visits - CDC |
The prevalence of childhood asthma in the United States increased from 8.7% in 2001 to 9.5% in 2011. This increased prevalence adds to the costs incurred by state Medicaid programs. We provide state-based cost estimates of pediatric asthma emergency department (ED) visits and highlight an opportunity for states to reduce these costs through a recently changed Centers for Medicare and Medicaid Services (CMS) regulation. |
| state Medicaid programs | 0.448164 |
| asthma preventive services | 0.375191 |
| community asthma case | 0.367526 |
| children | 0.358344 |
| asthma interventions | 0.424479 |
| Medicaid | 0.461441 |
| asthma costs | 0.399505 |
| total asthma | 0.350063 |
| asthma ED visits | 0.703843 |
| asthma prevalence data | 0.416458 |
| asthma health disparities | 0.374289 |
| asthma | 0.827032 |
| asthma treatment costs | 0.375502 |
| pediatric asthma ED | 0.624669 |
| asthma code | 0.357441 |
| home-based asthma education | 0.367312 |
| asthma prevention services | 0.392684 |
| low asthma prevalence | 0.388359 |
| community health workers | 0.339334 |
| asthma management | 0.391996 |
| ED asthma visits | 0.452469 |
| Asthma education programs | 0.392387 |
| asthma services | 0.354609 |
| United States | 0.353437 |
| asthma triggers | 0.345228 |
|
| Community-based asthma interventions | 0.367575 |
| ED visits | 0.955217 |
| childhood asthma | 0.452017 |
| higher asthma costs | 0.386581 |
| childhood asthma ED | 0.407244 |
| childhood asthma prevalence | 0.404482 |
| states | 0.405748 |
| asthma treatment | 0.411296 |
| certified asthma educators | 0.394411 |
| Community Asthma Initiative | 0.366649 |
| home-based asthma interventions | 0.370199 |
| asthma prevalence | 0.588828 |
| pediatric asthma emergency | 0.410416 |
| high asthma prevalence | 0.388306 |
| rule change | 0.335167 |
| pediatric ED visits | 0.423493 |
| asthma prevalence rate | 0.392148 |
| asthma home visitation | 0.382884 |
| National Asthma Education | 0.386174 |
| childhood asthma enrollee | 0.358084 |
| asthma education | 0.429394 |
| asthma symptoms | 0.372317 |
| New England Asthma | 0.365788 |
| preventive services | 0.379383 |
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| 11147 |
Centers for Disease Control and Prevention |
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2008 National Report on Biochemical Indicators of Diet and Nutrition - Table 2.1 |
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| 12743 |
Centers for Disease Control and Prevention |
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Vital Signs: Disparities in Nonsmokers' Exposure toSecondhand Smoke - United States, 1999-2012 |
On February 3, 2015, this report was posted as an MMWR Early Release on the MMWR website (http://www.cdc.gov/mmwr). |
| comprehensive statewide laws | 0.568447 |
| serum cotinine analysis | 0.557311 |
| multiunit housing residency | 0.569831 |
| exposure exist | 0.560324 |
| serum cotinine levels | 0.647146 |
| serum cotinine data | 0.555905 |
| children | 0.609546 |
| Serum cotinine values | 0.555365 |
| Nutrition Examination Survey | 0.574313 |
| housing status | 0.572193 |
| Mexican Americans | 0.628151 |
| poverty level | 0.641875 |
| serum cotinine | 0.713685 |
| percentage change | 0.707782 |
| non-Hispanic black households | 0.570409 |
| workplace SHS exposure | 0.654424 |
| persons | 0.556881 |
| SHS exposure | 0.996896 |
| smoke-free home rules | 0.554555 |
| nonsmokers | 0.724438 |
| Greater SHS exposure | 0.653009 |
| low socioeconomic status | 0.558802 |
| serum cotinine level | 0.567508 |
| voluntary smoke-free home | 0.618858 |
|
| interview response rates | 0.567884 |
| adult nonsmokers | 0.572444 |
| United States | 0.562882 |
| U.S. nonsmokers | 0.616752 |
| smoke-free rules | 0.56447 |
| comprehensive smoke-free laws | 0.605772 |
| Mexican American nonsmokers | 0.584349 |
| prevalence | 0.567951 |
| public places | 0.579388 |
| non-Hispanic blacks | 0.728405 |
| smoking | 0.576701 |
| smoke-free policies | 0.594668 |
| multiunit housing | 0.671023 |
| non-Hispanic white households | 0.570074 |
| higher cotinine levels | 0.563785 |
| Serum cotinine concentrations | 0.555636 |
| continued efforts | 0.55371 |
| non-Hispanic whites | 0.637177 |
| background SHS levels | 0.61047 |
| non-Hispanic white nonsmokers | 0.620091 |
| non-hispanic black nonsmokers | 0.650401 |
| preventable health hazard | 0.605635 |
| recent exposure | 0.568164 |
| population exposure | 0.567189 |
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| 14357 |
Centers for Disease Control and Prevention |
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Multistate Outbreak of Salmonella Muenchen Infections Linked to Alfalfa Sprouts Produced by Sweetwater Farms | February 2016 | Salmonella |
Multistate Outbreak of Salmonella Muenchen Infections Linked to Alfalfa Sprouts Produced by Sweetwater Farms |
| Salmonella | 0.437798 |
| PulseNet | 0.296873 |
| ill person | 0.29798 |
| Public health investigators | 0.331697 |
| national database | 0.273019 |
| contaminated seeds | 0.270479 |
| regulatory officials | 0.346669 |
| outbreak case count | 0.281526 |
| likely source | 0.274174 |
| Salmonella Muenchen infections | 0.30117 |
| possible outbreaks | 0.277835 |
| outbreak | 0.339444 |
| DNA fingerprinting | 0.274187 |
| U.S. Food | 0.27656 |
| Kansas Department | 0.310526 |
| traceback investigations | 0.310585 |
| Salmonella Cubana | 0.332023 |
| median age | 0.273746 |
| brand alfalfa sprouts | 0.341696 |
| public health partners | 0.266056 |
| alfalfa sprouts | 0.813702 |
| public health officials | 0.392152 |
| pulsed-field gel electrophoresis | 0.342619 |
| national subtyping network | 0.34154 |
| ill people | 0.983971 |
|
| Salmonella bacteria | 0.307631 |
| multistate outbreak | 0.293567 |
| FDA | 0.270605 |
| Collaborative investigative efforts | 0.329952 |
| regulatory agency laboratories | 0.336194 |
| Drug Administration | 0.280551 |
| food regulatory agency | 0.334182 |
| CDC PulseNet database | 0.268909 |
| Salmonella infections | 0.277932 |
| multiple states | 0.271102 |
| public health | 0.595679 |
| additional ill people | 0.304868 |
| outbreak strain | 0.284801 |
| Sweetwater Farms | 0.708858 |
| Salmonella Kentucky | 0.33566 |
| Case Count Map | 0.271978 |
| DNA fingerprint | 0.308448 |
| contaminated sprouts | 0.298503 |
| possibly eating sprouts | 0.386783 |
| local public health | 0.318893 |
| irrigation water | 0.315721 |
| DNA fingerprints | 0.274399 |
| Salmonella Muenchen | 0.428571 |
| federal public health | 0.324017 |
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Centers for Disease Control and Prevention |
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YRBS 2015 Results | CDC Online Newsroom | CDC |
Teen smoking rates are at the lowest level (11%) since CDC began monitoring in 1991! |
| ideal time | 0.386128 |
| risk behaviors | 0.742082 |
| health risk behaviors | 0.72447 |
| sexually active students | 0.484097 |
| wireless devices | 0.399695 |
| Disease Control | 0.406797 |
| prescription drugs | 0.394588 |
| drinking sugar-sweetened beverages | 0.466506 |
| best science | 0.388826 |
| physical fighting | 0.394275 |
| newly emerging behaviors | 0.53325 |
| good decision making | 0.455426 |
| average text | 0.390472 |
| survey findings | 0.485336 |
| National Youth Risk | 0.519565 |
| YRBS report | 0.468876 |
| lowest levels | 0.410118 |
| life-threatening. YRBS results | 0.463421 |
| fewer high school | 0.476429 |
| new challenges | 0.401513 |
| U.S. high school | 0.508072 |
| current cigarette | 0.411241 |
| youth risk behaviors | 0.555527 |
| new data | 0.398247 |
| sexual risk behaviors | 0.5631 |
|
| Behavior Survey | 0.409694 |
| healthy behaviors | 0.455107 |
| teens | 0.32741 |
| risk taking. | 0.398958 |
| percent | 0.387422 |
| 55 mph | 0.394087 |
| Nationwide | 0.333716 |
| key survey findings | 0.482399 |
| important health risk | 0.474954 |
| important tool | 0.384482 |
| sedentary related behaviors | 0.551679 |
| survey results | 0.409191 |
| risk taking | 0.395786 |
| texting | 0.322374 |
| high school students | 0.9136 |
| safety concerns | 0.393774 |
| Cigarette smoking | 0.519907 |
| e-cigarettes | 0.336187 |
| football field | 0.391767 |
| mixed results | 0.394963 |
| risks | 0.327841 |
| screen time | 0.392919 |
| overall trends | 0.382424 |
| HIV testing | 0.391623 |
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| 16172 |
Centers for Disease Control and Prevention |
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From Making Sandwiches to Being Sandwiched | CDC Features |
Work-life balance for working caregivers may be difficult. But you are not alone - among the 44 million unpaid elder caregivers in the US, 75% are employed. |
| parent | 0.427509 |
| working caregiver | 0.552402 |
| Caregiving website | 0.566615 |
| older persons | 0.476539 |
| short walk | 0.469447 |
| problem | 0.335846 |
| flexible work schedule | 0.619015 |
| employer | 0.369186 |
| old mother | 0.508617 |
| respite care | 0.478084 |
| health conditions | 0.491582 |
| old caregiver | 0.590616 |
| teenage sons | 0.498951 |
| local resources | 0.469946 |
| multi-million dollar program | 0.690577 |
| needs | 0.393443 |
| little time | 0.496854 |
| Join community caregiver | 0.684264 |
| additional resources | 0.47043 |
| normal family responsibilities | 0.634387 |
| Pew Research Center | 0.652949 |
| job | 0.487971 |
| support network | 0.466899 |
| U.S. businesses | 0.477284 |
|
| child | 0.363862 |
| exercise | 0.351871 |
| caregiving tasks | 0.582437 |
| after-school activities | 0.497143 |
| hot bath | 0.46897 |
| replacement costs | 0.468911 |
| unpaid elder caregivers | 0.917603 |
| job benefits | 0.48421 |
| demanding job | 0.48621 |
| work-life balance | 0.726189 |
| Alzheimer’s Disease | 0.507669 |
| emotional support | 0.462494 |
| lower quality | 0.474838 |
| average employed caregiver | 0.75237 |
| Talk | 0.365792 |
| chores | 0.335369 |
| adult day care | 0.47788 |
| higher levels | 0.475113 |
| help | 0.365739 |
| Sally | 0.427115 |
| Caregiving Resources | 0.563834 |
| sandwich generation | 0.494947 |
| job situation | 0.483774 |
| time | 0.526752 |
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| 16252 |
Centers for Disease Control and Prevention |
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FastStats - Accidents or Unintentional Injuries |
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| Medical Care Survey | 0.825635 |
| tables | 0.352104 |
| Emergency Department Summary | 0.817018 |
| PDF | 0.351199 |
|
| Final Data | 0.549326 |
| Deaths | 0.401537 |
| Source | 0.354106 |
| table | 0.338754 |
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