| 8739 |
Centers for Disease Control and Prevention |
Html |
en |
Preventing Chronic Disease | A Multilevel Approach to Estimating Small Area Childhood Obesity Prevalence at the Census Block-Group Level - CDC |
Traditional survey methods for obtaining nationwide small-area estimates (SAEs) of childhood obesity are costly. This study applied a geocoded national health survey in a multilevel modeling framework to estimate prevalence of childhood obesity at the census block-group level. |
| national childhood obesity | 0.520281 |
| data | 0.494418 |
| obesity rates | 0.486222 |
| obesity outcomes | 0.485909 |
| state-level prevalence estimates | 0.499441 |
| county | 0.475832 |
| childhood obesity epidemic | 0.531307 |
| model-based predicted SAEs | 0.482368 |
| block-group level estimates | 0.479554 |
| similar obesity estimates | 0.524033 |
| childhood obesity-prevalence SAEs | 0.48297 |
| small-area estimates | 0.488553 |
| children | 0.488796 |
| median household income | 0.632501 |
| obesity prevention | 0.50325 |
| state childhood obesity | 0.538125 |
| obesity risk | 0.533593 |
| block groups | 0.513613 |
| model-based saes | 0.569285 |
| childhood obesity measures | 0.539781 |
| Area Childhood Obesity | 0.543907 |
| model-based block-group estimates | 0.501983 |
| random effects | 0.538927 |
| NSCH prevalence estimates | 0.493832 |
| multilevel model | 0.522877 |
|
| zip code | 0.514056 |
| multilevel model-based zip | 0.486605 |
| direct survey estimates | 0.607228 |
| observed childhood obesity | 0.518663 |
| block group | 0.536573 |
| childhood obesity SAE | 0.522737 |
| state-level childhood obesity | 0.524789 |
| state-level model-based estimates | 0.499581 |
| census block-group level | 0.484668 |
| block-group level | 0.666688 |
| childhood obesity prevalence | 0.831068 |
| Obesity Prevalence Estimates | 0.549338 |
| model-based childhood obesity | 0.632685 |
| validated obesity outcome | 0.49491 |
| NSCH child obesity | 0.502438 |
| level small-area estimates | 0.48546 |
| state-specific model-based estimates | 0.498977 |
| childhood obesity estimate | 0.5203 |
| obesity status | 0.50657 |
| model-based estimates | 0.557552 |
| level obesity prevalence | 0.516437 |
| nationwide small-area estimates | 0.482181 |
| childhood obesity | 0.949901 |
| obesity data | 0.483973 |
|
CLICK HERE |
| 9565 |
Centers for Disease Control and Prevention |
Html |
en |
CDC Accomplishments |
Centers for Disease Control and Prevention Accomplishments, 2009-2012 |
| Field Epidemiology Training | 0.342317 |
| meaningful successes | 0.249331 |
| CDC | 0.833919 |
| proven steps | 0.232239 |
| real-time emergency response | 0.37235 |
| non-communicable diseases | 0.258014 |
| New CDC research | 0.583128 |
| H1N1 virus | 0.228958 |
| Disease Control | 0.274538 |
| premature deaths | 0.269282 |
| health systems | 0.281781 |
| Hepatitis C. Implementation | 0.349841 |
| Americans | 0.278541 |
| seat belt laws | 0.359513 |
| Thirty-nine states | 0.248459 |
| America’s health | 0.423547 |
| CDC’s laboratories | 0.457356 |
| lowers health care | 0.438927 |
| leadership role | 0.231309 |
| public health laboratories | 0.383099 |
| health protection agency | 0.456727 |
| rapid detection | 0.25397 |
| protected people | 0.250218 |
| CDC-supported FETPs | 0.231199 |
|
| disease tracking | 0.259307 |
| ignition interlock systems | 0.365491 |
| health threats | 0.976144 |
| unique public health | 0.432547 |
| U.S. borders | 0.231996 |
| CDC data | 0.487033 |
| health security | 0.301128 |
| surveillance systems | 0.227114 |
| key health threats | 0.523956 |
| fewer schools | 0.238427 |
| child safety seat | 0.36221 |
| sugar-sweetened beverages | 0.232742 |
| school grounds | 0.230616 |
| public health | 0.644369 |
| Key campaign | 0.242083 |
| healthy school environments | 0.343381 |
| local public health | 0.410193 |
| young drivers | 0.243709 |
| low-nutrition food | 0.235391 |
| teen driving injuries | 0.344401 |
| antiviral treatment | 0.238048 |
| key role | 0.241646 |
| highly trained disease | 0.342399 |
| motor vehicle crashes | 0.627201 |
|
CLICK HERE |
| 12754 |
Centers for Disease Control and Prevention |
Html |
en |
Interim Guidance on Testing, Specimen Collection, and Processing for Patients with Suspected Infection with Novel Influenza A Viruses with the Potential to Cause Severe Disease in Humans |
Interim Guidance on Testing, Specimen Collection, and Processing for Patients with Suspected Infection with Novel Influenza A Viruses with the Potential to Cause Severe Disease in Humans - CDC |
| avian influenza | 0.75358 |
| avian influenza findings | 0.513247 |
| United States | 0.410003 |
| avian H5 viruses | 0.409996 |
| novel influenza | 0.956822 |
| avian influenza viruses | 0.567826 |
| human influenza viruses | 0.516781 |
| seasonal influenza surveillance | 0.453242 |
| influenza specimen | 0.44679 |
| infection control | 0.393256 |
| novel avian influenza | 0.504915 |
| Influenza Division Epidemiology | 0.461302 |
| seasonal influenza viruses | 0.526006 |
| positive influenza | 0.447035 |
| clinical specimens | 0.408502 |
| infection control precautions | 0.392744 |
| influenza virus infection | 0.595377 |
| Influenza A Subtyping | 0.441145 |
| CDC Influenza Division | 0.517431 |
| state health | 0.38763 |
| public health | 0.660732 |
| lower respiratory tract | 0.412568 |
| influenza A virus | 0.647125 |
| virus infections | 0.445693 |
|
| respiratory specimens | 0.428853 |
| seasonal influenza virus | 0.542882 |
| H5 virus infections | 0.406779 |
| novel influenza virus | 0.509837 |
| seasonal influenza | 0.558949 |
| H5N1 virus | 0.415905 |
| currently circulating influenza | 0.465726 |
| influenza A H5 | 0.565041 |
| specimens | 0.485365 |
| local public health | 0.385066 |
| highly-pathogenic avian influenza | 0.494488 |
| influenza surveillance | 0.461753 |
| influenza viruses | 0.604435 |
| state public health | 0.454881 |
| severe disease | 0.577387 |
| H5 viruses | 0.445874 |
| public health laboratories | 0.511053 |
| influenza a viruses | 0.555534 |
| CDC Human Influenza | 0.48074 |
| public health laboratory | 0.472938 |
| influenza diagnostic tests | 0.468283 |
| variant influenza viruses2 | 0.459549 |
| Asian-lineage avian influenza | 0.515817 |
|
CLICK HERE |
| 12820 |
Centers for Disease Control and Prevention |
Html |
en |
New CDC Vital Signs: Secondhand Smoke Exposure |
CDC public health news, press releases, government public health news, medical and disease news, story ideas, photos. |
| 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 |
|
CLICK HERE |
| 13319 |
Centers for Disease Control and Prevention |
Html |
en |
Viral Hepatitis Resource Center |
null |
| MPEG | 0.741242 |
| site | 0.541063 |
| PDF | 0.544429 |
|
|
CLICK HERE |
| 13774 |
Centers for Disease Control and Prevention |
Html |
en |
Controlled Substance Prescribing Patterns - Prescription Behavior Surveillance System, Eight States, 2013 |
Leonard J. Paulozzi, MD1. |
| high rates | 0.407303 |
| data | 0.598506 |
| long-acting opioid prescriptions | 0.533467 |
| prescription drug misuse | 0.496586 |
| drug overdose | 0.372217 |
| commonly prescribed opioids | 0.385933 |
| SA opioid prescriptions | 0.503916 |
| groups opioid analgesics | 0.43545 |
| prescription drug abuse | 0.400842 |
| prescription drugs | 0.51951 |
| public health surveillance | 0.406859 |
| state | 0.649004 |
| opioid analgesic tramadol | 0.426461 |
| stimulants | 0.420942 |
| Prescription Behavior Surveillance | 0.452291 |
| benzodiazepines | 0.39633 |
| daily dosage | 0.418105 |
| Delaware | 0.417105 |
| Unintentional Injury Prevention | 0.41288 |
| LA/ER opioids | 0.409062 |
| prescription drug monitoring | 0.64559 |
| substance abuse treatment | 0.385443 |
| lowest opioid | 0.384464 |
| opioid prescribing rates | 0.787535 |
|
| PDMPs | 0.431112 |
| opioid overdose deaths | 0.408005 |
| Injury Prevention | 0.413096 |
| higher prescribing rates | 0.451144 |
| daily opioid dosage | 0.503542 |
| United States | 0.418177 |
| age group | 0.409231 |
| state Prescription Drug | 0.3946 |
| states | 0.831173 |
| West Virginia | 0.696388 |
| Monitoring Program Center | 0.427906 |
| multiple prescribers | 0.55273 |
| public health | 0.525196 |
| opioid prescriptions | 0.962322 |
| prescription drug | 0.65772 |
| state residents | 0.385825 |
| LA/ER prescriptions | 0.398166 |
| opioid analgesic category | 0.4209 |
| opioid analgesics | 0.748659 |
| LA prescriptions | 0.380878 |
| Drug Monitoring Program | 0.445186 |
| drug monitoring programs | 0.422844 |
| PBSS | 0.519419 |
| opioid prescribing occurs | 0.465381 |
|
CLICK HERE |
| 14198 |
Centers for Disease Control and Prevention |
Html |
en |
Using Electronic Health Records to Examine Disease Risk in Small Populations: Obesity Among American Indian Children, Wisconsin, 2007-2012 |
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. |
| American Indian population | 0.582802 |
| PHINEX database | 0.634048 |
| geographic designation | 0.571821 |
| high obesity rates | 0.565094 |
| Health Data Exchange | 0.550853 |
| American Indian patients | 0.603266 |
| AMA PRA | 0.549703 |
| census block group | 0.640894 |
| Census American Community | 0.55042 |
| high school education | 0.563025 |
| non-Hispanic white populations | 0.55507 |
| Health Information Exchange | 0.556909 |
| logistic regression | 0.548318 |
| obesity prevalence | 0.562807 |
| obesity | 0.594187 |
| block group level | 0.58629 |
| body mass index | 0.568918 |
| health care quality | 0.548188 |
| insurance status | 0.547306 |
| American Indian families | 0.560116 |
| American Indians | 0.551758 |
| electronic health | 0.594404 |
| non-Hispanic white children | 0.846466 |
| Public Health Information | 0.557198 |
|
| electronic health record | 0.582933 |
| disproportionately high obesity | 0.547806 |
| health record data | 0.555632 |
| federal poverty level | 0.562026 |
| non-Hispanic white patients | 0.57879 |
| EHR data | 0.56239 |
| Health primary care | 0.547822 |
| American Indian children | 0.97036 |
| data sets | 0.557621 |
| American Indian teenagers | 0.566644 |
| American Indian data | 0.579114 |
| health care | 0.616829 |
| public health | 0.582407 |
| American Indian records | 0.576015 |
| economic hardship index | 0.595055 |
| health | 0.63727 |
| electronic health records | 0.575763 |
| Indian Health Service | 0.56184 |
| American Indian race | 0.58923 |
| American Indian populations | 0.563872 |
| American Indian members | 0.568052 |
| childhood obesity | 0.570778 |
| American Indian/Alaska Native | 0.564678 |
| economic hardship | 0.647988 |
|
CLICK HERE |
| 15789 |
Centers for Disease Control and Prevention |
Html |
en |
Carbapenem-Resistant Enterobacteriaceae Transmission inHealth Care Facilities - Wisconsin, February-May 2015 |MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| infection prevention staff | 0.582057 |
| respiratory intensive care | 0.553554 |
| clinical microbiology laboratories | 0.497516 |
| laboratory-identified CRE events | 0.65778 |
| WDPH personnel | 0.510043 |
| certain CRE | 0.56595 |
| particular CRE | 0.567383 |
| interfacility transmission events | 0.487911 |
| transmission events | 0.750014 |
| carbapenemase-producing CRE | 0.73715 |
| laboratory-based CRE surveillance | 0.7982 |
| bacterial isolates | 0.541945 |
| CRE culture | 0.594059 |
| PCR testing | 0.514892 |
| Hygiene laboratory-based CRE | 0.699709 |
| related PFGE patterns | 0.613575 |
| case fatality rates | 0.515855 |
| intensive care unit | 0.53669 |
| National Healthcare Safety | 0.481047 |
| CRE transmission | 0.911329 |
| infection prevention personnel | 0.503001 |
| public health | 0.577223 |
| polymerase chain reaction | 0.510878 |
| closely related PFGE | 0.611563 |
|
| critical access hospitals | 0.513003 |
| WSLH laboratory-based CRE | 0.685761 |
| patients | 0.563743 |
| laboratory-identified CRE | 0.700774 |
| Wisconsin State Laboratory | 0.521417 |
| infection prevention | 0.750871 |
| infection control measures | 0.532761 |
| CRE transmission events | 0.682932 |
| prevention staff members | 0.565217 |
| statewide CRE surveillance | 0.617166 |
| CRE | 0.91228 |
| health care settings | 0.62585 |
| high case fatality | 0.517504 |
| CRE infections | 0.631332 |
| southeastern Wisconsin | 0.588153 |
| isolates | 0.557668 |
| CRE surveillance program | 0.782577 |
| report laboratory-identified CRE | 0.660055 |
| pulsed-field gel electrophoresis | 0.609002 |
| health care transmission | 0.520004 |
| Healthcare Safety Network | 0.481039 |
| low CRE prevalence | 0.610314 |
| respiratory care | 0.492799 |
|
CLICK HERE |
| 15840 |
Centers for Disease Control and Prevention |
Html |
en |
Prenatal Diagnosis of Microcephaly |
Information on Zika virus. Provided by the U.S. Centers for Disease Control and Prevention. |
|
| Prenatal Diagnosis | 0.832183 |
|
CLICK HERE |
| 16124 |
Centers for Disease Control and Prevention |
Html |
en |
Billing Codes | Diabetes |
National Diabetes Prevention Program |
| Ronald T. Ackermann | 0.663304 |
| screening | 0.420323 |
| S11-66. doi | 0.537458 |
| Guide | 0.418501 |
| official recognition | 0.533646 |
| standardized diabetes prevention | 0.747987 |
| York State Department | 0.632734 |
| group setting—such | 0.51292 |
| navigation Skip | 0.666505 |
| identification | 0.419259 |
| CDC-recognized lifestyle change | 0.606782 |
| medical billing | 0.53255 |
| intensive programs | 0.515946 |
| York State Diabetes | 0.767957 |
| Prediabetes Testing. | 0.519805 |
| diabetes—2013 | 0.418658 |
|
| list Skip | 0.667649 |
| program curriculum | 0.513191 |
| Health | 0.436193 |
| New York State | 0.822162 |
| page options Skip | 0.781543 |
| CPT code 0403T | 0.624704 |
| Ackermann RT | 0.573601 |
| NYS DPP | 0.56714 |
| permission | 0.426303 |
| medical care | 0.518483 |
| Standards | 0.418719 |
| billing codes | 0.534336 |
| NY Dept | 0.526476 |
| preventive behavior change | 0.616459 |
| intervention algorithm | 0.528869 |
| diabetes prevention program | 0.930426 |
|
CLICK HERE |