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Diagnosis and Screening for Obesity-Related Conditions AmongChildren and Teens Receiving Medicaid - Maryland, 2005-2010 |
Lee Hurt, DrPH1,2, Cheryl De Pinto, MD2, Johnna Watson2, Marti Grant, MA2, Julie Gielner3 (Author affiliations at end of text). |
| study participants | 0.643151 |
| Healthy Kids | 0.477488 |
| 85th–94th percentiles | 0.717995 |
| well-child visit | 0.49366 |
| obesity screening | 0.44779 |
| teens | 0.412181 |
| health-care providers | 0.39003 |
| elevated BMI | 0.385205 |
| comorbid conditions | 0.398407 |
| 85th percentile | 0.754099 |
| Medicaid/MCHP encounter data | 0.447615 |
| children | 0.653445 |
| BMI percentiles | 0.455803 |
| Maryland Medicaid | 0.515183 |
| laboratory screening | 0.367577 |
| lipid panel | 0.411835 |
| BMI percentile | 0.57014 |
| overweight category | 0.359858 |
| obesity-related conditions | 0.47824 |
| obesity prevalence | 0.424995 |
| obesity | 0.693064 |
| BMI | 0.706581 |
| risk factors | 0.47409 |
| Medicaid/MCHP enrollment data | 0.351547 |
|
| Maryland Medicaid/MCHP children | 0.397677 |
| Maryland Medicaid HealthChoice | 0.362279 |
| body mass index | 0.464589 |
| Expert Committee | 0.702271 |
| BMI groups | 0.381418 |
| laboratory tests | 0.777388 |
| obese study participants | 0.614047 |
| obesity risk factors | 0.401968 |
| screening laboratory tests | 0.387391 |
| significantly higher prevalence | 0.400815 |
| Maryland Department | 0.354477 |
| Maryland study participants | 0.406032 |
| family history | 0.526295 |
| Expert Committee recommendations | 0.637773 |
| childhood obesity | 0.404125 |
| Health Program enrollees | 0.416418 |
| obese participants | 0.416294 |
| non-Hispanic black children | 0.38368 |
| final study population | 0.358844 |
| national Hispanic prevalence | 0.371885 |
| maryland children | 0.463175 |
| Kids study participants | 0.486424 |
| 95th percentile | 0.914844 |
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Centers for Disease Control and Prevention |
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Science Clips - Monday, September 13, 2010 |
null |
| Cox PJ | 0.829149 |
| rotavirus diarrhea | 0.775704 |
| PLoS ONE. | 0.840521 |
| Swanson NG | 0.786268 |
| Valley fever outbreak | 0.782152 |
| CDC Science Clips | 0.93079 |
| national socioeconomic disparities | 0.790229 |
| Nutrition Examination Survey | 0.789839 |
| autism spectrum disorder | 0.774181 |
| new weekly digest | 0.794388 |
| current cigarette smoking | 0.773673 |
| new cocaine adulterant | 0.786414 |
| Chief Science Officer | 0.803815 |
| Shieh WJ | 0.79451 |
| U.S. cross-sectional study | 0.795613 |
| inflammatory bowel disease | 0.787762 |
| Clin Infect Dis. | 0.78823 |
| elongate mineral particles | 0.773667 |
| Rift Valley fever | 0.835954 |
| nurses benefits patients | 0.777222 |
| Dimens Dent Hyg. | 0.785046 |
| rapid diagnostic tests | 0.778328 |
| Stephen B. Thacker | 0.87637 |
| home healthcare workers | 0.780512 |
| abnormal flora management | 0.773176 |
|
| Parental socioeconomic position | 0.781054 |
| Rotavirus disease | 0.783859 |
| United States | 0.827142 |
| Njenga MK | 0.785608 |
| Child Health J. | 0.793586 |
| youth study | 0.801145 |
| Emerg Med J. | 0.77701 |
| Comparative field performance | 0.778994 |
| primary school outbreak | 0.798524 |
| national diabetes registries | 0.79241 |
| community response coalitions | 0.790531 |
| specimen processing methods | 0.7805 |
| African Rotavirus Surveillance | 0.810811 |
| public health literature | 0.790973 |
| B. Thacker CDC | 0.918532 |
| Caruso CC | 0.785937 |
| potent neurotrophic activity | 0.781001 |
| Steele AD | 0.821702 |
| elevated blood pressure | 0.794098 |
| Zaki SR | 0.786255 |
| intimate partner violence | 0.833486 |
| Breiman RF | 0.77903 |
| human rotavirus strains | 0.815967 |
| Thacker CDC Library | 0.918516 |
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Nebraska Activities to Prevent HAIs |
null |
| ELC Funding | 0.66711 |
| monthly update | 0.829279 |
| infectious disease | 0.835397 |
| Laboratory Capacity | 0.837497 |
| email address | 0.952824 |
|
| Infectious Diseases | 0.843669 |
| page | 0.425225 |
| Affordable Care Act | 0.74941 |
| Epidemiology | 0.459973 |
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Global Routine Vaccination Coverage, 2011 |
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. |
| regular vaccination coverage | 0.344626 |
| Haemophilus influenzae type | 0.381109 |
| global routine vaccination | 0.341935 |
| immunization program performance | 0.297297 |
| DTP doses | 0.327741 |
| polio vaccine | 0.30365 |
| routinely recommended vaccines | 0.287814 |
| oral poliovirus vaccine | 0.390817 |
| rotavirus vaccine | 0.295585 |
| routine vaccination coverage | 0.474277 |
| incompletely vaccinated children | 0.923447 |
| Western Pacific Region | 0.384524 |
| Global Immunization Vision | 0.334495 |
| United Nations Children | 0.428249 |
| vaccine doses | 0.426574 |
| vaccination coverage | 0.803462 |
| routine childhood vaccination | 0.29353 |
| national immunization programs | 0.437195 |
| Global Immunization Div | 0.301588 |
| global vaccination coverage | 0.357589 |
| particular vaccine dose | 0.441943 |
| pneumococcal conjugate vaccine | 0.356878 |
| routine immunization services | 0.304808 |
|
| coverage | 0.822665 |
| Americas Region | 0.282853 |
| 3-dose DTP series | 0.289737 |
| World Health Organization | 0.391909 |
| hepatitis B vaccine | 0.429419 |
| global DTP3 coverage | 0.344297 |
| global coverage | 0.39647 |
| traditional EPI vaccines | 0.288046 |
| global vaccine action | 0.358468 |
| countries | 0.644014 |
| administrative coverage | 0.34814 |
| DTP dose | 0.313929 |
| vaccine-preventable disease–associated morbidity | 0.286312 |
| South-East Asia Region | 0.349546 |
| rotavirus vaccination series | 0.294606 |
| national DTP3 coverage | 0.44221 |
| diphtheria-tetanus-pertussis vaccine | 0.40763 |
| vaccine | 0.690014 |
| DTP vaccine | 0.382335 |
| bacille Calmette-GuУЉrin vaccine | 0.335116 |
| measles-containing vaccine | 0.454435 |
| target age group | 0.49782 |
| type b vaccine | 0.352504 |
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Centers for Disease Control and Prevention |
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Risk and Protective Factors - Intimate Partner Violence |
null |
| Traditional gender norms | 0.593808 |
| IPV victimization | 0.560673 |
| protective factors | 0.569916 |
| Kantor GK | 0.515769 |
| multilevel factors | 0.595 |
| Smith DB | 0.49543 |
| Knoble NB | 0.517085 |
| workforce | 0.418608 |
| MJ | 0.419784 |
| prevention | 0.416659 |
| victims | 0.416458 |
| risk factors | 0.926087 |
| Capaldi DM | 0.528151 |
| Partner Abuse | 0.539779 |
| correlates | 0.422224 |
| community | 0.416918 |
| Williams LM | 0.503007 |
| certain risk factors | 0.731184 |
| Rothman EF | 0.51034 |
| various opportunities | 0.503308 |
| adolescent dating violence | 0.62818 |
| women | 0.416526 |
| Youth Adolesc. | 0.496915 |
| Shortt JW | 0.522353 |
|
| Vagi KJ | 0.503248 |
| IPV perpetrator | 0.521824 |
| Jasinski JL | 0.655672 |
| Persons | 0.418913 |
| Aggress Violent Behav. | 0.571774 |
| Hall DM | 0.508585 |
| perpetrators | 0.430346 |
| meta-analytic review | 0.510504 |
| partner violence | 0.883488 |
| direct causes | 0.515238 |
| Kim HK | 0.504042 |
| childhood | 0.415587 |
| future IPV perpetration | 0.664187 |
| societal factors | 0.594153 |
| Laztman NE | 0.49773 |
| systematic review | 0.503622 |
| Stith SM | 0.508353 |
| home | 0.4165 |
| factor analysis | 0.500122 |
| spouse physical maltreatment | 0.585891 |
| Tritt D. Risk | 0.598495 |
| intimate partner violence | 0.875033 |
| comprehensive review | 0.498832 |
| family | 0.416416 |
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PanFlu Storybook - War Stories |
War Stories, The first cases of illness from the 1918 flu pandemic in the United States were reported from Fort Riley, Kansas on March 11 when an Army private became ill; complaining of fever, sore throat, and headache. Military personnel were greatly impacted by the virus and many young recruits were dead from the flu before they ever saw combat. |
| young recruits | 0.478875 |
| 1918 flu pandemic | 0.781838 |
| list Skip | 0.777394 |
| cases | 0.246244 |
| United States | 0.460811 |
| page options Skip | 0.91163 |
| fever | 0.265063 |
| combat | 0.255015 |
|
| Kansas | 0.245233 |
| virus | 0.257268 |
| navigation Skip | 0.789164 |
| sore throat | 0.526898 |
| Military personnel | 0.455616 |
| headache | 0.272585 |
| Fort Riley | 0.48442 |
|
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Preventing Chronic Disease - CDC: Volume 10, 2013: 12_0238 |
Volumen 10 — el 25 de julio de 2013. |
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Centers for Disease Control and Prevention |
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El tabaquismo y la enfermedad de Buerger - Enfermedades & afecciones - Consejos de exfumadores |
La campaña Consejos de exfumadores muestra casos reales de personas que padecen afecciones por fumar o por la exposición al humo de segunda mano. |
| Archivo Apple Quicktime | 0.706668 |
| Archivo RealPlayer | 0.59422 |
| Archivo Zip Comprimido | 0.701663 |
| Archivo Microsoft PowerPoint | 0.730005 |
|
| Archivo Adobe PDF | 0.705275 |
| Archivo Microsoft Excel | 0.701641 |
| Archivo Microsoft | 0.965209 |
|
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Email Updates: March 10, 2014'Clinicians Outreach and Communication Activity (COCA) |
CDC Clinician Outreach and Communication Activity (COCA). Providing clinicians the most current and reliable information on emerging public health threats, such as pandemics, natural disasters, and bioterrorism. |
| Public Health Matters | 0.707214 |
| Emergency Preparedness | 0.654401 |
| FDA Safety Information | 0.699253 |
| – (CDC) | 0.74823 |
| new avian influenza | 0.681956 |
| CDC Science Clips | 0.845884 |
| Additional COCA Conference | 0.691582 |
| CDC Influenza Division | 0.822926 |
| new H7N9 virus | 0.720209 |
| important safety information | 0.670209 |
| National Poison Prevention | 0.778786 |
| health care providers | 0.771014 |
| Free CE credit/contact | 0.660854 |
| Weekly Flu View | 0.659839 |
| human medical products | 0.647798 |
| territorial health | 0.624405 |
| public health areas | 0.716843 |
| Current Travel Warnings | 0.647017 |
| various public health | 0.706155 |
| seasonal flu | 0.654858 |
| Event Reporting Program | 0.650696 |
| Roos Foods | 0.646979 |
| Toxic Substances Web | 0.796028 |
| United States | 0.6714 |
|
| chikungunya virus | 0.916696 |
| CDC professionals | 0.762725 |
| COCA Email Update | 0.702837 |
| FDA Investigates presence | 0.662959 |
| town hall teleconference | 0.799675 |
| public health community | 0.710618 |
| public health professionals | 0.716115 |
| National Flood Safety | 0.662558 |
| local chikungunya virus | 0.813538 |
| Flood Safety Awareness | 0.766171 |
| public health | 0.933011 |
| chikungunya virus epidemiology | 0.78768 |
| Substances Web Portal | 0.794855 |
| Specific Hazards preparedness | 0.671951 |
| mosquito-borne virus | 0.65889 |
| subject matter expert | 0.660656 |
| in-person training centers | 0.651581 |
| FoodSafety.gov Reports FDA | 0.681033 |
| weekly influenza surveillance | 0.655381 |
| severe respiratory illness | 0.636972 |
| CDC Vital Signs | 0.838666 |
| USDA Food Recalls | 0.645111 |
| Response Training Resources | 0.661183 |
| CDC subject matter | 0.991732 |
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How CDC Labs keep you safe |
CDC ensures America’s health security with more than 150 state-of-the-art laboratories that are a key line of defense against emerging health threats. |
| faster technologies | 0.364765 |
| CDC | 0.958394 |
| fast-moving disease outbreaks | 0.609314 |
| safety monitoring | 0.352941 |
| latest best practices | 0.511325 |
| laboratory science | 0.401088 |
| highest biosafety level | 0.512072 |
| infectious organisms | 0.399101 |
| advanced molecular methods | 0.498313 |
| relatively safe materials | 0.493428 |
| laboratory training | 0.373721 |
| biosecurity threats | 0.412136 |
| latest science | 0.358211 |
| Strong laboratory networks | 0.532171 |
| Infectious Disease Outbreaks | 0.605792 |
| genomic sequence | 0.358481 |
| special training | 0.357963 |
| environmental hazards | 0.383579 |
| safety processes | 0.360971 |
| patient samples | 0.362312 |
| vital reference laboratories | 0.629173 |
| food-borne outbreaks | 0.490229 |
| disease investigation | 0.373003 |
| critical disease detection | 0.528818 |
| health threats | 0.548556 |
|
| laboratory safety workgroups | 0.511605 |
| Advanced Molecular Detection | 0.499716 |
| state-of-the-art laboratories | 0.510261 |
| 21st century | 0.366491 |
| health risk factors | 0.555703 |
| deadliest germs | 0.523357 |
| health security | 0.405815 |
| CDC laboratories | 0.86343 |
| CDC scientists | 0.691311 |
| key findings | 0.347641 |
| laboratory incidents | 0.378009 |
| potential risk | 0.35693 |
| Key laboratory work | 0.548747 |
| human error | 0.352305 |
| deadly Ebola strain | 0.50433 |
| latest technology | 0.386669 |
| AMD method | 0.375764 |
| significant leaps | 0.369543 |
| lab staff | 0.356029 |
| blood supply | 0.386951 |
| key line | 0.39044 |
| biosafety levels | 0.400699 |
| passenger jet | 0.357005 |
| laboratory practices | 0.375545 |
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