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September is National Childhood Obesity Month | CDC Features |
The numbers of young people affected by obesity remain at high levels. Learn what you can do to combat childhood obesity.
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| healthy diet | 0.494695 |
| ways communities | 0.441932 |
| free drinking water | 0.509121 |
| physical activity behaviors | 0.586507 |
| lower-calorie foods | 0.43338 |
| National Childhood Obesity | 0.783794 |
| high cholesterol | 0.440239 |
| children | 0.674796 |
| age appropriate activities | 0.517808 |
| Certain groups | 0.442334 |
| mental health problems | 0.556075 |
| healthier foods | 0.547359 |
| risk factors | 0.437569 |
| Eat healthy meals | 0.595659 |
| body mass index | 0.51031 |
| healthy eating | 0.491487 |
| joint problems | 0.433682 |
| regular physical activity | 0.560413 |
| healthy growth | 0.538133 |
| Learn ways | 0.458236 |
| physical activity opportunities | 0.555194 |
| healthy school environment | 0.592919 |
| sure drinking water | 0.518152 |
| United States | 0.443991 |
| normal weight peers | 0.736535 |
|
| chronic health conditions | 0.55707 |
| childhood healthy weight | 0.632238 |
| Health Care Providers | 0.52595 |
| heart disease | 0.557646 |
| limit juice intake | 0.514675 |
| drinking water | 0.528209 |
| Help children | 0.480813 |
| lifelong physical | 0.455974 |
| local health departments | 0.522998 |
| simple solution | 0.442014 |
| limited screen time | 0.517837 |
| Adult obesity | 0.613427 |
| higher risk | 0.550371 |
| high calorie foods | 0.553533 |
| good health | 0.459642 |
| affordable food options | 0.507802 |
| healthy weight | 0.707813 |
| Teen BMI Calculator | 0.51566 |
| easy access | 0.530132 |
| physical activity | 0.972094 |
| potential weight issues | 0.545389 |
| Measure children | 0.457921 |
| high blood pressure | 0.55202 |
| childhood obesity | 0.857849 |
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Youth Tobacco Survey (YTS) - Smoking & Tobacco Use |
Data and statistics survey on the Youth Tobacco Survey (YTS). |
| documents | 0.316328 |
| control programs | 0.56735 |
| students | 0.269569 |
| Individual State Departments | 0.918612 |
| YTS Data | 0.51537 |
| grades | 0.271663 |
| young people | 0.56576 |
| zip software | 0.542018 |
| states | 0.376141 |
| capacity | 0.271013 |
| state agencies | 0.55751 |
| Youth Tobacco Survey | 0.878895 |
| trial version | 0.527251 |
|
| current users | 0.564169 |
| CDC staff | 0.615356 |
| tobacco prevention | 0.619698 |
| OSH | 0.47172 |
| YTS Startup Package | 0.862664 |
| master file | 0.526538 |
| following components | 0.590226 |
| WinZip | 0.294269 |
| Health plan | 0.5854 |
| purposes | 0.265828 |
| response | 0.259946 |
| continuous technical assistance | 0.836807 |
| organizations | 0.262734 |
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Association of workplace supports with active commuting. |
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| bicycle storage | 0.418664 |
| active commuting outcome | 0.500954 |
| Kansas State University | 0.393942 |
| physical workplace support | 0.445934 |
| active commuting behaviors | 0.502363 |
| moderate-intensity physical activity | 0.392855 |
| Binomial logistic regression | 0.404898 |
| cultural supports | 0.602346 |
| active transportation | 0.378583 |
| 0-7 d/wk | 0.424501 |
| active commuting differ | 0.49035 |
| workplace environment | 0.377967 |
| potential physical changes | 0.368022 |
| Public health guidelines | 0.362635 |
| physical health | 0.362737 |
| Yes/No/Don’t know | 0.36805 |
| physical support | 0.411706 |
| single physical support | 0.380171 |
| women | 0.445703 |
| physical workplace supports | 0.472116 |
| cultural support | 0.435146 |
| study | 0.386145 |
| physical supports | 0.578883 |
| age group | 0.372518 |
|
| bicycle storage policies | 0.403067 |
| Active commuting frequency | 0.527219 |
| city government bicycle | 0.364032 |
| utilitarian physical activity | 0.418897 |
| physical workplace | 0.510492 |
| active commuting | 0.984341 |
| active commuting behavior | 0.70082 |
| workers actively commute | 0.379009 |
| studies | 0.375007 |
| bicycle storage policy | 0.370575 |
| overall physical activity | 0.411243 |
| participants | 0.409851 |
| individual supports | 0.373698 |
| single physical workplace | 0.405905 |
| health | 0.388379 |
| sample | 0.405976 |
| online survey | 0.384441 |
| guidelines advisory committee | 0.379707 |
| physical activity | 0.698621 |
| workplace interventions | 0.381292 |
| bicycle parking | 0.461102 |
| employee active commuting | 0.569499 |
| older adults | 0.370215 |
| Introduction
Active commuting | 0.529994 |
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ATSDR launches health survey of Marine Corps personnel and civilians - Press Release: June 22, 2011 |
No Progress in Salmonella During Past 15 Years |
| North Carolina | 0.28112 |
| chemical exposures | 0.29122 |
| health survey | 0.743909 |
| toxic substances. | 0.252697 |
| Base Camp Lejeune | 0.529715 |
| Disease Control | 0.263692 |
| federal government | 0.257391 |
| ATSDR Health Survey | 0.729558 |
| scientifically useful health | 0.632486 |
| Health care providers | 0.407002 |
| Toxic Substance | 0.250147 |
| family members | 0.401361 |
| National Center | 0.265433 |
| Environmental Health | 0.305362 |
| survey findings | 0.302512 |
| sister agency | 0.397032 |
| Camp Pendleton | 0.921463 |
| detailed instructions | 0.272158 |
| ATSDR action | 0.521501 |
| civilian employees | 0.256299 |
| ATSDR | 0.782508 |
| mail notification | 0.25102 |
| Marine Corps Personnel | 0.384579 |
| peer-reviewed scientific journal | 0.360939 |
| health history | 0.321133 |
|
| High levels | 0.266138 |
| harmful exposures | 0.255983 |
| Eligible participants | 0.412795 |
| survey participant | 0.289475 |
| useful health information | 0.612957 |
| Web-based version | 0.258348 |
| U.S. DEPARTMENT | 0.36394 |
| Marine Corps | 0.597178 |
| potential exposure | 0.258225 |
| Christopher J. Portier | 0.453853 |
| contaminated water | 0.257986 |
| Camp Lejeune | 0.763752 |
| comprehensive health information | 0.437164 |
| comparison purposes | 0.264871 |
| congressional mandate | 0.263364 |
| accurate findings | 0.275657 |
| duty Marines | 0.254465 |
| mid-July. Portier | 0.303396 |
| civilian workers | 0.260471 |
| largest health survey | 0.476834 |
| Camp Lejeune. | 0.2868 |
| Disease Registry | 0.419601 |
| Toxic Substances | 0.285181 |
| public health agency | 0.416044 |
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Methyl hydrazine - NIOSH Pocket Guide to Chemical Hazards |
null |
| 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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Transmission | Ebola Hemorrhagic Fever |
null |
| hospital staff | 0.298211 |
| virus transmission | 0.328825 |
| large numbers | 0.31566 |
| wild animals | 0.305788 |
| Ebola virus | 0.853916 |
| instruments | 0.251611 |
| direct contact | 0.3145 |
| Ebola transmission | 0.601247 |
| contact | 0.373365 |
| affected people | 0.309459 |
| multiple spillover events | 0.421325 |
| mosquitoes | 0.22114 |
| natural reservoir host | 0.415333 |
| personal protective equipment | 0.378651 |
| primates | 0.242926 |
| bushmeat | 0.226523 |
| public health partners | 0.375357 |
| body fluids | 0.303866 |
| patient care | 0.297225 |
| past Ebola outbreaks | 0.753565 |
| monkeys | 0.246464 |
| highest risk | 0.300973 |
| scientists | 0.220299 |
| syringes | 0.221211 |
|
| Ebola patients | 0.668656 |
| Ebola | 0.964083 |
| Person-to-person transmission | 0.322386 |
| infected bats | 0.354324 |
| semen | 0.325181 |
| healthcare personnel | 0.298782 |
| Ebola viruses | 0.694522 |
| mucous membranes | 0.315934 |
| adequate sterilization | 0.301223 |
| close contact | 0.306021 |
| Proper cleaning | 0.297747 |
| man | 0.231025 |
| infected blood | 0.34753 |
| medical equipment | 0.297555 |
| sex | 0.234632 |
| fruit bat | 0.315366 |
| food | 0.238117 |
| way | 0.22047 |
| infected animal | 0.368116 |
| healthcare settings | 0.371387 |
| Healthcare providers | 0.302036 |
| time | 0.230414 |
| male Ebola survivors | 0.675366 |
| vaginal fluids | 0.299471 |
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Tetanus, Diphtheria, Pertussis Vaccination Coverage Before,During, and After Pregnancy - 16 States and New York City,2011 |
Indu B. Ahluwalia, PhD1; Helen Ding, MD2; Denise D'Angelo, MPH1; Kristen H. Shealy, MSPH2; James A. |
| health care provider | 0.355226 |
| Tdap recommendation | 0.39281 |
| Kenneth D. Rosenberg | 0.354325 |
| Weighted PRAMS data | 0.400363 |
| non-Hispanic black women | 0.37016 |
| seasonal influenza vaccination | 0.421522 |
| New York City | 0.406654 |
| pregnant women | 0.48961 |
| health care providers | 0.379854 |
| demographic groups | 0.353817 |
| health insurance coverage | 0.3696 |
| National Center | 0.359244 |
| pregnancy | 0.403264 |
| PRAMS participants | 0.363803 |
| Oregon PRAMS survey | 0.392427 |
| prenatal care | 0.442662 |
| PRAMS program | 0.369456 |
| postpartum vaccination | 0.433145 |
| vaccination promotion | 0.401909 |
| live-born infant | 0.475423 |
| women | 0.489732 |
| Indu B. Ahluwalia | 0.405421 |
| higher postpartum coverage | 0.372959 |
| overall coverage | 0.359539 |
| postpartum Tdap vaccination | 0.45975 |
|
| wide variation | 0.35377 |
| Kristen H. Shealy | 0.356552 |
| PRAMS response threshold | 0.391645 |
| Tdap vaccination postpartum | 0.536644 |
| greater Tdap coverage | 0.380916 |
| Pregnancy Risk Assessment | 0.366395 |
| state-specific Tdap vaccination | 0.471934 |
| overall Tdap vaccination | 0.457421 |
| ACIP | 0.359389 |
| immediate postpartum vaccination | 0.427526 |
| PRAMS data | 0.50008 |
| different data sets | 0.356424 |
| median percentage | 0.353253 |
| health care | 0.389807 |
| similar vaccination recommendations | 0.422356 |
| James A. Singleton | 0.356005 |
| current Tdap recommendations | 0.363286 |
| optimal time | 0.353518 |
| prenatal care providers | 0.364978 |
| Tdap vaccination status | 0.643544 |
| health care coverage | 0.368966 |
| Tdap vaccination coverage | 0.839805 |
| unknown Tdap vaccination | 0.440869 |
| non-Hispanic white women | 0.417589 |
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New School Meal Regulations and Consumption of Flavored Milk in Ten US Elementary Schools, 2010 and 2013 |
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. |
| elementary school students | 0.50147 |
| milk consumption | 0.818962 |
| B. Chocolate milk | 0.568999 |
| southern schools | 0.510349 |
| school lunch programs | 0.486443 |
| public school districts | 0.491674 |
| school meal standards | 0.482082 |
| excess weight gain | 0.469848 |
| Vermont Agricultural Experiment | 0.462713 |
| standard flavored milk | 0.6434 |
| nutrient intake | 0.501395 |
| Diet Assoc | 0.500889 |
| Child Nutr Manag | 0.461698 |
| overall diet quality | 0.477311 |
| flavored milk | 0.973516 |
| children | 0.546748 |
| flavored milks | 0.482826 |
| flavored milk formulations | 0.640744 |
| plain milk | 0.59255 |
| noon beverage consumption | 0.487116 |
| shortfall nutrients | 0.475941 |
| bone mass accumulation | 0.469997 |
| southern United States | 0.468323 |
| Vermont Institutional Review | 0.466636 |
|
| milk containers | 0.558398 |
| school districts | 0.495283 |
| sugar-sweetened beverage consumption | 0.489405 |
| recent American Academy | 0.462465 |
| school milk | 0.602283 |
| Economic Research | 0.462665 |
| beverage consumption | 0.496112 |
| linear mixed models | 0.464552 |
| fluid milk | 0.537774 |
| Food Sciences Department | 0.522035 |
| school nutrition directors | 0.493281 |
| Johnson RK | 0.464153 |
| school meals | 0.513373 |
| milk processors | 0.560957 |
| diverse sample | 0.469223 |
| overall milk consumption | 0.644655 |
| fewer children | 0.481095 |
| schools | 0.535223 |
| quasi-experimental plate-waste study | 0.47088 |
| Milk consumption patterns | 0.615406 |
| school lunch | 0.506902 |
| coronary heart disease | 0.533154 |
| children’s diets | 0.480649 |
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Disparities in Consistent Retention in HIV Care - 11 Statesand the District of Columbia, 2011-2013 | MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| National HIV/AIDS Strategy | 0.225834 |
| mitigating racial/ethnic disparities | 0.212872 |
| United States | 0.214497 |
| HIV prevention | 0.279295 |
| National HIV Surveillance | 0.297709 |
| blacks | 0.296795 |
| HIV care retention | 0.425723 |
| transmission category | 0.282478 |
| HIV infections | 0.261577 |
| clinical outcomes | 0.216399 |
| care facilitates ART | 0.200616 |
| HIV outcomes.** | 0.248117 |
| early HIV care | 0.341412 |
| complete laboratory | 0.234573 |
| HIV care limit | 0.339677 |
| viral suppression | 0.209901 |
| HIV diagnosis | 0.26476 |
|
| non-Hispanic blacks/African Americans | 0.249182 |
| health care providers | 0.203877 |
| racial/ethnic groups | 0.337375 |
| HIV surveillance data | 0.335024 |
| HIV outcomes | 0.301257 |
| HIV care | 0.902535 |
| reduced HIV transmission | 0.300199 |
| racial/ethnic disparities | 0.299964 |
| initial outpatient HIV | 0.267618 |
| persons | 0.245951 |
| HIV care engagement | 0.458677 |
| Fewer blacks | 0.213948 |
| human immunodeficiency virus | 0.243884 |
| HIV case management | 0.274412 |
| HIV infection | 0.553328 |
| consistent retention | 0.365922 |
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Prevalence of Inflammatory Bowel Disease Among Adults Aged?18 Years - United States, 2015 | MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| insurance coverage type | 0.603737 |
| representative data sources | 0.537475 |
| poverty status | 0.513628 |
| disease prevalence estimates | 0.591975 |
| higher prevalence | 0.722345 |
| higher prevalence rates | 0.604407 |
| National Health Interview | 0.539819 |
| central city | 0.49319 |
| population subgroups | 0.517161 |
| surgical procedures | 0.52711 |
| noninstitutionalized U.S. adult | 0.54345 |
| education level | 0.514613 |
| ulcerative colitis | 0.748705 |
| Sample Adult Core | 0.653982 |
| Crohn’s disease | 0.593667 |
| IBD status | 0.546043 |
| health insurance coverage | 0.60625 |
| claims data | 0.517224 |
| National Center | 0.493576 |
| U.S. health care | 0.614299 |
| financial burdens IBD | 0.574268 |
| Health Interview Survey | 0.539435 |
| inflammatory bowel disease | 0.918854 |
| significantly higher prevalence | 0.540867 |
| public health practice | 0.494946 |
|
| sociodemographic characteristics | 0.579675 |
| U.S. adult population | 0.608994 |
| federal poverty level | 0.527498 |
| United States | 0.600188 |
| adults | 0.802202 |
| IBD | 0.911289 |
| administrative claims data | 0.483677 |
| NHIS Sample Adult | 0.594912 |
| high school level | 0.536579 |
| Adult Core component | 0.532691 |
| IBD prevalence | 0.69756 |
| IBD cases | 0.561648 |
| non-Hispanic whites | 0.533907 |
| extensive morbidity | 0.482372 |
| nationally representative estimates | 0.488777 |
| representative data source | 0.627996 |
| nationally representative data | 0.595719 |
| U.S. adults | 0.742141 |
| health | 0.627897 |
| national prevalence estimates | 0.568074 |
| relative standard error | 0.569404 |
| IBD prevalence estimates | 0.659443 |
| employment status | 0.518439 |
| metropolitan statistical area | 0.577898 |
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