Mmwr Surveillance Summaries最新文献

{"title":"Rural and Urban Differences in Air Quality, 2008-2012, and Community Drinking Water Quality, 2010-2015 - United States.","authors":"Heather Strosnider, Caitlin Kennedy, Michele Monti, Fuyuen Yip","doi":"10.15585/mmwr.ss6613a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6613a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>The places in which persons live, work, and play can contribute to the development of adverse health outcomes. Understanding the differences in risk factors in various environments can help to explain differences in the occurrence of these outcomes and can be used to develop public health programs, interventions, and policies. Efforts to characterize urban and rural differences have largely focused on social and demographic characteristics. A paucity of national standardized environmental data has hindered efforts to characterize differences in the physical aspects of urban and rural areas, such as air and water quality.</p><p><strong>Reporting period: </strong>2008-2012 for air quality and 2010-2015 for water quality.</p><p><strong>Description of system: </strong>Since 2002, CDC's National Environmental Public Health Tracking Program has collaborated with federal, state, and local partners to gather standardized environmental data by creating national data standards, collecting available data, and disseminating data to be used in developing public health actions. The National Environmental Public Health Tracking Network (i.e., the tracking network) collects data provided by national, state, and local partners and includes 21 health outcomes, exposures, and environmental hazards. To assess environmental factors that affect health, CDC analyzed three air-quality measures from the tracking network for all counties in the contiguous United States during 2008-2012 and one water-quality measure for 26 states during 2010-2015. The three air-quality measures include 1) total number of days with fine particulate matter (PM<sub>2.5</sub>) levels greater than the U.S. Environmental Protection Agency's (EPA's) National Ambient Air Quality Standards (NAAQS) for 24-hour average PM<sub>2.5</sub> (PM<sub>2.5</sub> days); 2) mean annual average ambient concentrations of PM<sub>2.5</sub> in micrograms per cubic meter (mean PM<sub>2.5</sub>); and 3) total number of days with maximum 8-hour average ozone concentrations greater than the NAAQS (ozone days). The water-quality measure compared the annual mean concentration for a community water system (CWS) to the maximum contaminant level (MCL) defined by EPA for 10 contaminants: arsenic, atrazine, di(2-ethylhexyl) phthalate (DEHP), haloacetic acids (HAA5), nitrate, perchloroethene (PCE), radium, trichloroethene (TCE), total trihalomethanes (TTHM), and uranium. Findings are presented by urban-rural classification scheme: four metropolitan (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) and two nonmetropolitan (micropolitan and noncore) categories. Regression modeling was used to determine whether differences in the measures by urban-rural categories were statistically significant.</p><p><strong>Results: </strong>Patterns for all three air-quality measures suggest that air quality improves as areas become more rural (or less urb","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 13","pages":"1-10"},"PeriodicalIF":24.9,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15585/mmwr.ss6613a1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35112794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Malaria Surveillance - United States, 2014.","authors":"Kimberly E Mace, Paul M Arguin","doi":"10.15585/mmwr.ss6612a1","DOIUrl":"10.15585/mmwr.ss6612a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Malaria in humans is caused by intraerythrocytic protozoa of the genus Plasmodium. These parasites are transmitted by the bite of an infective female Anopheles mosquito. The majority of malaria infections in the United States occur among persons who have traveled to regions with ongoing malaria transmission. However, malaria is occasionally acquired by persons who have not traveled out of the country through exposure to infected blood products, congenital transmission, laboratory exposure, or local mosquitoborne transmission. Malaria surveillance in the United States is conducted to identify episodes of local transmission and to guide prevention recommendations for travelers.</p><p><strong>Period covered: </strong>This report summarizes cases in persons with onset of illness in 2014 and trends during previous years.</p><p><strong>Description of system: </strong>Malaria cases diagnosed by blood film, polymerase chain reaction, or rapid diagnostic tests are reported to local and state health departments by health care providers or laboratory staff. Case investigations are conducted by local and state health departments, and reports are transmitted to CDC through the National Malaria Surveillance System, National Notifiable Diseases Surveillance System, or direct CDC consultations. CDC conducts antimalarial drug resistance marker testing on blood samples submitted by health care providers or local or state health departments. Data from these reporting systems serve as the basis for this report.</p><p><strong>Results: </strong>CDC received reports of 1,724 confirmed malaria cases, including one congenital case and two cryptic cases, with onset of symptoms in 2014 among persons in the United States. The number of confirmed cases in 2014 is consistent with the number of confirmed cases reported in 2013 (n = 1,741; this number has been updated from a previous publication to account for delayed reporting for persons with symptom onset occurring in late 2013). Plasmodium falciparum, P. vivax, P. ovale, and P. malariae were identified in 66.1%, 13.3%, 5.2%, and 2.7% of cases, respectively. Less than 1.0% of patients were infected with two species. The infecting species was unreported or undetermined in 11.7% of cases. CDC provided diagnostic assistance for 14.2% of confirmed cases and tested 12.0% of P. falciparum specimens for antimalarial resistance markers. Of patients who reported purpose of travel, 57.5% were visiting friends and relatives (VFR). Among U.S. residents for whom information on chemoprophylaxis use and travel region was known, 7.8% reported that they initiated and adhered to a chemoprophylaxis drug regimen recommended by CDC for the regions to which they had traveled. Thirty-two cases were among pregnant women, none of whom had adhered to chemoprophylaxis. Among all reported cases, 17.0% were classified as severe illness, and five persons with malaria died. CDC received 137 P. falciparum-positive sam","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 12","pages":"1-24"},"PeriodicalIF":37.3,"publicationDate":"2017-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829864/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35026354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surveillance of Vaccination Coverage among Adult Populations - United States, 2015.","authors":"Walter W Williams, Peng-Jun Lu, Alissa O'Halloran, David K Kim, Lisa A Grohskopf, Tamara Pilishvili, Tami H Skoff, Noele P Nelson, Rafael Harpaz, Lauri E Markowitz, Alfonso Rodriguez-Lainz, Amy Parker Fiebelkorn","doi":"10.15585/mmwr.ss6611a1","DOIUrl":"10.15585/mmwr.ss6611a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Overall, the prevalence of illness attributable to vaccine-preventable diseases is greater among adults than among children. Adults are recommended to receive vaccinations based on their age, underlying medical conditions, lifestyle, prior vaccinations, and other considerations. Updated vaccination recommendations from CDC are published annually in the U.S. Adult Immunization Schedule. Despite longstanding recommendations for use of many vaccines, vaccination coverage among U.S. adults is low.</p><p><strong>Period covered: </strong>August 2014-June 2015 (for influenza vaccination) and January-December 2015 (for pneumococcal, tetanus and diphtheria [Td] and tetanus and diphtheria with acellular pertussis [Tdap], hepatitis A, hepatitis B, herpes zoster, and human papillomavirus [HPV] vaccination).</p><p><strong>Description of system: </strong>The National Health Interview Survey (NHIS) is a continuous, cross-sectional national household survey of the noninstitutionalized U.S. civilian population. In-person interviews are conducted throughout the year in a probability sample of households, and NHIS data are compiled and released annually. The survey objective is to monitor the health of the U.S. population and provide estimates of health indicators, health care use and access, and health-related behaviors.</p><p><strong>Results: </strong>Compared with data from the 2014 NHIS, increases in vaccination coverage occurred for influenza vaccine among adults aged ≥19 years (a 1.6 percentage point increase compared with the 2013-14 season to 44.8%), pneumococcal vaccine among adults aged 19-64 years at increased risk for pneumococcal disease (a 2.8 percentage point increase to 23.0%), Tdap vaccine among adults aged ≥19 years and adults aged 19-64 years (a 3.1 percentage point and 3.3 percentage point increase to 23.1% and to 24.7%, respectively), herpes zoster vaccine among adults aged ≥60 years and adults aged ≥65 years (a 2.7 percentage point and 3.2 percentage point increase to 30.6% and to 34.2%, respectively), and hepatitis B vaccine among health care personnel (HCP) aged ≥19 years (a 4.1 percentage point increase to 64.7%). Herpes zoster vaccination coverage in 2015 met the Healthy People 2020 target of 30%. Aside from these modest improvements, vaccination coverage among adults in 2015 was similar to estimates from 2014. Racial/ethnic differences in coverage persisted for all seven vaccines, with higher coverage generally for whites compared with most other groups. Adults without health insurance reported receipt of influenza vaccine (all age groups), pneumococcal vaccine (adults aged 19-64 years at increased risk), Td vaccine (adults aged ≥19 years, 19-64 years, and 50-64 years), Tdap vaccine (adults aged ≥19 years and 19-64 years), hepatitis A vaccine (adults aged ≥19 years overall and among travelers), hepatitis B vaccine (adults aged ≥19 years, 19-49 years, and among travelers), herpes zoster vaccine (adult","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 11","pages":"1-28"},"PeriodicalIF":24.9,"publicationDate":"2017-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15585/mmwr.ss6611a1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34967314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diabetes Self-Management Education Programs in Nonmetropolitan Counties - United States, 2016.","authors":"Stephanie A Rutledge, Svetlana Masalovich, Rachel J Blacher, Magon M Saunders","doi":"10.15585/mmwr.ss6610a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6610a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Diabetes self-management education (DSME) is a clinical practice intended to improve preventive practices and behaviors with a focus on decision-making, problem-solving, and self-care. The distribution and correlates of established DSME programs in nonmetropolitan counties across the United States have not been previously described, nor have the characteristics of the nonmetropolitan counties with DSME programs.</p><p><strong>Reporting period: </strong>July 2016.</p><p><strong>Description of systems: </strong>DSME programs recognized by the American Diabetes Association or accredited by the American Association of Diabetes Educators (i.e., active programs) as of July 2016 were shared with CDC by both organizations. The U.S. Census Bureau's census geocoder was used to identify the county of each DSME program site using documented addresses. County characteristic data originated from the U.S. Census Bureau, compiled by the U.S. Department of Agriculture's Economic Research Service into the 2013 Atlas of Rural and Small-Town America data set. County levels of diagnosed diabetes prevalence and incidence, as well as the number of persons with diagnosed diabetes, were previously estimated by CDC. This report defined nonmetropolitan counties using the rural-urban continuum code from the 2013 Atlas of Rural and Small-Town America data set. This code included six nonmetropolitan categories of 1,976 urban and rural counties (62% of counties) adjacent to and nonadjacent to metropolitan counties.</p><p><strong>Results: </strong>In 2016, a total of 1,065 DSME programs were located in 38% of the 1,976 nonmetropolitan counties; 62% of nonmetropolitan counties did not have a DSME program. The total number of DSME programs for nonmetropolitan counties with at least one DSME program ranged from 1 to 8, with an average of 1.4 programs. After adjusting for county-level characteristics, the odds of a nonmetropolitan county having at least one DSME program increased as the percentage insured increased (adjusted odds ratio [AOR] = 1.10, 95% confidence interval [CI] = 1.08-1.13), the percentage with a high school education or less decreased (AOR = 1.06, 95% CI = 1.04-1.07), the unemployment rate decreased (AOR = 1.19, 95% CI = 1.11-1.23), and the natural logarithm of the number of persons with diabetes increased (AOR = 3.63, 95% CI = 3.15-4.19).</p><p><strong>Interpretation: </strong>In 2016, there were few DMSE programs in nonmetropolitan, socially disadvantaged counties in the United States. The number of persons with diabetes, percentage insured, percentage with a high school education or less, and the percentage unemployed were significantly associated with whether a DSME program was located in a nonmetropolitan county.</p><p><strong>Public health action: </strong>Monitoring the distribution of DSME programs at the county level provides insight needed to strategically address rural disparities in diabetes care and outcomes. The","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 10","pages":"1-6"},"PeriodicalIF":24.9,"publicationDate":"2017-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829897/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34948254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differences in Health Care, Family, and Community Factors Associated with Mental, Behavioral, and Developmental Disorders Among Children Aged 2-8 Years in Rural and Urban Areas - United States, 2011-2012.","authors":"Lara R Robinson, Joseph R Holbrook, Rebecca H Bitsko, Sophie A Hartwig, Jennifer W Kaminski, Reem M Ghandour, Georgina Peacock, Akilah Heggs, Coleen A Boyle","doi":"10.15585/mmwr.ss6608a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6608a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Mental, behavioral, and developmental disorders (MBDDs) begin in early childhood and often affect lifelong health and well-being. Persons who live in rural areas report more health-related disparities than those in urban areas, including poorer health, more health risk behaviors, and less access to health resources.</p><p><strong>Reporting period: </strong>2011-2012.</p><p><strong>Description of system: </strong>The National Survey of Children's Health (NSCH) is a cross-sectional, random-digit-dial telephone survey of parents or guardians that collects information on noninstitutionalized children aged <18 years in the United States. Interviews included indicators of health and well-being, health care access, and family and community characteristics. Using data from the 2011-2012 NSCH, this report examines variations in health care, family, and community factors among children aged 2-8 years with and without MBDDs in rural and urban settings. Restricting the data to U.S. children aged 2-8 years with valid responses for child age and sex, each MBDD, and zip code resulted in an analytic sample of 34,535 children; MBDD diagnosis was determined by parent report and was not validated with health care providers or medical records.</p><p><strong>Results: </strong>A higher percentage of all children in small rural and large rural areas compared with all children in urban areas had parents who reported experiencing financial difficulties (i.e., difficulties meeting basic needs such as food and housing). Children in all rural areas more often lacked amenities and lived in a neighborhood in poor condition. However, a lower percentage of children in small rural and isolated areas had parents who reported living in an unsafe neighborhood, and children in isolated areas less often lived in a neighborhood lacking social support, less often lacked a medical home, and less often had a parent with fair or poor mental health. Across rural subtypes, approximately one in six young children had a parent-reported MBDD diagnosis. A higher prevalence was found among children in small rural areas (18.6%) than in urban areas (15.2%). In urban and the majority of rural subtypes, children with an MBDD more often lacked a medical home, had a parent with poor mental health, lived in families with financial difficulties, and lived in a neighborhood lacking physical and social resources than children without an MBDD within each of those community types. Only in urban areas did a higher percentage of children with MBDDs lack health insurance than children without MBDDs. After adjusting for race/ethnicity and poverty among children with MBDDs, those in rural areas more often had a parent with poor mental health and lived in resource-low neighborhoods than those in urban areas.</p><p><strong>Interpretation: </strong>Certain health care, family, and community disparities were more often reported among children with MBDDS than among children with","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 8","pages":"1-11"},"PeriodicalIF":24.9,"publicationDate":"2017-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15585/mmwr.ss6608a1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34818950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Traumatic Brain Injury-Related Emergency Department Visits, Hospitalizations, and Deaths - United States, 2007 and 2013.","authors":"Christopher A Taylor, Jeneita M Bell, Matthew J Breiding, Likang Xu","doi":"10.15585/mmwr.ss6609a1","DOIUrl":"10.15585/mmwr.ss6609a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Traumatic brain injury (TBI) has short- and long-term adverse clinical outcomes, including death and disability. TBI can be caused by a number of principal mechanisms, including motor-vehicle crashes, falls, and assaults. This report describes the estimated incidence of TBI-related emergency department (ED) visits, hospitalizations, and deaths during 2013 and makes comparisons to similar estimates from 2007.</p><p><strong>Reporting period: </strong>2007 and 2013.</p><p><strong>Description of system: </strong>State-based administrative health care data were used to calculate estimates of TBI-related ED visits and hospitalizations by principal mechanism of injury, age group, sex, and injury intent. Categories of injury intent included unintentional (motor-vehicle crashes, falls, being struck by or against an object, mechanism unspecified), intentional (self-harm and assault/homicide), and undetermined intent. These health records come from the Healthcare Cost and Utilization Project's National Emergency Department Sample and National Inpatient Sample. TBI-related death analyses used CDC multiple-cause-of-death public-use data files, which contain death certificate data from all 50 states and the District of Columbia.</p><p><strong>Results: </strong>In 2013, a total of approximately 2.8 million TBI-related ED visits, hospitalizations, and deaths (TBI-EDHDs) occurred in the United States. This consisted of approximately 2.5 million TBI-related ED visits, approximately 282,000 TBI-related hospitalizations, and approximately 56,000 TBI-related deaths. TBIs were diagnosed in nearly 2.8 million (1.9%) of the approximately 149 million total injury- and noninjury-related EDHDs that occurred in the United States during 2013. Rates of TBI-EDHDs varied by age, with the highest rates observed among persons aged ≥75 years (2,232.2 per 100,000 population), 0-4 years (1,591.5), and 15-24 years (1,080.7). Overall, males had higher age-adjusted rates of TBI-EDHDs (959.0) compared with females (810.8) and the most common principal mechanisms of injury for all age groups included falls (413.2, age-adjusted), being struck by or against an object (142.1, age-adjusted), and motor-vehicle crashes (121.7, age-adjusted). The age-adjusted rate of ED visits was higher in 2013 (787.1) versus 2007 (534.4), with fall-related TBIs among persons aged ≥75 years accounting for 17.9% of the increase in the number of TBI-related ED visits. The number and rate of TBI-related hospitalizations also increased among persons aged ≥75 years (from 356.9 in 2007 to 454.4 in 2013), primarily because of falls. Whereas motor-vehicle crashes were the leading cause of TBI-related deaths in 2007 in both number and rate, in 2013, intentional self-harm was the leading cause in number and rate. The overall age-adjusted rate of TBI-related deaths for all ages decreased from 17.9 in 2007 to 17.0 in 2013; however, age-adjusted TBI-related death rates attributable to","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 9","pages":"1-16"},"PeriodicalIF":37.3,"publicationDate":"2017-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829835/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34818952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surveillance for Health Care Access and Health Services Use, Adults Aged 18-64 Years - Behavioral Risk Factor Surveillance System, United States, 2014.","authors":"Catherine A Okoro, Guixiang Zhao, Jared B Fox, Paul I Eke, Kurt J Greenlund, Machell Town","doi":"10.15585/mmwr.ss6607a1","DOIUrl":"10.15585/mmwr.ss6607a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>As a result of the 2010 Patient Protection and Affordable Care Act, millions of U.S. adults attained health insurance coverage. However, millions of adults remain uninsured or underinsured. Compared with adults without barriers to health care, adults who lack health insurance coverage, have coverage gaps, or skip or delay care because of limited personal finances might face increased risk for poor physical and mental health and premature mortality.</p><p><strong>Period covered: </strong>2014.</p><p><strong>Description of system: </strong>The Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing, state-based, landline- and cellular-telephone survey of noninstitutionalized adults aged ≥18 years residing in the United States. Data are collected from states, the District of Columbia, and participating U.S. territories on health risk behaviors, chronic health conditions, health care access, and use of clinical preventive services (CPS). An optional Health Care Access module was included in the 2014 BRFSS. This report summarizes 2014 BRFSS data from all 50 states and the District of Columbia on health care access and use of selected CPS recommended by the U.S. Preventive Services Task Force or the Advisory Committee on Immunization Practices among working-aged adults (aged 18-64 years), by state, state Medicaid expansion status, expanded geographic region, and federal poverty level (FPL). This report also provides analysis of primary type of health insurance coverage at the time of interview, continuity of health insurance coverage during the preceding 12 months, and other health care access measures (i.e., unmet health care need because of cost, unmet prescription need because of cost, medical debt [medical bills being paid off over time], number of health care visits during the preceding year, and satisfaction with received health care) from 43 states that included questions from the optional BRFSS Health Care Access module.</p><p><strong>Results: </strong>In 2014, health insurance coverage and other health care access measures varied substantially by state, state Medicaid expansion status, expanded geographic region (i.e., states categorized geographically into nine regions), and FPL category. The following proportions refer to the range of estimated prevalence for health insurance and other health care access measures by examined geographical unit (unless otherwise specified), as reported by respondents. Among adults with health insurance coverage, the range was 70.8%-94.5% for states, 78.8%-94.5% for Medicaid expansion states, 70.8%-89.1% for nonexpansion states, 73.3%-91.0% for expanded geographic regions, and 64.2%-95.8% for FPL categories. Among adults who had a usual source of health care, the range was 57.2%-86.6% for states, 57.2%-86.6% for Medicaid expansion states, 61.8%-83.9% for nonexpansion states, 64.4%-83.6% for expanded geographic regions, and 61.0%-81.6% for FPL categories. Among adu","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 7","pages":"1-42"},"PeriodicalIF":24.9,"publicationDate":"2017-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829627/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34759224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health-Related Behaviors by Urban-Rural County Classification — United States, 2013","authors":"Kevin A. Matthews, J. Croft, Yong Liu, Hua Lu, D. Kanny, A. Wheaton, T. Cunningham, L. Khan, R. Caraballo, J. Holt, P. Eke, W. Giles","doi":"10.15585/mmwr.ss6605a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6605a1","url":null,"abstract":"Problem/Condition Persons living in rural areas are recognized as a health disparity population because the prevalence of disease and rate of premature death are higher than for the overall population of the United States. Surveillance data about health-related behaviors are rarely reported by urban-rural status, which makes comparisons difficult among persons living in metropolitan and nonmetropolitan counties. Reporting Period 2013. Description of System The Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing, state-based, random-digit-dialed landline- and cellular-telephone survey of noninstitutionalized adults aged ≥18 years residing in the United States. BRFSS collects data on health-risk behaviors, chronic diseases and conditions, access to health care, and use of preventive health services related to the leading causes of death and disability. BRFSS data were analyzed for 398,208 adults aged ≥18 years to estimate the prevalence of five self-reported health-related behaviors (sufficient sleep, current nonsmoking, nondrinking or moderate drinking, maintaining normal body weight, and meeting aerobic leisure time physical activity recommendations) by urban-rural status. For this report, rural is defined as the noncore counties described in the 2013 National Center for Health Statistics Urban-Rural Classification Scheme for Counties. Results Approximately one third of U.S. adults practice at least four of these five behaviors. Compared with adults living in the four types of metropolitan counties (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan), adults living in the two types of nonmetropolitan counties (micropolitan and noncore) did not differ in the prevalence of sufficient sleep; had higher prevalence of nondrinking or moderate drinking; and had lower prevalence of current nonsmoking, maintaining normal body weight, and meeting aerobic leisure time physical activity recommendations. The overall age-adjusted prevalence of reporting at least four of the five health-related behaviors was 30.4%. The prevalence among the estimated 13.3 million adults living in noncore counties was lower (27.0%) than among those in micropolitan counties (28.8%), small metropolitan counties (29.5%), medium metropolitan counties (30.5%), large fringe metropolitan counties (30.2%), and large metropolitan centers (31.7%). Interpretation This is the first report of the prevalence of these five health-related behaviors for the six urban-rural categories. Nonmetropolitan counties have lower prevalence of three and clustering of at least four health-related behaviors that are associated with the leading chronic disease causes of death. Prevalence of sufficient sleep was consistently low and did not differ by urban-rural status. Public Health Action Chronic disease prevention efforts focus on improving the communities, schools, worksites, and health systems in which persons live, learn, work, and play. Eviden","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"25 1","pages":"1 - 8"},"PeriodicalIF":24.9,"publicationDate":"2017-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81230000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surveillance for Cancer Incidence and Mortality — United States, 2013","authors":"Simple D. Singh, S. Henley, A. B. Ryerson","doi":"10.15585/mmwr.ss6604a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6604a1","url":null,"abstract":"This report provides, in tabular and graphic form, official federal statistics on cancer incidence and mortality for 2013 and trends for 1999-2013 as reported by CDC and the National Cancer Institute (NCI). Data in this report come from the United States Cancer Statistics (USCS) system (1), which includes cancer incidence data from population-based cancer registries that participate in CDC's National Program of Cancer Registries (NPCR) and NCI's Surveillance, Epidemiology, and End Results (SEER) program reported as of November 2015 and cancer mortality data from death certificate information reported to state vital statistics offices as of June 2015 and compiled into a national file for the entire United States by CDC's National Center for Health Statistics (NCHS) National Vital Statistics System (NVSS).","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"59 1","pages":"1 - 36"},"PeriodicalIF":24.9,"publicationDate":"2017-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82998816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Childhood Blood Lead Levels in Children Aged <5 Years — United States, 2009–2014","authors":"J. Raymond, M. Brown","doi":"10.15585/mmwr.ss6603a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6603a1","url":null,"abstract":"This report provides data concerning childhood blood lead levels (BLLs) in the United States during 2009-2014. These data were collected and compiled from raw data extracts sent by state and local health departments to CDC's Childhood Blood Lead Surveillance (CBLS) system. These raw data extracts have been de-identified and coded into a format specifically for childhood blood lead reporting. The numbers of children aged <5 years for 2014 are reported with newly confirmed BLLs ≥10 µg/dL by month (Table 1) and geographic location (Table 2). The incidence of BLLs ≥10 µg/dL is reported by age group for 2009-2014 (Table 3). The numbers of children aged <5 years are reported by the prevalence of BLLs 5-9 µg/dL by age group and sample type during 2009-2014 (Tables 4 and 5). For the period 2009-2014, the numbers of children newly confirmed with BLLs ≥70 µg/dL are summarized (Figure 1) as well as the percentage of children with BLLs ≥5 µg/dL (Figure 2).","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"4 1","pages":"1 - 10"},"PeriodicalIF":24.9,"publicationDate":"2017-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83657972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}