Mmwr Surveillance Summaries最新文献

{"title":"Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 4 Years - Early Autism and Developmental Disabilities Monitoring Network, Seven Sites, United States, 2010, 2012, and 2014.","authors":"Deborah L Christensen, Matthew J Maenner, Deborah Bilder, John N Constantino, Julie Daniels, Maureen S Durkin, Robert T Fitzgerald, Margaret Kurzius-Spencer, Sydney D Pettygrove, Cordelia Robinson, Josephine Shenouda, Tiffany White, Walter Zahorodny, Karen Pazol, Patricia Dietz","doi":"10.15585/mmwr.ss6802a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6802a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Autism spectrum disorder (ASD) is estimated to affect up to 3% of children in the United States. Public health surveillance for ASD among children aged 4 years provides information about trends in prevalence, characteristics of children with ASD, and progress made toward decreasing the age of identification of ASD so that evidence-based interventions can begin as early as possible.</p><p><strong>Period covered: </strong>2010, 2012, and 2014.</p><p><strong>Description of system: </strong>The Early Autism and Developmental Disabilities Monitoring (Early ADDM) Network is an active surveillance system that provides biennial estimates of the prevalence and characteristics of ASD among children aged 4 years whose parents or guardians lived within designated sites. During surveillance years 2010, 2012, or 2014, data were collected in seven sites: Arizona, Colorado, Missouri, New Jersey, North Carolina, Utah, and Wisconsin. The Early ADDM Network is a subset of the broader ADDM Network (which included 13 total sites over the same period) that has been conducting ASD surveillance among children aged 8 years since 2000. Each Early ADDM site covers a smaller geographic area than the broader ADDM Network. Early ADDM ASD surveillance is conducted in two phases using the same methods and project staff members as the ADDM Network. The first phase consists of reviewing and abstracting data from children's records, including comprehensive evaluations performed by community professionals. Sources for these evaluations include general pediatric health clinics and specialized programs for children with developmental disabilities. In addition, special education records (for children aged ≥3 years) were reviewed for Arizona, Colorado, New Jersey, North Carolina, and Utah, and early intervention records (for children aged 0 to <3 years) were reviewed for New Jersey, North Carolina, Utah, and Wisconsin; in Wisconsin, early intervention records were reviewed for 2014 only. The second phase involves a review of the abstracted evaluations by trained clinicians using a standardized case definition and method. A child is considered to meet the surveillance case definition for ASD if one or more comprehensive evaluations of that child completed by a qualified professional describes behaviors consistent with the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR) diagnostic criteria for any of the following conditions: autistic disorder, pervasive developmental disorder-not otherwise specified (PDD-NOS, including atypical autism), or Asperger disorder (2010, 2012, and 2014). For 2014 only, prevalence estimates based on surveillance case definitions according to DSM-IV-TR and the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) were compared. This report provides estimates of overall ASD prevalence and prevalence by sex and race/ethnicity; characteristics of children age","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"68 2","pages":"1-19"},"PeriodicalIF":24.9,"publicationDate":"2019-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6476327/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37141776","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":"Foodborne Illness Outbreaks at Retail Establishments - National Environmental Assessment Reporting System, 16 State and Local Health Departments, 2014-2016.","authors":"Lauren E Lipcsei, Laura G Brown, Erik W Coleman, Adam Kramer, Matthew Masters, Beth C Wittry, Kirsten Reed, Vincent J Radke","doi":"10.15585/mmwr.ss6801a1","DOIUrl":"10.15585/mmwr.ss6801a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>State and local public health departments report hundreds of foodborne illness outbreaks each year to CDC and are primarily responsible for investigations of these outbreaks. Typically, investigations involve epidemiology, laboratory, and environmental health components. Health departments voluntarily report epidemiologic and laboratory data from their foodborne illness outbreak investigations to CDC through the Foodborne Disease Outbreak Surveillance System (FDOSS); however, minimal environmental health data from outbreak investigations are reported to FDOSS.</p><p><strong>Period covered: </strong>2014-2016.</p><p><strong>Description of system: </strong>In 2014, CDC launched the National Environmental Assessment Reporting System (NEARS) to complement FDOSS surveillance and to use these data to enhance prevention efforts. State and local health departments voluntarily report data from their foodborne illness outbreak investigations of retail food establishments. These data include characteristics of foodborne illness outbreaks (e.g., agent), characteristics of establishments with outbreaks (e.g., number of meals served daily), food safety policies and practices of these establishments (e.g., glove use policies), and characteristics of outbreak investigations (e.g., timeliness of investigation activities). NEARS is the only available data source that includes characteristics of retail establishments with foodborne illness outbreaks.</p><p><strong>Results: </strong>During 2014-2016, a total of 16 state and local public health departments reported data to NEARS on 404 foodborne illness outbreaks at retail establishments. The majority of outbreaks with a suspected or confirmed agent were caused by norovirus (61.1%). The majority of outbreaks with identified contributing factors had at least one factor associated with food contamination by a worker who was ill or infectious (58.6%). Almost half (47.4%) of establishments with outbreaks had a written policy excluding ill workers from handling food or working. Approximately one third (27.7%) had a written disposable glove use policy. Paid sick leave was available for at least one worker in 38.3% of establishments. For most establishments with outbreaks (68.7%), environmental health investigators initiated their component of the investigation soon after learning about the outbreak (i.e., the same day) and completed their component in one or two visits to the establishment (75.0%). However, in certain instances, contacting the establishment and completing the environmental health component of the investigation occurred much later (>8 days).</p><p><strong>Interpretation: </strong>Most outbreaks reported to NEARS were caused by norovirus, and contamination of food by workers who were ill or infectious contributed to more than half of outbreaks with contributing factors; these findings are consistent with findings from other national outbreak data sets and highlight the ","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"68 1","pages":"1-20"},"PeriodicalIF":37.3,"publicationDate":"2019-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6392478/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36986287","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":"Evaluation of an HIV-Related Mortuary Surveillance System - Nairobi, Kenya, Two Sites, 2015.","authors":"Hammad Ali, Catherine Kiama, Lilly Muthoni, Anthony Waruru, Peter W Young, Emily Zielinski-Gutierrez, Wanjiru Waruiru, Richelle Harklerode, Andrea A Kim, Mahesh Swaminathan, Kevin M De Cock, Joyce Wamicwe","doi":"10.15585/mmwr.ss6714a1.","DOIUrl":"10.15585/mmwr.ss6714a1.","url":null,"abstract":"<p><strong>Problem/condition: </strong>Use of human immunodeficiency virus (HIV)-mortality surveillance data can help public health officials monitor, evaluate, and improve HIV treatment programs. Many high-income countries have high-coverage civil registration and vital statistics (CRVS) systems linked to case-based HIV surveillance on which to base HIV mortality estimates. However, in the absence of comprehensive CRVS systems in low- and medium-income countries, such as Kenya, mortuary surveillance can be used to understand the occurrence of HIV infection among cadavers. In 2015, a pilot HIV-related mortuary surveillance system was implemented in the two largest mortuaries in Nairobi, Kenya. CDC conducted an evaluation to assess performance attributes and identify strengths and weaknesses of the surveillance system pilot.</p><p><strong>Period covered: </strong>Data collection: January 29-March 3, 2015; evaluation: November 2015.</p><p><strong>Description of the system: </strong>The surveillance system objectives were to determine HIV positivity among cadavers at two mortuary sites in Nairobi, Kenya, and to determine annual cause-specific and HIV-specific mortality rates among the cadavers. Cadavers of persons aged ≥15 years at death admitted to either mortuary during a 33-day period were included. Demographic information and place and time of death were entered into a surveillance register. Cardiac blood was collected using transthoracic aspiration, and blood specimens were tested for HIV in a central laboratory. Causes of death were abstracted from mortuary and hospital records. Of the 807 cadavers brought to the mortuaries, 610 (75.6%) had an HIV test result available. The overall unadjusted HIV-positivity rate was 19.5% (119/610), which differed significantly by sex (14.6% among men versus 29.5% among women).</p><p><strong>Evaluation: </strong>The evaluation was conducted using CDC guidelines for evaluating public health surveillance systems. The attributes of simplicity, flexibility, data quality (completeness and validity), acceptability, sensitivity, predictive value positive, representativeness, timeliness, and stability were examined. The evaluation steps included review of the surveillance system documents, in-depth interviews with 20 key informants (surveillance system staff, including mortuary and laboratory staff, and stakeholders involved in funding or implementation), and review of the surveillance database.</p><p><strong>Results and interpretation: </strong>Implementation of the pilot mortuary surveillance system was complex because of extensive paperwork and the need to collect and process specimens outside of business hours. However, the flexibility of the system accommodated multiple changes during implementation, including changes in specimen collection techniques and data collection tools. Acceptability was initially low among the mortuary staff but increased after concerns regarding workload were resolved. Timeliness of spe","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"67 14","pages":"1-12"},"PeriodicalIF":37.3,"publicationDate":"2018-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6309216/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36848418","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":"Abortion Surveillance - United States, 2015.","authors":"Tara C Jatlaoui, Maegan E Boutot, Michele G Mandel, Maura K Whiteman, Angeline Ti, Emily Petersen, Karen Pazol","doi":"10.15585/mmwr.ss6713a1","DOIUrl":"10.15585/mmwr.ss6713a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Since 1969, CDC has conducted abortion surveillance to document the number and characteristics of women obtaining legal induced abortions in the United States.</p><p><strong>Period covered: </strong>2015.</p><p><strong>Description of system: </strong>Each year, CDC requests abortion data from the central health agencies of 52 reporting areas (the 50 states, the District of Columbia, and New York City). The reporting areas provide this information voluntarily. For 2015, data were received from 49 reporting areas. Abortion data provided by these 49 reporting areas for each year during 2006-2015 were used in trend analyses. Census and natality data were used to calculate abortion rates (number of abortions per 1,000 women aged 15-44 years) and ratios (number of abortions per 1,000 live births), respectively.</p><p><strong>Results: </strong>A total of 638,169 abortions for 2015 were reported to CDC from 49 reporting areas. Among these 49 reporting areas, the abortion rate for 2015 was 11.8 abortions per 1,000 women aged 15-44 years, and the abortion ratio was 188 abortions per 1,000 live births. From 2014 to 2015, the total number of reported abortions decreased 2% (from 652,639), the abortion rate decreased 2% (from 12.1 abortions per 1,000 women aged 15-44 years), and the abortion ratio decreased 2% (from 192 abortions per 1,000 live births). From 2006 to 2015, the total number of reported abortions decreased 24% (from 842,855), the abortion rate decreased 26% (from 15.9 abortions per 1,000 women aged 15-44 years), and the abortion ratio decreased 19% (from 233 abortions per 1,000 live births). In 2015, all three measures reached their lowest level for the entire period of analysis (2006-2015). In 2015 and throughout the period of analysis, women in their 20s accounted for the majority of abortions and had the highest abortion rates; women aged ≥30 years accounted for a smaller percentage of abortions and had lower abortion rates. In 2015, women aged 20-24 and 25-29 years accounted for 31.1% and 27.6% of all reported abortions, respectively, and had abortion rates of 19.9 and 17.9 abortions per 1,000 women aged 20-24 and 25-29 years, respectively. In contrast, women aged 30-34, 35-39, and ≥40 years accounted for 17.7%, 10.0%, and 3.5% of all reported abortions, respectively, and had abortion rates of 11.6, 7.0, and 2.5 abortions per 1,000 women aged 30-34, 35-39, and ≥40 years, respectively. From 2006 to 2015, the abortion rate decreased among women in all age groups. In 2015, adolescents aged <15 and 15-19 years accounted for 0.3% and 9.8% of all reported abortions, respectively, and had abortion rates of 0.5 and 6.7 abortions per 1,000 adolescents aged <15 and 15-19 years, respectively. From 2006 to 2015, the percentage of abortions accounted for by adolescents aged 15-19 years decreased 41%, and their abortion rate decreased 54%. This decrease in abortion rate was greater than the decreases for women in any","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"67 13","pages":"1-45"},"PeriodicalIF":24.9,"publicationDate":"2018-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6289084/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36694261","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":"Abortion Surveillance - United States, 2014.","authors":"Tara C Jatlaoui, Jill Shah, Michele G Mandel, Jamie W Krashin, Danielle B Suchdev, Denise J Jamieson, Karen Pazol","doi":"10.15585/mmwr.ss6625a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6625a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Since 1969, CDC has conducted abortion surveillance to document the number and characteristics of women obtaining legal induced abortions in the United States.</p><p><strong>Period covered: </strong>2014.</p><p><strong>Description of system: </strong>Each year, CDC requests abortion data from the central health agencies of 52 reporting areas (the 50 states, the District of Columbia, and New York City). The reporting areas provide this information voluntarily. For 2014, data were received from 49 reporting areas. For trend analysis, abortion data were evaluated from 48 areas that reported data every year during 2005-2014. Census and natality data, respectively, were used to calculate abortion rates (number of abortions per 1,000 women aged 15-44 years) and ratios (number of abortions per 1,000 live births).</p><p><strong>Results: </strong>A total of 652,639 abortions were reported to CDC for 2014. Of these abortions, 98.4% were from the 48 reporting areas that provided data every year during 2005-2014. Among these 48 reporting areas, the abortion rate for 2014 was 12.1 abortions per 1,000 women aged 15-44 years, and the abortion ratio was 193 abortions per 1,000 live births. From 2013 to 2014, the total number and rate of reported abortions decreased 2%, and the ratio decreased 3%. From 2005 to 2014, the total number, rate, and ratio of reported abortions decreased 21%, 22%, and 18%, respectively. In 2014, all three measures reached their lowest level for the entire period of analysis (2005-2014). In 2014 and throughout the period of analysis, women in their 20s accounted for the majority of abortions and had the highest abortion rates; women in their 30s and older accounted for a much smaller percentage of abortions and had lower abortion rates. In 2014, women aged 20-24 and 25-29 years accounted for 32.2% and 26.7% of all reported abortions, respectively, and had abortion rates of 21.3 and 18.4 abortions per 1,000 women aged 20-24 and 25-29 years, respectively. In contrast, women aged 30-34, 35-39, and ≥40 years accounted for 17.1%, 9.7%, and 3.6% of all reported abortions, respectively, and had abortion rates of 11.9, 7.2, and 2.6 abortions per 1,000 women aged 30-34 years, 35-39 years, and ≥40 years, respectively. From 2005 to 2014, the abortion rate decreased among women aged 20-24, 25-29, 30-34, and 35-39 years by 27%, 16%, 12%, and 5%, respectively, but increased 4% among women aged ≥40 years. In 2014, adolescents aged <15 and 15-19 years accounted for 0.3% and 10.4% of all reported abortions, respectively, and had abortion rates of 0.5 and 7.5 abortions per 1,000 adolescents aged <15 and 15-19 years, respectively. From 2005 to 2014, the percentage of abortions accounted for by adolescents aged 15-19 years decreased 38%, and their abortion rate decreased 49%. These decreases were greater than the decreases for women in any older age group. In contrast to the percentage distribution of abortions and abo","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 25","pages":"1-44"},"PeriodicalIF":24.9,"publicationDate":"2018-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15585/mmwr.ss6625a1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36694260","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":"Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2012.","authors":"Deborah L Christensen, Kim Van Naarden Braun, Jon Baio, Deborah Bilder, Jane Charles, John N Constantino, Julie Daniels, Maureen S Durkin, Robert T Fitzgerald, Margaret Kurzius-Spencer, Li-Ching Lee, Sydney Pettygrove, Cordelia Robinson, Eldon Schulz, Chris Wells, Martha S Wingate, Walter Zahorodny, Marshalyn Yeargin-Allsopp","doi":"10.15585/mmwr.ss6513a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6513a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Autism spectrum disorder (ASD).</p><p><strong>Period covered: </strong>2012.</p><p><strong>Description of system: </strong>The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence and characteristics of ASD among children aged 8 years whose parents or guardians reside in 11 ADDM Network sites in the United States (Arkansas, Arizona, Colorado, Georgia, Maryland, Missouri, New Jersey, North Carolina, South Carolina, Utah, and Wisconsin). Surveillance to determine ASD case status is conducted in two phases. The first phase consists of screening and abstracting comprehensive evaluations performed by professional service providers in the community. Data sources identified for record review are categorized as either 1) education source type, including developmental evaluations to determine eligibility for special education services or 2) health care source type, including diagnostic and developmental evaluations. The second phase involves the review of all abstracted evaluations by trained clinicians to determine ASD surveillance case status. A child meets the surveillance case definition for ASD if one or more comprehensive evaluations of that child completed by a qualified professional describes behaviors that are consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision diagnostic criteria for any of the following conditions: autistic disorder, pervasive developmental disorder-not otherwise specified (including atypical autism), or Asperger disorder. This report provides ASD prevalence estimates for children aged 8 years living in catchment areas of the ADDM Network sites in 2012, overall and stratified by sex, race/ethnicity, and the type of source records (education and health records versus health records only). In addition, this report describes the proportion of children with ASD with a score consistent with intellectual disability on a standardized intellectual ability test, the age at which the earliest known comprehensive evaluation was performed, the proportion of children with a previous ASD diagnosis, the specific type of ASD diagnosis, and any special education eligibility classification.</p><p><strong>Results: </strong>For 2012, the combined estimated prevalence of ASD among the 11 ADDM Network sites was 14.5 per 1,000 (one in 69) children aged 8 years. Estimated prevalence was significantly higher among boys aged 8 years (23.4 per 1,000) than among girls aged 8 years (5.2 per 1,000). Estimated ASD prevalence was significantly higher among non-Hispanic white children aged 8 years (15.3 per 1,000) compared with non-Hispanic black children (13.1 per 1,000), and Hispanic (10.2 per 1,000) children aged 8 years. Estimated prevalence varied widely among the 11 ADDM Network sites, ranging from 8.2 per 1,000 children aged 8 years (in the area of the Maryland site where only h","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"65 13","pages":"1-23"},"PeriodicalIF":24.9,"publicationDate":"2018-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36729639","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 Cancers Associated with Tobacco Use - United States, 2010-2014.","authors":"M Shayne Gallaway, S Jane Henley, C Brooke Steele, Behnoosh Momin, Cheryll C Thomas, Ahmed Jamal, Katrina F Trivers, Simple D Singh, Sherri L Stewart","doi":"10.15585/mmwr.ss6712a1","DOIUrl":"10.15585/mmwr.ss6712a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Tobacco use is the leading preventable cause of cancer, contributing to at least 12 types of cancer, including acute myeloid leukemia (AML) and cancers of the oral cavity and pharynx; esophagus; stomach; colon and rectum; liver; pancreas; larynx; lung, bronchus, and trachea; kidney and renal pelvis; urinary bladder; and cervix. This report provides a comprehensive assessment of recent tobacco-associated cancer incidence for each cancer type by sex, age, race/ethnicity, metropolitan county classification, tumor characteristics, U.S. census region, and state. These data are important for initiation, monitoring, and evaluation of tobacco prevention and control measures.</p><p><strong>Period covered: </strong>2010-2014.</p><p><strong>Description of system: </strong>Cancer incidence data from CDC's National Program of Cancer Registries and the National Cancer Institute's Surveillance, Epidemiology, and End Results program were used to calculate average annual age-adjusted incidence rates for 2010-2014 and trends in annual age-adjusted incidence rates for 2010-2014. These cancer incidence data cover approximately 99% of the U.S.</p><p><strong>Population: </strong>This report provides age-adjusted cancer incidence rates for each of the 12 cancer types known to be causally associated with tobacco use, including liver and colorectal cancer, which were deemed to be causally associated with tobacco use by the U.S. Surgeon General in 2014. Findings are reported by demographic and geographic characteristics, percentage distributions for tumor characteristics, and trends in cancer incidence by sex.</p><p><strong>Results: </strong>During 2010-2014, approximately 3.3 million new tobacco-associated cancer cases were reported in the United States, approximately 667,000 per year. Age-adjusted incidence rates ranged from 4.2 AML cases per 100,000 persons to 61.3 lung cancer cases per 100,000 persons. By cancer type, incidence rates were higher among men than women (excluding cervical cancer), higher among non-Hispanics than Hispanics (for all cancers except stomach, liver, kidney, and cervical), higher among persons in nonmetropolitan counties than those in metropolitan counties (for all cancers except stomach, liver, pancreatic, and AML), and lower in the West than in other U.S. census regions (all except stomach, liver, bladder, and AML). Compared with other racial/ethnic groups, certain cancer rates were highest among whites (oral cavity and pharyngeal, esophageal, bladder, and AML), blacks (colon and rectal, pancreatic, laryngeal, lung and bronchial, cervical, and kidney), and Asians/Pacific Islanders (stomach and liver). During 2010-2014, the rate of all tobacco-associated cancers combined decreased 1.2% per year, influenced largely by decreases in cancers of the larynx (3.0%), lung (2.2%), colon and rectum (2.1%), and bladder (1.3%).</p><p><strong>Interpretation: </strong>Although tobacco-associated cancer incidence decre","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"67 12","pages":"1-42"},"PeriodicalIF":37.3,"publicationDate":"2018-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6220819/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36683223","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 Violent Deaths - National Violent Death Reporting System, 27 States, 2015.","authors":"Shane P D Jack, Emiko Petrosky, Bridget H Lyons, Janet M Blair, Allison M Ertl, Kameron J Sheats, Carter J Betz","doi":"10.15585/mmwr.ss6711a1","DOIUrl":"10.15585/mmwr.ss6711a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>In 2015, approximately 62,000 persons died in the United States as a result of violence-related injuries. This report summarizes data from CDC's National Violent Death Reporting System (NVDRS) regarding violent deaths from 27 U.S. states for 2015. Results are reported by sex, age group, race/ethnicity, location of injury, method of injury, circumstances of injury, and other selected characteristics.</p><p><strong>Reporting period: </strong>2015.</p><p><strong>Description of system: </strong>NVDRS collects data regarding violent deaths obtained from death certificates, coroner/medical examiner reports, law enforcement reports, and secondary sources (e.g., child fatality review team data, supplemental homicide reports, hospital data, and crime laboratory data). This report includes data from 27 states that collected statewide data for 2015 (Alaska, Arizona, Colorado, Connecticut, Georgia, Hawaii, Kansas, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oklahoma, Oregon, Rhode Island, South Carolina, Utah, Vermont, Virginia, and Wisconsin). NVDRS collates documents for each death and links deaths that are related (e.g., multiple homicides, a homicide followed by a suicide, or multiple suicides) into a single incident.</p><p><strong>Results: </strong>For 2015, NVDRS captured 30,628 fatal incidents involving 31,415 deaths in the 27 states included in this report. The majority (65.1%) of deaths were suicides, followed by homicides (23.5%), deaths of undetermined intent (9.5%), legal intervention deaths (1.3%) (i.e., deaths caused by law enforcement and other persons with legal authority to use deadly force, excluding legal executions), and unintentional firearm deaths (<1.0%). (The term \"legal intervention\" is a classification incorporated into the International Classification of Diseases, Tenth Revision [ICD-10] and does not denote the lawfulness or legality of the circumstances surrounding a death caused by law enforcement.) Demographic patterns varied by manner of death. Suicide rates were highest among males, non-Hispanic American Indian/Alaska Natives, non-Hispanic whites, adults aged 45-54 years, and men aged ≥75 years. The most common method of injury was a firearm. Suicides often were preceded by a mental health, intimate partner, substance abuse, or physical health problem, or a crisis during the previous or upcoming 2 weeks. Homicide rates were higher among males and persons aged <1 year and 20-34 years. Among males, non-Hispanic blacks accounted for the majority of homicides and had the highest rate of any racial/ethnic group. Homicides primarily involved a firearm, were precipitated by arguments and interpersonal conflicts, were related to intimate partner violence (particularly for females), or occurred in conjunction with another crime. When the relationship between a homicide victim and a suspected perpetrator was k","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"67 11","pages":"1-32"},"PeriodicalIF":37.3,"publicationDate":"2018-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6181254/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36529547","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 Foodborne Disease Outbreaks - United States, 2009-2015.","authors":"Daniel Dewey-Mattia, Karunya Manikonda, Aron J Hall, Matthew E Wise, Samuel J Crowe","doi":"10.15585/mmwr.ss6710a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6710a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Known foodborne disease agents are estimated to cause approximately 9.4 million illnesses each year in the United States. Although only a small subset of illnesses are associated with recognized outbreaks, data from outbreak investigations provide insight into the foods and pathogens that cause illnesses and the settings and conditions in which they occur.</p><p><strong>Reporting period: </strong>2009-2015 DESCRIPTION OF SYSTEM: The Foodborne Disease Outbreak Surveillance System (FDOSS) collects data on foodborne disease outbreaks, which are defined as the occurrence of two or more cases of a similar illness resulting from the ingestion of a common food. Since the early 1960s, foodborne outbreaks have been reported voluntarily to CDC by state, local, and territorial health departments using a standard form. Beginning in 2009, FDOSS reporting was made through the National Outbreak Reporting System, a web-based platform launched that year.</p><p><strong>Results: </strong>During 2009-2015, FDOSS received reports of 5,760 outbreaks that resulted in 100,939 illnesses, 5,699 hospitalizations, and 145 deaths. All 50 states, the District of Columbia, Puerto Rico, and CDC reported outbreaks. Among 2,953 outbreaks with a single confirmed etiology, norovirus was the most common cause of outbreaks (1,130 outbreaks [38%]) and outbreak-associated illnesses (27,623 illnesses [41%]), followed by Salmonella with 896 outbreaks (30%) and 23,662 illnesses (35%). Outbreaks caused by Listeria, Salmonella, and Shiga toxin-producing Escherichia coli (STEC) were responsible for 82% of all hospitalizations and 82% of deaths reported. Among 1,281 outbreaks in which the food reported could be classified into a single food category, fish were the most commonly implicated category (222 outbreaks [17%]), followed by dairy (136 [11%]) and chicken (123 [10%]). The food categories responsible for the most outbreak-associated illnesses were chicken (3,114 illnesses [12%]), pork (2,670 [10%]), and seeded vegetables (2,572 [10%]). Multistate outbreaks comprised only 3% of all outbreaks reported but accounted for 11% of illnesses, 34% of hospitalizations, and 54% of deaths.</p><p><strong>Interpretation: </strong>Foodborne disease outbreaks provide information about the pathogens and foods responsible for illness. Norovirus remains the leading cause of foodborne disease outbreaks, highlighting the continued need for food safety improvements targeting worker health and hygiene in food service settings. Outbreaks caused by Listeria, Salmonella, and STEC are important targets for public health intervention efforts, and improving the safety of chicken, pork, and seeded vegetables should be a priority.</p><p><strong>Public health action: </strong>The causes of foodborne illness should continue to be tracked and analyzed to inform disease prevention policies and initiatives. Strengthening the capacity of state and local health departments to investigat","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"67 10","pages":"1-11"},"PeriodicalIF":24.9,"publicationDate":"2018-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15585/mmwr.ss6710a1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36345251","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 Certain Health Behaviors and Conditions Among States and Selected Local Areas - Behavioral Risk Factor Surveillance System, United States, 2015.","authors":"Cassandra M Pickens, Carol Pierannunzi, William Garvin, Machell Town","doi":"10.15585/mmwr.ss6709a1","DOIUrl":"10.15585/mmwr.ss6709a1","url":null,"abstract":"<p><strong>Problem: </strong>Chronic conditions and disorders (e.g., diabetes, cardiovascular diseases, arthritis, and depression) are leading causes of morbidity and mortality in the United States. Healthy behaviors (e.g., physical activity, avoiding cigarette use, and refraining from binge drinking) and preventive practices (e.g., visiting a doctor for a routine check-up, tracking blood pressure, and monitoring blood cholesterol) might help prevent or successfully manage these chronic conditions. Monitoring chronic diseases, health-risk behaviors, and access to and use of health care are fundamental to the development of effective public health programs and policies at the state and local levels.</p><p><strong>Reporting period: </strong>January-December 2015.</p><p><strong>Description of the system: </strong>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 and use of health care, and use of preventive health services related to the leading causes of death and disability. This report presents results for all 50 states, the District of Columbia, the Commonwealth of Puerto Rico (Puerto Rico), and Guam and for 130 metropolitan and micropolitan statistical areas (MMSAs) (N = 441,456 respondents) for 2015.</p><p><strong>Results: </strong>The age-adjusted prevalence estimates of health-risk behaviors, self-reported chronic health conditions, access to and use of health care, and use of preventive health services varied substantially by state, territory, and MMSA in 2015. Results are summarized for selected BRFSS measures. Each set of proportions refers to the median (range) of age-adjusted prevalence estimates for health-risk behaviors, self-reported chronic diseases or conditions, or use of preventive health care services by geographic jurisdiction, as reported by survey respondents. Adults with good or better health: 84.6% (65.9%-88.8%) for states and territories and 85.2% (66.9%-91.3%) for MMSAs. Adults with ≥14 days of poor physical health in the past 30 days: 10.9% (8.2%-17.2%) for states and territories and 10.9% (6.6%-19.1%) for MMSAs. Adults with ≥14 days of poor mental health in the past 30 days: 11.3% (7.3%-15.8%) for states and territories and 11.4% (5.6%-20.5%) for MMSAs. Adults aged 18-64 years with health care coverage: 86.8% (72.0%-93.8%) for states and territories and 86.8% (63.2%-95.7%) for MMSAs. Adults who received a routine physical checkup during the preceding 12 months: 69.0% (58.1%-79.8%) for states and territories and 69.4% (57.1%-81.1%) for MMSAs. Adults who ever had their blood cholesterol checked: 79.1% (73.3%-86.7%) for states and territories and 79.5% (65.1%-87.3%) for MMSAs. Current cigarette smoking among adults: 17.7% (9.0%-27.2%) for states and territories and 17.","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"67 9","pages":"1-90"},"PeriodicalIF":37.3,"publicationDate":"2018-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6023179/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36266653","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}