Stephanie A Rutledge, Svetlana Masalovich, Rachel J Blacher, Magon M Saunders
{"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}
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
{"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}
Christopher A Taylor, Jeneita M Bell, Matthew J Breiding, Likang Xu
{"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}
Catherine A Okoro, Guixiang Zhao, Jared B Fox, Paul I Eke, Kurt J Greenlund, Machell Town
{"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}
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
{"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}
Alejandro Azofeifa, Margaret E Mattson, Gillian Schauer, Tim McAfee, Althea Grant, Rob Lyerla
{"title":"National Estimates of Marijuana Use and Related Indicators - National Survey on Drug Use and Health, United States, 2002-2014.","authors":"Alejandro Azofeifa, Margaret E Mattson, Gillian Schauer, Tim McAfee, Althea Grant, Rob Lyerla","doi":"10.15585/mmwr.ss6511a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6511a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>In the United States, marijuana is the most commonly used illicit drug. In 2013, 7.5% (19.8 million) of the U.S. population aged ≥12 years reported using marijuana during the preceding month. Because of certain state-level policies that have legalized marijuana for medical or recreational use, population-based data on marijuana use and other related indicators are needed to help monitor behavioral health changes in the United States.</p><p><strong>Period covered: </strong>2002-2014.</p><p><strong>Description of system: </strong>The National Survey on Drug Use and Health (NSDUH) is a national- and state-level survey of a representative sample of the civilian, noninstitutionalized U.S. population aged ≥12 years. NSDUH collects information about the use of illicit drugs, alcohol, and tobacco; initiation of substance use; frequency of substance use; substance dependence and abuse; perception of substance harm risk or no risk; and other related behavioral health indicators. This report describes national trends for selected marijuana use and related indicators, including prevalence of marijuana use; initiation; perception of harm risk, approval, and attitudes; perception of availability and mode of acquisition; dependence and abuse; and perception of legal penalty for marijuana possession.</p><p><strong>Results: </strong>In 2014, a total of 2.5 million persons aged ≥12 years had used marijuana for the first time during the preceding 12 months, an average of approximately 7,000 new users each day. During 2002-2014, the prevalence of marijuana use during the past month, past year, and daily or almost daily increased among persons aged ≥18 years, but not among those aged 12-17 years. Among persons aged ≥12 years, the prevalence of perceived great risk from smoking marijuana once or twice a week and once a month decreased and the prevalence of perceived no risk increased. The prevalence of past year marijuana dependence and abuse decreased, except among persons aged ≥26 years. Among persons aged ≥12 years, the percentage reporting that marijuana was fairly easy or very easy to obtain increased. The percentage of persons aged ≥12 reporting the mode of acquisition of marijuana was buying it and growing it increased versus getting it for free and sharing it. The percentage of persons aged ≥12 years reporting that the perceived maximum legal penalty for the possession of an ounce or less of marijuana in their state is a fine and no penalty increased versus probation, community service, possible prison sentence, and mandatory prison sentence.</p><p><strong>Interpretation: </strong>Since 2002, marijuana use in the United States has increased among persons aged ≥18 years, but not among those aged 12-17 years. A decrease in the perception of great risk from smoking marijuana combined with increases in the perception of availability (i.e., fairly easy or very easy to obtain marijuana) and fewer punitive legal penalties (e.g.,","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"65 11","pages":"1-28"},"PeriodicalIF":24.9,"publicationDate":"2016-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34409047","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}
Bridget H Lyons, Katherine A Fowler, Shane P D Jack, Carter J Betz, Janet M Blair
{"title":"Surveillance for Violent Deaths - National Violent Death Reporting System, 17 States, 2013.","authors":"Bridget H Lyons, Katherine A Fowler, Shane P D Jack, Carter J Betz, Janet M Blair","doi":"10.15585/mmwr.ss6510a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6510a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>In 2013, more than 57,000 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 17 U.S. states for 2013. Results are reported by sex, age group, race/ethnicity, marital status, location of injury, method of injury, circumstances of injury, and other selected characteristics.</p><p><strong>Reporting period covered: </strong>2013.</p><p><strong>Description of system: </strong>NVDRS collects data from participating states 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 17 states that collected statewide data for 2013 (Alaska, Colorado, Georgia, Kentucky, Maryland, Massachusetts, North Carolina, New Jersey, New Mexico, Ohio, Oklahoma, Oregon, Rhode Island, South Carolina, Utah, 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) from a single incident.</p><p><strong>Results: </strong>For 2013, a total of 18,765 fatal incidents involving 19,251 deaths were captured by NVDRS in the 17 states included in this report. The majority (66.2%) of deaths were suicides, followed by homicides (23.2%), deaths of undetermined intent (8.8%), deaths involving legal intervention (1.2%) (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%). (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.) Suicides occurred at higher rates among males, non-Hispanic whites, American Indian/Alaska Natives, persons aged 45-64 years, and males aged ≥75 years. Suicides were preceded primarily by a mental health, intimate partner, or physical health problem or a crisis during the previous or upcoming 2 weeks. Homicide rates were higher among males and persons aged 15-44 years; rates were highest among non-Hispanic black males. Homicides primarily were precipitated by arguments and interpersonal conflicts, occurrence in conjunction with another crime, or were related to intimate partner violence (particularly for females). A known relationship between a homicide victim and a suspected perpetrator was most likely either that of an acquaintance or friend or an intimate partner. Legal intervention death rates were highest among males and persons aged 20-24 years and 30-34 years; rates were highest among non-Hispanic black males. Precipitating facto","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"65 10","pages":"1-42"},"PeriodicalIF":24.9,"publicationDate":"2016-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34674004","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}
Laura Kann, Emily O'Malley Olsen, Tim McManus, William A Harris, Shari L Shanklin, Katherine H Flint, Barbara Queen, Richard Lowry, David Chyen, Lisa Whittle, Jemekia Thornton, Connie Lim, Yoshimi Yamakawa, Nancy Brener, Stephanie Zaza
{"title":"Sexual Identity, Sex of Sexual Contacts, and Health-Related Behaviors Among Students in Grades 9-12 - United States and Selected Sites, 2015.","authors":"Laura Kann, Emily O'Malley Olsen, Tim McManus, William A Harris, Shari L Shanklin, Katherine H Flint, Barbara Queen, Richard Lowry, David Chyen, Lisa Whittle, Jemekia Thornton, Connie Lim, Yoshimi Yamakawa, Nancy Brener, Stephanie Zaza","doi":"10.15585/mmwr.ss6509a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6509a1","url":null,"abstract":"<p><strong>Problem: </strong>Sexual identity and sex of sexual contacts can both be used to identify sexual minority youth. Significant health disparities exist between sexual minority and nonsexual minority youth. However, not enough is known about health-related behaviors that contribute to negative health outcomes among sexual minority youth and how the prevalence of these health-related behaviors compare with the prevalence of health-related behaviors among nonsexual minorities.</p><p><strong>Reporting period: </strong>September 2014-December 2015.</p><p><strong>Description of the system: </strong>The Youth Risk Behavior Surveillance System (YRBSS) monitors six categories of priority health-related behaviors among youth and young adults: 1) behaviors that contribute to unintentional injuries and violence; 2) tobacco use; 3) alcohol and other drug use; 4) sexual behaviors related to unintended pregnancy and sexually transmitted infections, including human immunodeficiency virus infection; 5) unhealthy dietary behaviors; and 6) physical inactivity. In addition, YRBSS monitors the prevalence of obesity and asthma and other priority health-related behaviors. YRBSS includes a national school-based Youth Risk Behavior Survey (YRBS) conducted by CDC and state and large urban school district school-based YRBSs conducted by state and local education and health agencies. For the 2015 YRBSS cycle, a question to ascertain sexual identity and a question to ascertain sex of sexual contacts was added for the first time to the national YRBS questionnaire and to the standard YRBS questionnaire used by the states and large urban school districts as a starting point for their YRBS questionnaires. This report summarizes results for 118 health-related behaviors plus obesity, overweight, and asthma by sexual identity and sex of sexual contacts from the 2015 national survey, 25 state surveys, and 19 large urban school district surveys conducted among students in grades 9-12.</p><p><strong>Results: </strong>Across the 18 violence-related risk behaviors nationwide, the prevalence of 16 was higher among gay, lesbian, and bisexual students than heterosexual students and the prevalence of 15 was higher among students who had sexual contact with only the same sex or with both sexes than students who had sexual contact with only the opposite sex. Across the 13 tobacco use-related risk behaviors, the prevalence of 11 was higher among gay, lesbian, and bisexual students than heterosexual students and the prevalence of 10 was higher among students who had sexual contact with only the same sex or with both sexes than students who had sexual contact with only the opposite sex. Similarly, across the 19 alcohol or other drug use-related risk behaviors, the prevalence of 18 was higher among gay, lesbian, and bisexual students than heterosexual students and the prevalence of 17 was higher among students who had sexual contact with only the same sex or with both sexes than students","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"65 9","pages":"1-202"},"PeriodicalIF":24.9,"publicationDate":"2016-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34642974","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}