Mmwr Surveillance Summaries最新文献

{"title":"Disparities in Preconception Health Indicators - \u2028Behavioral Risk Factor Surveillance System, 2013-2015, and Pregnancy Risk Assessment Monitoring System, 2013-2014.","authors":"Cheryl Robbins, Sheree L Boulet, Isabel Morgan, Denise V D'Angelo, Lauren B Zapata, Brian Morrow, Andrea Sharma, Charlan D Kroelinger","doi":"10.15585/mmwr.ss6701a1","DOIUrl":"10.15585/mmwr.ss6701a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Preconception health is a broad term that encompasses the overall health of nonpregnant women during their reproductive years (defined here as aged 18-44 years). Improvement of both birth outcomes and the woman's health occurs when preconception health is optimized. Improving preconception health before and between pregnancies is critical for reducing maternal and infant mortality and pregnancy-related complications. The National Preconception Health and Health Care Initiative's Surveillance and Research work group suggests ten prioritized indicators that states can use to monitor programs or activities for improving the preconception health status of women of reproductive age. This report includes overall and stratified estimates for nine of these preconception health indicators.</p><p><strong>Reporting period: </strong>2013-2015.</p><p><strong>Description of systems: </strong>Survey data from two surveillance systems are included in this report. The Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing state-based, landline and cellular telephone survey of noninstitutionalized adults in the United States aged ≥18 years that is conducted by state and territorial health departments. BRFSS is the main source of self-reported data for states on health risk behaviors, chronic health conditions, and preventive health services primarily related to chronic disease in the United States. The Pregnancy Risk Assessment Monitoring System (PRAMS) is an ongoing U.S. state- and population-based surveillance system administered collaboratively by CDC and state health departments. PRAMS is designed to monitor selected maternal behaviors, conditions, and experiences that occur before, during, and shortly after pregnancy that are self-reported by women who recently delivered a live-born infant. This report summarizes BRFSS and PRAMS data on nine of 10 prioritized preconception health indicators (i.e., depression, diabetes, hypertension, current cigarette smoking, normal weight, recommended physical activity, recent unwanted pregnancy, prepregnancy multivitamin use, and postpartum use of a most or moderately effective contraceptive method) for which the most recent data are available. BRFSS data from all 50 states and the District of Columbia were used for six preconception health indicators: depression, diabetes (excluded if occurring only during pregnancy or if limited to borderline/prediabetes conditions), hypertension (excluded if occurring only during pregnancy or if limited to borderline/prehypertension conditions), current cigarette smoking, normal weight, and recommended physical activity. PRAMS data from 30 states, the District of Columbia, and New York City were used for three preconception health indicators: recent unwanted pregnancy, prepregnancy multivitamin use, and postpartum use of a most or moderately effective contraceptive method by women or their husbands or partners (i.e., male or female sterili","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"67 1","pages":"1-16"},"PeriodicalIF":24.9,"publicationDate":"2018-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829866/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35748188","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.ss6624a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6624a1","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 186 abortions per 1,000 live births. From 2013 to 2014, the total number and rate of reported abortions decreased 2%, and the ratio decreased 7%. From 2005 to 2014, the total number, rate, and ratio of reported abortions decreased 21%, 22%, and 21%, 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 24","pages":"1-48"},"PeriodicalIF":24.9,"publicationDate":"2017-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35276533","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":"Racial/Ethnic Health Disparities Among Rural Adults - United States, 2012-2015.","authors":"Cara V James, Ramal Moonesinghe, Shondelle M Wilson-Frederick, Jeffrey E Hall, Ana Penman-Aguilar, Karen Bouye","doi":"10.15585/mmwr.ss6623a1","DOIUrl":"10.15585/mmwr.ss6623a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Rural communities often have worse health outcomes, have less access to care, and are less diverse than urban communities. Much of the research on rural health disparities examines disparities between rural and urban communities, with fewer studies on disparities within rural communities. This report provides an overview of racial/ethnic health disparities for selected indicators in rural areas of the United States.</p><p><strong>Reporting period: </strong>2012-2015.</p><p><strong>Description of system: </strong>Self-reported data from the 2012-2015 Behavioral Risk Factor Surveillance System were pooled to evaluate racial/ethnic disparities in health, access to care, and health-related behaviors among rural residents in all 50 states and the District of Columbia. Using the National Center for Health Statistics 2013 Urban-Rural Classification Scheme for Counties to assess rurality, this analysis focused on adults living in noncore (rural) counties.</p><p><strong>Results: </strong>Racial/ethnic minorities who lived in rural areas were younger (more often in the youngest age group) than non-Hispanic whites. Except for Asians and Native Hawaiians and other Pacific Islanders (combined in the analysis), more racial/ethnic minorities (compared with non-Hispanic whites) reported their health as fair or poor, that they had obesity, and that they were unable to see a physician in the past 12 months because of cost. All racial/ethnic minority populations were less likely than non-Hispanic whites to report having a personal health care provider. Non-Hispanic whites had the highest estimated prevalence of binge drinking in the past 30 days.</p><p><strong>Interpretation: </strong>Although persons in rural communities often have worse health outcomes and less access to health care than those in urban communities, rural racial/ethnic minority populations have substantial health, access to care, and lifestyle challenges that can be overlooked when considering aggregated population data. This study revealed difficulties among non-Hispanic whites as well, primarily related to health-related risk behaviors. Across each population, the challenges vary.</p><p><strong>Public health action: </strong>Stratifying data by different demographics, using community health needs assessments, and adopting and implementing the National Culturally and Linguistically Appropriate Services Standards can help rural communities identify disparities and develop effective initiatives to eliminate them, which aligns with a Healthy People 2020 overarching goal: achieving health equity.</p>","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 23","pages":"1-9"},"PeriodicalIF":24.9,"publicationDate":"2017-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829953/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35612190","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 Lyme Disease — United States, 2008–2015","authors":"Amy M Schwartz, A. Hinckley, P. Mead, S. Hook, K. Kugeler","doi":"10.15585/mmw.ss6622a1","DOIUrl":"https://doi.org/10.15585/mmw.ss6622a1","url":null,"abstract":"Problem/Condition Lyme disease is the most commonly reported vectorborne disease in the United States but is geographically focal. The majority of Lyme disease cases occur in the Northeast, mid-Atlantic, and upper Midwest regions. Lyme disease can cause varied clinical manifestations, including erythema migrans, arthritis, facial palsy, and carditis. Lyme disease occurs most commonly among children and older adults, with a slight predominance among males. Reporting Period 2008–2015. Description of System Lyme disease has been a nationally notifiable condition in the United States since 1991. Possible Lyme disease cases are reported to local and state health departments by clinicians and laboratories. Health department staff conduct case investigations to classify cases according to the national surveillance case definition. Those that qualify as confirmed or probable cases of Lyme disease are reported to CDC through the National Notifiable Diseases Surveillance System. States with an average annual incidence during this reporting period of ≥10 confirmed Lyme disease cases per 100,000 population were classified as high incidence. States that share a border with those states or that are located between areas of high incidence were classified as neighboring states. All other states were classified as low incidence. Results During 2008–2015, a total of 275,589 cases of Lyme disease were reported to CDC (208,834 confirmed and 66,755 probable). Although most cases continue to be reported from states with high incidence in the Northeast, mid-Atlantic, and upper Midwest regions, case counts in most of these states have remained stable or decreased during the reporting period. In contrast, case counts have increased in states that neighbor those with high incidence. Overall, demographic characteristics associated with confirmed cases were similar to those described previously, with a slight predominance among males and a bimodal age distribution with peaks among young children and older adults. Yet, among the subset of cases reported from states with low incidence, infection occurred more commonly among females and older adults. In addition, probable cases occurred more commonly among females and with a higher modal age than confirmed cases. Interpretation Lyme disease continues to be the most commonly reported vectorborne disease in the United States. Although concentrated in historically high-incidence areas, the geographic distribution is expanding into neighboring states. The trend of stable to decreasing case counts in many states with high incidence could be a result of multiple factors, including actual stabilization of disease incidence or artifact due to modifications in reporting practices employed by some states to curtail the resource burden associated with Lyme disease surveillance. Public Health Action This report highlights the continuing public health challenge of Lyme disease in states with high incidence and demonstrates its emergence in","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"111 1","pages":"1 - 12"},"PeriodicalIF":24.9,"publicationDate":"2017-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89768445","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 Lyme Disease - United States, 2008-2015.","authors":"Amy M Schwartz,&nbsp;Alison F Hinckley,&nbsp;Paul S Mead,&nbsp;Sarah A Hook,&nbsp;Kiersten J Kugeler","doi":"10.15585/mmwr.ss6622a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6622a1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Problem/condition: &lt;/strong&gt;Lyme disease is the most commonly reported vectorborne disease in the United States but is geographically focal. The majority of Lyme disease cases occur in the Northeast, mid-Atlantic, and upper Midwest regions. Lyme disease can cause varied clinical manifestations, including erythema migrans, arthritis, facial palsy, and carditis. Lyme disease occurs most commonly among children and older adults, with a slight predominance among males.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Reporting period: &lt;/strong&gt;2008-2015.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Description of system: &lt;/strong&gt;Lyme disease has been a nationally notifiable condition in the United States since 1991. Possible Lyme disease cases are reported to local and state health departments by clinicians and laboratories. Health department staff conduct case investigations to classify cases according to the national surveillance case definition. Those that qualify as confirmed or probable cases of Lyme disease are reported to CDC through the National Notifiable Diseases Surveillance System. States with an average annual incidence during this reporting period of ≥10 confirmed Lyme disease cases per 100,000 population were classified as high incidence. States that share a border with those states or that are located between areas of high incidence were classified as neighboring states. All other states were classified as low incidence.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;During 2008-2015, a total of 275,589 cases of Lyme disease were reported to CDC (208,834 confirmed and 66,755 probable). Although most cases continue to be reported from states with high incidence in the Northeast, mid-Atlantic, and upper Midwest regions, case counts in most of these states have remained stable or decreased during the reporting period. In contrast, case counts have increased in states that neighbor those with high incidence. Overall, demographic characteristics associated with confirmed cases were similar to those described previously, with a slight predominance among males and a bimodal age distribution with peaks among young children and older adults. Yet, among the subset of cases reported from states with low incidence, infection occurred more commonly among females and older adults. In addition, probable cases occurred more commonly among females and with a higher modal age than confirmed cases.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Interpretation: &lt;/strong&gt;Lyme disease continues to be the most commonly reported vectorborne disease in the United States. Although concentrated in historically high-incidence areas, the geographic distribution is expanding into neighboring states. The trend of stable to decreasing case counts in many states with high incidence could be a result of multiple factors, including actual stabilization of disease incidence or artifact due to modifications in reporting practices employed by some states to curtail the resource burden associated with Lyme disease surveillance.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Public health action: &lt;/strong&gt;","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 22","pages":"1-12"},"PeriodicalIF":24.9,"publicationDate":"2017-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829628/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10266148","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":"Occupational Exposure to Vapor-Gas, Dust, and Fumes in a Cohort of Rural Adults in Iowa Compared with a Cohort of Urban Adults.","authors":"Brent C Doney,&nbsp;Paul K Henneberger,&nbsp;Michael J Humann,&nbsp;Xiaoming Liang,&nbsp;Kevin M Kelly,&nbsp;Jean M Cox-Ganser","doi":"10.15585/mmwr.ss6621a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6621a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Many rural residents work in the field of agriculture; however, employment in nonagricultural jobs also is common. Because previous studies in rural communities often have focused on agricultural workers, much less is known about the occupational exposures in other types of jobs in rural settings. Characterizing airborne occupational exposures that can contribute to respiratory diseases is important so that differences between rural and urban working populations can be assessed.</p><p><strong>Reporting period: </strong>1994-2011.</p><p><strong>Description of system: </strong>This investigation used data from the baseline questionnaire completed by adult rural residents participating in the Keokuk County Rural Health Study (KCRHS). The distribution of jobs and occupational exposures to vapor-gas, dust, and fumes (VGDF) among all participants was analyzed and stratified by farming status (current, former, and never) then compared with a cohort of urban workers from the Multi-Ethnic Study of Atherosclerosis (MESA). Occupational exposure in the last job was assessed with a job-exposure matrix (JEM) developed for chronic obstructive pulmonary disease (COPD). The COPD JEM assesses VGDF exposure at levels of none or low, medium, and high.</p><p><strong>Results: </strong>The 1,699 KCRHS (rural) participants were more likely to have medium or high occupational VGDF exposure (43.2%) at their last job than their urban MESA counterparts (15.0% of 3,667 participants). One fifth (20.8%) of the rural participants currently farmed, 43.1% were former farmers, and approximately one third (36.1%) had never farmed. These three farming groups differed in VGDF exposure at the last job, with the prevalence of medium or high exposure at 80.2% for current farmers, 38.7% for former farmers, and 27.4% for never farmers, and all three percentages were higher than the 15.0% medium or high level of VGDF exposure for urban workers.</p><p><strong>Interpretation: </strong>Rural workers, including those who had never farmed, were more likely to experience occupational VGDF exposure than urban workers.</p><p><strong>Public health action: </strong>The occupational exposures of rural adults assessed using the COPD JEM will be used to investigate their potential association with obstructive respiratory health problems (e.g., airflow limitation and chronic bronchitis). This assessment might highlight occupations in need of preventive interventions.</p>","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 21","pages":"1-5"},"PeriodicalIF":24.9,"publicationDate":"2017-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829718/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35565904","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":"Receipt of Selected Preventive Health Services for Women and Men of Reproductive Age - United States, 2011-2013.","authors":"Karen Pazol, Cheryl L Robbins, Lindsey I Black, Katherine A Ahrens, Kimberly Daniels, Anjani Chandra, Anjel Vahratian, Lorrie E Gavin","doi":"10.15585/mmwr.ss6620a1","DOIUrl":"10.15585/mmwr.ss6620a1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Problem/condition: &lt;/strong&gt;Receipt of key preventive health services among women and men of reproductive age (i.e., 15-44 years) can help them achieve their desired number and spacing of healthy children and improve their overall health. The 2014 publication Providing Quality Family Planning Services: Recommendations of CDC and the U.S. Office of Population Affairs (QFP) establishes standards for providing a core set of preventive services to promote these goals. These services include contraceptive care for persons seeking to prevent or delay pregnancy, pregnancy testing and counseling, basic infertility services for those seeking to achieve pregnancy, sexually transmitted disease (STD) services, and other preconception care and related preventive health services. QFP describes how to provide these services and recommends using family planning and other primary care visits to screen for and offer the full range of these services. This report presents baseline estimates of the use of these preventive services before the publication of QFP that can be used to monitor progress toward improving the quality of preventive care received by women and men of reproductive age.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Period covered: &lt;/strong&gt;2011-2013.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Description of the system: &lt;/strong&gt;Three surveillance systems were used to document receipt of preventive health services among women and men of reproductive age as recommended in QFP. The National Survey of Family Growth (NSFG) collects data on factors that influence reproductive health in the United States since 1973, with a focus on fertility, sexual activity, contraceptive use, reproductive health care, family formation, child care, and related topics. NSFG uses a stratified, multistage probability sample to produce nationally representative estimates for the U.S. household population of women and men aged 15-44 years. This report uses data from the 2011-2013 NSFG. The Pregnancy Risk Assessment Monitoring System (PRAMS) is an ongoing, state- and population-based surveillance system designed to monitor selected maternal behaviors and experiences that occur before, during, and shortly after pregnancy among women who deliver live-born infants in the United States. Annual PRAMS data sets are created and used to produce statewide estimates of preconception and perinatal health behaviors and experiences. This report uses PRAMS data for 2011-2012 from 11 states (Hawaii, Maine, Maryland, Michigan, Minnesota, Nebraska, New Jersey, Tennessee, Utah, Vermont, and West Virginia). The National Health Interview Survey (NHIS) is a nationally representative survey of noninstitutionalized civilians in the United States. NHIS collects data on a broad range of health topics, including the prevalence, distribution, and effects of illness and disability and the services rendered for or because of such conditions. Households are identified through a multistage probability household sampling design, and estimates are produced ","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 20","pages":"1-31"},"PeriodicalIF":37.3,"publicationDate":"2017-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5879726/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35643327","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":"Illicit Drug Use, Illicit Drug Use Disorders, and Drug Overdose Deaths in Metropolitan and Nonmetropolitan Areas - United States.","authors":"Karin A Mack, Christopher M Jones, Michael F Ballesteros","doi":"10.15585/mmwr.ss6619a1","DOIUrl":"10.15585/mmwr.ss6619a1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Problem/condition: &lt;/strong&gt;Drug overdoses are a leading cause of injury death in the United States, resulting in approximately 52,000 deaths in 2015. Understanding differences in illicit drug use, illicit drug use disorders, and overall drug overdose deaths in metropolitan and nonmetropolitan areas is important for informing public health programs, interventions, and policies.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Reporting period: &lt;/strong&gt;Illicit drug use and drug use disorders during 2003-2014, and drug overdose deaths during 1999-2015.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Description of data: &lt;/strong&gt;The National Survey of Drug Use and Health (NSDUH) collects information through face-to-face household interviews about the use of illicit drugs, alcohol, and tobacco among the U.S. noninstitutionalized civilian population aged ≥12 years. Respondents include residents of households and noninstitutional group quarters (e.g., shelters, rooming houses, dormitories, migratory workers' camps, and halfway houses) and civilians living on military bases. NSDUH variables include sex, age, race/ethnicity, residence (metropolitan/nonmetropolitan), annual household income, self-reported drug use, and drug use disorders. National Vital Statistics System Mortality (NVSS-M) data for U.S. residents include information from death certificates filed in the 50 states and the District of Columbia. Cases were selected with an underlying cause of death based on the ICD-10 codes for drug overdoses (X40-X44, X60-X64, X85, and Y10-Y14). NVSS-M variables include decedent characteristics (sex, age, and race/ethnicity) and information on intent (unintentional, suicide, homicide, or undetermined), location of death (medical facility, in a home, or other [including nursing homes, hospices, unknown, and other locations]) and county of residence (metropolitan/nonmetropolitan). Metropolitan/nonmetropolitan status is assigned independently in each data system. NSDUH uses a three-category system: Core Based Statistical Area (CBSA) of ≥1 million persons; CBSA of &lt;1 million persons; and not a CBSA, which for simplicity were labeled large metropolitan, small metropolitan, and nonmetropolitan. Deaths from NVSS-M are categorized by the county of residence of the decedent using CDC's National Center for Health Statistics 2013 Urban-Rural Classification Scheme, collapsed into two categories (metropolitan and nonmetropolitan).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Although both metropolitan and nonmetropolitan areas experienced significant increases from 2003-2005 to 2012-2014 in self-reported past-month use of illicit drugs, the prevalence was highest for the large metropolitan areas compared with small metropolitan or nonmetropolitan areas throughout the study period. Notably, past-month use of illicit drugs declined over the study period for the youngest respondents (aged 12-17 years). The prevalence of past-year illicit drug use disorders among persons using illicit drugs in the past year varied by metropolitan/nonmetropoli","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 19","pages":"1-12"},"PeriodicalIF":24.9,"publicationDate":"2017-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15585/mmwr.ss6619a1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35530002","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":"Suicide Trends Among and Within Urbanization Levels by Sex, Race/Ethnicity, Age Group, and Mechanism of Death - United States, 2001-2015.","authors":"Asha Z Ivey-Stephenson, Alex E Crosby, Shane P D Jack, Tadesse Haileyesus, Marcie-Jo Kresnow-Sedacca","doi":"10.15585/mmwr.ss6618a1","DOIUrl":"10.15585/mmwr.ss6618a1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Problem/condition: &lt;/strong&gt;Suicide is a public health problem and one of the top 10 leading causes of death in the United States. Substantial geographic variations in suicide rates exist, with suicides in rural areas occurring at much higher rates than those occurring in more urban areas. Understanding demographic trends and mechanisms of death among and within urbanization levels is important to developing and targeting future prevention efforts.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Reporting period: &lt;/strong&gt;2001-2015.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Description of system: &lt;/strong&gt;Mortality data from the National Vital Statistics System (NVSS) include demographic, geographic, and cause of death information derived from death certificates filed in the 50 states and the District of Columbia. NVSS was used to identify suicide deaths, defined by International Classification of Diseases, 10th Revision (ICD-10) underlying cause of death codes X60-X84, Y87.0, and U03. This report examines annual county level trends in suicide rates during 2001-2015 among and within urbanization levels by select demographics and mechanisms of death. Counties were collapsed into three urbanization levels using the 2006 National Center for Health Statistics classification scheme.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Suicide rates increased across the three urbanization levels, with higher rates in nonmetropolitan/rural counties than in medium/small or large metropolitan counties. Each urbanization level experienced substantial annual rate changes at different times during the study period. Across urbanization levels, suicide rates were consistently highest for men and non-Hispanic American Indian/Alaska Natives compared with rates for women and other racial/ethnic groups; however, rates were highest for non-Hispanic whites in more metropolitan counties. Trends indicate that suicide rates for non-Hispanic blacks were lowest in nonmetropolitan/rural counties and highest in more urban counties. Increases in suicide rates occurred for all age groups across urbanization levels, with the highest rates for persons aged 35-64 years. For mechanism of death, greater increases in rates of suicide by firearms and hanging/suffocation occurred across all urbanization levels; rates of suicide by firearms in nonmetropolitan/rural counties were almost two times that of rates in larger metropolitan counties.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Interpretation: &lt;/strong&gt;Suicide rates in nonmetropolitan/rural counties are consistently higher than suicide rates in metropolitan counties. These trends also are observed by sex, race/ethnicity, age group, and mechanism of death.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Public health action: &lt;/strong&gt;Interventions to prevent suicides should be ongoing, particularly in rural areas. Comprehensive suicide prevention efforts might include leveraging protective factors and providing innovative prevention strategies that increase access to health care and mental health care in rural communities. In addition, distribution of socioecon","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 18","pages":"1-16"},"PeriodicalIF":24.9,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829833/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35574865","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":"Rural and Urban Differences in Passenger-Vehicle-Occupant Deaths and Seat Belt Use Among Adults - United States, 2014.","authors":"Laurie F Beck,&nbsp;Jonathan Downs,&nbsp;Mark R Stevens,&nbsp;Erin K Sauber-Schatz","doi":"10.15585/mmwr.ss6617a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6617a1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Problem/condition: &lt;/strong&gt;Motor-vehicle crashes are a leading cause of death in the United States. Compared with urban residents, rural residents are at an increased risk for death from crashes and are less likely to wear seat belts. These differences have not been well described by levels of rurality.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Reporting period: &lt;/strong&gt;2014.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Description of systems: &lt;/strong&gt;Data from the Fatality Analysis Reporting System (FARS) and the Behavioral Risk Factor Surveillance System (BRFSS) were used to identify passenger-vehicle-occupant deaths from motor-vehicle crashes and estimate the prevalence of seat belt use. FARS, a census of U.S. motor-vehicle crashes involving one or more deaths, was used to identify passenger-vehicle-occupant deaths among adults aged ≥18 years. Passenger-vehicle occupants were defined as persons driving or riding in passenger cars, light trucks, vans, or sport utility vehicles. Death rates per 100,000 population, age-adjusted to the 2000 U.S. standard population and the proportion of occupants who were unrestrained at the time of the fatal crash, were calculated. BRFSS, an annual, state-based, random-digit-dialed telephone survey of the noninstitutionalized U.S. civilian population aged ≥18 years, was used to estimate prevalence of seat belt use. FARS and BRFSS data were analyzed by a six-level rural-urban designation, based on the U.S. Department of Agriculture 2013 rural-urban continuum codes, and stratified by census region and type of state seat belt enforcement law (primary or secondary).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Within each census region, age-adjusted passenger-vehicle-occupant death rates per 100,000 population increased with increasing rurality, from the most urban to the most rural counties: South, 6.8 to 29.2; Midwest, 5.3 to 25.8; West, 3.9 to 40.0; and Northeast, 3.5 to 10.8. (For the Northeast, data for the most rural counties were not reported because of suppression criteria; comparison is for the most urban to the second-most rural counties.) Similarly, the proportion of occupants who were unrestrained at the time of the fatal crash increased as rurality increased. Self-reported seat belt use in the United States decreased with increasing rurality, ranging from 88.8% in the most urban counties to 74.7% in the most rural counties. Similar differences in age-adjusted death rates and seat belt use were observed in states with primary and secondary seat belt enforcement laws.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Interpretation: &lt;/strong&gt;Rurality was associated with higher age-adjusted passenger-vehicle-occupant death rates, a higher proportion of unrestrained passenger-vehicle-occupant deaths, and lower seat belt use among adults in all census regions and regardless of state seat belt enforcement type.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Public health actions: &lt;/strong&gt;Seat belt use decreases and age-adjusted passenger-vehicle-occupant death rates increase with increasing levels of rurality. Improving seat belt use","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 17","pages":"1-13"},"PeriodicalIF":24.9,"publicationDate":"2017-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829699/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35533678","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}