Brent C Doney, Paul K Henneberger, Michael J Humann, Xiaoming Liang, Kevin M Kelly, Jean M Cox-Ganser
Problem/condition: 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.
Reporting period: 1994-2011.
Description of system: 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.
Results: 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.
Interpretation: Rural workers, including those who had never farmed, were more likely to experience occupational VGDF exposure than urban workers.
Public health action: 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.
{"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, Paul K Henneberger, Michael J Humann, Xiaoming Liang, Kevin M Kelly, 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}
Karen Pazol, Cheryl L Robbins, Lindsey I Black, Katherine A Ahrens, Kimberly Daniels, Anjani Chandra, Anjel Vahratian, Lorrie E Gavin
Problem/condition: 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.
Period covered: 2011-2013.
Description of the system: 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
{"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":"<p><strong>Problem/condition: </strong>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.</p><p><strong>Period covered: </strong>2011-2013.</p><p><strong>Description of the system: </strong>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}
Karin A Mack, Christopher M Jones, Michael F Ballesteros
<p><strong>Problem/condition: </strong>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.</p><p><strong>Reporting period: </strong>Illicit drug use and drug use disorders during 2003-2014, and drug overdose deaths during 1999-2015.</p><p><strong>Description of data: </strong>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 <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).</p><p><strong>Results: </strong>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
问题/状况:药物过量是美国伤害死亡的主要原因，2015年造成约5.2万人死亡。了解大都市和非大都市地区在非法药物使用、非法药物使用障碍和总体药物过量死亡方面的差异，对公共卫生计划、干预措施和政策的通报非常重要。报告期间:2003-2014年期间非法药物使用和药物使用障碍，1999-2015年期间药物过量死亡。数据描述:全国药物使用和健康调查(NSDUH)通过面对面的家庭访谈收集有关美国非机构平民中年龄≥12岁的非法药物、酒精和烟草使用情况的信息。受访者包括家庭居民和非机构群体宿舍(如庇护所、宿舍、宿舍、移徙工人营地和中途之家)以及居住在军事基地的平民。NSDUH变量包括性别、年龄、种族/民族、居住地(大都市/非大都市)、家庭年收入、自我报告的药物使用情况和药物使用障碍。美国居民的国家生命统计系统死亡率(NVSS-M)数据包括来自50个州和哥伦比亚特区的死亡证明信息。根据ICD-10药物过量代码(X40-X44、X60-X64、X85和Y10-Y14)选择具有潜在死亡原因的病例。NVSS-M变量包括死者特征(性别、年龄和种族/民族)和意图(无意、自杀、他杀或未确定)、死亡地点(医疗设施、家中或其他[包括养老院、临终关怀院、未知地点和其他地点])和居住县(大都市/非大都市)的信息。城域/非城域状态在每个数据系统中独立分配。NSDUH采用三类系统:核心统计区(CBSA)人口≥100万;结果CBSA:尽管从2003-2005年到2012-2014年，大都市和非大都市地区的自我报告的过去一个月的非法药物使用都显着增加，但在整个研究期间，与小大都市或非大都市地区相比，大城市地区的患病率最高。值得注意的是，在研究期间，最年轻的答复者(12-17岁)过去一个月使用非法药物的情况有所下降。过去一年非法药物使用者中非法药物使用障碍的流行率因大都市/非大都市状况而异，并随时间而变化。2003-2014年期间，在大都市和非大都市地区，过去一年的非法药物使用障碍患病率均有所下降。2015年，大都市区药物过量死亡人数是非大都市区的六倍(大都市区:45,059人;nonmetropolitan: 7345)。1999年，大都市地区的药物过量死亡率(每10万人中6.4人)高于非大都市地区(每10万人中4.0人)，但在2004年两者趋于一致，到2015年，非大都市地区的药物过量死亡率(17.0人)略高于大都市地区(16.2人)。解释:药物使用和随后的过量使用仍然是大都市/非大都市地区一个关键和复杂的公共卫生挑战。2012-2014年期间，青年非法药物使用下降，农村地区非法药物使用障碍患病率下降，这是令人鼓舞的迹象。然而，农村地区吸毒过量死亡率的上升，超过了城市地区，这令人关切。公共卫生行动:了解大都市和非大都市地区在药物使用、药物使用障碍和药物过量死亡方面的差异可以帮助公共卫生专业人员识别、监测和优先考虑应对措施。考虑到人们居住的地方和他们死于过量的地方，可以加强具体的过量预防干预措施，如纳洛酮给药或抢救呼吸培训。CDC阿片类药物治疗慢性疼痛指南(Dowell D, Haegerich TM, Chou R. CDC阿片类药物治疗慢性疼痛指南-美国，2016)。MMWR建议Rep 2016;66[No. 6]RR-1])，促进更好地获得美沙酮、丁丙诺啡或纳曲酮等药物辅助治疗，可以使阿片类药物使用障碍率高的社区受益。
{"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":"<p><strong>Problem/condition: </strong>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.</p><p><strong>Reporting period: </strong>Illicit drug use and drug use disorders during 2003-2014, and drug overdose deaths during 1999-2015.</p><p><strong>Description of data: </strong>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 <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).</p><p><strong>Results: </strong>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}
Asha Z Ivey-Stephenson, Alex E Crosby, Shane P D Jack, Tadesse Haileyesus, Marcie-Jo Kresnow-Sedacca
<p><strong>Problem/condition: </strong>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.</p><p><strong>Reporting period: </strong>2001-2015.</p><p><strong>Description of system: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Interpretation: </strong>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.</p><p><strong>Public health action: </strong>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
{"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":"<p><strong>Problem/condition: </strong>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.</p><p><strong>Reporting period: </strong>2001-2015.</p><p><strong>Description of system: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Interpretation: </strong>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.</p><p><strong>Public health action: </strong>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}
Laurie F Beck, Jonathan Downs, Mark R Stevens, Erin K Sauber-Schatz
Problem/condition: 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.
Reporting period: 2014.
Description of systems: 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).
Results: 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.
Interpretation: 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.
Public health actions: Seat belt use decreases and age-adjusted passenger-vehicle-occupant death rates increase with increasing levels of rurality. Improving seat belt use
{"title":"Rural and Urban Differences in Passenger-Vehicle-Occupant Deaths and Seat Belt Use Among Adults - United States, 2014.","authors":"Laurie F Beck, Jonathan Downs, Mark R Stevens, Erin K Sauber-Schatz","doi":"10.15585/mmwr.ss6617a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6617a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>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.</p><p><strong>Reporting period: </strong>2014.</p><p><strong>Description of systems: </strong>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).</p><p><strong>Results: </strong>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.</p><p><strong>Interpretation: </strong>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.</p><p><strong>Public health actions: </strong>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}
Sonya Gamble, Tebitha Mawokomatanda, Fang Xu, Pranesh P Chowdhury, Carol Pierannunzi, David Flegel, William Garvin, Machell Town
<p><strong>Problem: </strong>Chronic diseases and conditions (e.g., heart diseases, stroke, arthritis, and diabetes) are the leading causes of morbidity and mortality in the United States. These conditions are costly to the U.S. economy, yet they are often preventable or controllable. Behavioral risk factors (e.g., excessive alcohol consumption, tobacco use, poor diet, frequent mental distress, and insufficient sleep) are linked to the leading causes of morbidity and mortality. Adopting positive health behaviors (e.g., staying physically active, quitting tobacco use, obtaining routine physical checkups, and checking blood pressure and cholesterol levels) can reduce morbidity and mortality from chronic diseases and conditions. Monitoring the health risk behaviors, chronic diseases and conditions, access to health care, and use of preventive health services at multilevel public health points (states, territories, and metropolitan and micropolitan statistical areas [MMSA]) can provide important information for development and evaluation of health intervention programs.</p><p><strong>Reporting period: </strong>2013 and 2014.</p><p><strong>Description of the system: </strong>The Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing, state-based, random-digit-dialed 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 and practices related to the leading causes of death and disability in the United States and participating territories. This is the first BRFSS report to include age-adjusted prevalence estimates. For 2013 and 2014, these age-adjusted prevalence estimates are presented for all 50 states, the District of Columbia, the Commonwealth of Puerto Rico, Guam, and selected MMSA.</p><p><strong>Results: </strong>Age-adjusted prevalence estimates of health status indicators, health care access and preventive practices, health risk behaviors, chronic diseases and conditions, and cardiovascular conditions vary by state, territory, and MMSA. Each set of proportions presented refers to the range of age-adjusted prevalence estimates of selected BRFSS measures as reported by survey respondents. The following are estimates for 2013. Adults reporting frequent mental distress: 7.7%-15.2% in states and territories and 6.3%-19.4% in MMSA. Adults with inadequate sleep: 27.6%-49.2% in states and territories and 26.5%-44.4% in MMSA. Adults aged 18-64 years having health care coverage: 66.9%-92.4% in states and territories and 60.5%-97.6% in MMSA. Adults identifying as current cigarette smokers: 10.1%-28.8% in states and territories and 6.1%-33.6% in MMSA. Adults reporting binge drinking during the past month: 10.5%-25.2% in states and territories and 7.2%-25.3% in MMSA. Adults with obesity: 21.0%-35.2% in states and territories and 12.1%-37.1% in MMSA. Adults aged ≥45 years w
{"title":"Surveillance for Certain Health Behaviors and Conditions Among States and Selected Local Areas - Behavioral Risk Factor Surveillance System, United States, 2013 and 2014.","authors":"Sonya Gamble, Tebitha Mawokomatanda, Fang Xu, Pranesh P Chowdhury, Carol Pierannunzi, David Flegel, William Garvin, Machell Town","doi":"10.15585/mmwr.ss6616a1","DOIUrl":"10.15585/mmwr.ss6616a1","url":null,"abstract":"<p><strong>Problem: </strong>Chronic diseases and conditions (e.g., heart diseases, stroke, arthritis, and diabetes) are the leading causes of morbidity and mortality in the United States. These conditions are costly to the U.S. economy, yet they are often preventable or controllable. Behavioral risk factors (e.g., excessive alcohol consumption, tobacco use, poor diet, frequent mental distress, and insufficient sleep) are linked to the leading causes of morbidity and mortality. Adopting positive health behaviors (e.g., staying physically active, quitting tobacco use, obtaining routine physical checkups, and checking blood pressure and cholesterol levels) can reduce morbidity and mortality from chronic diseases and conditions. Monitoring the health risk behaviors, chronic diseases and conditions, access to health care, and use of preventive health services at multilevel public health points (states, territories, and metropolitan and micropolitan statistical areas [MMSA]) can provide important information for development and evaluation of health intervention programs.</p><p><strong>Reporting period: </strong>2013 and 2014.</p><p><strong>Description of the system: </strong>The Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing, state-based, random-digit-dialed 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 and practices related to the leading causes of death and disability in the United States and participating territories. This is the first BRFSS report to include age-adjusted prevalence estimates. For 2013 and 2014, these age-adjusted prevalence estimates are presented for all 50 states, the District of Columbia, the Commonwealth of Puerto Rico, Guam, and selected MMSA.</p><p><strong>Results: </strong>Age-adjusted prevalence estimates of health status indicators, health care access and preventive practices, health risk behaviors, chronic diseases and conditions, and cardiovascular conditions vary by state, territory, and MMSA. Each set of proportions presented refers to the range of age-adjusted prevalence estimates of selected BRFSS measures as reported by survey respondents. The following are estimates for 2013. Adults reporting frequent mental distress: 7.7%-15.2% in states and territories and 6.3%-19.4% in MMSA. Adults with inadequate sleep: 27.6%-49.2% in states and territories and 26.5%-44.4% in MMSA. Adults aged 18-64 years having health care coverage: 66.9%-92.4% in states and territories and 60.5%-97.6% in MMSA. Adults identifying as current cigarette smokers: 10.1%-28.8% in states and territories and 6.1%-33.6% in MMSA. Adults reporting binge drinking during the past month: 10.5%-25.2% in states and territories and 7.2%-25.3% in MMSA. Adults with obesity: 21.0%-35.2% in states and territories and 12.1%-37.1% in MMSA. Adults aged ≥45 years w","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 16","pages":"1-144"},"PeriodicalIF":37.3,"publicationDate":"2017-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829867/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10264661","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}
Katherine Kolor, Zhuo Chen, Scott D Grosse, Juan L Rodriguez, Ridgely Fisk Green, W David Dotson, M Scott Bowen, Julie A Lynch, Muin J Khoury
<p><strong>Problem/condition: </strong>Genetic testing for breast cancer 1 (BRCA1) and breast cancer 2 (BRCA2) gene mutations can identify women at increased risk for breast and ovarian cancer. These testing results can be used to select preventive interventions and guide treatment. Differences between nonmetropolitan and metropolitan populations in rates of BRCA testing and receipt of preventive interventions after testing have not previously been examined.</p><p><strong>Period covered: </strong>2009-2014.</p><p><strong>Description of system: </strong>Medical claims data from Truven Health Analytics MarketScan Commercial Claims and Encounters databases were used to estimate rates of BRCA testing and receipt of preventive interventions after BRCA testing among women aged 18-64 years with employer-sponsored health insurance in metropolitan and nonmetropolitan areas of the United States, both nationally and regionally.</p><p><strong>Results: </strong>From 2009 to 2014, BRCA testing rates per 100,000 women aged 18-64 years with employer-sponsored health insurance increased 2.3 times (102.7 to 237.8) in metropolitan areas and 3.0 times (64.8 to 191.3) in nonmetropolitan areas. The relative difference in BRCA testing rates between metropolitan and nonmetropolitan areas decreased from 37% in 2009 (102.7 versus 64.8) to 20% in 2014 (237.8 versus 191.3). The relative difference in BRCA testing rates between metropolitan and nonmetropolitan areas decreased more over time in younger women than in older women and decreased in all regions except the West. Receipt of preventive services 90 days after BRCA testing in metropolitan versus nonmetropolitan areas throughout the period varied by service: the percentage of women who received a mastectomy was similar, the percentage of women who received magnetic resonance imaging of the breast was lower in nonmetropolitan areas (as low as 5.8% in 2014 to as high as 8.2% in 2011) than metropolitan areas (as low as 7.3% in 2014 to as high as 10.3% in 2011), and the percentage of women who received mammography was lower in nonmetropolitan areas in earlier years but was similar in later years.</p><p><strong>Interpretation: </strong>Possible explanations for the 47% decrease in the relative difference in BRCA testing rates over the study period include increased access to genetic services in nonmetropolitan areas and increased demand nationally as a result of publicity. The relative differences in metropolitan and nonmetropolitan BRCA testing rates were smaller among women at younger ages compared with older ages.</p><p><strong>Public health action: </strong>Improved data sources and surveillance tools are needed to gather comprehensive data on BRCA testing in the United States, monitor adherence to evidence-based guidelines for BRCA testing, and assess receipt of preventive interventions for women with BRCA mutations. Programs can build on the recent decrease in geographic disparities in receipt of BRCA testing while sim
问题/状况:乳腺癌1号(BRCA1)和乳腺癌2号(BRCA2)基因突变的基因检测可以识别出乳腺癌和卵巢癌风险增加的女性。这些检测结果可用于选择预防干预措施和指导治疗。非大都市人群和大都市人群在BRCA检测率和检测后接受预防性干预措施方面的差异此前未被研究过。涵盖期间:2009-2014年。系统描述:来自Truven Health Analytics MarketScan Commercial claims和Encounters数据库的医疗索赔数据被用于估计美国大都市和非大都市地区18-64岁雇主赞助的健康保险女性的BRCA检测率和BRCA检测后预防性干预的接受率，包括国家和地区。结果:2009 - 2014年，大城市地区每10万名18-64岁雇主赞助医疗保险女性的BRCA检测率增加了2.3倍(102.7至237.8)，非大城市地区增加了3.0倍(64.8至191.3)。大都市和非大都市地区BRCA检测率的相对差异从2009年的37%(102.7对64.8)下降到2014年的20%(237.8对191.3)。随着时间的推移，年轻女性和非大都市地区BRCA检测率的相对差异比老年女性下降得更多，除西部地区外，所有地区都有所下降。在大都市地区和非大都市地区，BRCA检测后90天内接受预防服务的情况因服务而异:妇女接受乳房切除术的比例是相似的,女性的比例接受核磁共振成像的乳房nonmetropolitan地区较低(低至2014年的5.8%到2011年高达8.2%)比大城市(低至2014年的7.3%到2011年高达10.3%),和妇女接受乳房x光检查的百分比低nonmetropolitan地区早些年但在晚年很相似。解释:在研究期间，BRCA检测率的相对差异降低了47%，可能的解释包括非大都市地区获得遗传服务的机会增加，以及由于宣传而导致全国需求增加。与老年妇女相比，年轻妇女在大都市和非大都市BRCA检测率上的相对差异较小。公共卫生行动:需要改进数据来源和监测工具，以收集美国BRCA检测的综合数据，监测BRCA检测循证指南的遵守情况，并评估BRCA突变妇女预防性干预措施的接受情况。项目可以建立在最近接受BRCA检测的地域差异减少的基础上，同时教育公众和卫生保健提供者关于美国预防服务工作组的建议和其他BRCA检测和咨询的临床指南。
{"title":"BRCA Genetic Testing and Receipt of Preventive Interventions Among Women Aged 18-64 Years with Employer-Sponsored Health Insurance in Nonmetropolitan and Metropolitan Areas - United States, 2009-2014.","authors":"Katherine Kolor, Zhuo Chen, Scott D Grosse, Juan L Rodriguez, Ridgely Fisk Green, W David Dotson, M Scott Bowen, Julie A Lynch, Muin J Khoury","doi":"10.15585/mmwr.ss6615a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6615a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Genetic testing for breast cancer 1 (BRCA1) and breast cancer 2 (BRCA2) gene mutations can identify women at increased risk for breast and ovarian cancer. These testing results can be used to select preventive interventions and guide treatment. Differences between nonmetropolitan and metropolitan populations in rates of BRCA testing and receipt of preventive interventions after testing have not previously been examined.</p><p><strong>Period covered: </strong>2009-2014.</p><p><strong>Description of system: </strong>Medical claims data from Truven Health Analytics MarketScan Commercial Claims and Encounters databases were used to estimate rates of BRCA testing and receipt of preventive interventions after BRCA testing among women aged 18-64 years with employer-sponsored health insurance in metropolitan and nonmetropolitan areas of the United States, both nationally and regionally.</p><p><strong>Results: </strong>From 2009 to 2014, BRCA testing rates per 100,000 women aged 18-64 years with employer-sponsored health insurance increased 2.3 times (102.7 to 237.8) in metropolitan areas and 3.0 times (64.8 to 191.3) in nonmetropolitan areas. The relative difference in BRCA testing rates between metropolitan and nonmetropolitan areas decreased from 37% in 2009 (102.7 versus 64.8) to 20% in 2014 (237.8 versus 191.3). The relative difference in BRCA testing rates between metropolitan and nonmetropolitan areas decreased more over time in younger women than in older women and decreased in all regions except the West. Receipt of preventive services 90 days after BRCA testing in metropolitan versus nonmetropolitan areas throughout the period varied by service: the percentage of women who received a mastectomy was similar, the percentage of women who received magnetic resonance imaging of the breast was lower in nonmetropolitan areas (as low as 5.8% in 2014 to as high as 8.2% in 2011) than metropolitan areas (as low as 7.3% in 2014 to as high as 10.3% in 2011), and the percentage of women who received mammography was lower in nonmetropolitan areas in earlier years but was similar in later years.</p><p><strong>Interpretation: </strong>Possible explanations for the 47% decrease in the relative difference in BRCA testing rates over the study period include increased access to genetic services in nonmetropolitan areas and increased demand nationally as a result of publicity. The relative differences in metropolitan and nonmetropolitan BRCA testing rates were smaller among women at younger ages compared with older ages.</p><p><strong>Public health action: </strong>Improved data sources and surveillance tools are needed to gather comprehensive data on BRCA testing in the United States, monitor adherence to evidence-based guidelines for BRCA testing, and assess receipt of preventive interventions for women with BRCA mutations. Programs can build on the recent decrease in geographic disparities in receipt of BRCA testing while sim","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 15","pages":"1-11"},"PeriodicalIF":24.9,"publicationDate":"2017-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5879728/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35382016","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}
S Jane Henley, Robert N Anderson, Cheryll C Thomas, Greta M Massetti, Brandy Peaker, Lisa C Richardson
Problem/condition: Previous reports have shown that persons living in nonmetropolitan (rural or urban) areas in the United States have higher death rates from all cancers combined than persons living in metropolitan areas. Disparities might vary by cancer type and between occurrence and death from the disease. This report provides a comprehensive assessment of cancer incidence and deaths by cancer type in nonmetropolitan and metropolitan counties.
Reporting period: 2004-2015.
Description of system: 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 2009-2013 and trends in annual age-adjusted incidence rates for 2004-2013. Cancer mortality data from the National Vital Statistics System were used to calculate average annual age-adjusted death rates for 2011-2015 and trends in annual age-adjusted death rates for 2006-2015. For 5-year average annual rates, counties were classified into four categories (nonmetropolitan rural, nonmetropolitan urban, metropolitan with population <1 million, and metropolitan with population ≥1 million). For the trend analysis, which used annual rates, these categories were combined into two categories (nonmetropolitan and metropolitan). Rates by county classification were examined by sex, age, race/ethnicity, U.S. census region, and cancer site. Trends in rates were examined by county classification and cancer site.
Results: During the most recent 5-year period for which data were available, nonmetropolitan rural areas had lower average annual age-adjusted cancer incidence rates for all anatomic cancer sites combined but higher death rates than metropolitan areas. During 2006-2015, the annual age-adjusted death rates for all cancer sites combined decreased at a slower pace in nonmetropolitan areas (-1.0% per year) than in metropolitan areas (-1.6% per year), increasing the differences in these rates. In contrast, annual age-adjusted incidence rates for all cancer sites combined decreased approximately 1% per year during 2004-2013 both in nonmetropolitan and metropolitan counties.
Interpretation: This report provides the first comprehensive description of cancer incidence and mortality in nonmetropolitan and metropolitan counties in the United States. Nonmetropolitan rural counties had higher incidence of and deaths from several cancers related to tobacco use and cancers that can be prevented by screening. Differences between nonmetropolitan and metropolitan counties in cancer incidence might reflect differences in risk factors such as cigarette smoking, obesity, and physical inactivity, whereas differences in cancer death rates might reflect disparities in access to health care and timely diagnosis and treatment.
{"title":"Invasive Cancer Incidence, 2004-2013, and Deaths, 2006-2015, in Nonmetropolitan and Metropolitan Counties - United States.","authors":"S Jane Henley, Robert N Anderson, Cheryll C Thomas, Greta M Massetti, Brandy Peaker, Lisa C Richardson","doi":"10.15585/mmwr.ss6614a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6614a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Previous reports have shown that persons living in nonmetropolitan (rural or urban) areas in the United States have higher death rates from all cancers combined than persons living in metropolitan areas. Disparities might vary by cancer type and between occurrence and death from the disease. This report provides a comprehensive assessment of cancer incidence and deaths by cancer type in nonmetropolitan and metropolitan counties.</p><p><strong>Reporting period: </strong>2004-2015.</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 2009-2013 and trends in annual age-adjusted incidence rates for 2004-2013. Cancer mortality data from the National Vital Statistics System were used to calculate average annual age-adjusted death rates for 2011-2015 and trends in annual age-adjusted death rates for 2006-2015. For 5-year average annual rates, counties were classified into four categories (nonmetropolitan rural, nonmetropolitan urban, metropolitan with population <1 million, and metropolitan with population ≥1 million). For the trend analysis, which used annual rates, these categories were combined into two categories (nonmetropolitan and metropolitan). Rates by county classification were examined by sex, age, race/ethnicity, U.S. census region, and cancer site. Trends in rates were examined by county classification and cancer site.</p><p><strong>Results: </strong>During the most recent 5-year period for which data were available, nonmetropolitan rural areas had lower average annual age-adjusted cancer incidence rates for all anatomic cancer sites combined but higher death rates than metropolitan areas. During 2006-2015, the annual age-adjusted death rates for all cancer sites combined decreased at a slower pace in nonmetropolitan areas (-1.0% per year) than in metropolitan areas (-1.6% per year), increasing the differences in these rates. In contrast, annual age-adjusted incidence rates for all cancer sites combined decreased approximately 1% per year during 2004-2013 both in nonmetropolitan and metropolitan counties.</p><p><strong>Interpretation: </strong>This report provides the first comprehensive description of cancer incidence and mortality in nonmetropolitan and metropolitan counties in the United States. Nonmetropolitan rural counties had higher incidence of and deaths from several cancers related to tobacco use and cancers that can be prevented by screening. Differences between nonmetropolitan and metropolitan counties in cancer incidence might reflect differences in risk factors such as cigarette smoking, obesity, and physical inactivity, whereas differences in cancer death rates might reflect disparities in access to health care and timely diagnosis and treatment.</p><p><strong>Public h","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 14","pages":"1-13"},"PeriodicalIF":24.9,"publicationDate":"2017-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5879727/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35148803","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}
<p><strong>Problem/condition: </strong>The places in which persons live, work, and play can contribute to the development of adverse health outcomes. Understanding the differences in risk factors in various environments can help to explain differences in the occurrence of these outcomes and can be used to develop public health programs, interventions, and policies. Efforts to characterize urban and rural differences have largely focused on social and demographic characteristics. A paucity of national standardized environmental data has hindered efforts to characterize differences in the physical aspects of urban and rural areas, such as air and water quality.</p><p><strong>Reporting period: </strong>2008-2012 for air quality and 2010-2015 for water quality.</p><p><strong>Description of system: </strong>Since 2002, CDC's National Environmental Public Health Tracking Program has collaborated with federal, state, and local partners to gather standardized environmental data by creating national data standards, collecting available data, and disseminating data to be used in developing public health actions. The National Environmental Public Health Tracking Network (i.e., the tracking network) collects data provided by national, state, and local partners and includes 21 health outcomes, exposures, and environmental hazards. To assess environmental factors that affect health, CDC analyzed three air-quality measures from the tracking network for all counties in the contiguous United States during 2008-2012 and one water-quality measure for 26 states during 2010-2015. The three air-quality measures include 1) total number of days with fine particulate matter (PM<sub>2.5</sub>) levels greater than the U.S. Environmental Protection Agency's (EPA's) National Ambient Air Quality Standards (NAAQS) for 24-hour average PM<sub>2.5</sub> (PM<sub>2.5</sub> days); 2) mean annual average ambient concentrations of PM<sub>2.5</sub> in micrograms per cubic meter (mean PM<sub>2.5</sub>); and 3) total number of days with maximum 8-hour average ozone concentrations greater than the NAAQS (ozone days). The water-quality measure compared the annual mean concentration for a community water system (CWS) to the maximum contaminant level (MCL) defined by EPA for 10 contaminants: arsenic, atrazine, di(2-ethylhexyl) phthalate (DEHP), haloacetic acids (HAA5), nitrate, perchloroethene (PCE), radium, trichloroethene (TCE), total trihalomethanes (TTHM), and uranium. Findings are presented by urban-rural classification scheme: four metropolitan (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) and two nonmetropolitan (micropolitan and noncore) categories. Regression modeling was used to determine whether differences in the measures by urban-rural categories were statistically significant.</p><p><strong>Results: </strong>Patterns for all three air-quality measures suggest that air quality improves as areas become more rural (or less urb
{"title":"Rural and Urban Differences in Air Quality, 2008-2012, and Community Drinking Water Quality, 2010-2015 - United States.","authors":"Heather Strosnider, Caitlin Kennedy, Michele Monti, Fuyuen Yip","doi":"10.15585/mmwr.ss6613a1","DOIUrl":"https://doi.org/10.15585/mmwr.ss6613a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>The places in which persons live, work, and play can contribute to the development of adverse health outcomes. Understanding the differences in risk factors in various environments can help to explain differences in the occurrence of these outcomes and can be used to develop public health programs, interventions, and policies. Efforts to characterize urban and rural differences have largely focused on social and demographic characteristics. A paucity of national standardized environmental data has hindered efforts to characterize differences in the physical aspects of urban and rural areas, such as air and water quality.</p><p><strong>Reporting period: </strong>2008-2012 for air quality and 2010-2015 for water quality.</p><p><strong>Description of system: </strong>Since 2002, CDC's National Environmental Public Health Tracking Program has collaborated with federal, state, and local partners to gather standardized environmental data by creating national data standards, collecting available data, and disseminating data to be used in developing public health actions. The National Environmental Public Health Tracking Network (i.e., the tracking network) collects data provided by national, state, and local partners and includes 21 health outcomes, exposures, and environmental hazards. To assess environmental factors that affect health, CDC analyzed three air-quality measures from the tracking network for all counties in the contiguous United States during 2008-2012 and one water-quality measure for 26 states during 2010-2015. The three air-quality measures include 1) total number of days with fine particulate matter (PM<sub>2.5</sub>) levels greater than the U.S. Environmental Protection Agency's (EPA's) National Ambient Air Quality Standards (NAAQS) for 24-hour average PM<sub>2.5</sub> (PM<sub>2.5</sub> days); 2) mean annual average ambient concentrations of PM<sub>2.5</sub> in micrograms per cubic meter (mean PM<sub>2.5</sub>); and 3) total number of days with maximum 8-hour average ozone concentrations greater than the NAAQS (ozone days). The water-quality measure compared the annual mean concentration for a community water system (CWS) to the maximum contaminant level (MCL) defined by EPA for 10 contaminants: arsenic, atrazine, di(2-ethylhexyl) phthalate (DEHP), haloacetic acids (HAA5), nitrate, perchloroethene (PCE), radium, trichloroethene (TCE), total trihalomethanes (TTHM), and uranium. Findings are presented by urban-rural classification scheme: four metropolitan (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) and two nonmetropolitan (micropolitan and noncore) categories. Regression modeling was used to determine whether differences in the measures by urban-rural categories were statistically significant.</p><p><strong>Results: </strong>Patterns for all three air-quality measures suggest that air quality improves as areas become more rural (or less urb","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 13","pages":"1-10"},"PeriodicalIF":24.9,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15585/mmwr.ss6613a1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35112794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p><strong>Problem/condition: </strong>Malaria in humans is caused by intraerythrocytic protozoa of the genus Plasmodium. These parasites are transmitted by the bite of an infective female Anopheles mosquito. The majority of malaria infections in the United States occur among persons who have traveled to regions with ongoing malaria transmission. However, malaria is occasionally acquired by persons who have not traveled out of the country through exposure to infected blood products, congenital transmission, laboratory exposure, or local mosquitoborne transmission. Malaria surveillance in the United States is conducted to identify episodes of local transmission and to guide prevention recommendations for travelers.</p><p><strong>Period covered: </strong>This report summarizes cases in persons with onset of illness in 2014 and trends during previous years.</p><p><strong>Description of system: </strong>Malaria cases diagnosed by blood film, polymerase chain reaction, or rapid diagnostic tests are reported to local and state health departments by health care providers or laboratory staff. Case investigations are conducted by local and state health departments, and reports are transmitted to CDC through the National Malaria Surveillance System, National Notifiable Diseases Surveillance System, or direct CDC consultations. CDC conducts antimalarial drug resistance marker testing on blood samples submitted by health care providers or local or state health departments. Data from these reporting systems serve as the basis for this report.</p><p><strong>Results: </strong>CDC received reports of 1,724 confirmed malaria cases, including one congenital case and two cryptic cases, with onset of symptoms in 2014 among persons in the United States. The number of confirmed cases in 2014 is consistent with the number of confirmed cases reported in 2013 (n = 1,741; this number has been updated from a previous publication to account for delayed reporting for persons with symptom onset occurring in late 2013). Plasmodium falciparum, P. vivax, P. ovale, and P. malariae were identified in 66.1%, 13.3%, 5.2%, and 2.7% of cases, respectively. Less than 1.0% of patients were infected with two species. The infecting species was unreported or undetermined in 11.7% of cases. CDC provided diagnostic assistance for 14.2% of confirmed cases and tested 12.0% of P. falciparum specimens for antimalarial resistance markers. Of patients who reported purpose of travel, 57.5% were visiting friends and relatives (VFR). Among U.S. residents for whom information on chemoprophylaxis use and travel region was known, 7.8% reported that they initiated and adhered to a chemoprophylaxis drug regimen recommended by CDC for the regions to which they had traveled. Thirty-two cases were among pregnant women, none of whom had adhered to chemoprophylaxis. Among all reported cases, 17.0% were classified as severe illness, and five persons with malaria died. CDC received 137 P. falciparum-positive sam
{"title":"Malaria Surveillance - United States, 2014.","authors":"Kimberly E Mace, Paul M Arguin","doi":"10.15585/mmwr.ss6612a1","DOIUrl":"10.15585/mmwr.ss6612a1","url":null,"abstract":"<p><strong>Problem/condition: </strong>Malaria in humans is caused by intraerythrocytic protozoa of the genus Plasmodium. These parasites are transmitted by the bite of an infective female Anopheles mosquito. The majority of malaria infections in the United States occur among persons who have traveled to regions with ongoing malaria transmission. However, malaria is occasionally acquired by persons who have not traveled out of the country through exposure to infected blood products, congenital transmission, laboratory exposure, or local mosquitoborne transmission. Malaria surveillance in the United States is conducted to identify episodes of local transmission and to guide prevention recommendations for travelers.</p><p><strong>Period covered: </strong>This report summarizes cases in persons with onset of illness in 2014 and trends during previous years.</p><p><strong>Description of system: </strong>Malaria cases diagnosed by blood film, polymerase chain reaction, or rapid diagnostic tests are reported to local and state health departments by health care providers or laboratory staff. Case investigations are conducted by local and state health departments, and reports are transmitted to CDC through the National Malaria Surveillance System, National Notifiable Diseases Surveillance System, or direct CDC consultations. CDC conducts antimalarial drug resistance marker testing on blood samples submitted by health care providers or local or state health departments. Data from these reporting systems serve as the basis for this report.</p><p><strong>Results: </strong>CDC received reports of 1,724 confirmed malaria cases, including one congenital case and two cryptic cases, with onset of symptoms in 2014 among persons in the United States. The number of confirmed cases in 2014 is consistent with the number of confirmed cases reported in 2013 (n = 1,741; this number has been updated from a previous publication to account for delayed reporting for persons with symptom onset occurring in late 2013). Plasmodium falciparum, P. vivax, P. ovale, and P. malariae were identified in 66.1%, 13.3%, 5.2%, and 2.7% of cases, respectively. Less than 1.0% of patients were infected with two species. The infecting species was unreported or undetermined in 11.7% of cases. CDC provided diagnostic assistance for 14.2% of confirmed cases and tested 12.0% of P. falciparum specimens for antimalarial resistance markers. Of patients who reported purpose of travel, 57.5% were visiting friends and relatives (VFR). Among U.S. residents for whom information on chemoprophylaxis use and travel region was known, 7.8% reported that they initiated and adhered to a chemoprophylaxis drug regimen recommended by CDC for the regions to which they had traveled. Thirty-two cases were among pregnant women, none of whom had adhered to chemoprophylaxis. Among all reported cases, 17.0% were classified as severe illness, and five persons with malaria died. CDC received 137 P. falciparum-positive sam","PeriodicalId":48549,"journal":{"name":"Mmwr Surveillance Summaries","volume":"66 12","pages":"1-24"},"PeriodicalIF":37.3,"publicationDate":"2017-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829864/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35026354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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