The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States.

Introduction: Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. Objective: To use the results of the Global Burden of Disease Study (GBD) to report trends in the burden of diseases, injuries, and risk factors at the state level from 1990 to 2016. Design and Setting: A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year. Main Outcomes and Measures: Prevalence, incidence, mortality, life expectancy, healthy life expectancy (HALE), years of life lost (YLLs) due to premature mortality, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 333 causes and 84 risk factors with 95% uncertainty intervals (UIs) were computed. Results: Between 1990 and 2016, overall death rates in the United States declined from 745.2 (95% UI, 740.6 to 749.8) per 100 000 persons to 578.0 (95% UI, 569.4 to 587.1) per 100 000 persons. The probability of death among adults aged 20 to 55 years declined in 31 states and Washington, DC from 1990 to 2016. In 2016, Hawaii had the highest life expectancy at birth (81.3 years) and Mississippi had the lowest (74.7 years), a 6.6-year difference. Minnesota had the highest HALE at birth (70.3 years), and West Virginia had the lowest (63.8 years), a 6.5-year difference. The leading causes of DALYs in the United States for 1990 and 2016 were ischemic heart disease and lung cancer, while the third leading cause in 1990 was low back pain, and the third leading cause in 2016 was chronic obstructive pulmonary disease. Opioid use disorders moved from the 11th leading cause of DALYs in 1990 to the 7th leading cause in 2016, representing a 74.5% (95% UI, 42.8% to 93.9%) change. In 2016, each of the following 6 risks individually accounted for more than 5% of risk-attributable DALYs: tobacco consumption, high body mass index (BMI), poor diet, alcohol and drug use, high fasting plasma glucose, and high blood pressure. Across all US states, the top risk factors in terms of attributable DALYs were due to 1 of the 3 following causes: tobacco consumption (32 states), high BMI (10 states), or alcohol and drug use (8 states). Conclusions and Relevance: There are wide differences in the burden of disease at the state level. Specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention. These data can be used to inform national health priorities for research, clinical care, and policy

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe

Use of System Dynamics Modeling to Explicate the Theory-of-Change of a Social Marketing Innovation

Community coalitions are an important part of the public health milieu and thus subject to many of the same external pressures as public health organizations--including changes in required strategic orientation. Many funding agencies have shifted their funding agenda from program development to policy change. Thus, the Florida Prevention Research Center created the Community-Based Prevention Marketing for Policy Development framework to teach community coalitions how to apply social marketing to policy change. The dissertation research reported here was designed to explicate the framework\u27s theory-of-change. The research question was: What are the linkages and connections between CBPM inputs, activities, immediate outcomes, intermediate outcomes, and ultimate impacts? The author implemented a case study design, with the case being a normative community coalition. The study adhered to a well-developed series of steps for system dynamics modeling. Results from model simulations show how gains in performance depend on a community coalition\u27s initial culture and initial efficiency, and that only the most efficient coalitions may see benefits in coalition performance from implementing Community-Based Prevention Marketing for Policy Development. Theoretical implications for social marketers--e.g., real-world example of how to work `upstream\u27--and system dynamics modelers--e.g., application of generic structures--are discussed. Practical implications for the framework\u27s developers--namely, the importance of managing the early expectations of framework adopters--are discussed as well

Use of System Dynamics Modeling to Explicate the Theory-of-Change of a Social Marketing Innovation

Community coalitions are an important part of the public health milieu and thus subject to many of the same external pressures as public health organizations--including changes in required strategic orientation. Many funding agencies have shifted their funding agenda from program development to policy change. Thus, the Florida Prevention Research Center created the Community-Based Prevention Marketing for Policy Development framework to teach community coalitions how to apply social marketing to policy change. The dissertation research reported here was designed to explicate the framework\u27s theory-of-change. The research question was: What are the linkages and connections between CBPM inputs, activities, immediate outcomes, intermediate outcomes, and ultimate impacts? The author implemented a case study design, with the case being a normative community coalition. The study adhered to a well-developed series of steps for system dynamics modeling. Results from model simulations show how gains in performance depend on a community coalition\u27s initial culture and initial efficiency, and that only the most efficient coalitions may see benefits in coalition performance from implementing Community-Based Prevention Marketing for Policy Development. Theoretical implications for social marketers--e.g., real-world example of how to work `upstream\u27--and system dynamics modelers--e.g., application of generic structures--are discussed. Practical implications for the framework\u27s developers--namely, the importance of managing the early expectations of framework adopters--are discussed as well

The History of Non- Criminal Background Checks: A Review

Several criminal justice and policy researchers have questioned the benefit of conducting pre- employment background checks. Our review of the background check literature suggests that persons with physical and cognitive disabilities have a much higher probability of being financially exploited, neglected, or abused. We recommend a balance of employment for incarcerated persons for re- entry into society, however, caution putting violent felons into employment providing long- term care services

Social marketing comes of age: A brief history of the community of practice, profession, and related associations, with recommendations for future growth

The emergence of the International Social Marketing Association (iSMA) and its affiliated regional associations is a key indicator that social marketing is maturing, both as a community of practice and as a profession. Through these associations, the international social marketing community has developed a consensus definition of the discipline and a consensus list of basic competencies for social marketing certificate programs. The associations are currently working on certification programs and a code of ethics. Continued movement toward professionalization can help social marketers be recognized and valued more highly for their relevant skills, knowledge, expertise, trustworthiness and altruism. At the same time, the discipline must address a number of key challenges and opportunities, to stay relevant and thrive