Modifiable Behavioral Risk Factors and the Value of Lifetime Earnings Lost among US Citizens From 2000-2016.
There has been a steady, long-term decline in mortality rates in the US. Yet, modifiable behavioral risk factors still appear responsible for approximately one million yearly premature deaths or 40% of the annual total mortalities in the United States. This study evaluated seven modifiable behavioral risk factors (tobacco smoking, misuse of alcohol, poor diet and physical inactivity, motor vehicle crashes, suicide, illicit use of drugs, and risky sexual behaviors) with respect to using the value of lifetime earnings lost (VLTEL) attributable to premature deaths. In this study, we estimated US annual deaths caused by modifiable behavioral risk factors for the period of years inclusive of 2000-2016 and it was stratified by age groups. Annual deaths per modifiable risk factor and age group were used to estimate trends on mortality. Potential economic cost of these deaths was calculated using mortality cost and expected death distribution. Finally, expected life tables were obtained using yearly mortality. We assessed the overall trends of the seven modifiable risk factors over the last 16 years in the US and found putatively more than 1 million premature mortalities. This study also showed VLTEL associated with premature mortalities to be almost $400 billion on an annual basis. Smoking and obesity were the two most common risk factors. Illicit drug use and misuse of alcohol have been increasing quite rapidly over the last decade. There are several noteworthy trends in the data. Smoking is one modifiable risk factor that has been decreasing among US citizens. In contrast, several other risk factors, such as illicit use of drugs, have been increasing in both incidence and monetary costs. The premature deaths examined in this study are important from a public health and health management perspective because they represent potentially preventable loss of life.
A memetic algorithm for the generalised machine layout problem
Designing efficient machine layouts is a key issue to ensure profitability in manufacturing environments. The major decisions in designing machine layouts are: The selection of machines (including machine replicas); the assigning of machines to the plant floor; the selection of production mix (i.e., determine the products to be produced); and the assigning of products to machines (i.e., determining the product flows). The generalised machine layout problem (GMALP) integrates these factors under a single problem. The contribution of this paper is the development of a memetic algorithm for the GMALP. The memetic algorithm takes advantage of the diversification strategies of the genetic algorithm combined with the intensification strategies of tabu search. Results obtained with the memetic algorithm compares favourably with the results presented in the literature.
Analysing Africa’s Total Factor Productivity Growth: A DEA-Malmquist and Bootstrap Approach
Using data envelopment analysis (DEA), the authors investigate the productivity changes of 42 African countries by computing the Malmquist productivity indices. Subsequently, the measured Malmquist productivity indices become the dependent variables of a pooled truncated regression. The point estimates of the Malmquist indices indicate that TFP improved at an annual rate of 1.97% over the period 1992-2007. The decomposition of TFP shows that the major contribution of TFP growth is technological progress. Nevertheless, technical efficiency also appears to be trending upwards. Therefore, these results suggest that contrary to the dominant view in previous studies, Africa's TFP since the early 1990s has been accompanied by positive technological change rather than stagnation. The second stage results suggest that improving the quality of human capital and FDI not only augments the quality of labor, but also indirectly improves TFP. Regression results also show that an increase in openness positively affects TFP growth as this facilitates adoption of more efficient techniques of production.
Trends in Behavioral Risk Factors Resulting in Premature Death in US from 2000-2015.
Several of the leading causes of mortality – heart disease, cancer, diabetes, and stroke – are attributable at least partially to modifiable behavioral risk factors. These behavioral risk factors include smoking, poor diet/physical inactivity, and misuse of alcohol. We examined the trends of seven factors (tobacco smoking, misuse of alcohol, poor diet and physical inactivity, accidents, suicide, illicit use of drugs, and sexual behaviors) over the past 15 years in the United States with respect to avoidable deaths. Our data was extracted from the Centers for Disease Control and Prevention Wonder database. The mortality data utilizes the International Classification of Disease Codes, Tenth Edition, to track causes of death. There were several noteworthy trends in the data. Despite intensified attention to preventive health measures, avoidable deaths related to smoking, obesity (due to poor diet/lack of physical exercise), accidents, and sexually transmitted diseases, have remained relatively constant in the aggregate. In contrast, avoidable deaths attributable to illicit drug use, misuse of alcohol and suicide have dramatically increased. Between the year 2000 and 2015, illicit drug use has increased by more than 150%, misuse of alcohol has increased by more than 35% and suicide by more than 50%. These factors have also increased in varying degrees with respect to age cohorts. Many of the leading causes of mortality in the United States are chronic diseases and have genetic components, but they are also the major lifestyle diseases that trace tangibly to behavioral factors. The prospect for future declines in these diseases will most likely depend on a decrease in modifiable risk factors, media and policy advocacy, environmental interventions, improved education and lifestyle modifications.
Using Data Envelope Analysis to Examine US State Health Efficiencies Over 2008-2015.
Health spending in the United States (US) has been steadily rising over the past several decades. The Affordable Care Act (ACA) became law in 2010, but was not operational until 2014. The principal intention of the legislation was to provide insurance coverage to millions of US citizens who previously did not possess health insurance to improve Americans’ health. In our study, we compare the efficiency of health care resources on a state-by-state population basis in the US between the years of 2008-2015. Efficiencies are calculated using Data Envelopment Analysis (DEA). DEA can be defined as a non-parametric technique that uses linear programming (lp) to compare the relative efficiencies of homogenous Decision Making Units (DMU) in transforming inputs into outputs. In this case, the DMUs represent the states. DEA uses lp models to build an efficiency frontier. The efficiency frontier is determined by the most efficient states (i.e., DMUs). Therefore the efficiency of each state can be compared against the frontier and therefore against the most efficient ones.
Premature Mortality Costs Associated with Lifestyle Factors among US Citizen
Purpose: The leading causes of mortality in the US include chronic diseases such as heart disease, stroke, and cancer. These diseases may also be classified as major “lifestyle” diseases that trace partially to imprudent living and risky behavior. Design: To examine the monetary costs of lifestyle choices. Setting: USA Subjects: USA citizens Measures: We utilized the most recent data from the National Center for Health Statistics and mortality costs from the USA Census Bureau in order to estimate the costs of lifestyle decisions leading to premature death. Analysis: This study examines the monetary costs associated with six personal lifestyle decisions-smoking, diet, excessive alcohol consumption, illicit drug use, accidents, sexually transmitted infections-and consequent premature mortalities. Results: Our study showed that 40.0% of the 2.47 million deaths annually in the USA may be attributed to lifestyle decisions. The majority of premature deaths that occurred were associated with three lifestyle decisions-smoking, obesity or excessive alcohol consumption. Smoking, obesity, sexually transmitted infections and accidents decreased vis-à-vis the previous decade; whereas, illicit drugs and alcohol-related premature deaths increased from the previous decade. Conclusion: The value of lifetime earnings lost among individuals as a consequence of lifestyle choices is $241 billion annually. The prospect for future declines in these premature deaths will most likely depend on a decrease in risk factors, continued lifestyle modification and population-based intervention strategies.