Co-benefits of climate mitigation: Counting statistical lives or life-years?

2017 ◽  
Vol 79 ◽  
pp. 11-18 ◽  
Author(s):  
Mikael Skou Andersen
Keyword(s):  
Climate Mitigation ◽  
Life Years ◽  
Statistical Lives

Uneven Decoupling

2019 ◽  
Vol 5 (4) ◽  
pp. 410-427 ◽  
Author(s):  
Ryan P. Thombs ◽  
Xiaorui Huang
Keyword(s):  
Economic Growth ◽  
Co2 Emissions ◽  
Ecological Modernization ◽  
Climate Mitigation ◽  
Data Limitations ◽  
Treadmill Of Production ◽  
Global North ◽  
Organization Of Production ◽  
Changes Over Time ◽  
Over Time

The macro-comparative decoupling literature has often sought to test the arguments made by the treadmill of production (TP) and ecological modernization (EM) theories. However, due to data limitations, these studies have been limited to analyzing the years after 1960. Given that both theories discuss historical processes operating before 1960, analyzing pre-1960 data is warranted to more comprehensively test the propositions made by both theories. We assess the long-term relationship between economic growth and CO2 emissions from 1870 to 2014 using a sample of global North nations. We use Prais-Winsten regression models with time interactions to assess whether, when, and how much CO2 emissions have decoupled from economic growth over time. We find that significant relative decoupling has occurred twice since 1870: during the last 30 years of the nineteenth century, the timing of which is contrary to what both the EM and TP theories might expect, and after 1970. We also observe that the relationship remained relatively stable from the turn of the twentieth century to approximately 1970, which aligns with the arguments made by the classical TP work. We conclude that shifts in the global organization of production have shaped the magnitude of the economic growth–CO2 emissions relationship and its changes over time, which has implications for climate mitigation policy.

The monetary value of disability-adjusted-life-years lost in Kenya in 2017.pdf

2019 ◽  
Author(s):  
Joses Kirigia ◽  
Rose Nabi Deborah Karimi Muthuri
Keyword(s):  
New York ◽  
International Monetary Fund ◽  
Health Expenditure ◽  
Analytical Framework ◽  
World Health ◽  
Gdp Per Capita ◽  
Current Health ◽  
Monetary Value ◽  
Life Years ◽  
Per Capita

<div>A variant of human capital (or net output) analytical framework was applied to monetarily value DALYs lost from 166 diseases and injuries. The monetary value of each of the 166 diseases (or injuries) was obtained through multiplication of the net 2019 GDP per capita for Kenya by the number of DALYs lost from each specific cause. Where net GDP per capita was calculated by subtracting current health expenditure from the GDP per capita. </div><div> </div><p>The DALYs data for the 166 causes were from IHME (Global Burden of Disease Collaborative Network, 2018), GDP per capita data from the International Monetary Fund world economic outlook database (International Monetary Fund, 2019), and the current health expenditure per person data from the WHO Global Health Expenditure Database (World Health Organization, 2019b). A model consisting of fourteen equations was calculated with Excel Software developed by Microsoft (New York).</p><p> </p>

Analysis of Land Use Land Cover in Annapurna Conservation Area in Gandaki Province, Nepal using Vegetation Index and Land Use Land Cover Datasets

2019 ◽  
Vol 2 (2) ◽  
pp. 87-99
Author(s):  
Shiva Pokhrel ◽  
Chungla Sherpa
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
National Level ◽  
Climate Mitigation ◽  
Land Use Land Cover ◽  
Conservation Area ◽  
Barren Land ◽  
Wide Range ◽  
Annapurna Conservation Area

Conservation areas are originally well-known for protecting landscape features and wildlife. They are playing key role in conserving and providing a wide range of ecosystem services, social, economic and cultural benefits as well as vital places for climate mitigation and adaptation. We have analyzed decadal changes in land cover and status of vegetation cover in the conservation area using both national level available data on land use land cover (LULC) changes (1990-2010) and normalized difference vegetation index (NDVI) (2010-2018) in Annapurna conservation area. LULC showed the barren land as the most dominant land cover types in all three different time series 1990, 2000 and 2010 with followed by snow cover, grassland, forest, agriculture and water body. The highest NDVI values were observed at Southern, Southwestern and Southeastern part of conservation area consisting of forest area, shrub land and grassland while toward low to negative in the upper middle to the Northern part of the conservation area.

Identifying Public Health Problems

2018 ◽  
Author(s):  
Scott Burris ◽  
Micah L. Berman ◽  
Matthew Penn, and ◽  
Tara Ramanathan Holiday
Keyword(s):  
Public Health ◽  
Health Problems ◽  
Health Priorities ◽  
Disability Adjusted Life Years ◽  
Quality Adjusted Life Years ◽  
Disability Adjusted Life ◽  
Life Years ◽  
Study Designs ◽  
Quality Adjusted Life

Chapter 5 discusses the use of epidemiology to identify the source of public health problems and inform policymaking. It uses a case study to illustrate how researchers, policymakers, and practitioners detect diseases, identify their sources, determine the extent of an outbreak, and prevent new infections. The chapter also defines key measures in epidemiology that can indicate public health priorities, including morbidity and mortality, years of potential life lost, and measures of lifetime impacts, including disability-adjusted life years and quality-adjusted life years. Finally, the chapter reviews epidemiological study designs, differentiating between experimental and observational studies, to show how to interpret data and identify limitations.

Health and Well-Being in Adolescence

2018 ◽  
Author(s):  
Susan M. Sawyer ◽  
George C. Patton
Keyword(s):  
Adolescent Health ◽  
Social Determinants ◽  
Well Being ◽  
Brain Maturation ◽  
Health Determinants ◽  
Physical And Mental Health ◽  
Disability Adjusted Life ◽  
Life Years ◽  
High Benefit ◽  
Health And Well Being

This chapter describes how the profile of physical and mental health and well-being changes across adolescence. The biological context of healthy adolescent growth and development is reviewed, including secular patterns of puberty and brain maturation. The structural and social determinants of adolescent health are then described. Adolescent health outcomes, including patterns of risk behaviors, emerge from the interaction between biological influences and social health determinants. Estimates of mortality and disability-adjusted life years are used to describe three patterns of adolescent health and well-being that vary by age, sex, and national wealth. Globally, the burden of disease increases across adolescence, varying markedly between and within countries. Comprehensive, multisectoral, evidence-informed actions are required that match these conspicuous adolescent health problems, emerging health risks, and major social determinants. Such actions, including quality education and health services, differ greatly from those that benefit younger children yet have similarly high benefit–cost ratios.

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