44 research outputs found
Fitting the integrated Spectral Energy Distributions of Galaxies
Fitting the spectral energy distributions (SEDs) of galaxies is an almost
universally used technique that has matured significantly in the last decade.
Model predictions and fitting procedures have improved significantly over this
time, attempting to keep up with the vastly increased volume and quality of
available data. We review here the field of SED fitting, describing the
modelling of ultraviolet to infrared galaxy SEDs, the creation of
multiwavelength data sets, and the methods used to fit model SEDs to observed
galaxy data sets. We touch upon the achievements and challenges in the major
ingredients of SED fitting, with a special emphasis on describing the interplay
between the quality of the available data, the quality of the available models,
and the best fitting technique to use in order to obtain a realistic
measurement as well as realistic uncertainties. We conclude that SED fitting
can be used effectively to derive a range of physical properties of galaxies,
such as redshift, stellar masses, star formation rates, dust masses, and
metallicities, with care taken not to over-interpret the available data. Yet
there still exist many issues such as estimating the age of the oldest stars in
a galaxy, finer details ofdust properties and dust-star geometry, and the
influences of poorly understood, luminous stellar types and phases. The
challenge for the coming years will be to improve both the models and the
observational data sets to resolve these uncertainties. The present review will
be made available on an interactive, moderated web page (sedfitting.org), where
the community can access and change the text. The intention is to expand the
text and keep it up to date over the coming years.Comment: 54 pages, 26 figures, Accepted for publication in Astrophysics &
Space Scienc
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Track A Basic Science
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138319/1/jia218438.pd
Repositioning of the global epicentre of non-optimal cholesterol
High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol—which is a marker of cardiovascular risk—changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million–4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.</p
Repositioning of the global epicentre of non-optimal cholesterol
High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol�which is a marker of cardiovascular risk�changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95 credible interval 3.7 million�4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world. © 2020, The Author(s), under exclusive licence to Springer Nature Limited