ability to understand the basis of these differences. The UNPD and USCB predict adult mortality from under-5 mortality in many lower-SDI countries, which might be a contributing factor. The UNPD and USCB use model life table systems based on a set of life tables collected before 1980; there are many reasons to expect that these mortality patterns are not relevant to the current period.
96,97Limitations
Although this study includes many methodological
advances, it also has limitations. First, the accuracy of the
estimates depends crucially on the available data sources
and density of data by time period. For child mortality, at
least one year of data was available for all countries. For
adults, however, there were 12 countries with no data; in
these cases, estimates depend critically on covariates and
the ST-GPR statistical model. Additionally, for
country-years with input data, data quality, as determined by both
sampling and non-sampling errors, varies across
locations and over time within the same location. This
adds to the uncertainty in comparing the same metric
from different locations, even though we have made
every effort to systematically propagate uncertainty
throughout our estimation process. Second, for many
countries with limited or absent VR systems, particularly
in sub-Saharan Africa, we use sibling history data to
estimate levels and trends in adult mortality. Sibling
history data have several known biases.
17,22,98In settings
outside of sub-Saharan Africa we found no net biases in
our estimates based on sibling histories when compared
with equivalent estimates derived from other sources of
information such as VR systems. Although differences
in adoption practices in parts of sub-Saharan Africa
create the potential for sibling histories to perform
differently than in other settings, Obermeyer and
colleagues,
25Helleringer and colleagues,
98and
Masquelier
99did not find a consistent direction of bias in
sibling history data in these settings. Third, our
assessment of mortality depends on the validity of our
modelling of HIV/AIDS epidemics, particularly in
settings such as in eastern and southern sub-Saharan
Africa, which have large generalised epidemics. While
there are relatively robust data available on the prevalence
of HIV/AIDS from population-based surveys in many of
these countries, such data are often available only for
selected years, and the data on HIV/AIDS-specific
mortality and CD4 progression rates, both on and off
ART, are far more scarce. Death rates on ART by
CD4 count are also confounded by other indications for
ART such as the presence of opportunistic infections.
100–102All combined, there is a much higher level of uncertainty
in the HIV/AIDS-specific mortality estimates than in
all-cause mortality estimation and these are used as a key
(Figure 9 continues on next page) Czech Republic
Cyprus Cuba Croatia Côte d’Ivoire Costa Rica Congo (Brazzaville) Comoros Colombia China Chile Chad Central African Republic Cape Verde Canada Cameroon Cambodia Burundi Burkina Faso Bulgaria Brunei Brazil Botswana Bosnia and Herzegovina Bolivia Bhutan Bermuda Benin Belize Belgium Belarus Barbados Bangladesh Bahrain Azerbaijan Austria Australia Armenia Argentina Antigua and Barbuda Angola Andorra American Samoa Algeria Albania Afghanistan
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Difference in life expectancy at birth (GBD 2016 minus indicated estimate, years) US Census Bureau
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Males Females
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Kiribati Kenya Kazakhstan Jordan Japan Jamaica Italy Israel Ireland Iraq Iran Indonesia India Iceland Hungary Honduras Haiti Guyana Guinea-Bissau Guinea Guatemala Guam Grenada Greenland Greece Ghana Germany Georgia Gabon France Finland Fiji Federated States of Micronesia Ethiopia Estonia Eritrea Equatorial Guinea El Salvador Egypt Ecuador Dominican Republic Dominica Djibouti Denmark DR Congo
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Difference in life expectancy at birth (GBD 2016 minus indicated estimate, years) US Census Bureau
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Males Females
Portugal Poland Philippines Peru Paraguay Papua New Guinea Panama Palestine Pakistan Oman Norway Northern Mariana Islands North Korea Nigeria Niger Nicaragua New Zealand Netherlands Nepal Namibia Myanmar Mozambique Morocco Montenegro Mongolia Moldova Mexico Mauritius Mauritania Marshall Islands Malta Mali Maldives Malaysia Malawi Madagascar Macedonia Luxembourg Lithuania Libya Liberia Lesotho Lebanon Latvia Laos Kyrgyzstan
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Difference in life expectancy at birth (GBD 2016 minus indicated estimate, years) US Census Bureau
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Males Females
(Figure 9 continues on next page)
United Arab Emirates Ukraine Uganda Turkmenistan Turkey Tunisia Trinidad and Tobago Tonga Togo Timor-Leste The Gambia The Bahamas Thailand Tanzania Tajikistan Taiwan (Province of China) Syria Switzerland Sweden Swaziland Suriname Sudan Sri Lanka Spain South Sudan South Korea South Africa Somalia Solomon Islands Slovenia Slovakia Singapore Sierra Leone Seychelles Serbia Senegal Saudi Arabia São Tomé and Príncipe Samoa Saint Vincent and the Grenadines Saint Lucia Rwanda Russia Romania Qatar Puerto Rico
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Difference in life expectancy at birth (GBD 2016 minus indicated estimate, years) US Census Bureau
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Males Females
(Figure 9 continues on next page)