ambient air pollution - world health organization · exposure to ambient air pollution 23 2.1....
TRANSCRIPT
ContentList of tables 7
List of figures 7
List of annexes 9
Preface 11
Abbreviations 13
Summary 15
1. Introduction 19
2. Exposure to ambient air pollution 23
2.1. Exposure : ground measurements of PM10 and PM2.5 23 2.1.1. Methods 23 2.1.2. Results 25 2.1.3. Discussion 31
2.2 Exposure : modelled estimates of PM2.5 32 2.2.1. Methods 32 2.2.2. Results 32 2.2.3. Discussion 37
3. Burden of disease attributable to ambient air pollution 39
3.1. Methods 39 3.1.1. Source of datas 39 3.1.2. Estimation of the disease burden 39 3.1.3. Uncertainty analysis 40
3.2. Results 40
3.3. Discussion 47
4. Conclusion and way forward 49
References 51
Acknowledgment 55
Annex 1. Modelled population exposure to particulate matter (PM2.5), by country 57
Annex 2. Deaths, YLL’s and DALY’S Attributable to Ambient Air Pollution, by country 63
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Table 1 : Ambient air pollution database : Proportion of settlements by population size
Table 2 : Total number of towns and cities in AAP database, 2016 version, by region
Table 3 : Number of cities included for the PM2.5 and PM10 comparison over a five-year period (mostly 2008-2013), by region
Table 4 : Trend for the five-year period (mostly 2008-2013) in PM2.5 or PM10 based on cities available in several versions of the database, by region
Table 5 : Deaths attributable to AAP in 2012, by disease, age and sex
Table 6 : Disability-adjusted life years (DALYs) attributable to AAP in 2012, by disease, age and sex
Table 7 : Population attributable fraction for disability-adjusted life years attributable to AAP in 2012, by disease, age, sex and region
Table A1 : Annual median concentration of particulate matter of an aerodynamic diameter of 2.5 μm or less (PM2.5) with lower and upper bound, population-weighted and modelled, by area and country
Table A2.1 : Deaths attributable to AAP in 2012 in both sex, by disease and country
Table A2.2 : Deaths attributable to AAP in 2012 in women, by disease and country
Table A2.3 : Deaths attributable to AAP in 2012 in men, by disease and country
Table A2.4 : Years of life lost (YLLs) attributable to AAP in 2012 in both sex, by disease and country
Table A2.5 : Years of life lost (YLLs) attributable to AAP in 2012 in women, by disease and country
Table A2.6 : Years of life lost (YLLs) attributable to AAP in 2012 in men, by disease and country
Table A2.7 : Disability-adjusted life years (DALY) attributable to AAP in 2012 in both sex, by disease and country
Table A2.8 : Disability-adjusted life years (DALY) attributable to AAP in 2012 in women, by disease and country
Table A2.9 : Disability-adjusted life years (DALY) attributable to AAP in 2012 in men, by disease and country
Figure 1 : Number of towns and cities with accessible PM10 and PM2.5 data in 2016 per urban population
Figure 2 : Location of the monitoring stations and PM2.5 concentration in nearly 3 000 human settlements, 2008-2015
List of tables
List of figures
9
Figure 3 : PM10 levels by region and city size, for available cities and towns latest year in the period 2008-2015
Figure 4 : PM10 levels for selected cities by region, for the last available year in the period 2011-2015
Figure 5 : PM10 levels for available mega-cities of more than 14 million habitants for the last available year in the period 2011-2015
Figure 6 : Annual mean particulate matter concentration of the assessed towns and cities compared to the WHO Air Quality Guidelines a
Figure 7 : Percentage of cities with increasing and decreasing PM2.5 or PM10 annual means over a five-year period (mostly 2008-2013), by region
Figure 8 : Percentage of city population experiencing increasing and decreasing PM2.5 or PM10 annual means over a five-year period (mostly 2008-2013), by region
Figure 9 : Global map of modelled annual median concentration of PM2.5, in μg / m3
Figure 10 : Annual median exposure to ambient (outdoor) PM2.5 in μg / m3, by region - urban and rural population, 2014
Figure 11 : Annual median exposure to ambient (outdoor) PM2.5 in μg / m3, by region - urban population only, 2014
Figure 12 : Median PM2.5 concentration, by geographic region – urban and rural areas combined, 2014
Figure 13 : Modelled annual median particulate matter concentration compared to the WHO Air Quality Guidelines (AQG)
Figure 14 : Deaths attributable to AAP in 2012, by disease and region
Figure 15 : Age-standardized deaths per capita attributable to AAP in 2012, by disease and region
Figure 16 : Deaths attributable to AAP in 2012, by country
Figure 17 : DALYs attributable to AAP in 2012, by country
Figure 18 : Age-standardized deaths per 100 000 capita attributable to AAP in 2012, by country
Figure 19 : Age-standardized DALYs per 100 000 capita attributable to AAP in 2012, by country
Figure 20 : Deaths attributable to AAP in 2012, by disease
List of annexesAnnex 1 : Modelled population exposure to particulate matter of PM2.5, by country
Annex 2 : Deaths, YLLs and DALYs attributable to ambient air pollution, by country
11
This report presents a summary of methods and results of the latest World Health Organi-zation (WHO) global assessment of ambient air pollution exposure and the resulting burden of disease.
Air pollution has become a growing concern in the past few years, with an increasing number of acute air pollution episodes in many cities worldwide. As a result, data on air quality is becoming increasingly available and the science underlying the related health impacts is also evolving rapidly.
To date, air pollution – both ambient (outdoor) and household (indoor) – is the biggest envi-ronmental risk to health, carrying responsibility for about one in every nine deaths annually. Ambient (outdoor) air pollution alone kills around 3 million people each year, mainly from noncommunicable diseases. Only one person in ten lives in a city that complies with the WHO Air quality guidelines. Air pollution continues to rise at an alarming rate, and affects econo-mies and people’s quality of life ; it is a public health emergency.
Interventions and policies for tackling air pollu-tion issues exist and have been proven to be effective. The implementation of WHO resolution WHA68.8, which maps out a road map for en-hanced global responses to the adverse effects of air pollution, provides an essential framework for decision-makers to choose and implement the most efficient policies.
Air pollution has also been identified as a global health priority in the sustainable development agenda. WHO has responsibility for stewarding three air pollution-related indicators for monito-ring progress against the Sustainable Develop-ment Goals (SDGs) : in health (Goal 3), in cities (Goal 11) and in energy (Goal 7).
Air pollution affects practically all countries in the world and all parts of society.
The role of the health sector is crucial, and there is a need to engage with other sectors to maxi-mize the co-benefits of health, climate, environ-ment, social and development. Saving people’s lives is the overarching aim to implement policies aiming at tackling air pollution in the health, trans-port, energy, and urban development sectors.
Dr Maria Neira Director of Public Health, Environmental and Social Determinants of Health
World Health Organization
Preface
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AbbreviationsAAP ambient air pollution
AFR Africa Region
ALRI acute lower respiratory disease
AMR Americas Region
AQG Air quality guidelines
BoD burden of disease
COPD chronic obstructive pulmonary disease
DALY disability-adjusted life year
DIMAQ data integration model for air quality
EMR Eastern Mediterranean Region
EUR European Region
GBD global burden of disease
HAP household air pollution
HIC high-income countries
IER integrated exposure risk
IHD ischeamic heart disease
LMIC low-and middle-income countries
PAF population attributable fraction
PM2.5 particulate matter of diameter of less than 2.5 μm in μg / m3
PM10 particulate matter of diameter of less than 10 μm in μg / m3
RR relative risk
SDGs Sustainable Development Goals
SEAR South East Asia Region
UN United Nations
YLD year lived with disability
YLL year of life lost
WHO World Health Organization
WPR Western Pacific Region
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Air pollution represents the biggest environ-mental risk to health. In 2012, one out of every nine deaths was the result of air pollution-rela-ted conditions. Of those deaths, around 3 mil-lion are attributable solely to ambient (outdoor) air pollution. Air pollution affects all regions, settings, socioeconomic groups, and age groups. While all people living in a given area breathe from the same air, there are never-theless important geographical differences in exposure to air pollution. Citizens in Africa, Asia or the Middle East breathe much higher levels of air pollutants that those in living other parts of the world. Some places have air pollution levels that are several times higher than those consi-dered safe by the World Health Organization (WHO) Air quality guidelines.
Air pollution is used as a marker of sustai-nable development, as sources of air pollu-tion also produce climate-modifying pollutants (e.g. CO2 or black carbon). Policies to address air pollution also generate a range of bene-fits to human health, not only through air quality improvements but also other health benefits, such as injury prevention or enabling physical activity.
Consequently, concerns about air pollution are reflected in the Sustainable Development Goals (SDGs) : Air pollution levels in cities is cited as an indicator for urban sustainable development (SDG 11) ; access to clean energy – particular-ly clean household fuels and technologies – is highlighted as an indicator for sustainable en-ergy (SDG 7) ; and mortality due to air pollution (ambient and household) is used an indicator for the health SDG goal (SDG 3). Reliable estimates of exposure to and impacts from air pollutants are key to better inform policy-makers, as well as development partners. These figures are neces-sary to track progress in air quality improvements and to help evaluate the effectiveness of policies aiming at reducing air pollution, as well as as-sessment of how much they are contributing to protect health.
In 2015, to respond to this major global public health threat, the 194 WHO Member States adop-ted the first World Health Assembly resolution to “ address the adverse health effects of air pollu-tion ”. The following year, Member States agreed on a road map for “ an enhanced global response to the adverse health effects of air pollution ”.
Among the main elements of this road map are the monitoring and reporting of air pollution, and enhanced systems, structures and processes for monitoring and reporting health trends asso-ciated with air pollution and its sources.
The current report presents methods and data for two of the SDG indicators reported by WHO :
· SDG Indicator 11.6.2 : Annual mean levels of fine particulate matter (PM2.5) in cities (population-weighted) ; and
· SDG Indicator 3.9.1 : Mortality rate attribu-ted to household and ambient air pollution.
This report presents the updated results of morta-lity and morbidity attributed to ambient air pollu-tion (also known as ‘ burden of disease due to air pollution ’). It includes information on the sources of data on air pollution available to the WHO, on the methodology used to estimate human exposure to air pollution and related burden of disease, as well as the actual estimates of human exposure to particulate matter of a diameter less than 2.5 micrometres (PM2.5) for countries and for the globe ; and the related national burden of disease attributable to long-term exposure to ambient (outdoor) air pollution for the year 2012.
The global exposure assessment to air pollu-tion consists of modelled data of population-weighted annual mean PM2.5 concentrations. Data are modelled through combining remote satellite sensing data with ground measure-ments from the 2016 WHO ambient (outdoor) air quality database, which serves for calibration of the satellite data.
Summary
17
This database compiles information on PM2.5 and PM10
1 from measurements for about 3000 cities and towns worldwide. The modelled estimates indicate that in 2014 only about one in ten people breathe clean air, as defined by the WHO Air quality guidelines.
The burden of disease attributed to ambient air pollution was estimated using methodology developed for the Comparative Risk Assessment study. This methodology is based on combi-ning estimates of exposure to air pollution and its distribution in the population, with results from epidemiological studies that indicate the additio-nal disease burden from different levels of expo-sure to air pollution, after adjusting for other risk factors (e.g. tobacco smoke).
The results are refered to by epidemiologists as exposure-risk estimates at each level of expo-sure. Health outcomes, for which there is enough epidemiological evidence to be included in the analysis, comprise acute lower respiratory, chronic obstructive pulmonary disease, stroke, ischeamic heart disease and lung cancer. Many other diseases have been associated with air pollution, but are not included in this assess-ment because the evidence was not considered sufficiently robust.
The actual impact of air pollution on health pre-sented here is a conservative figure, as it does not include the separate impacts of health from other air pollutants such as nitrogen oxides (NOx) or ozone (O3), and excludes health impacts where evidence is still limited (e.g. pre-term birth or low birth weight).
Through this combined approach, the current report summarizes three sets of data and the interrelationship between them : 1) The compi-lation of the PM2.5 and PM10 measurements data in the 2016 WHO ambient (outdoor) air quality database ; 2) the modelled estimates of PM2.5 ; and 3) the associated burden of disease.
1 Particulate matter of a diameter less than 25 and 10 micrometres respectively.
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This document summarizes the methods and the results of the latest WHO global assessment of air pollution exposure and related burden of disease.
Exposure to air pollutants can affect human health in various ways, leading to increased mor-tality and morbidity (1). Epidemiological evidence on the health effects of air pollution is growing and evolving quickly. Today, air pollution is the largest environmental risk factor (2).
Reliable estimates of exposure to air pollu-tants and related impacts on health are key to better inform policy-makers, as well as other health and development partners. Such infor-mation is essential to implementing, monitoring and evaluating policies that help to tackle air pollution while also protecting health.
The 194 WHO Member States recently adop-ted a resolution to respond to the adverse health effects of air pollution (3), as well as a road map for an enhanced global response (4). The road map outlines goals and approaches for monitoring and reporting of air pollution, as well as enhancing systems, structures and processes necessary to support monitoring and reporting on health trends associated with air pollution and its sources.
Air pollution is a clear marker for sustainable deve-lopment, as sources of air pollution also produce climate pollutants (like CO2 or black carbon).
Policies to address air pollution generate a num-ber of benefits to human health, not only through air quality improvements but also other health benefits, such as injury prevention or enabling physical activity. Adressing air pollution there-fore features highly in the global agenda.
In September 2015, the United Nations (UN) General Assembly adopted Transforming our world : The 2030 Agenda for sustainable deve-lopment, which paves the way for a renewed global commitment to combat the world’s most persistent development issues over the next 15
years (5). A framework of indicators for the 17 SDGs and 169 SDG-related targets has been developed, and includes three air pollution-rela-ted indicators, which fall under WHO’s reporting responsibility :
· SDG Indicator 3.9.1 : Mortality rate attri-buted to household and ambient air pollution for the health goal (SDG 3).
· SDG Indicator 11.6.2 : Annual mean levels of fine particulate matter (PM2.5) in cities (population-weighted) for the urban sus-tainable development goal (SDG 11).
· SDG Indicator 7.1.2 : Proportion of popu-lation with primary reliance on clean fuels and technologies for the sustainable energy goal (SDG 3).
Reporting for Indicators 3.9.1 and 11.6.2 are based on the methods and results presented in the current document, while the methods for estimating SDG Indicator 7.1.2. are presented elsewhere (6).
While a number of air pollutants are associa-ted with significant excess mortality or morbi-dity, including NOx, ozone, carbon monoxide and sulfur dioxides in particular, PM2.5 is the air pollutant that has been most closely studied and is most commonly used as proxy indicator of exposure to air pollution more generally (1).
Particulate matter consists of a complex mixture of solid and liquid particles of organic and inor-ganic substances suspended in the air. The ma-jor components of PM are sulphates, nitrates, ammonia, sodium chloride, black carbon, mine-ral dust and water. The most health-damaging particles are those with a diameter of 10 μm or less, which can penetrate and lodge deep in-side the lungs. Both short- and long-term expo-sure to air pollutants have been associated with health impacts.
1. Introduction
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Small particle pollution has health impacts even at very low concentrations – indeed no threshold has been identified below which no damage to health is observed. Therefore, the WHO Air quality guidelines (AQGs) recommend aiming for, and achieving, the lowest concentrations of PM possible (1). The guideline values are :
PM2.5 PM10 10 µg / m3 annual mean 20 µ / m3 annual mean 25 µg / m3 24-hour mean 50 µg / m3 24-hour mean
Reflecting the rising number of air pollution episodes in cities worldwide – and the resulting increased awareness about its impacts on health - PM2.5 is increasingly measured and monitored by national air quality monitoring networks. WHO has been compiling annual mean concentrations for PM2.5 and PM10 in cities since 2011 (7,8).
A summary of a recent update of the WHO ambient (outdoor) air quality database (9) containing average annual estimates for PM2.5 exposure globally, by region and for 3 000 spe-cific human settlements is presented as part of this report.
The present work on global exposure modelling further develops recent innovations in global exposure estimates for PM2.5 (10,11), as used to model global burden of disease attributable to ambient air pollution (2, 12–14).
It was also presented and reviewed at the Global Platform on Air Quality and Health, ini-tiatied by WHO and other partners in 2014 (15).
Academic researchers, scientists and interna-tional organizations have combined efforts to harmonize in developing comprehensive and reliable models of population exposure to PM2.5, which can be used for health impact estimation.
Coverage of the entire exposure range for long-term exposure to PM2.5 has been achieved through the development of the integrated ex-posure risk (IER) functions (16) that have been developed for the Global Burden of Disease Study (17).
This allows for the integration of available rela-tive risks information from studies of ambient air pollution, household air pollution, second-hand smoke and active smoking. The IERs have been used to derive estimates for both household- and ambient air pollution-attributable burden of disease for the GBD Project (12, 14, 18) and by the WHO (2, 6).
They currently cover cause-specific mortality such as acute lower respiratory in children under five years of age, and chronic obstructive pulmo-nary disease (COPD), ischeaemic heart disease (IHD), stroke and lung cancers in adults.
Other health outcomes have been associated with long-term exposure to particulate matter, such as adverse birth outcomes, childhood respiratory disease, diabetes, atherosclerosis, and neurodevelopment and cognitive function, but are not considered here (19).
The current report presents the latest national mortality and morbidity estimates attributable to ambient air pollution.
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2.1.1. MethodsDescription of methods
The database compiles ground measurements of annual mean concentrations of particulate matter of a diameter of less than 10 μm (PM10) or 2.5 μm (PM2.5) and aims to compile an ave-rage for each city / town. Years of measurements range from 2010 to 2015, unless the latest avai-lable data precede these times, in which case the most recent was used.
Scope of data
The database covers 3 000 human settlements ranging in size from a few hundred to more than 10 million inhabitants. Most of these are urban areas of 20 000 inhabitants or more – hence reference to an “ urban air quality data base ”. However, about 25 % of settlements in the data-base are smaller areas of up to 20 000 residents, and a limited proportion (mostly in Europe) are settlements of only a few hundred to a few thou-sand inhabitants - although these may also be located in proximity to larger urban agglomera-tions (see Table 1).
Table 1. Ambient air pollution database : Proportion of settlements by population size
Percentages of observations
Settlement size
1 % 05 % 1 24010 % 4 17325 % 20 00041 % 50 00050 % 80 75675 % 314 71990 % 1 150 15395 % 2 313 32899 % 8 741 365Mean settlement size 543 664Number of settlements 2977
Data sources
Primary sources of data include official repor-ting from countries to WHO, official national /sub-national reports and national/sub-national web sites containing measurements of PM10 or PM2.5. Furthermore, measurements reported by the following regional networks were used : Clean Air Asia for Asia (20), and the Air quality e-reporting database (21) from the European Environment Agency for Europe. In the absence of the above-mentioned data, data from UN agen-cies, development agencies, articles from peer reviewed journals and ground measurements compiled in the framework of the Global Burden of Disease Project (17) were used. 2
The data was compiled between Septem-ber–November 2015 from the above-mentio-ned sources / partners, or from web searches when not availbable. The web search strategy included the following approaches :
1. Screening of the web sites of respective minis-tries of environment, health, and statistics offices.
2. Web searches with the terms « air quality », « air pollution », « suspended particles », « moni-toring », « PM10 », « PM2.5 ».
Language variations used included English, French, Spanish, Portuguese, Italian, and German.
Type of data used
The database incorporated annual mean concentrations of particulate matter (PM10 or PM2.5) based on daily measurements, or other data that could be aggregated into annual mean values. In the absence of annual means, mea-surements covering a more limited period of the year were exceptionally used and extrapolated.
2 For the full list of references, please refer to the online version of the WHO database (9).
2. Exposure to ambient air pollution2.1. Exposure : ground measurements of PM10 and PM2.5
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In order to derive air quality that is largely repre-sentative of human exposure in urban contexts, mainly data from urban background readings, residential areas, and commercial (or mixed) area measurements were used. Air quality sta-tions characterized as covering particular ‘ hot spots ’ or exclusively industrial areas were not included, unless they were contained in repor-ted city means and could not be disaggregated.
This selection is in accordance with the aim of capturing representative values for average human exposure. In contrast, measurements from hot spots and industrial areas are often captured for the purpose of identifying the highest exposure areas, and were deemed to be less representative of mean exposures for most of the urban population. Hot spots were either designated as such by the original reports, or were qualified as such due to their exceptional nature (e.g. exceptionally busy roads etc.). Omitting these, may, however, have led to an underestimation of the mean air pollu-tion levels of a given city.
Where the data from various sources were available, only the latest data and most reliable sources were used. Only data measured since 2008 were included in the database.
It was not always possible to retrieve or use all publicly available data of interest. Reasons included language barriers, or incomplete infor-mation on data or data quality (e.g. missing year of reference). Data were used as presented in original sources. The indicated numbers of monitors do not necessarily correspond to the total number of existing or operational stations in the cities, but to the numbers of stations used for deriving the indicated city data.
Data processing and reporting
Where available, urban means reported by the original sources are included in the data-base. Where no urban means were available, the eligible city data were averaged using appropriate denominators.
Population data - used for weighting and for estimating the share of urban population co-vered - were either based on : UN population statistics when available for all human settle-ments covered (22), or census data from national statistical offices (23).
For completeness, cities with only PM10 (or resp. PM2.5) reported, PM2.5 (or PM10) concentration was calculated from PM10 (resp. PM2.5) using national conversion factors (PM2.5 / PM10 ratio) either provided by the country or estimated as population-weighted averages of urban-speci-fic conversion factors for the country. Urban-specific conversion factors were estimated as the mean ratio of PM2.5 to PM10 of stations for the same year. If national conversion factors were not available, regional ones were used, which were obtained by averaging country-specific conversion factors.
As exposure to PM2.5 serves as indicator for burden of disease calculation, PM2.5 data were converted from PM10 in the absence of their measurement because they were used to cali-brate the model described below.
As the conversion factor PM2.5 / PM10 may vary according to location (generally between 0.4 and 0.8), the converted PM10 value for individual sett-lements may deviate from the actual value, and should only be considered as approximations.
The temporal coverage represents the number of days per year covered by measurements, or any alternative qualification (as provided in the original sources). If data from several moni-toring stations in one city or town were available, their average temporal coverage was used for the overall average. Information on temporal coverage was not always available ; however reporting agencies often respect a specific reporting threshold for the number of days cove-red before reporting on a given measurement va-lue, or using it for estimating the city annual mean.
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2.1.2. ResultsData availability
The 2016 version of the WHO ambient (outdoor) air quality database consists mainly of urban air quality data - annual means for PM10 and / or PM2.5 - covering about 3 000 human settlements in 103 countries, for the years 2008-2015 (9). The regional distribution and the number of settlements, and correspon-ding accessible data are described in Table 2 and Figure 1, respectively.
Table 2 : Total number of towns and cities in AAP database, 2016 version, by region
Region
Number of towns / cities
Number of countries with data
Total number of countries in region
Africa (Sub-Saharan) (LMIC) 39 10 47Americas (LMIC) 102 13 24
Americas (HIC) 524 6 11Eastern Mediterranean (LMIC) 53 8 15Eastern Mediterranean (HIC) 31 6 6Europe (LMIC) 165 9 19
Europe (HIC) 1 549 33 34South-East Asia (LMIC) 175 9 11Western Pacific (LMIC) 225 4 21Western Pacific (HIC) 109 5 6Global 2 972 103 194
AAP : Ambient air pollution database ; LMIC : Low-and middle-income countries ; HIC : high-income countries.
Figure 1 : Number of towns and cities with accessible PM10 and PM2.5 data in 2016 per urban population.
PM10 / 2.5 : Fine particulate matter of 10 / 2.5 microns or less ; Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr: Western Pacific; LMIC : low- and middle-income countries ; HIC : high-income countries.
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Eur (HIC)
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Emr (HIC)
Amr (LMIC)
Amr (HIC)
Afr
Nr of towns and cities per 1 million urban inhabitants
26
PM2.5 measurements can be directly linked to estimates of health risks, and are therefore of particular interest. In high-income countries, PM2.5 measurements are conducted widely. In low- and middle-income countries (LMICs), PM2.5 measures are not readily available in many countries but there have been large improve-ments since in the past three years.
Annual mean PM2.5 measurements were avai-lable for 339 cities, or almost five times more than in the 2014 version of the database.
Annual mean PM10 measurements could be accessed in as many as 586 cities in LMICs.
In high-income countries (HIC), 1 241 cities and towns with PM2.5 measures could be accessed, compared to 1639 cities and towns with PM10 measurements.
The 3 000 cities and towns currently covered by the WHO database represent about 1.6 billion people, or 43 % of the global urban population.
Ground measurements of annual mean concen-tration of PM2.5 for the 3000 towns and cities is shown in Figure 2.
Figure 2 : Location of the monitoring stations and PM2.5 concentration in nearly 3 000 human settlements, 2008-2015
PM2.5 : Fine particulate matter of 2.5 microns or less.
27
Data summary
An overview of PM10 levels for the WHO regions and selected cities is presented in Figures 3, 4 and 5.
Figure 3 : PM10 levels by region and city size, for available cities and towns latest year in the period 2008–2015
PM10 : Particulate matter of 10 microns or less ; Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific ; LMIC : low- and middle-income countries ; HIC : high-income countries. PM10 values for the world are regional urban population-weighted.
Figure 4 : PM10 levels for selected 3 cities by region, for the last available year in the period 2011-2015
PM10 : Particulate matter of 10 microns or less; Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific ; LMIC : low- and middle-income countries ; HIC : high-income countries.
3 Selection criteria : For year of measurement (2011 or more recent), the largest city or capital for each country within a region (or two cities for one country if only two countries available in the region. City size ranges from 140 000 to 26 million habitants.
<100 000 habitants
100 000 - < 500 000 habitants
1 million - < 3 million habitants
above 3 million habitants
1 million - < 3 million habitants
all cities
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Figure 5 : PM10 levels for available mega-cities of more than 14 million habitants for the last available year in the period 2011-2015
PM10 : Particulate matter of 10 microns or less.
Compliance with Air Quality Guidelines
Figure 6 shows the regional percentages of the assessed towns and cities with PM measurements expe-riencing PM10 or PM2.5 air pollution levels that meet or exceed the WHO Air Quality Guidelines (AQG) (i.e. annual mean values of 20 µg / m3 (for PM10) and 10 µg / m3 (for PM2.5)).4 Globally, according to the currently available data, only 16 % of the assessed population is exposed to PM10or PM2.5 annual mean levels complying with AQG levels. This increases to 27 % for the interim target 3 (i.e. IT-3 : 30 µg / m3 for PM10 and 15 µg / m3 for PM2.5) of the AQG, 46 % for interim target 2 (i.e. IT-2 : 50 µg / m3 for PM10 and 25 µg / m3 for PM2.5), and 56 % for interim target 1 (IT-1 : 70 µg / m3 for PM10 and 35 µg / m3 for PM2.5).
Figure 6 : Annual mean particulate matter concentration of the assessed towns and cities, compared to the WHO Air Quality Guidelinesa
Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific; LMIC: low- and middle-income countries; HIC : high-income countries ; AQG : WHO Air Quality Guidelines. a Annual mean PM10 : 20 µg / m3 ; Annual mean PM2.5 : 10 µg / m3. 4 For town and cities with both PM10 and PM2.5 values, PM2.5 were used.
0
50
100
150
200
250
IstanbulKolkata
Buenos AiresDhaka
CairoBeijing
Mexico cityMumbai
Sao PauloShanghai
Delhi
PM10 (μg/m3)
0%
20%
40%
60%
80%
100%
1.2
Emr (HIC)
WPr (LMIC)
SearEmr (LMIC)
AfrEur (LMIC)
Amr (LMIC)
Eur (HIC)
Wpr (HIC)
Amr (HIC)
% of cities assessedbelow AQG
exceed AQG
Comparison of urban air pollution levels in recent years
A total of 792 towns and cities in 67 countries were selected for a more refined comparison of PM2.5 (where available), or PM10 values over a period of five or more years (Table 3). The selection was made according to the following criteria: These cities/towns have either measured PM.2.5 or PM10 values in the three databases, and cover a period of three years or more; or these towns/cities are repre-sented in the data that was collected in 2011, 2014 or 2016 and cover a period of four years or more. The 2011 version of the database contains data for 2010 or earlier and the 2014 version for 2012 or earlier. To compare levels of air pollution for the equivalent of a five-year period (mostly 2008–2013) for cities included in such a selection, a linear regression was made. Table 4 presents a regional summary by WHO region and income groups. Globally, annual PM levels are estimated to have increased by 8 % during the recent five-year period in the assessed cities. (The cited global increase is weighted by the regional urban population)
Table 3 : Number of cities included for the PM2.5 and PM10 comparison over a five-year period (mostly 2008-2013), by regionRegion Number of town and cities Number of countriesAfrica (Sub-Saharan) 1 2 2America (LMIC) 13 7America (HIC) 343 6Eastern Mediterranean (LMIC) 16 6Eastern Mediterranean (HIC) 6 2Europe (LMIC) 32 5Europe (HIC) 277 30South-East Asia 53 5Western Pacific (LMIC) 33 2Western Pacific (HIC) 21 3Global 796 68
LMIC : Low- and middle-income countries ; HIC : High-income countries. Regions with less than five cities were not included in the analysis, due to poor representatation.
Figure 7 shows the percentage of towns and cities with decreasing levels of annual mean PM2.5 or PM10 (in green), increasing levels (in light orange), and levels with changes of ≤10 % over a five-year period (in blue), by region. The variation in population living in cities with increasing or decreasing population levels is represented in Figure 8.
Table 4 : Trend for the five-year period (mostly 2008-2013) in PM2.5 or PM10 based on cities available in several versions of the database, by region 1
Region Trend over the mean period 2008-2013 2
Africa (Sub-Saharan) NA
America (LMIC) America (HIC)
Eastern Mediterranean (LMIC)Eastern Mediterranean (HIC)Europe (LMIC)Europe (HIC)
South-East Asia Western Pacific (LMIC)Western Pacific (HIC)Global 3
1 Criteria for inclusion : cities with measured PM2.5 or PM10 values in the three database versions covering a period of three years or more, or in two versions and covering a period of four years or more. 2 : No more than 5 % change over the five-year period ; : More than 5 % decrease over the five-year period ; : More than 5 % increase over the five-year period.3 Based on weighting by regional urban population. LMIC : Low- and middle-income countries ; HIC : high-income countries ; NA : not available. Results are based on 795 cities and are to be interpreted with caution, as : a) cities included might not ensure representativeness ; a) yearly variations due for example to climatic changes can be important ; and c) a five-year comparison does not necessarily represent trends, in particular when changes are limited.
30
Figure 7 : Percentage of cities 1 with increasing and decreasing PM2.5 or PM10 annual means over a five-year period (mostly 2008–2013), by region
Amr : Americas ; Emr : Eastern Mediterranean; Eur : Europe ; Sear : South-East Asia, Wpr : Western Pacific ; LMIC : Low- and middle-income countries ; HIC : high-income countries. 1 The number of cities is indicated in bracket. * The world figure is regional population-weighted.
Figure 8 : Percentage of city population experiencing increasing and decreasing PM2.5 or PM10 annual means over a five-year period (mostly 2008-2013), by region
Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia, Wpr : Western Pacific ; LMIC : Low- and middle-income countries ; HIC : high-income countries.
0%
20%
40%
60%
80%
100%
1.2
World* (792)
WPr (LMIC) (32)
Emr (HIC) (6)
Sear (53)
Emr (LMIC) (15)
Amr (HIC) (343)
Wpr (HIC) (21)
Eur (HIC)
(277)
Amr (LMIC) (13)
Eur(LMIC)(30)
% cities decreasing
Limited change (≤10% over 5 years)
% cities increasing
0%
20%
40%
60%
80%
100%
1.2
WorldEmr (HIC)
WPr (LMIC)
SearEmr (LMIC)
Eur (HIC)
Amr (LMIC)
Wpr (HIC)
Amr (HIC)
Eur (LMIC)
with decreasing air pollution
Limited change (≤10% over 5 years) in air pollution
with increasing air pollution
31
The WHO urban ambient air quality database presents data on annual mean concentration of particulate matter (PM) for almost 3 000 human settlements, mostly cities, in 103 countries and is the most comprehensive database of its kind to date. The number of cities and towns repor-ting on PM measurements has nearly doubled since the previous version of the database was published in 2014 (1 600 cities) (8) and nearly tripled since the first 2011 version (1 100 cities) (7), which indicates an increased awareness of the risks posed by air pollution. In the past two years, the number of ground measurements available in high-income countries has doubled, while there has been a 50 % increase in low-and middle-income countries.
Monitoring the air quality is the first, but key, step to be taken by public authorities, both at the national and city levels, to tackle the mul-tisectoral challenge of addressing air pollution. However, there are still huge monitoring and reporting gaps between high-income countries and low- and middle-income counterparts. Most air quality data still comes from Europe and the Americas, with regions such as Africa, South East Asia, and Eastern Mediterranean lagging behind.
The data presented in the latest database reflects a number of important limitations. The ground measurements are of limited compara-bility because of various reasons : a) Differing locations of measurement stations ; b) varying measurement methods ; c) different temporal coverage of certain measurements (i.e. if only part of the year was covered, the measurement may significantly deviate from the annual mean due to seasonal variability) ; d) possible inclu-sion of data that should not have been eligible for this database due to insufficient information to ensure compliance ; e) differences in sizes of urban areas covered (i.e. for certain countries, only measurements for larger cities were found, whereas for others also cities with just a few thou-sand inhabitants were available) ; and f) varying quality of measurements.
In addition, some existing data may have been omitted, either because it could not yet be accessed due to language issues or limited ac-cessibility. Finally, the city means presented in the database may differ from the ones calculated by the cities or municipalities themselves because they are averaged from multiple station data.
The comparison of air pollution levels for a given set of cities over the five-year period 2008-2013 shows a global increase of 8% in annual mean concentrations of PM2.5. High-income regions of the Americas, Europe and Western Pacific demonstrate decreasing air pollution, while the other regions have increasing levels.
However, such a comparison of air pollution levels has a number of limitations. First of all, when PM2.5 measurements were not available, PM10 values (converted into PM2.5) were used for the compari-son, which may have influenced the results.
Second, the period of comparison is relatively short. Yearly variations may for example be in-fluenced by weather patterns and data within a five-year period may not be sufficient to reflect a longer-term trend. A longer time period of com-parison would be required to confirm any trends.
Third, although sampling locations are reaso-nably stable over time, they may have changed within the period of comparison, and variations in annual mean PM levels for a given city may reflect different sampling locations rather than a genuine trend. As the data collected is used for calibrating the model that derives global PM2.5 estimates, data quality is crucial, as well as loca-tion details and the type of monitoring stations : information that is also used in the modeling exer-cise. Efforts and investments should be made to encourage cities and countries to monitor air quality closely, using standard, good quality and comparable methods and instruments, as well as making this information widely available.
To date, only particulate matter concentrations have been compiled in the database. Additional pollutants – such as nitreous oxide (NO2), ozone (O3) or others – might be added to the database in the future.
2.1.3. Discussion
32
Assessment of the global effects of air pollution requires a comprehensive set of estimates of exposure for all populations. Ground monito-ring networks have provided the primary source of this information but, although coverage has increased, there remain regions in which there is no or very little monitoring.
Ground measurement data therefore need to be supplemented with information from other sources, such as estimates from satellite retrie-vals of aerosol optical depth and chemical transport models. The recently developed Data Integration Model for Air Quality (DIMAQ) incor-porates data from multiple sources in order to provide estimates of exposures to PM2.5 at high spatial resolution (0.1o × 0.1o) globally.
Sources of data include : Ground measurements from 6 003 monitoring locations around the world (9,10), satellite remote sensing ; population estimates ; topography ; and information on local monitoring networks and measures of specific contributors of air pollution from chemical trans-port models. The DIMAQ model calibrates data from these sources with ground measurements. The relationships between the various sources of data may be complex and will vary between regions due to differences in the composition of PM2.5, and other factors.
DIMAQ has a hierarchical structure within which calibration equations are produced for indivi-dual countries using, as a priority, data from that country where available. Where data within a country is insufficient to produce accurate estimates, it is supplemented with regional information. When calibration equations have been established and tested, the model is used to estimate exposures, together with associa-ted measures of uncertainty across the globe. These high-resolution estimates can be used to produce air quality profiles for individual countries, regions and globally.
A full description of the model development and evaluation is available separately (24).
Global exposure to PM2.5 has been modelled for the year 2014 in order to provide a com-prehensive global coverage of estimates of air quality. The key parameter is the annual median concentration of PM2.5, which is highly relevant for estimating health impacts. Modelled exposure to ambient PM2.5 levels provides more comprehensive information for countries than measured data, which only provide data for a selection of towns and cities. A comprehensive set of estimated exposures such as this will be required, when estimating the health impacts of ambient air pollution for a given country.
Estimates of exposure are required for all areas, including those that may not be covered by ground monitoring networks. Estimates of air quality, expressed in terms of median concen-trations of PM2.5 are now available for all regions of the world, including areas in which PM2.5 monitoring is not available (Figure 9) . It can be viewed on an interactive map at www.who.int/phe/health_topics/outdoorair/databases/en. Estimates of exposure, by country, are pre-sented in Table A1 of Annex 1.
2.2. Exposure : modelled estimates of PM2.5
2.2.1. Methods 2.2.2. Results
33
In the majority of regions of the world, annual median concentrations of air pollution are higher than the WHO guideline levels of 10 μg / m3 (Figures 10 and 11). Exposures are particularly high in the Eastern Mediterranean, South-East Asian and Western Pacific Regions. Air pollution does not exclusively originate from human activity, and can be greatly influenced by dust storms, for example, particularly in areas close to deserts. This is partially illustra-ted in Figure 12, where modelled annual median PM2.5 concentration by area (rural / urban) is pre-sented and where rural areas in the African and Eastern Mediterranean Regions show greater concentrations than urban ones.
Based on the modelled data, 92 % of the world population are exposed to PM2.5 air pollution concentrations tha are above the annual mean WHO AQG levels of 10 μg / m3 (Figure 13). With the exception of the region of the Americas, all regions – both HIC and LMIC – have less than 20 % of the population living in places in com-pliance with the WHO AQG.
Figure 9 : Global map of modelled annual median concentration of PM2.5, in µg / m3
PM2.5 : Fine particulate matter of 2.5 microns or less.
34
Figure 10 : Annual median exposure to ambient (outdoor) mean annual concentration of PM2.5 in µg / m3, by region - urban and rural population population, 2014
Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur: Europe ; Sear : South-East Asia, Wpr : Western Pacific ; LMIC: low- and middle-income countries ; HIC : high-income countries ; PM2.5 : particulate matter with an aerodynamic diameter of 2.5 µm or less. WHO AQG : WHO Air Quality Guidelines.
Figure 11 : Annual median exposure to ambient (outdoor) PM2.5 in µg / m3, by region - urban population only, 2014
Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia, Wpr : Western Pacific ; LMIC : low- and middle-income countries ; HIC : high-income countries. PM2.5 : particulate matter with an aerodynamic diameter of 2.5 µPM2.5 : pa. WHO AQG : WHO Air Quality Guidelines.
WHO AQG for PM2.5: 10 μg/m3
PM2.5 (μg/m3)
37
18
9
104
59
15
28
59
16
54
43
0
20
40
60
80
100
120
WorldWPr (LMIC)
WPr (HIC)
SearEUR (LMIC)
Eur (HIC)
Emr (LMIC)
Emr (HIC)
Amr (LMIC)
Amr (HIC)
Afr
WHO AQG for PM2.5: 10 μg/m3
PM2.5 (μg/m3)
32
9
17
91
55
14
25
55
49
39
15
0
20
40
60
80
100
WorldWPr (LMIC)
Wpr (HIC)
SearEur (LMIC)
Eur (HIC)
Emr (LMIC)
Emr (HIC)
Amr (LMIC)
Amr (HIC)
Afr
35
Figure 12 : Median PM2.5 concentration, by geographic region - urban and rural areas combined, 2014
Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia, Wpr : Western Pacific ; LMIC : low- and middle-income countries ; HIC : high-income countries. Note : This graph represents the median PM2.5 of regional urban and rural areas. These estimates are not in relation to the number of people exposed to those levels.
Figure 13 : Modelled annual median particulate matter concentration compared to the WHO Air Quality Guidelines (AQG) a
Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific ; LMIC : Low- and middle-income countries ; HIC : high-income countries ; AQG : WHO Air Quality Guidelines.a Annual mean PM10 : 20 µg / m3 ; Annual mean PM2.5 : 10 µg / m3.
0
20
40
60
80
100
WPr (LMIC).
Wpr (HIC)
SearEur (LMIC)
Eur (HIC)
Eur (LMIC)
Emr (HIC)
Amr (LMIC)
Amr (HIC)
Afr
PM2.5 (μg/m3)
2937
86
15 14
8992
5249
13
7
25
19
46
35
128
49
30
rural
urban
0%
20%
40%
60%
80%
100%
1.2
WorldEmr (LMIC)
Emr (HIC)
WPr (LMIC)
Afr (LMIC)
Eur (LMIC)
SearWpr (HIC)
Eur (HIC)
Amr (LMIC)
Amr (HIC)
below AQG
exceed AQG
76
20 1816
2 1.0 0.7 0.5 0.0 0.0 8%
37
Global population exposure to PM2.5 matter has been modelled for the year 2014 to provide a comprehensive global coverage of estimates of air quality. Annual mean concentration of PM2.5 is highly relevant for estimating health impacts and is used as an exposure indicator for calculating the burden of disease attributable to ambient air pollution.
The model used for this study currently has several limitations, however. The first limitation relates to population data. While the quality of estimates of population data and population density, used to calculate the average esti-mates of PM2.5 for urban and rural areas is gene-rally good for high-income countries, it can be relatively poor for some low- and middle-income areas. Furthermore, the definition of urban / rural may greatly vary by country.
The second limitation relates to resolution : The grid size is 0.1° x 0.1° (11 x 11 km close to the equator, but smaller towards the poles). This resolution may cause limitations when considering local situations. However, finer resolutions are planned for future studies. Regarding lack of monitoring data in countries, the model produces a calibration equation for each country using country level data as a prio-rity, with regional data being used to supple-ment local information for countries with sparse, or no, ground monitoring data. It is acknowle-dged that the estimates for data-poor countries may be relatively imprecise and that this may re-sult in apparent changes in levels of air pollution at borders with data-poor countries. In order to achiever reduced uncertainty in modelled data it is important that countries continue and / or improve ground measurement programmes.
Finally, where measurements of PM2.5 are not avai-lable, PM10 measurements are used after conver-sion to PM2.5 using either city, country or regional conversion factors. Conversion factors typically range between 0.4 - 0.8 depending on location. Localised conversion factors are likely to be more accurate, but the ability to calculate them relies on availability of localised data. The potential for inaccuracies in conversion factors means that model outputs for areas using large numbers of converted values may be less accurate than those based on measurements of PM2.5 and extra cau-tion should be taken in their interpretation.
Wherever possible, estimates of PM2.5 have been computed using standardized categories and methods in order to enhance cross-natio-nal comparability. This approach may result in some cases in differences between the esti-mates presented here and the official national statistics prepared and endorsed by indivi-dual WHO Member States. These differences between WHO and national statistics may be larger in countries with small cities and settle-ments which may not be fully represented by the resolution of the WHO model. This may be compounded for isolated regions where air pollution is primarily from local sources and is experienced at very local levels.
2.2.3. Discussion
39
3.1. Methods
3. Burden of disease attributable to ambient air pollution
The burden of disease attributable to ambient air pollution was estimated for the year 2012 based on Comparative Risk Assessment methods (25) and in consultation with expert groups for the Global Burden of Disease (GBD) study (12, 14).This methodology is based on combining expo-sure to air pollution and its distribution in the population with exposure-risk estimates at each level of exposure. This results in a population attributable fraction of disease burden, which is then applied to the health outcome of interest.
3.1.1. Source of the dataHealth data
The total number of deaths, years of life lost (YLLs), years lived with disability (YLDs) and disability-adjusted life years (DALYs) by disease, country, sex and age group have been deve-loped by the World Health Organization (26).
Exposure data
Annual mean concentration of PM2.5 were modelled according to the description in the section Exposure : modelled estimates of PM2.5. The model output provided the percentage of the population exposed to PM2.5 by country, in increments of 1 µg / m3.
Exposure-risk relationship
The integrated exposure-response (IER) func-tions, developed for the GBD 2010 study (16) and further updated for the GBD 2013 study (14 ; 27), were used for acute lower respiratory infections (ALRI), lung cancer, chronic obstruc-tive pulmonary disease (COPD), stroke and ischaemic heart disease (IHD) and can be des-cribed with the following formula (16) :
where z is the annual mean concentration of PM2.5, zcf is the counterfactual PM2.5 concentra-tion, α, γ and δ are the parameter estimates. The IERs are age-specific for both IHD and stroke.
Demographic data
Population data from the UN Population Division (21) were used.
3.1.2. Estimation of disease burden The percentage of the population exposed to PM2.5 was provided by country, in incre-ments of 1 µg / m3 ; relative risks were calcu-lated for each PM2.5 increment, based on the integrated exposure-response functions (IER). The counterfactual concentration was selec-ted to be a uniform distribution with lower and upper limits of 5.9 and 8.7 µg / m3 respectively, given by the average of the minimum and and 5th percentiles of outdoor air pollution cohort exposure distribution, as described elsewhere (14, 16). The country population attributable fractions (PAF) for ALRI, COPD, lung can-cer, stroke and IHD were calculated using the following formula, for each sex and age group :
where i is the level of PM2.5 in µg / m3, and Pi is the percentage of the population exposed to that level of air pollution, and RR is the relative risk.
40
The attributable burden is calculated by multi-plying the population-attributable fraction (PAF) by the health outcome, for each health outcome, sex and age group :
AB = PAF x health outcome
where AB is the attributable burden, PAF is the population-attributable fraction and the health out-come of interest, e.g. deaths, DALYs, YLLs, etc. DALYs are calculated by adding the years of life lived with disability (YLDs) and the YLLs. The relative risks (RRs) for YLDs were adjus-ted by a scalar of 1 for ALRI, lung cancer, and COPD ; of 0.141 for IHD and of 0.553 for stroke (27). The age groups included in the analysis were children less than five years of age for ALRI, and adults above 25 years for the other diseases as previously reported (2, 6).
3.1.3. Uncertainty analysisThe uncertainty intervals are based on the fol-lowing sources of uncertainty : (a) Uncertainty around the exposure to air pollution; and (b) uncertainty around relative risks of the integra-ted exposure-function. To account for uncer-tainty in exposure, the upper and lower expo-sure was obtained from the model (24) for each country, i.e. upper and lower credible limits for the estimate of the percentage of the population exposed to PM2.5.
Alternative burden of disease estimates were calculated for each of these exposures. For the integrated exposure-response function, 1 000 draws of each parameter of the function were obtained (27) and population attributable frac-tions were calculated for each draw.
The final uncertainty intervals were obtained as the 2.5 and 97.5 percentiles of the draws for the alternative burden of disease calculations. As uncertainty for total mortality by cause was not taken into account, this is a partial accounting of uncertainty, and is likely to be underestimated.
3.2. Results Globally, 3 million deaths were attributable to ambient air pollution (AAP) in 2012. About 87 % of these deaths occur in LMICs , which repre-sent 82 % of the world population.
The WHO Western Pacific and South East Asian regions bear most of the burden with 1.1 mil-lion and 799 000 deaths, respectively. In other regions, about 211 000 deaths occur in Sub-Saharan Africa, 194 000 in the Eastern Mediter-ranean region, 190 000 in Europe, and 93 000 in the Americas. The remaining deaths occur in high-income countries of Europe (289 000), the Americas (44 000), Western Pacific (44 000), and Eastern Mediterranean (10 000) (Figure 14).
Age-standardized deaths and DALYs are shown in Figures 15 to 19. Age-standardized measures of deaths and disease are often used to compare countries, as they adjust for age distribution differences by applying age-specific mortality rates for each population. Country estimates of deaths, YLLs and DALYs are provided by disease and sex in Annex 2. The methods for exposure assessment and burden of disease estimation have been slight-ly updated compared with the previous esti-mate of 3.7 million deaths from AAP (2012), as released in 2014 (2).
The variation is thought to be due to : 1) Addi-tional evidence that has become available on the relationship between exposure and health outcomes, and the use of an updated version of the integrated exposure-response functions leading to modified estimates depending on the disease ; and 2) revised population exposure to air pollution leading to modified estimates according to the region.
41
Figure 14 : Deaths attributable to AAP in 2012, by disease and region
AAP : ambient air pollution ; Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific ; LMIC : Low- and middle-income countries ; HIC : High-income countries
Figure 15 : Age-standardized deaths per capita attributable to AAP in 2012, by disease and region
AAP : ambient air pollution ; Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Wes-tern Pacific ; LMIC : Low- and middle-income countries ; HIC : High-income countries.
0
250
500
750
1000
1250
1500
Emr (HIC)
Wpr (HIC)
Amr (HIC)
Amr (LMIC)
Eur (LMIC)
Emr (LMIC)
AfrEur (HIC)
SearWpr (LMIC)
1 102
799
289211 194 190
9344 44
10
Number of deaths (000s)
Stroke
IHD
COPD
Lung cancer
ALRI
0
10
20
30
40
50
60
70
80
Amr (HIC)
Wpr (HIC)
Amr (LMIC)
Eur (HIC)
AfrWorldEmr (HIC)
Emr (LMIC)
Eur (LMIC)
SearWpr (LMIC)
Age-standardized deaths per 100 000 capita
Stroke
IHD
COPD
Lung cancer
ALRI
65
59 5955
54
47
39
25
18
10 7
42
Figure 16 : Deaths attributable to AAP in 2012, by country
Figure 17 : DALYs attributable to AAP in 2012, by country
AAP : Ambient air pollution
AAP : Ambient air pollution
43
Figure 18 : Age-standardized deaths per 100 000 capita attributable to AAP in 2012, by country
Figure 19 : Age-standardized DALYs per 100 000 capita attributable to AAP in 2012, by country
AAP : Ambient air pollution
AAP : Ambient air pollution
44
Almost 94 % of deaths worldwide are due to noncommunicable diseases in adults, such as cardiovas-cular diseases (stroke and ischaemic heart disease), chronic obstructive pulmonary disease and lung cancers. The remaining deaths occur in children under five years of age due to acute lower respiratory infections (Figure 20 and Tables 5 and 6).
Figure 20 : Deaths attributable to AAP in 2012, by disease
Percentage represents percentage of total AAP burden. AAP : ambient air pollution ; ALRI : acute lower respiratory disease ; COPD : chronic obstructive pulmonary disease ; IHD : ischaemic heart disease.
Table 5 : Deaths attributable to AAP in 2012, by disease, age and sex
DeathsDisease Children < 5 years Men Women TotalALRI 169 250 - - 169 250COPD - 135 900 106 350 242 250Lung cancer - 285 900 116 450 402 350IHD - 606 350 472 450 1 078 800Stroke - 540 600 542 150 1 082 750Total 169 250 1 568 750 1 237 400 2 975 400
AAP : ambient air pollution ; ALRI : acute lower respiratory disease ; COPD : chronic obstructive pulmonary disease ; IHD : ischaemic heart disease. Men and women are adults of 25 years and above.
Table 6 : Disability-adjusted life years (DALYs) attributable to AAP in 2012, by disease, age and sex
DALYs (‘000s)Disease Children < 5 years Men Women TotalALRI 15 478 - - 15 478COPD - 3 758 2 862 6 620Lung cancer - 7 076 2 736 9 812IHD - 16 782 10 105 26 887Stroke - 13 927 12 210 26 137Total 15 478 41 544 27 913 84 934
DALYs : disability-adjusted life years; AAP : ambient air pollution ; ALRI : acute lower respiratory disease ; COPD : chronic obstructive pulmonary disease ; IHD : ischaemic heart disease. Men and women are adults of 25 years and above.
The fraction of each individual disease attributable to ambient air pollution is presented in Table 7 for DALYs, and ranges from 8 % for COPD to 25 % for lung cancers. ALRI, stroke and IHD lie in the middle with population attributable fraction of around 16 %.
STROKE
COPD
ALRILUNG CANCER
IHD
402 350
242 250
169 250
14%
8%6%
1 078 80036%
1 082 750
36%
45
Tabl
e 7 :
Pop
ulat
ion
attri
buta
ble
fract
ion
(PAF
) for
the
Dis
abilit
y-ad
just
ed li
fe y
ears
(DAL
Y) a
ttrib
utab
le A
AP in
201
2, b
y di
seas
e, a
ge, s
ex a
nd re
gion
.
ALR
IC
OPD
Lung
can
cer
IHD
Stro
ke
Chi
ldre
nM
enW
omen
Both
Men
Wom
enBo
thM
enW
omen
Both
Men
Wom
enBo
th
< 5
year
s≥ 2
5 ye
ars
≥ 25
year
s≥ 2
5 ye
ars
≥ 25
year
s
Afr
16 %
5 %5 %
5 %26
%27
%27
%18
%16
%17
%18
%17
%18
%
Amr (
HIC
)6 %
1 %0 %
1 %5 %
5 %5 %
6 %5 %
6 %5 %
5 %5 %
Amr (
LMIC
)12
%2 %
2 %2 %
15 %
16 %
15 %
12 %
11 %
12 %
11 %
10 %
11 %
Emr (
HIC
)23
%14
%14
%14
%47
%47
%47
%23
%20
%22
%25
%22
%24
%
Emr (
LMIC
)18
%9 %
9 %9 %
35 %
36 %
36 %
19 %
18 %
18 %
20 %
19 %
20 %
Eur (
HIC
)10
%2 %
2 %2 %
15 %
15 %
15 %
12 %
10 %
11 %
11 %
9 %10
%
Eur (
LMIC
)15
%4 %
4 %4 %
24 %
23 %
23 %
14 %
12 %
13 %
14 %
12 %
13 %
Sear
19 %
10 %
10 %
10 %
33 %
32 %
33 %
20 %
18 %
19 %
20 %
18 %
19 %
Wpr
(HIC
)8 %
2 %2 %
2 %15
%14
%15
%10
%8 %
9 %10
%8 %
9 %
Wpr
(LM
IC)
17 %
9 %9 %
9 %38
%38
%38
%17
%16
%17
%19
%18
%19
%
HIC
10 %
2 %1 %
1 %13
%11
%12
%10
%9 %
10 %
10%
9 %9 %
LMIC
17%
9 %9 %
9 %34
%34
%34
%18
%16
%17
%19
%17
%18
%
Wor
ld17
%8 %
8 %8 %
26 %
24 %
25 %
16 %
14 %
15 %
17 %
16 %
16 %
DAL
Y : D
isab
ility-
adju
sted
life
year
s ; P
AF: p
opul
atio
n at
tribu
tabl
e fra
ctio
n ; A
AP : A
mbi
ent a
ir po
llutio
n ; A
LRI :
Acut
e lo
wer
resp
irato
ry d
isea
se ; C
OPD
: Chr
onic
obs
truct
ive
pulm
onar
y di
seas
e ; IH
D: I
scha
emic
he
art d
isea
se. A
fr : A
frica
; Am
r : A
mer
ica ;
Em
r : E
aste
rn M
edite
rrane
an ; E
ur : E
urop
e ; S
ear:
Sout
h-Ea
st A
sia ;
Wpr
: Wes
tern
Pac
ific ;
LM
IC : L
ow- a
nd m
iddl
e-in
com
e co
untri
es ; H
IC : H
igh-
inco
me
coun
tries
.
47
In 2012, ambient air pollution from particu-late matter was responsible for about 3 million deaths and 85 million DALYs. Burden of disease calculation is based on : 1) Population exposure assessment ; 2) exposure-response functions ; and 3) underlying health data. As data on air quality and epidemiological evidence is accu-mulating rapidly, and methodolodies for both points 1) and 2) are being revised on a regular basis, and these figures are evolving.
Decision-makers and researchers need accurate and reliable estimates of air pollution exposure and the related health impacts. Differing needs (cause-specific vs all-cause mortality, national or regional assessment), publication schedules and audience may lead to different approaches and data use, and therefore different results (28–31). The methods used in this report were developed for global reporting and using the latest available evidence and health data that complied with WHO standards ; they may therefore differ from official national statistics prepared and endorsed by individual WHO Member States.
Some regions, such as the Eastern Mediterra-nean and Africa are highly affected by natural desert dust particles. This results in high health burden according to the current methods, which assume natural dust affects health the same way as PM2.5 from other sources.
The health impacts associated with exposure to dust are not yet fully understood, and are current-ly treated the same way as those from air pollu-tion in industrialized countries where most of the epidemiological studies have been performed.
There is a need to for a better assessment of the health impacts from natural dust, as it could result in much lower burden than those from antropogenic particulate matter (32, 33).
The actual impact of air pollution on health presented here is a conservative figure. Many other diseases have been associated with air pollution but are not included in this assessment, because the evidence was not considered to be sufficiently robust, such as pre-term birth or low birth weight. Also, it does not include the separate impacts of health from other air pollutants such as nitrogen oxides (NOx) or ozone (O3).
As data on air pollutants, methods to assess population exposure and epidemiological evidence accumulates, health effects of additio-nal pollutants should be taken into account in the future as it has already been done for ozone (14). In addition, assessments of the health im-pacts from interventions to reduce air pollution using rigorous epidemiological methodology are much needed. These would be able to take account of context, of intervention packages and provide a stronger basis for assessing real-life impacts of air quality improvement efforts.
3.3. Discussion
49
Ambient air pollution kills about 3 million people annually and is affecting all regions of the world, although Western Pacific and South East Asia are the most affected. About 90 % of people breathe air that does not comply with the WHO Air Quality Guidelines.
The data presented here carry significant uncertainties but constitute the best evidence available to date. Air quality data and epidemio-logical evidence on the effects of air pollutants on health are growing quickly. They will conti-nue to improve exposure assessment to parti-culate matter and other pollutants, as well as for burden of disease estimation.
More epidemiological studies of the long-term effects of exposure to air pollution in low-income settings, where air pollution reaches unaccep-table levels, are urgently needed to better inform the exposure-response relationships. Additional evidence on health outcomes cur-rently not assessed in the analysis, because of lack of knowledge, is also crucial.
In terms of monitoring and reporting, there is a huge gap in monitoring and reporting air pollutants in low and middle-income regions, especially in Africa and Asia but also other regions. Strengthening capacities of cities to monitor their air quality with standardized methods, reliable and good quality instrumenta-tion, and sustainable structures is key.
4. Conclusion and way forward
51
1. Air quality guidelines : Global update 2005. Copenhagen : WHO Regional Office for Europe ; 2005.
2. Methods for burden of disease attributable to ambient air pollution for the year 2012. Geneva : World Health Organization ; 2014. (http:/ /www.who.int /phe/health_topics/outdoorair/databases/AAP_BoD_methods_March2014.pdf?ua=1, accessed May 2016).
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5. Transforming our world : The 2030 Agenda for Sustainable Development (resolution A/RES/70/1). New York : United Nations ; 2015.
6. Methods for burden of disease attribu-table to household air pollution for the year 2012. Geneva : World Health Organization ; 2014. (http://www.who.int/phe/health_topics/outdoorair/databases/HAP_BoD_methods_March2014.pdf?ua=1, accessed May 2016).
7. WHO Outdoor Air Pollution Database. Geneva : World Health Organization ; 2011. (http://www.who.int/phe/health_topics/outdoo-rair/databases/cities-2011/en/, accessed 26 May 2016).
8. WHO Ambient (Outdoor) Air Quality Data-base 2014. Geneva : World Health Organiza-tion ; 2014. (http://www.who.int/phe/health_topics/outdoorair/databases/cities-2014/en/accessed 26 May 2016).
9. WHO Urban Ambient (Outdoor) Air Qua-lity Database (update 2016). Geneva : World Health Organization; 2016. (http://www.who.int/phe/health_topics/outdoorair/databases/cities/en/, accessed 19 May 2016).
10. Brauer M et al. Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution. Environmental Science & Technology. 2012 ; 46(2):652–60. (doi: 10.1021/es2025752).
11. Brauer M et al. Ambient air pollution exposure estimation for the Global Burden of Disease 2013. Environmental Science & Tech-nology. 2015 ; 50:79–88.
12. Lim SS et al. The Lancet. 2012 ; 380(9859):2224–60. (doi:10.1016/S0140-6736(12)61766-8).
13. Apte J et al (2015). Addressing Global Mortality from Ambient PM2.5. Environmental Science & Technology. 2015 ; 49:8057–8066.
14. Forouzanfar et al (2015). Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupatio-nal, and metabolic risks or clusters of risks in 188 countries, 1990–2013 : a systematic ana-lysis for the Global Burden of Disease Study 2013. The Lancet. 2015 ; 386:2287–323.
15. WHO Global Platform on Air Quality and Health. Geneva : World Health Organization ; 2016. (www.who.int/phe/health_topics/outdoo-rair/global_plateform/en, accessed June 2016).
16. Burnett R et al. An Integrated Risk Func-tion for Estimating the Global Burden of Disease Attributable to Ambient Fine Particu-late Matter Exposure. Environmental Health Perspectives. 2014 ; 122, Issue 4:397–403.
17.Global burden of disease. Seattle : Institute for Health Metrics and Evaluation ; 2015.(www.healthdata.org/gbd, accessed October 2015).
18. Smith KR et al. Millions dead: how do we know and what does it mean ? Methods used in the Comparative risk assessment of house-hold air pollution. Annual Review of Public Health. 2014; 35:185–206.
19. Review of evience on health aspects of air pollution – REVIHAAP Project. Technical Report. Copenhagen : WHO Regional Office for Europe ; 2013.
20. Clean Air Asia. Manila : Clean Air Asia ; 2015. (http://cleanairasia.org/, accessed October 2015).
21. Air quality e-reporting database. Copen-hagen : European Environment Agency ; 2015. (http://www.eea.europa.eu/data-and-maps/data/aqereporting, accessed November 2015).
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22. World population prospects : 2015 revi-sion. New York : United Nations Population Division ; 2015.
23. Citypopulation (2016). (http://www.citypo-pulation.de, accessed February 2016).
24. Shaddick G. et al. Data Integration Model for Air Quality : A Hierarchical Approach to the Global Estimation of Exposures to Ambient Air Pollution (2016, submitted). http://arxiv.org/abs/1609.00141, accessed September 2016.
25. Ezzati M. et al. Selected major risk factors and global and regional burden of disease. The Lancet. 2002; 360(9343):1347-60.
26. Global health estimates 2013 : Deaths by cause, age and sex, by Country, 2000-2012. Geneva : World Health Organization ; 2014.
27. Institute for Health Metrics and Evalua-tion. Seattle : Institute for Health Metrics and Evaluation ; 2016. (https://cloud.ihme.washing-ton.edu/index.php/s/mQiX0vGIaBTbaT7, accessed September 2016).
28. Health risks of air pollution in Europe - HRA-PIE Project : Recommandations for concentra-tion-response functions for cost-benefit analy-sis of particulate matter, ozone and nitrogen dioxide. Copenhagen : WHO Regional Office for Europe ; 2013.
29. Economic cost of the health impact of air pollution in Europe : Clean air, health and wealth. Copenhagen : WHO Regional Office for Europe; 2015.
30. Air quality in Europe - 2015 report. Copen-hagen : European Environement Agency ; 2015.
31. The economic consequences of outdoor air pollution. Paris : OECD Publishing ; 2016.(http://dx.doi.org/10.1787/9789264257474-en, accessed July 2016).
32. Giannadaki et al. Modeled global effects of airborne desert dust. Atmospheric Chemistry and Physics. 2014 ; 14, 957–968.
33. Lelieveld et al. The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature. 2015; 525: 367.
55
This document was prepared by Sophie Gumy, and Annette Prüss-Üstün (WHO Geneva), with inputs and comments from Heather Adair-Ro-hani, Carlos Dora and Elaine Fletcher (WHO Geneva), Gavin Shaddick and Matthew Tho-mas (University of Bath, United Kingdom). The interactive map and the static map of expo-sure to air pollution were prepared by Ravi San-thana Gopala Krishnan (WHO Geneva) ; all other maps were prepared by Florence Rusciano (WHO Geneva).
Exposure : ground measurements of PM10 and PM2.5
The database was compiled during 2015 with some updates in the first quarter of 2016 by Sophie Gumy, Tara Neville, Kristina Dushaj and Annette Prüss-Ustün (WHO Geneva) with contributions from Mazen Malkawi (WHO CEHA, Amman), Christian Gapp (WHO ECEH, Bonn), Alberto González Ortiz (European Environment Agency), Kaye Patdu and Candy Tong (Clean Air Asia), Michael Brauer (School of Population and Public Health, University of British Colum-bia, Canada), and several national institutions.
Exposure : modelled estimates of PM2.5
The model to produce the estimates was deve-loped under the leadership of WHO and the University of Bath, United Kingdom, with the input and review of an expert group of 12 lea-ding scientists in the area. The scientist leading the work was Gavin Shaddick (University of Bath) who was assisted by Matthew Thomas and Amelia Jobling (University of Bath). The expert group consisted of Gavin Shaddick, Michael Brauer (University of British Columbia), Aaron van Donkelaar (Dalhousie University), Rick Burnett (Health Canada), Howard Chang
(Emory University), Aaron Cohen (Health Effects Institute), Rita van Dingenen (Joint Research Centre, European Commission), Yang Liu (Emo-ry University), Randall Martin (Dalhousie), Lance Waller (Emory University), Jason West (North Carolina) and Jim Zidek (University of British Columbia), in addition to Annette Prüss-Us-tün, Sophie Gumy and Carlos Dora of WHO. The model was presented and reviewed at the WHO Global Platform on Air Quality, Geneva, in August 2015.
Burden of disease attributable to ambient air pollution
The burden of disease was calculated by Sophie Gumy and Annette Prüss-Ustün (WHO Geneva).
Acknowledgment
57
Annex 1 : Modelled population exposure to particulate matter (PM2.5 ), by country Country income grouping is based on the World Bank analytical income classification of economies 1 corresponding to the year of the data.
Table A1 : Annual median concentration of particulate matter of an aerodynamic diameter of 2.5 mm or less (PM2.5) with lower and upper bound, population-weighted and modelled, by area and country
PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas
Region Country Median Lower Upper Median Lower Upper
Emr (LMIC) Afghanistan 46 26 80 63 41 98
Eur (LMIC) Albania 16 9 29 17 10 30
Afr Algeria 27 9 74 25 8 73
Eur (HIC) Andorra 10 6 18 11 6 17
Afr Angola 27 8 95 42 9 182
Amr (HIC) Antigua and Barbuda 13 6 28 13 6 28
Amr (LMIC) Argentina 13 8 22 14 9 24
Eur (LMIC) Armenia 21 7 66 25 7 87
Wpr (HIC) Australia 6 4 8 6 4 9
Eur (HIC) Austria 16 11 23 17 12 24
Eur (LMIC) Azerbaijan 24 8 73 26 8 86
Amr (HIC) Bahamas 13 6 28 13 6 28
Emr (HIC) Bahrain 60 43 82 60 44 82
Sear Bangladesh 84 53 131 89 58 134
Amr (HIC) Barbados 14 6 31 14 6 31
Eur (LMIC) Belarus 17 6 48 18 6 54
Eur (HIC) Belgium 15 11 22 16 11 23
Amr (LMIC) Belize 22 7 64 21 7 62
Afr Benin 31 9 107 28 7 106
Sear Bhutan 48 30 79 39 30 50
Amr (LMIC) Bolivia, Plurinational States of 27 17 45 32 20 49
Eur (LMIC) Bosnia and Herzegovina 42 23 76 55 30 100
Afr Botswana 16 6 42 19 6 57
Amr (LMIC) Brazil 10 7 16 11 8 17
Wpr HIC Brunei Darussalam 5 3 9 5 3 9
Eur (LMIC) Bulgaria 27 18 40 30 21 42
Afr Burkina Faso 37 12 119 37 10 132
1 For more information, see : Country classification. Washington (DC): World Bank (https://datahelpdesk.worldbank.org/knowledgebase/topics/19280-country-classification, accessed February 2016).
58
PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas
Region Country Median Lower Upper Median Lower Upper
Afr Burundi 38 11 136 49 12 198
Afr Cabo Verde 36 14 96
Wpr (LMIC) Cambodia 23 7 75 25 6 99
Afr Cameroon 65 38 111 64 39 104
Amr (HIC) Canada 7 5 10 7 5 10
Afr Central African Republic 39 12 129 56 15 217
Afr Chad 39 14 115 61 18 207
Amr (HIC) Chile 20 13 30 25 18 36
Wpr (LMIC) China 54 37 80 59 42 84
Amr (LMIC) Colombia 17 11 25 18 13 26
Afr Comoros 16 8 32 16 8 32
Afr Congo 40 11 143 57 13 236
Wpr (LMIC) Cook Islands NA NA NA NA NA NA
Amr (LMIC) Costa Rica 18 12 27 19 13 27
Eur (HIC) Croatia 19 12 31 20 13 32
Amr (LMIC) Cuba 17 7 38 16 7 38
Eur (HIC) Cyprus 17 11 26 17 11 26
Eur (HIC) Czech Republic 20 14 29 21 15 29
Afr Côte d’Ivoire 22 7 71 19 5 71
Sear Democratic People’s Republic of Korea 27 8 92 31 8 118
Afr Democratic Republic of the Congo 38 12 121 61 16 225
Eur (HIC) Denmark 10 7 16 11 7 17
Emr (LMIC) Djibouti 39 9 159 46 10 211
Amr (LMIC) Dominica 13 6 28 13 6 28
Amr (LMIC) Dominican Republic 16 7 37 17 7 40
Amr (LMIC) Ecuador 13 9 20 13 9 20
Emr (LMIC) Egypt 93 50 171 101 54 188
Amr (LMIC) El Salvador 35 20 62 37 22 64
Afr Equatorial Guinea 33 7 153 32 8 128
Afr Eritrea 35 10 126 36 9 138
Eur (HIC) Estonia 8 5 13 8 5 13
Afr Ethiopia 30 9 94 36 10 132
Wpr (LMIC) Fiji 6 2 22 6 2 22
Eur (HIC) Finland 7 5 11 7 5 11
Eur (HIC) France 12 8 17 13 9 18
Afr Gabon 30 8 115 36 7 169
Afr Gambia 39 7 234 43 6 306
Eur (LMIC) Georgia 19 11 33 23 13 40
NANA NA
59
PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas
Region Country Median Lower Upper Median Lower Upper
Eur (HIC) Germany 14 9 20 14 10 21
Afr Ghana 24 12 46 22 10 46
Eur (HIC) Greece 12 8 18 13 9 18
Amr (LMIC) Grenada 14 6 31 14 6 32
Amr (LMIC) Guatemala 32 20 51 33 23 49
Afr Guinea 21 7 66 19 5 68
Afr Guinea-Bissau 27 7 103 29 6 138
Amr (LMIC) Guyana 15 5 45 16 5 54
Amr (LMIC) Haiti 22 7 63 25 8 79
Amr (LMIC) Honduras 35 20 60 40 23 68
Eur (LMIC) Hungary 21 14 32 23 16 33
Eur (HIC) Iceland 8 5 12 8 5 12
Sear India 62 41 95 66 45 97
Sear Indonesia 14 9 23 18 11 28
Emr (LMIC) Iran (Islamic Republic of) 42 27 63 40 28 58
Emr (LMIC) Iraq 50 18 141 51 17 154
Eur (HIC) Ireland 9 6 14 10 7 14
Eur (HIC) Israel 19 13 28 19 14 27
Eur (HIC) Italy 17 12 25 18 13 26
Amr (LMIC) Jamaica 16 11 25 17 12 25
Wpr (HIC) Japan 13 8 19 13 9 19
Emr (LMIC) Jordan 36 24 53 38 27 52
Eur (LMIC) Kazakhstan 15 6 43 21 7 67
Afr Kenya 16 9 28 17 10 29
Wpr (LMIC) Kiribati 5 1 20
Emr (HIC) Kuwait 75 50 112 78 53 116
Eur (LMIC) Kyrgyzstan 15 8 27 15 8 28
Wpr (LMIC) Lao People’s DemocraticRepublic 27 9 76 34 10 106
Eur (HIC) Latvia 19 12 29 20 13 31
Emr (LMIC) Lebanon 30 19 45 31 21 45
Afr Lesotho 18 4 76 22 4 113
Afr Liberia 8 4 17 6 3 15
Emr (LMIC) Libya 61 22 171 58 19 175
Eur (HIC) Lithuania 18 12 28 19 13 28
Eur (HIC) Luxembourg 16 11 24 17 12 23
Afr Madagascar 17 9 33 32 19 54
Afr Malawi 22 7 72 26 7 95
Wpr (LMIC) Malaysia 15 9 24 17 10 26
Sear Maldives 16 8 29
NA NA NA
NA NA NA
60
PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas
Region Country Median Lower Upper Median Lower Upper
Afr Mali 39 13 124 35 10 120
Eur (HIC) Malta 14 9 21 14 10 20
Wpr (LMIC) Marshall Islands NA NA NA NA NA NA
Afr Mauritania 65 19 230 86 21 368
Afr Mauritius 14 9 23 14 8 24
Amr (LMIC) Mexico 20 13 30 20 13 31
Wpr (LMIC) Micronesia (FederatedStates of) 6 2 22 6 2 23
Eur (HIC) Monaco 9 6 18 9 6 18
Wpr (LMIC) Mongolia 20 13 32 32 20 51
Eur (LMIC) Montenegro 22 14 35 24 15 38
Emr (LMIC) Morocco 20 13 32 19 12 29
Afr Mozambique 17 6 47 22 7 69
Sear Myanmar 51 32 80 57 35 90
Afr Namibia 18 6 51 18 6 57
Wpr (LMIC) Nauru NA NA NA NA NA NA
Sear Nepal 64 33 123 74 39 140
Eur (HIC) Netherlands 15 10 22 15 10 22
Wpr (HIC) New Zealand 5 4 8 5 4 8
Amr (LMIC) Nicaragua 24 8 74 26 7 95
Afr Niger 59 19 191 51 15 177
Afr Nigeria 39 25 61 38 24 58
Wpr (LMIC) Niue NA NA NA NA NA NA
Eur (HIC) Norway 9 6 13 9 6 14
Emr (HIC) Oman 48 18 132 47 15 145
Emr (LMIC) Pakistan 60 37 97 68 43 107
Wpr (LMIC) Palau NA NA NA NA NA NA
Amr (LMIC) Panama 12 7 20 13 7 23
Wpr (LMIC) Papua New Guinea 10 2 45 12 2 71
Amr (LMIC) Paraguay 15 9 25 17 10 28
Amr (LMIC) Peru 26 16 42 36 23 54
Wpr (LMIC) Philippines 22 14 35 27 17 43
Eur (HIC) Poland 24 16 35 25 18 36
Eur (HIC) Portugal 9 6 14 10 6 14
Emr (HIC) Qatar 103 67 160 105 69 159
Wpr (HIC) Republic of Korea 27 18 39 28 19 40
Eur (LMIC) Republic of Moldova 17 5 59 17 4 68
Eur (LMIC) Romania 19 13 28 20 14 29
Eur (HIC) Russian Federation 15 8 27 17 9 31
Afr Rwanda 43 13 143 51 14 185
61
PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas
Region Country Median Lower Upper Median Lower Upper
Amr (HIC) Saint Kitts and Nevis NA NA NA NA NA NA
Amr (LMIC) Saint Lucia 15 7 31 15 7 32
Amr (LMIC) Saint Vincent and theGrenadines 13 6 28
Wpr (LMIC) Samoa NA NA NA NA NA NA
Eur (HIC) San Marino NA NA NA NA NA NA
Afr Sao Tome and Principe 13 5 29
Emr (HIC) Saudi Arabia 108 67 174 127 79 205
Afr Senegal 34 21 55 43 29 64
Eur (LMIC) Serbia 19 12 31 21 14 33
Afr Seychelles 13 7 27 13 7 27
Afr Sierra Leone 17 4 69 17 3 86
Wpr (HIC) Singapore 17 9 31 17 9 31
Eur (HIC) Slovakia 19 13 29 20 14 29
Eur (HIC) Slovenia 18 12 27 19 14 28
Wpr (LMIC) Solomon Islands 5 1 18 5 1 19
Emr (LMIC) Somalia 16 5 49 17 4 66
Afr South Africa 27 18 42 31 21 48
Emr (LMIC) South Sudan 29 11 81 32 12 91
Eur (HIC) Spain 9 7 14 10 7 14
Sear Sri Lanka 27 14 51 28 15 55
Emr (LMIC) Sudan 44 14 137 53 16 178
Amr (LMIC) Suriname 16 5 51 16 4 63
Afr Swaziland 18 5 59 20 5 72
Eur (HIC) Sweden 6 4 9 6 4 9
Eur (HIC) Switzerland 12 8 18 13 8 18
Emr (LMIC) Syrian Arab Republic 34 12 98 34 11 105
Eur (LMIC) Tajikistan 41 12 138 51 14 187
Sear Thailand 25 16 37 27 19 38
Eur (LMIC) The former Yugoslav Republic of Macedonia 37 23 59 43 28 65
Sear Timor-Leste 15 3 65 15 3 69
Afr Togo 28 8 107 26 6 113
Wpr (LMIC) Tonga NA NA NA NA NA NA
Amr (HIC) Trinidad and Tobago 13 6 28 13 6 28
Emr (LMIC) Tunisia 36 22 61 35 21 59
Eur (LMIC) Turkey 34 22 50 35 24 51
Eur (LMIC) Turkmenistan 25 8 76 26 7 95
Wpr (LMIC) Tuvalu NA NA NA NA NA NA
Afr Uganda 57 30 108 80 46 138
Eur (LMIC) Ukraine 16 6 44 17 6 48
NA NA NA
NA NA NA
62
PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas
Region Country Median Lower Upper Median Lower Upper
Emr (HIC) United Arab Emirates 64 39 104 64 39 106
Eur (HIC) United Kingdom 12 8 18 12 8 18
Afr United Republic of Tanzania 22 11 42 24 12 47
Amr (HIC) United States of America 8 5 12 8 6 12
Amr (HIC) Uruguay 11 8 17 11 8 17
Eur (LMIC) Uzbekistan 32 10 102 38 12 128
Wpr (LMIC) Vanuatu 6 2 23 7 2 26
Amr (LMIC) Venezuela, Bolivarian Republic of 22 13 39 24 14 41
Wpr (LMIC) Viet Nam 26 15 43 28 17 45
Emr (LMIC) Yemen 43 11 173 42 9 208
Afr Zambia 23 9 64 29 10 90
Afr Zimbabwe 20 7 55 24 8 75
PM2.5 : Particulate matter of a diameter of 2.5 mm or less ; ALRI : Acute lower respiratory disease ; COPD : Chronic obs-tructive pulmonary disease ; IHD : Ischaemic heart disease. Afr : Africa ; Amr : America ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific ; LMIC : Low- and middle-income countries ; HIC : High-income countries ; NA : Not available.
Wherever possible, estimates of PM2.5 have been computed using standardized categories and methods in order to enhance cross-national comparability. This approach may result in some cases in differences between the estimates presented here and the official national statistics prepared and endorsed by individual WHO Member States.
These differences between WHO and national statistics may be larger for occur in countries with small cities and settlements which may not be fully represented by the resolution of the WHO model. This may be compounded for isolated regions where air pollution is primarily from local sources and is experienced at very local levels.
65
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Af
ghan
ista
n3
772
188
301
3 81
33
071
11 1
45(8
961,
135
70)
3781
Eur (
LMIC
)Al
bani
a8
2018
485
078
01
842
(744
, 245
2)64
47
Afr
Alge
ria34
113
163
35
087
5 23
111
424
(457
7, 1
6150
)31
41
Eur (
HIC
) An
dorra
00
313
622
(0, 3
3)27
12
Afr
Ango
la3
687
131
391
491
1 71
07
058
(137
7, 1
1428
)31
51
Amr (
HIC
)An
tigua
and
Bar
buda
00
110
617
(0, 2
5)19
20
Amr (
LMIC
)Ar
gent
ina
8519
21
500
5 25
62
723
9 75
6(2
660,
133
85)
2318
Eur (
LMIC
)Ar
men
ia8
5337
01
643
676
2 75
0(1
07, 4
229)
9267
Wpr
(HIC
)Au
stra
lia0
114
5820
93(1
, 282
9)0.
40.
2
Eur (
HIC
)Au
stria
163
687
1 64
249
62
890
(201
0, 3
587)
3415
Eur (
LMIC
)Az
erba
ijan
135
4523
82
656
1 22
24
297
(954
, 622
0)46
57
Amr (
HIC
)Ba
ham
as3
05
3119
57(0
, 86)
1517
Emr (
HIC
)Ba
hrai
n2
725
7639
148
(132
, 165
)11
33
Sear
Bang
lade
sh3
850
8 31
64
375
10 2
9110
617
37 4
49(3
0245
, 460
36)
2438
Amr (
HIC
)Ba
rbad
os1
04
2217
44(0
, 64)
1510
Eur (
LMIC
)Be
laru
s4
5756
36
680
2 14
69
450
(159
, 137
17)
100
58
Eur (
HIC
)Be
lgiu
m1
115
1 23
21
276
718
3 34
3(2
135,
429
4)30
14
Amr (
LMIC
)Be
lize
11
318
1336
(5, 5
4)11
21
Afr
Beni
n71
441
1976
71
065
2 60
6(9
09, 3
972)
2652
Sear
Bhut
an20
2914
7653
192
(154
, 237
)26
40
Amr (
LMIC
)Bo
livia
, Plu
rinat
iona
l St
ates
of
265
6888
1 12
697
32
521
(198
3, 3
045)
2531
Eur (
LMIC
)Bo
snia
and
H
erze
govi
na2
100
583
1 39
81
454
3 53
8(2
753,
437
3)92
53
Afr
Bots
wan
a35
310
8913
627
3(2
, 423
)13
26
Amr (
LMIC
)Br
azil
198
539
2 90
112
987
9 61
626
241
(112
92, 3
9983
)13
14
Wpr
HIC
Brun
ei D
arus
sala
m0
00
00
1(0
, 40)
0.2
0.3
Eur (
LMIC
)Bu
lgar
ia20
195
960
4 03
13
428
8 63
4(7
033,
102
10)
118
55
Afr
Burk
ina
Faso
1 65
172
451
120
1 73
54
623
(238
1, 6
922)
2858
66
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Buru
ndi
1 37
845
2153
21
025
3 00
1(1
348,
468
9)30
48
Afr
Cab
o Ve
rde
315
6223
01
249
1 07
82
934
(222
, 451
0)20
37
Wpr
(LM
IC)
Cam
bodi
a2
621
169
621
736
2 41
37
000
(575
5, 8
463)
3254
Afr
Cam
eroo
n1
2350
31
060
300
1 88
6(2
9, 6
607)
53
Amr (
HIC
)C
anad
a5
71
3778
128
(79,
181
)25
37
Afr
Cen
tral A
frica
n Re
publ
ic45
264
1230
638
11
215
(610
, 188
9)26
40
Afr
Cha
d2
426
6120
731
1 10
14
340
(241
0, 6
438)
3452
Amr (
HIC
)C
hile
1789
587
1 08
71
042
2 82
2(2
064,
346
5)16
13
Wpr
(LM
IC)
Chi
na6
716
90 6
2622
8 47
925
7 63
844
9 37
31
032
833
(869
033,
121
2034
)76
70
Amr (
LMIC
)C
olom
bia
158
270
748
3 68
81
638
6 50
2(4
499,
806
3)14
17
Afr
Com
oros
322
131
5912
5(2
9, 1
74)
1734
Afr
Con
go32
443
838
648
41
244
(605
, 191
0)29
50
Wpr
(LM
IC)
Coo
k Is
land
sN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)C
osta
Ric
a2
2665
380
172
644
(469
, 786
)14
14
Eur (
HIC
)C
roat
ia0
4958
31
404
806
2 84
2(2
028,
355
6)66
31
Amr (
LMIC
)C
uba
771
975
1 98
91
086
4 12
7(3
38, 6
115)
3623
Eur (
HIC
)C
ypru
s0
356
120
4522
3(1
50, 2
81)
2014
Eur (
HIC
)C
zech
Rep
ublic
383
1 21
03
620
1 19
46
110
(478
8, 7
314)
5829
Afr
Côt
e d’
Ivoi
re1
431
6442
1 39
42
038
4 97
0(6
88, 7
767)
2443
Sear
Dem
ocra
tic P
eopl
e’s
Repu
blic
of K
orea
230
1 21
03
334
3 91
06
911
15 5
96(2
047,
263
52)
6362
Afr
Dem
ocra
tic R
epub
lic
of th
e C
ongo
10 5
2047
387
4 82
87
124
23 0
34(1
1528
, 350
80)
3352
Eur (
HIC
)D
enm
ark
039
402
434
263
1 13
8(5
2, 1
845)
2010
Emr (
LMIC
)D
jibou
ti54
55
5792
212
(82,
336
)25
42
Amr (
LMIC
)D
omin
ica
00
16
513
(1, 1
9)18
16
Amr (
LMIC
)D
omin
ican
Rep
ublic
8520
164
1 09
864
12
008
(173
, 286
4)20
24
Amr (
LMIC
)Ec
uado
r86
4315
287
561
51
771
(860
, 230
8)11
14
Emr (
LMIC
)Eg
ypt
951
1 96
82
079
22 3
2716
206
43 5
31(3
6017
, 518
17)
5177
Amr (
LMIC
)El
Sal
vado
r46
7697
953
326
1 49
8(1
189,
182
8)25
27
67
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Equa
toria
l Gui
nea
628
575
7722
8(1
8, 3
84)
2950
Afr
Eritr
ea36
222
1730
753
41
243
(543
, 190
4)25
56
Eur (
HIC
)Es
toni
a0
136
233
4831
9(4
, 624
)24
11
Afr
Ethi
opia
5 56
540
037
62
320
4 59
513
257
(489
0, 2
0742
)14
23
Wpr
(LM
IC)
Fiji
00
02
02
(0, 3
02)
0.2
0.3
Eur (
HIC
)Fi
nlan
d0
131
233
6232
7(1
, 160
9)6
3
Eur (
HIC
)Fr
ance
412
64
256
3 79
32
774
10 9
54(3
825,
152
04)
178
Afr
Gab
on58
1816
138
155
385
(76,
622
)24
34
Afr
Gam
bia
114
75
100
160
386
(24,
675
)21
46
Eur (
LMIC
)G
eorg
ia12
5219
22
127
1 35
83
741
(234
1, 4
741)
9051
Eur (
HIC
)G
erm
any
556
96
821
13 3
925
372
26 1
60(1
2729
, 342
29)
3313
Afr
Gha
na96
872
751
810
2 80
45
728
(381
6, 7
407)
2241
Eur (
HIC
)G
reec
e1
7084
42
388
1 70
55
008
(171
7, 6
683)
4519
Amr (
LMIC
)G
rena
da0
01
119
22(0
, 32)
2123
Amr (
LMIC
)G
uate
mal
a39
669
162
880
473
1 98
0(1
598,
237
8)13
19
Afr
Gui
nea
690
3216
723
1 00
62
466
(273
, 383
2)21
38
Afr
Gui
nea-
Biss
au15
97
412
017
446
4(3
8, 7
55)
2747
Amr (
LMIC
)G
uyan
a3
14
123
9923
0(0
, 352
)30
43
Amr (
LMIC
)H
aiti
574
1498
801
1 53
53
022
(381
, 453
2)29
46
Amr (
LMIC
)H
ondu
ras
9981
9380
949
31
575
(124
2, 1
927)
2032
Eur (
LMIC
)H
unga
ry4
160
2 00
04
324
1 65
98
147
(627
9, 9
881)
8242
Eur (
HIC
)Ic
elan
d0
04
124
21(0
, 64)
64
Sear
Indi
a39
914
110
500
26 3
3424
9 38
819
5 00
162
1 13
8(5
1524
2, 7
4441
6)49
68
Sear
Indo
nesi
a2
534
1 00
04
951
16 7
8136
527
61 7
92(3
2783
, 818
76)
2538
Emr (
LMIC
)Ira
n
(Isla
mic
Rep
ublic
of)
600
434
1 46
016
484
7 29
026
267
(225
83, 3
0064
)34
50
Emr (
LMIC
)Ira
q1
010
173
728
4 97
43
200
10 0
85(6
690,
136
84)
3168
Eur (
HIC
)Ire
land
012
142
403
124
681
(43,
107
1)15
10
Eur (
HIC
)Is
rael
135
411
509
262
1 21
9(9
12, 1
501)
1611
Eur (
HIC
)Ita
ly2
558
6 39
18
292
5 81
421
057
(142
91, 2
6531
)35
13
68
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Amr (
LMIC
)Ja
mai
ca8
882
246
349
693
(484
, 869
)25
22
Wpr
(HIC
)Ja
pan
1828
19
743
10 2
8610
463
30 7
90(1
1488
, 419
45)
249
Emr (
LMIC
)Jo
rdan
6334
159
743
484
1 48
3(1
269,
170
4)21
43
Eur (
LMIC
)Ka
zakh
stan
8911
766
96
307
3 11
110
293
(132
2, 1
5858
)61
69
Afr
Keny
a2
021
3179
1 19
21
780
5 10
2(1
993,
697
1)12
21
Wpr
(LM
IC)
Kirib
ati
00
00
00
(0, 2
2)0.
00.
0
Emr (
HIC
)Ku
wai
t12
335
319
117
487
(433
, 544
)14
45
Eur (
LMIC
)Ky
rgyz
stan
4833
731
357
617
2 12
9(8
50, 2
784)
3859
Wpr
(LM
IC)
Lao
Peop
le’s
D
emoc
ratic
Rep
ublic
399
4812
266
862
01
857
(758
, 273
0)29
52
Eur (
HIC
)La
tvia
07
199
1 15
649
61
859
(136
3, 2
268)
9142
Emr (
LMIC
)Le
bano
n6
2520
992
127
41
434
(118
3, 1
679)
2930
Afr
Leso
tho
8216
689
195
387
(0, 7
19)
1931
Afr
Libe
ria63
42
7591
236
(0, 6
21)
611
Emr (
LMIC
)Li
bya
3060
251
1 03
867
42
054
(140
8, 2
758)
3358
Eur (
HIC
)Li
thua
nia
116
223
1 42
455
32
216
(167
1, 2
678)
7335
Eur (
HIC
)Lu
xem
bour
g0
437
3530
106
(69,
135
)20
11
Afr
Mad
agas
car
914
4713
61
135
1 98
44
215
(195
3, 5
715)
1939
Afr
Mal
awi
747
4213
697
1 20
72
706
(87,
427
3)17
35
Wpr
(LM
IC)
Mal
aysi
a29
148
670
3 63
01
773
6 25
1(3
548,
803
6)22
32
Sear
Mal
dive
s1
13
2320
48(1
2, 6
5)14
23
Afr
Mal
i2
291
154
491
122
1 60
15
218
(279
4, 7
902)
3260
Eur (
HIC
)M
alta
01
2776
2512
9(6
6, 1
64)
3116
Wpr
(LM
IC)
Mar
shal
l Isl
ands
NA
NA
NA
NA
NA
NA
NA
NA
NA
Afr
Mau
ritan
ia34
023
1023
736
997
8(5
97, 1
453)
2646
Afr
Mau
ritiu
s2
223
144
8225
2(1
09, 3
26)
2018
Amr (
LMIC
)M
exic
o46
774
21
336
9 98
34
269
16 7
98(1
2475
, 205
28)
1417
Wpr
(LM
IC)
Mic
rone
sia
(Fed
erat
ed S
tate
s of
)0
00
00
0(0
, 19)
0.1
0.2
Eur (
HIC
)M
onac
o0
01
42
8(0
, 14)
209
69
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Wpr
(LM
IC)
Mon
golia
3918
6057
243
41
123
(779
, 138
9)40
70
Eur (
LMIC
)M
onte
negr
o0
177
160
145
382
(284
, 472
)61
39
Emr (
LMIC
)M
oroc
co36
984
767
3 37
93
535
8 13
4(6
109,
990
7)25
31
Afr
Moz
ambi
que
1 35
058
5859
81
278
3 34
3(1
32, 5
360)
1321
Sear
Mya
nmar
1 53
01
561
2 78
05
476
11 3
1622
664
(187
44, 2
6942
)43
61
Afr
Nam
ibia
3410
992
162
306
(40,
481
)13
27
Wpr
(LM
IC)
Nau
ruN
AN
AN
AN
AN
AN
AN
AN
AN
A
Sear
Nep
al74
01
770
923
3 32
83
183
9 94
3(7
426,
130
57)
3656
Eur (
HIC
)N
ethe
rland
s1
137
1 83
91
203
836
4 01
7(2
176,
539
4)24
12
Wpr
(HIC
)N
ew Z
eala
nd0
03
134
20(0
, 463
)0.
50.
3
Amr (
LMIC
)N
icar
agua
7240
6467
139
91
247
(196
, 187
4)21
31
Afr
Nig
er3
168
997
1 07
31
835
6 18
3(3
802,
914
6)35
57
Afr
Nig
eria
22 2
3365
226
49
618
13 9
8346
750
(380
31, 5
6243
)28
44
Wpr
(LM
IC)
Niu
eN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)N
orw
ay0
1213
733
015
663
6(2
4, 1
226)
136
Emr (
HIC
)O
man
106
2525
718
047
7(3
26, 6
34)
1336
Emr (
LMIC
)Pa
kist
an13
683
5 68
82
394
20 7
7216
705
59 2
41(4
8757
, 713
40)
3352
Wpr
(LM
IC)
Pala
uN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Pa
nam
a15
536
227
142
425
(54,
615
)11
12
Wpr
(LM
IC)
Papu
a N
ew G
uine
a16
510
2618
613
251
9(0
, 120
8)7
12
Amr (
LMIC
)Pa
ragu
ay42
1610
852
946
51
159
(534
, 152
3)18
25
Amr (
LMIC
)Pe
ru16
312
865
11
949
1 34
84
239
(327
7, 5
148)
1417
Wpr
(LM
IC)
Philip
pine
s1
666
599
2 24
014
067
10 1
2428
696
(220
37, 3
4736
)30
47
Eur (
HIC
)Po
land
1248
35
731
11 9
878
376
26 5
89(2
1327
, 316
70)
6939
Eur (
HIC
)Po
rtuga
l1
2032
364
777
91
769
(66,
289
4)17
7
Emr (
HIC
)Q
atar
12
3410
436
179
(158
, 200
)9
31
Wpr
(HIC
)Re
publ
ic o
f Kor
ea7
284
4 69
52
638
3 89
911
523
(905
4, 1
3963
)23
16
Eur (
LMIC
)Re
publ
ic o
f Mol
dova
1626
188
1 96
781
13
008
(0, 4
776)
7457
Eur (
LMIC
)Ro
man
ia88
164
2 11
56
794
5 33
614
497
(110
01, 1
7576
)73
39
70
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
HIC
)Ru
ssia
n Fe
dera
tion
133
723
9 84
083
938
46 2
1614
0 85
1(5
9079
, 192
348)
9861
Afr
Rwan
da73
834
1949
694
02
227
(122
0, 3
320)
2140
Amr (
HIC
)Sa
int K
itts
and
Nev
isN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Sa
int L
ucia
10
315
1838
(6, 5
5)21
19
Amr (
LMIC
)Sa
int V
ince
nt a
nd th
e G
rena
dine
s0
01
128
21(0
, 31)
1921
Wpr
(LM
IC)
Sam
oaN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)Sa
n M
arin
oN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Sao
Tom
e an
d Pr
inci
pe5
11
612
25(0
, 40)
1426
Emr (
HIC
)Sa
udi A
rabi
a59
236
362
4 12
83
335
8 11
9(7
027,
929
3)28
67
Afr
Sene
gal
613
6732
529
764
2 00
5(1
592,
244
0)15
28
Eur (
LMIC
)Se
rbia
488
1 34
12
049
1 95
25
435
(382
1, 6
858)
6134
Afr
Seyc
helle
s0
02
105
18(1
, 26)
1919
Afr
Sier
ra L
eone
745
158
398
617
1 78
3(0
, 319
6)30
50
Wpr
(HIC
)Si
ngap
ore
116
285
544
248
1 09
4(5
43, 1
479)
2116
Eur (
HIC
)Sl
ovak
ia5
2141
62
210
813
3 46
5(2
681,
415
6)64
40
Eur (
HIC
)Sl
oven
ia0
1021
726
524
073
2(5
22, 9
15)
3517
Wpr
(LM
IC)
Solo
mon
Isla
nds
00
00
00
(0, 8
1)0.
00.
0
Emr (
LMIC
)So
mal
ia1
362
1622
273
471
2 14
4(1
22, 3
734)
2127
Afr
Sout
h Af
rica
1 16
046
41
638
4 60
86
486
14 3
56(1
1397
, 172
06)
2739
Emr (
LMIC
)So
uth
Suda
n1
200
4332
493
864
2 63
2(1
271,
389
5)24
36
Eur (
HIC
)Sp
ain
312
51
834
3 13
41
765
6 86
0(1
210,
110
62)
157
Sear
Sri L
anka
3327
536
54
846
2 27
37
792
(567
5, 9
843)
3838
Emr (
LMIC
)Su
dan
2 87
819
911
81
738
3 16
18
093
(464
4, 1
1955
)21
36
Amr (
LMIC
)Su
rinam
e2
08
3133
74(0
, 122
)14
16
Afr
Swaz
iland
527
447
7818
8(0
, 318
)15
28
Eur (
HIC
)Sw
eden
00
426
940
(0, 1
886)
0.4
0.2
Eur (
HIC
)Sw
itzer
land
028
408
750
295
1 48
2(3
96, 2
031)
188
Emr (
LMIC
)Sy
rian
Arab
Rep
ublic
116
6653
83
779
1 49
65
994
(354
2, 8
251)
3060
Eur (
LMIC
)Ta
jikis
tan
501
8695
1 74
31
189
3 61
5(2
044,
524
6)46
89
71
AAP:
Am
bien
t air
pollu
tion;
ALR
I: Ac
ute
low
er re
spira
tory
dis
ease
; CO
PD: C
hron
ic o
bstru
ctiv
e pu
lmon
ary
dise
ase;
IHD
: Isc
haem
ic h
eart
dise
ase.
Afr:
Afri
ca; A
mr:
Amer
ica;
Em
r: Ea
ster
n M
edite
rrane
an; E
ur:
Euro
pe; S
ear:
Sout
h-Ea
st A
sia;
Wpr
: Wes
tern
Pac
ific;
LM
IC: L
ow- a
nd m
iddl
e-in
com
e co
untri
es; H
IC: H
igh-
inco
me
coun
tries
; NA:
Not
ava
ilabl
e.a A
ge g
roup
incl
udes
less
than
5 y
ears
old
.b A
ge g
roup
incl
udes
25
year
s an
d ab
ove.
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Sear
Thai
land
104
976
4 32
39
669
7 30
222
375
(177
90, 2
6921
)33
28
Eur (
LMIC
)Th
e fo
rmer
Yug
oslav
Re
publ
ic of
Mac
edon
ia1
2329
239
066
01
366
(110
7, 1
635)
6647
Sear
Tim
or-L
este
502
2673
5821
0(0
, 403
)19
31
Afr
Togo
484
1912
372
566
1 45
4(2
87, 2
322)
2242
Wpr
(LM
IC)
Tong
aN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
HIC
)Tr
inid
ad a
nd T
obag
o3
228
223
9635
1(0
, 515
)26
24
Emr (
LMIC
)Tu
nisi
a45
102
492
2 46
51
527
4 63
1(3
739,
554
0)43
44
Eur (
LMIC
)Tu
rkey
240
1 06
56
498
14 8
1310
053
32 6
68(2
7197
, 382
89)
4448
Eur (
LMIC
)Tu
rkm
enis
tan
130
5511
42
425
944
3 66
7(1
134,
519
7)71
108
Wpr
(LM
IC)
Tuva
luN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Uga
nda
3 14
119
212
61
624
2 90
57
989
(623
9, 1
0044
)23
45
Eur (
LMIC
)U
krai
ne63
268
2 64
438
707
12 8
2454
507
(673
, 791
37)
120
65
Emr (
HIC
)U
nite
d Ar
ab E
mira
tes
913
6239
917
265
5(5
64, 7
49)
728
Eur (
HIC
)U
nite
d Ki
ngdo
m12
424
4 80
37
366
3 74
916
355
(538
7, 2
2534
)26
13
Afr
Uni
ted
Repu
blic
of
Tanz
ania
1 91
211
036
1 59
92
108
5 76
5(3
513,
764
5)12
21
Amr (
HIC
)U
nite
d St
ates
of
Amer
ica
3372
18
836
22 5
605
893
38 0
43(1
539,
808
04)
127
Amr (
HIC
)U
rugu
ay4
1416
930
821
771
3(1
94, 9
96)
2113
Eur (
LMIC
)U
zbek
ista
n72
219
544
49
984
4 93
616
282
(793
7, 2
3064
)57
85
Wpr
(LM
IC)
Vanu
atu
00
01
12
(0, 4
1)1
2
Amr (
LMIC
)Ve
nezu
ela,
Bol
ivar
ian
Repu
blic
of
125
126
814
3 46
61
582
6 11
3(4
424,
761
2)20
27
Wpr
(LM
IC)
Viet
Nam
591
1 12
74
897
5 08
115
644
27 3
40(1
9758
, 348
35)
3033
Emr (
LMIC
)Ye
men
1 41
513
512
22
849
2 14
46
667
(302
8, 1
0148
)27
58
Afr
Zam
bia
997
1824
519
854
2 41
1(6
79, 3
600)
1630
Afr
Zim
babw
e70
051
123
366
616
1 85
6(1
37, 2
949)
1323
73
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Af
ghan
ista
n1
798
8877
1 82
81
752
5 54
4(4
463,
673
9)38
81
Eur (
LMIC
)Al
bani
a3
963
400
440
915
(352
, 121
7)64
42
Afr
Alge
ria14
947
118
2 00
02
537
4 85
1(1
930,
686
2)26
34
Eur (
HIC
)An
dorra
00
16
310
(0, 1
4)24
8
Afr
Ango
la1
452
5414
653
924
3 09
6(6
25, 4
980)
2747
Amr (
HIC
)An
tigua
and
Bar
buda
00
05
38
(0, 1
2)17
17
Amr (
LMIC
)Ar
gent
ina
3681
443
2 37
51
359
4 29
4(1
094,
583
1)20
13
Eur (
LMIC
)Ar
men
ia3
2165
721
351
1 16
1(3
4, 1
756)
7745
Wpr
(HIC
)Au
stra
lia0
06
2412
43(0
, 131
2)0.
40.
2
Eur (
HIC
)Au
stria
127
250
797
296
1 37
2(9
60, 1
694)
3211
Eur (
LMIC
)Az
erba
ijan
6019
521
176
656
1 96
2(4
07, 2
839)
4246
Amr (
HIC
)Ba
ham
as1
01
139
25(0
, 37)
1312
Emr (
HIC
)Ba
hrai
n1
37
2517
52(4
6, 5
8)10
27
Sear
Bang
lade
sh1
728
3 72
985
93
345
5 42
215
084
(120
74, 1
8726
)20
31
Amr (
HIC
)Ba
rbad
os0
01
109
20(0
, 28)
137
Eur (
LMIC
)Be
laru
s1
1270
3 28
91
206
4 57
8(4
4, 6
579)
9038
Eur (
HIC
)Be
lgiu
m1
4231
949
939
81
258
(832
, 159
4)22
9
Amr (
LMIC
)Be
lize
10
19
717
(2, 2
5)10
21
Afr
Beni
n32
314
738
755
31
284
(450
, 194
4)25
49
Sear
Bhut
an9
117
3129
86(6
9, 1
05)
2540
Amr (
LMIC
)Bo
livia
, Plu
rinat
iona
l St
ates
of
120
3545
509
454
1 16
4(9
13, 1
410)
2327
Eur (
LMIC
)Bo
snia
and
H
erze
govi
na1
4412
462
383
01
623
(126
8, 2
005)
8441
Afr
Bots
wan
a17
12
4990
160
(1, 2
46)
1528
Amr (
LMIC
)Br
azil
9022
31
144
5 11
04
634
11 2
01(4
747,
171
19)
1111
Wpr
HIC
Brun
ei D
arus
sala
m0
00
00
0(0
, 17)
0.1
0.2
Eur (
LMIC
)Bu
lgar
ia8
8316
91
896
1 85
04
006
(327
1, 4
734)
107
40
Afr
Burk
ina
Faso
763
3321
579
873
2 26
9(1
179,
338
7)27
52
74
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Buru
ndi
625
2211
210
455
1 32
3(5
89, 2
082)
2642
Afr
Cab
o Ve
rde
133
2883
615
557
1 41
6(1
02, 2
163)
1932
Wpr
(LM
IC)
Cam
bodi
a1
165
6222
824
1 24
93
322
(273
7, 4
005)
3151
Afr
Cam
eroo
n1
1123
442
117
183
8(9
, 299
6)5
2
Amr (
HIC
)C
anad
a2
21
1438
57(3
5, 8
1)23
28
Afr
Cen
tral A
frica
n Re
publ
ic18
630
414
620
557
0(2
89, 8
82)
2436
Afr
Cha
d1
028
298
344
536
1 94
5(1
086,
287
7)31
47
Amr (
HIC
)C
hile
739
237
385
500
1 16
8(8
45, 1
444)
139
Wpr
(LM
IC)
Chi
na2
831
42 9
0367
281
129
846
219
575
462
436
(389
791,
542
399)
7060
Amr (
LMIC
)C
olom
bia
6612
629
91
555
886
2 93
2(2
017,
364
3)12
14
Afr
Com
oros
141
014
2756
(12,
78)
1529
Afr
Con
go12
316
217
325
556
8(2
79, 8
63)
2645
Wpr
(LM
IC)
Coo
k Is
land
sN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)C
osta
Ric
a1
1322
147
8727
0(1
94, 3
31)
1211
Eur (
HIC
)C
roat
ia0
1814
669
344
01
297
(941
, 160
5)58
21
Amr (
LMIC
)C
uba
331
353
863
540
1 79
1(1
32, 2
638)
3218
Eur (
HIC
)C
ypru
s0
112
4025
78(5
3, 9
8)14
8
Eur (
HIC
)C
zech
Rep
ublic
133
364
1 70
268
52
786
(219
4, 3
323)
5220
Afr
Côt
e d’
Ivoi
re65
219
1658
088
12
147
(293
, 335
1)21
40
Sear
Dem
ocra
tic P
eopl
e’s
Repu
blic
of K
orea
114
571
1 56
11
830
3 21
17
288
(890
, 123
33)
5846
Afr
Dem
ocra
tic R
epub
lic
of th
e C
ongo
4 66
519
925
2 22
63
836
10 9
52(5
520,
166
14)
3150
Eur (
HIC
)D
enm
ark
021
199
180
145
546
(19,
896
)19
8
Emr (
LMIC
)D
jibou
ti23
32
2541
94(3
6, 1
50)
2236
Amr (
LMIC
)D
omin
ica
00
03
36
(0, 9
)17
14
Amr (
LMIC
)D
omin
ican
Rep
ublic
3510
6457
535
01
035
(82,
147
0)20
23
Amr (
LMIC
)Ec
uado
r38
1861
380
299
797
(378
, 104
1)10
11
Emr (
LMIC
)Eg
ypt
490
868
564
10 0
187
743
19 6
82(1
6245
, 234
95)
4664
Amr (
LMIC
)El
Sal
vado
r20
4445
478
180
767
(607
, 941
)24
24
75
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Equa
toria
l Gui
nea
233
126
3588
(7, 1
48)
2342
Afr
Eritr
ea15
211
913
024
554
7(2
39, 8
40)
2246
Eur (
HIC
)Es
toni
a0
09
116
2715
2(1
, 292
)22
7
Afr
Ethi
opia
2 04
951
196
911
2 05
55
263
(197
3, 8
087)
1119
Wpr
(LM
IC)
Fiji
00
00
01
(0, 9
5)0.
10.
2
Eur (
HIC
)Fi
nlan
d0
010
100
3514
6(0
, 722
)5
2
Eur (
HIC
)Fr
ance
146
1 15
31
547
1 60
24
349
(151
4, 5
912)
135
Afr
Gab
on21
85
6487
185
(36,
295
)23
30
Afr
Gam
bia
502
145
7217
1(1
1, 2
96)
1942
Eur (
LMIC
)G
eorg
ia4
2333
1 04
476
41
868
(115
6, 2
365)
8638
Eur (
HIC
)G
erm
any
224
62
238
6 03
33
133
11 6
52(5
497,
151
13)
289
Afr
Gha
na45
033
1685
31
676
3 02
8(2
013,
392
3)23
41
Eur (
HIC
)G
reec
e0
3314
91
039
957
2 17
8(7
07, 2
867)
3813
Amr (
LMIC
)G
rena
da0
00
54
9(0
, 13)
1716
Amr (
LMIC
)G
uate
mal
a17
832
6839
823
691
2(7
36, 1
096)
1216
Afr
Gui
nea
313
125
373
515
1 21
9(1
37, 1
882)
2138
Afr
Gui
nea-
Biss
au69
22
6186
220
(18,
355
)26
44
Amr (
LMIC
)G
uyan
a2
01
5347
104
(0, 1
60)
2740
Amr (
LMIC
)H
aiti
264
652
408
815
1 54
4(1
96, 2
313)
3044
Amr (
LMIC
)H
ondu
ras
4535
3733
422
767
8(5
33, 8
32)
1826
Eur (
LMIC
)H
unga
ry2
6671
42
164
878
3 82
4(2
973,
461
8)73
29
Eur (
HIC
)Ic
elan
d0
02
52
10(0
, 32)
63
Sear
Indi
a20
455
47 2
106
202
89 7
2796
383
259
977
(214
832,
312
709)
4357
Sear
Indo
nesi
a1
081
297
1 34
15
875
18 3
4726
941
(141
14, 3
5705
)22
31
Emr (
LMIC
)Ira
n (Is
lam
ic
Repu
blic
of)
289
177
469
6 85
83
513
11 3
06(9
706,
129
63)
3046
Emr (
LMIC
)Ira
q46
669
204
1 88
41
394
4 01
6(2
657,
548
1)25
51
Eur (
HIC
)Ire
land
06
5916
971
305
(15,
480
)13
7
Eur (
HIC
)Is
rael
014
139
209
139
501
(378
, 615
)13
7
Eur (
HIC
)Ita
ly2
224
1 66
13
808
3 43
49
128
(629
7, 1
1395
)30
8
76
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Amr (
LMIC
)Ja
mai
ca3
218
114
184
322
(225
, 402
)23
18
Wpr
(HIC
)Ja
pan
963
2 67
04
089
5 05
211
883
(438
3, 1
5975
)18
5
Emr (
LMIC
)Jo
rdan
289
2127
623
957
3(4
92, 6
56)
1733
Eur (
LMIC
)Ka
zakh
stan
3843
121
2 94
81
744
4 89
5(5
99, 7
483)
5653
Afr
Keny
a89
214
3147
781
52
229
(865
, 305
2)10
18
Wpr
(LM
IC)
Kirib
ati
00
00
00
(0, 7
)0.
00.
0
Emr (
HIC
)Ku
wai
t5
19
7542
131
(116
, 147
)9
34
Eur (
LMIC
)Ky
rgyz
stan
2114
1863
929
198
3(3
80, 1
283)
3447
Wpr
(LM
IC)
Lao
Peop
le’s
D
emoc
ratic
Rep
ublic
167
2435
325
305
856
(353
, 125
3)26
45
Eur (
HIC
)La
tvia
02
3459
129
692
3(6
77, 1
121)
8327
Emr (
LMIC
)Le
bano
n3
1062
274
160
508
(417
, 599
)21
21
Afr
Leso
tho
386
148
120
213
(0, 3
87)
2029
Afr
Libe
ria31
21
3747
117
(0, 3
07)
611
Emr (
LMIC
)Li
bya
1323
3143
333
183
1(5
78, 1
113)
2745
Eur (
HIC
)Li
thua
nia
04
3476
534
21
146
(865
, 137
9)70
24
Eur (
HIC
)Lu
xem
bour
g0
212
1417
45(3
0, 5
7)17
8
Afr
Mad
agas
car
410
2324
489
1 01
51
961
(910
, 265
9)18
36
Afr
Mal
awi
383
175
371
664
1 44
1(4
4, 2
267)
1835
Wpr
(LM
IC)
Mal
aysi
a13
4222
01
342
820
2 43
6(1
379,
312
4)17
27
Sear
Mal
dive
s0
10
95
16(4
, 22)
917
Afr
Mal
i1
046
4720
647
924
2 68
5(1
469,
399
8)34
62
Eur (
HIC
)M
alta
00
632
1251
(26,
64)
2511
Wpr
(LM
IC)
Mar
shal
l Isl
ands
NA
NA
NA
NA
NA
NA
NA
NA
NA
Afr
Mau
ritan
ia12
910
412
319
445
9(2
84, 6
74)
2444
Afr
Mau
ritiu
s1
06
5335
95(3
9, 1
22)
1512
Amr (
LMIC
)M
exic
o20
534
850
54
307
2 25
57
620
(562
0, 9
341)
1214
Wpr
(LM
IC)
Mic
rone
sia
(Fed
erat
ed S
tate
s of
)0
00
00
0(0
, 7)
0.1
0.1
Eur (
HIC
)M
onac
o0
00
21
4(0
, 6)
186
77
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Wpr
(LM
IC)
Mon
golia
157
1322
419
845
8(3
16, 5
67)
3253
Eur (
LMIC
)M
onte
negr
o0
019
4763
130
(97,
161
)41
22
Emr (
LMIC
)M
oroc
co15
928
851
506
1 99
13
769
(285
1, 4
570)
2327
Afr
Moz
ambi
que
567
3321
313
636
1 56
9(6
4, 2
509)
1219
Sear
Mya
nmar
644
893
1 20
83
257
5 49
111
493
(951
1, 1
3676
)43
56
Afr
Nam
ibia
165
350
103
177
(22,
275
)15
28
Wpr
(LM
IC)
Nau
ruN
AN
AN
AN
AN
AN
AN
AN
AN
A
Sear
Nep
al35
490
243
81
446
1 58
84
728
(350
5, 6
257)
3351
Eur (
HIC
)N
ethe
rland
s1
6469
247
549
41
726
(953
, 230
7)20
9
Wpr
(HIC
)N
ew Z
eala
nd0
02
53
10(0
, 230
)0.
40.
2
Amr (
LMIC
)N
icar
agua
3019
2529
019
055
4(8
1, 8
37)
1925
Afr
Nig
er1
313
431
559
942
2 85
9(1
773,
419
3)33
58
Afr
Nig
eria
9 51
927
613
24
347
7 00
821
283
(173
47, 2
5554
)26
42
Wpr
(LM
IC)
Niu
eN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)N
orw
ay0
659
146
9130
2(1
0, 5
83)
125
Emr (
HIC
)O
man
52
688
6616
7(1
14, 2
23)
1329
Emr (
LMIC
)Pa
kist
an5
883
1 31
336
19
764
9 06
826
390
(220
64, 3
1251
)31
49
Wpr
(LM
IC)
Pala
uN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Pa
nam
a8
311
8469
174
(21,
253
)9
9
Wpr
(LM
IC)
Papu
a N
ew G
uine
a75
39
8542
214
(0, 4
88)
610
Amr (
LMIC
)Pa
ragu
ay18
522
200
204
450
(206
, 588
)14
19
Amr (
LMIC
)Pe
ru72
6631
284
765
11
948
(149
8, 2
377)
1314
Wpr
(LM
IC)
Philip
pine
s75
616
063
65
226
4 29
711
074
(852
0, 1
3378
)23
34
Eur (
HIC
)Po
land
517
11
678
5 28
44
514
11 6
51(9
373,
138
62)
5825
Eur (
HIC
)Po
rtuga
l0
667
273
415
762
(25,
121
1)14
5
Emr (
HIC
)Q
atar
11
521
734
(30,
38)
728
Wpr
(HIC
)Re
publ
ic o
f Kor
ea3
891
326
1 10
01
914
4 43
1(3
523,
533
8)18
10
Eur (
LMIC
)Re
publ
ic o
f Mol
dova
79
381
024
433
1 51
2(0
, 236
6)71
45
Eur (
LMIC
)Ro
man
ia40
5143
23
037
2 76
76
327
(483
0, 7
618)
6226
Eur (
HIC
)Ru
ssia
n Fe
dera
tion
6219
21
682
39 3
1326
465
67 7
14(2
7433
, 922
71)
8841
78
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Rwan
da32
916
722
245
21
026
(562
, 153
1)18
33
Amr (
HIC
)Sa
int K
itts
and
Nev
isN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Sa
int L
ucia
00
16
916
(2, 2
4)18
15
Amr (
LMIC
)Sa
int V
ince
nt a
nd th
e G
rena
dine
s0
00
64
11(0
, 15)
2019
Wpr
(LM
IC)
Sam
oaN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)Sa
n M
arin
oN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Sao
Tom
e an
d Pr
inci
pe2
00
47
13(0
, 20)
1526
Emr (
HIC
)Sa
udi A
rabi
a29
9092
1 42
91
559
3 19
9(2
746,
369
5)25
56
Afr
Sene
gal
265
2412
263
398
962
(768
, 116
5)14
26
Eur (
LMIC
)Se
rbia
133
363
829
1 08
02
306
(164
9, 2
892)
5024
Afr
Seyc
helle
s0
00
42
7(0
, 10)
1512
Afr
Sier
ra L
eone
353
63
203
323
887
(0, 1
582)
2951
Wpr
(HIC
)Si
ngap
ore
14
9519
812
242
0(2
08, 5
66)
1611
Eur (
HIC
)Sl
ovak
ia2
611
11
072
421
1 61
2(1
250,
192
8)58
28
Eur (
HIC
)Sl
oven
ia0
463
112
134
313
(227
, 389
)30
11
Wpr
(LM
IC)
Solo
mon
Isla
nds
00
00
00
(0, 2
7)0.
00.
0
Emr (
LMIC
)So
mal
ia62
710
1011
321
997
9(5
5, 1
714)
1924
Afr
Sout
h Af
rica
509
162
579
1 98
73
690
6 92
8(5
511,
828
1)26
31
Emr (
LMIC
)So
uth
Suda
n52
416
1421
542
01
190
(577
, 175
7)22
32
Eur (
HIC
)Sp
ain
126
324
1 24
998
02
581
(426
, 398
1)11
4
Sear
Sri L
anka
1396
100
1 74
596
12
915
(211
7, 3
689)
2826
Emr (
LMIC
)Su
dan
1 22
475
4075
91
537
3 63
5(2
095,
535
0)19
32
Amr (
LMIC
)Su
rinam
e0
02
1316
32(0
, 52)
1213
Afr
Swaz
iland
234
127
5511
0(0
, 183
)18
30
Eur (
HIC
)Sw
eden
00
212
619
(0, 9
26)
0.4
0.1
Eur (
HIC
)Sw
itzer
land
012
148
328
172
660
(160
, 899
)16
6
Emr (
LMIC
)Sy
rian
Arab
Rep
ublic
4822
961
418
513
2 09
7(1
261,
286
2)21
41
Eur (
LMIC
)Ta
jikis
tan
214
4736
893
700
1 88
9(1
070,
274
1)48
92
79
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Sear
Thai
land
4221
91
424
4 32
03
406
9 41
2(7
563,
112
00)
2821
Eur (
LMIC
)Th
e fo
rmer
Yug
osla
v Re
publ
ic o
f M
aced
onia
18
5314
134
254
3(4
42, 6
50)
5233
Sear
Tim
or-L
este
231
938
2999
(0, 1
87)
1829
Afr
Togo
231
74
189
296
727
(145
, 115
4)21
40
Wpr
(LM
IC)
Tong
aN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
HIC
)Tr
inid
ad a
nd T
obag
o1
08
8344
137
(0, 2
00)
2017
Emr (
LMIC
)Tu
nisi
a19
4329
1 01
073
21
833
(148
9, 2
188)
3332
Eur (
LMIC
)Tu
rkey
101
411
862
6 27
35
054
12 7
01(1
0666
, 148
18)
3333
Eur (
LMIC
)Tu
rkm
enis
tan
5326
261
037
482
1 62
4(4
83, 2
310)
6289
Wpr
(LM
IC)
Tuva
luN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Uga
nda
1 33
597
6666
01
393
3 55
2(2
767,
447
3)20
39
Eur (
LMIC
)U
krai
ne26
7643
920
654
7 47
928
673
(245
, 413
29)
118
48
Emr (
HIC
)U
nite
d Ar
ab E
mira
tes
34
1359
3911
8(1
00, 1
37)
526
Eur (
HIC
)U
nite
d Ki
ngdo
m6
207
2 16
62
843
2 20
77
429
(222
2, 1
0324
)23
9
Afr
Uni
ted
Repu
blic
of
Tanz
ania
841
4715
692
980
2 57
5(1
568,
341
6)11
19
Amr (
HIC
)U
nite
d St
ates
of
Amer
ica
1537
84
004
9 35
53
362
17 1
13(6
08, 3
6782
)11
5
Amr (
HIC
)U
rugu
ay2
436
117
120
278
(74,
380
)16
8
Eur (
LMIC
)U
zbek
ista
n30
390
111
4 62
22
560
7 68
5(3
717,
109
05)
5371
Wpr
(LM
IC)
Vanu
atu
00
00
01
(0, 1
4)1
1
Amr (
LMIC
)Ve
nezu
ela,
Bol
ivar
ian
Repu
blic
of
5462
344
1 25
374
82
461
(176
3, 3
091)
1620
Wpr
(LM
IC)
Viet
Nam
230
557
1 24
52
177
7 29
211
502
(831
2, 1
4709
)25
21
Emr (
LMIC
)Ye
men
631
6429
1 06
099
72
781
(124
2, 4
274)
2349
Afr
Zam
bia
473
1310
210
379
1 08
4(2
95, 1
633)
1524
Afr
Zim
babw
e34
523
4119
436
596
8(7
0, 1
524)
1322
AAP
: Am
bien
t air
pollu
tion ;
ALR
I : Ac
ute
low
er re
spira
tory
dis
ease
; CO
PD : C
hron
ic o
bstru
ctiv
e pu
lmon
ary
dise
ase ;
IHD
: Isc
haem
ic h
eart
dise
ase.
Afr
: Afri
ca ; A
mr :
Am
eric
a ; E
mr :
Eas
tern
Med
iterra
nean
; Eu
r : E
urop
e ; S
ear:
Sout
h-Ea
st A
sia ;
Wpr
: Wes
tern
Pac
ific ;
LM
IC : L
ow- a
nd m
iddl
e-in
com
e co
untri
es ; H
IC : H
igh-
inco
me
coun
tries
; NA
: Not
ava
ilabl
e.a A
ge g
roup
incl
udes
less
than
5 y
ears
old
.b A
ge g
roup
incl
udes
25
year
s an
d ab
ove.
81
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Af
ghan
ista
n1
974
100
224
1 98
51
318
5 60
1(4
497,
682
9)37
80
Eur (
LMIC
)Al
bani
a5
1112
145
134
092
8(3
79, 1
237)
6451
Afr
Alge
ria19
284
515
3 08
82
694
6 57
3(2
638,
929
3)35
48
Eur (
HIC
)An
dorra
00
28
312
(0, 1
8)31
17
Afr
Ango
la2
235
7726
838
786
3 96
2(7
50, 6
449)
3556
Amr (
HIC
)An
tigua
and
Bar
buda
00
15
39
(0, 1
3)22
24
Amr (
LMIC
)Ar
gent
ina
4911
11
057
2 88
01
364
5 46
2(1
548,
754
7)27
26
Eur (
LMIC
)Ar
men
ia5
3230
692
232
41
589
(67,
247
4)10
795
Wpr
(HIC
)Au
stra
lia0
09
348
51(1
, 152
0)0.
40.
3
Eur (
HIC
)Au
stria
035
437
845
200
1 51
8(1
047,
189
0)37
20
Eur (
LMIC
)Az
erba
ijan
7526
186
1 48
156
62
334
(540
, 338
2)50
69
Amr (
HIC
)Ba
ham
as2
03
189
32(0
, 48)
1823
Emr (
HIC
)Ba
hrai
n1
418
5122
96(8
6, 1
07)
1237
Sear
Bang
lade
sh2
121
4 58
73
516
6 94
65
195
22 3
65(1
8175
, 273
11)
2945
Amr (
HIC
)Ba
rbad
os0
03
129
24(0
, 35)
1813
Eur (
LMIC
)Be
laru
s3
4649
33
392
940
4 87
3(1
00, 7
150)
110
88
Eur (
HIC
)Be
lgiu
m1
7491
377
732
02
085
(130
1, 2
703)
3821
Amr (
LMIC
)Be
lize
01
29
619
(3, 2
9)11
22
Afr
Beni
n39
226
1238
051
21
322
(455
, 202
8)26
56
Sear
Bhut
an12
187
4524
106
(84,
132
)27
39
Amr (
LMIC
)Bo
livia
, Plu
rinat
iona
l St
ates
of
145
3343
617
518
1 35
7(1
070,
163
5)26
35
Eur (
LMIC
)Bo
snia
and
H
erze
govi
na1
5645
877
562
41
915
(148
0, 2
370)
100
67
Afr
Bots
wan
a18
28
3946
113
(1, 1
77)
1124
Amr (
LMIC
)Br
azil
108
317
1 75
77
877
4 98
215
041
(648
6, 2
2871
)15
18
Wpr
HIC
Brun
ei D
arus
sala
m0
00
00
0(0
, 24)
0.2
0.3
Eur (
LMIC
)Bu
lgar
ia12
112
791
2 13
51
578
4 62
8(3
756,
548
3)13
073
Afr
Burk
ina
Faso
888
3924
541
862
2 35
4(1
202,
353
6)29
65
Afr
Buru
ndi
753
2310
322
570
1 67
7(7
59, 2
607)
3455
82
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Cab
o Ve
rde
182
3514
763
452
11
519
(116
, 234
8)21
44
Wpr
(LM
IC)
Cam
bodi
a1
456
107
4091
11
163
3 67
7(3
017,
445
7)34
58
Afr
Cam
eroo
n0
1226
963
912
91
049
(17,
361
2)6
4
Amr (
HIC
)C
anad
a3
51
2339
70(4
4, 1
00)
2849
Afr
Cen
tral A
frica
n Re
publ
ic26
634
816
017
664
4(3
20, 1
007)
2844
Afr
Cha
d1
398
3312
388
564
2 39
5(1
324,
356
1)38
56
Amr (
HIC
)C
hile
1149
350
702
542
1 65
4(1
216,
202
4)19
18
Wpr
(LM
IC)
Chi
na3
885
47 7
2416
1 19
812
7 79
122
9 79
857
0 39
6(4
7890
4, 6
6994
9)81
81
Amr (
LMIC
)C
olom
bia
9214
444
92
133
752
3 57
1(2
479,
442
2)15
20
Afr
Com
oros
171
118
3369
(16,
96)
1939
Afr
Con
go20
127
621
322
967
6(3
25, 1
046)
3255
Wpr
(LM
IC)
Coo
k Is
land
sN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)C
osta
Ric
a1
1343
233
8437
4(2
73, 4
55)
1617
Eur (
HIC
)C
roat
ia0
3143
771
136
61
546
(107
8, 1
953)
7543
Amr (
LMIC
)C
uba
440
622
1 12
654
52
337
(191
, 348
0)41
28
Eur (
HIC
)C
ypru
s0
244
8020
145
(96,
184
)25
20
Eur (
HIC
)C
zech
Rep
ublic
250
846
1 91
750
93
324
(258
2, 3
990)
6440
Afr
Côt
e d’
Ivoi
re77
945
2681
41
157
2 82
3(3
92, 4
417)
2645
Sear
Dem
ocra
tic P
eopl
e’s
Repu
blic
of K
orea
117
639
1 77
22
080
3 70
08
308
(108
1, 1
4021
)69
87
Afr
Dem
ocra
tic R
epub
lic
of th
e C
ongo
5 85
527
462
2 60
23
289
12 0
82(6
010,
184
71)
3455
Eur (
HIC
)D
enm
ark
018
203
253
119
593
(32,
949
)21
12
Emr (
LMIC
)D
jibou
ti31
22
3250
118
(45,
186
)28
48
Amr (
LMIC
)D
omin
ica
00
13
26
(0, 1
0)18
18
Amr (
LMIC
)D
omin
ican
Rep
ublic
5010
101
523
291
974
(88,
139
5)19
24
Amr (
LMIC
)Ec
uado
r49
2491
495
316
975
(480
, 126
9)13
16
Emr (
LMIC
)Eg
ypt
461
1 10
01
515
12 3
108
463
23 8
49(1
9760
, 283
30)
5593
Amr (
LMIC
)El
Sal
vado
r26
3253
475
146
731
(582
, 888
)26
30
Afr
Equa
toria
l Gui
nea
395
449
4214
0(1
1, 2
36)
3557
83
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Eritr
ea21
111
817
728
969
7(3
04, 1
065)
2868
Eur (
HIC
)Es
toni
a0
127
118
2116
7(2
, 334
)27
18
Afr
Ethi
opia
3 51
634
918
01
409
2 54
07
994
(290
2, 1
2647
)17
28
Wpr
(LM
IC)
Fiji
00
01
01
(0, 2
08)
0.3
0.4
Eur (
HIC
)Fi
nlan
d0
121
133
2718
1(1
, 892
)7
4
Eur (
HIC
)Fr
ance
380
3 10
32
246
1 17
26
605
(228
2, 9
311)
2112
Afr
Gab
on38
1111
7368
200
(40,
328
)25
38
Afr
Gam
bia
645
455
8721
5(1
3, 3
79)
2450
Eur (
LMIC
)G
eorg
ia8
3015
91
083
594
1 87
3(1
176,
237
9)95
68
Eur (
HIC
)G
erm
any
332
34
583
7 35
92
240
14 5
08(6
932,
191
42)
3718
Afr
Gha
na51
739
5995
71
128
2 70
0(1
801,
348
9)21
42
Eur (
HIC
)G
reec
e1
3869
41
349
748
2 82
9(9
88, 3
824)
5226
Amr (
LMIC
)G
rena
da0
01
75
13(0
, 19)
2432
Amr (
LMIC
)G
uate
mal
a21
837
9448
223
71
068
(862
, 128
3)14
23
Afr
Gui
nea
376
1911
350
491
1 24
7(1
36, 1
950)
2138
Afr
Gui
nea-
Biss
au90
42
5988
243
(19,
399
)29
49
Amr (
LMIC
)G
uyan
a2
12
7052
126
(0, 1
93)
3347
Amr (
LMIC
)H
aiti
310
846
393
720
1 47
8(1
84, 2
220)
2948
Amr (
LMIC
)H
ondu
ras
5446
5647
526
689
6(7
09, 1
095)
2339
Eur (
LMIC
)H
unga
ry2
931
286
2 16
178
24
324
(330
0, 5
271)
9159
Eur (
HIC
)Ic
elan
d0
02
72
11(0
, 32)
74
Sear
Indi
a19
459
63 2
9120
132
159
661
98 6
1836
1 16
1(3
0041
8, 4
3187
3)55
80
Sear
Indo
nesi
a1
453
703
3 60
910
906
18 1
7934
851
(185
54, 4
6214
)28
45
Emr (
LMIC
)Ira
n (Is
lam
ic
Repu
blic
of)
311
257
991
9 62
63
776
14 9
61(1
2870
, 171
01)
3954
Emr (
LMIC
)Ira
q54
410
452
43
090
1 80
76
069
(403
2, 8
209)
3689
Eur (
HIC
)Ire
land
06
8423
453
377
(26,
591
)16
13
Eur (
HIC
)Is
rael
121
273
300
123
718
(533
, 887
)19
16
Eur (
HIC
)Ita
ly1
335
4 73
04
484
2 38
011
929
(793
4, 1
5165
)41
18
Amr (
LMIC
)Ja
mai
ca5
664
132
164
371
(257
, 468
)27
26
84
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Wpr
(HIC
)Ja
pan
921
87
072
6 19
75
410
18 9
07(7
055,
260
40)
3113
Emr (
LMIC
)Jo
rdan
3525
138
468
244
910
(776
, 104
9)25
54
Eur (
LMIC
)Ka
zakh
stan
5074
548
3 35
81
367
5 39
8(6
97, 8
392)
6791
Afr
Keny
a1
129
1747
715
965
2 87
3(1
130,
392
0)14
25
Wpr
(LM
IC)
Kirib
ati
00
00
00
(0, 1
5)0.
00.
0
Emr (
HIC
)Ku
wai
t8
226
245
7535
6(3
17, 3
97)
1952
Eur (
LMIC
)Ky
rgyz
stan
2819
5571
832
61
145
(468
, 150
2)41
75
Wpr
(LM
IC)
Lao
Peop
le’s
D
emoc
ratic
Rep
ublic
232
2487
344
315
1 00
1(4
04, 1
477)
3160
Eur (
HIC
)La
tvia
05
165
565
200
937
(678
, 115
0)10
165
Emr (
LMIC
)Le
bano
n3
1514
764
711
492
6(7
66, 1
080)
3739
Afr
Leso
tho
449
541
7517
5(0
, 332
)17
33
Afr
Libe
ria33
21
3845
119
(0, 3
14)
611
Emr (
LMIC
)Li
bya
1837
220
605
343
1 22
2(8
29, 1
646)
3873
Eur (
HIC
)Li
thua
nia
012
189
659
210
1 07
0(7
96, 1
302)
7751
Eur (
HIC
)Lu
xem
bour
g0
225
2212
61(3
9, 7
8)23
15
Afr
Mad
agas
car
504
2311
164
696
82
253
(104
7, 3
058)
2042
Afr
Mal
awi
364
248
326
542
1 26
4(4
2, 2
006)
1635
Wpr
(LM
IC)
Mal
aysi
a16
106
450
2 28
895
43
814
(216
6, 4
914)
2737
Sear
Mal
dive
s0
13
1415
32(8
, 43)
1929
Afr
Mal
i1
245
107
2947
567
72
533
(132
6, 3
904)
3157
Eur (
HIC
)M
alta
01
2144
1378
(39,
100
)38
22
Wpr
(LM
IC)
Mar
shal
l Isl
ands
NA
NA
NA
NA
NA
NA
NA
NA
NA
Afr
Mau
ritan
ia21
113
611
417
551
9(3
14, 7
79)
2749
Afr
Mau
ritiu
s1
117
9247
158
(68,
204
)25
26
Amr (
LMIC
)M
exic
o26
239
383
15
677
2 01
49
178
(683
7, 1
1188
)15
20
Wpr
(LM
IC)
Mic
rone
sia
(Fed
erat
ed S
tate
s of
)0
00
00
0(0
, 12)
0.1
0.2
Eur (
HIC
)M
onac
o0
01
21
4(0
, 8)
2312
Wpr
(LM
IC)
Mon
golia
2411
4734
723
666
5(4
62, 8
22)
4889
Eur (
LMIC
)M
onte
negr
o0
158
112
8125
2(1
87, 3
11)
8259
85
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)M
oroc
co21
056
683
1 87
31
544
4 36
6(3
247,
534
4)27
34
Afr
Moz
ambi
que
784
2537
285
642
1 77
3(6
7, 2
850)
1424
Sear
Mya
nmar
887
669
1 57
22
219
5 82
511
171
(923
4, 1
3274
)44
68
Afr
Nam
ibia
186
642
5813
0(1
6, 2
06)
1226
Wpr
(LM
IC)
Nau
ruN
AN
AN
AN
AN
AN
AN
AN
AN
A
Sear
Nep
al38
586
948
41
882
1 59
55
216
(392
2, 6
802)
3961
Eur (
HIC
)N
ethe
rland
s1
741
147
727
342
2 29
1(1
220,
308
9)28
16
Wpr
(HIC
)N
ew Z
eala
nd0
02
72
11(0
, 235
)0.
50.
3
Amr (
LMIC
)N
icar
agua
4221
3938
120
969
2(1
11, 1
037)
2439
Afr
Nig
er1
855
557
514
894
3 32
5(2
028,
495
0)37
56
Afr
Nig
eria
12 7
1437
613
25
271
6 97
525
467
(206
92, 3
0689
)30
46
Wpr
(LM
IC)
Niu
eN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)N
orw
ay0
679
184
6633
4(1
4, 6
44)
138
Emr (
HIC
)O
man
54
1916
811
431
0(2
12, 4
11)
1442
Emr (
LMIC
)Pa
kist
an7
800
4 37
52
032
11 0
087
637
32 8
52(2
6659
, 401
54)
3656
Wpr
(LM
IC)
Pala
uN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Pa
nam
a7
325
143
7325
0(3
3, 3
62)
1315
Wpr
(LM
IC)
Papu
a N
ew G
uine
a91
617
101
9030
5(0
, 721
)8
15
Amr (
LMIC
)Pa
ragu
ay24
1087
329
260
709
(327
, 936
)22
32
Amr (
LMIC
)Pe
ru91
6233
91
103
697
2 29
1(1
779,
277
2)15
20
Wpr
(LM
IC)
Philip
pine
s91
043
91
605
8 84
15
827
17 6
22(1
3500
, 213
70)
3661
Eur (
HIC
)Po
land
731
24
053
6 70
43
863
14 9
38(1
1904
, 178
34)
8056
Eur (
HIC
)Po
rtuga
l0
1325
637
436
41
007
(42,
168
5)20
10
Emr (
HIC
)Q
atar
11
3084
2914
5(1
28, 1
62)
1032
Wpr
(HIC
)Re
publ
ic o
f Kor
ea5
195
3 36
91
538
1 98
57
092
(552
0, 8
637)
2925
Eur (
LMIC
)Re
publ
ic o
f Mol
dova
817
150
943
378
1 49
6(0
, 241
2)76
72
Eur (
LMIC
)Ro
man
ia48
113
1 68
33
757
2 56
98
170
(613
7, 9
965)
8454
Eur (
HIC
)Ru
ssia
n Fe
dera
tion
7253
18
158
44 6
2419
752
73 1
37(3
1229
, 100
241)
110
91
Afr
Rwan
da40
918
1227
448
81
201
(657
, 179
0)23
48
86
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Amr (
HIC
)Sa
int K
itts
and
Nev
isN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Sa
int L
ucia
10
29
921
(3, 3
1)24
24
Amr (
LMIC
)Sa
int V
ince
nt a
nd th
e G
rena
dine
s0
01
64
10(0
, 15)
1923
Wpr
(LM
IC)
Sam
oaN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)Sa
n M
arin
oN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Sao
Tom
e an
d Pr
inci
pe3
01
35
12(0
, 19)
1327
Emr (
HIC
)Sa
udi A
rabi
a30
145
270
2 69
91
776
4 92
1(4
282,
560
4)30
78
Afr
Sene
gal
348
4320
266
366
1 04
3(8
25, 1
274)
1531
Eur (
LMIC
)Se
rbia
355
978
1 22
187
23
128
(216
4, 3
974)
7145
Afr
Seyc
helle
s0
01
63
11(1
, 16)
2227
Afr
Sier
ra L
eone
392
95
195
294
895
(0, 1
614)
3049
Wpr
(HIC
)Si
ngap
ore
112
190
346
126
674
(336
, 914
)26
22
Eur (
HIC
)Sl
ovak
ia2
1530
41
139
392
1 85
2(1
422,
222
8)71
55
Eur (
HIC
)Sl
oven
ia0
715
315
310
641
9(2
94, 5
27)
4125
Wpr
(LM
IC)
Solo
mon
Isla
nds
00
00
00
(0, 5
4)0.
00.
0
Emr (
LMIC
)So
mal
ia73
66
1216
025
21
165
(67,
202
0)23
30
Afr
Sout
h Af
rica
651
302
1 05
92
622
2 79
67
429
(587
6, 8
928)
2953
Emr (
LMIC
)So
uth
Suda
n67
627
1827
844
41
442
(693
, 213
8)26
40
Eur (
HIC
)Sp
ain
298
1 51
01
885
785
4 27
9(7
59, 7
106)
1910
Sear
Sri L
anka
1917
826
63
101
1 31
24
877
(355
5, 6
154)
4954
Emr (
LMIC
)Su
dan
1 65
412
478
979
1 62
44
458
(254
9, 6
608)
2440
Amr (
LMIC
)Su
rinam
e2
06
1816
42(0
, 70)
1620
Afr
Swaz
iland
293
319
2478
(0, 1
35)
1325
Eur (
HIC
)Sw
eden
00
215
421
(0, 9
61)
0.4
0.2
Eur (
HIC
)Sw
itzer
land
016
260
422
123
821
(227
, 113
2)21
11
Emr (
LMIC
)Sy
rian
Arab
Rep
ublic
6744
442
2 36
198
33
898
(227
8, 5
388)
3980
Eur (
LMIC
)Ta
jikis
tan
287
3959
850
489
1 72
6(9
75, 2
507)
4386
Sear
Thai
land
6175
72
899
5 34
93
896
12 9
62(1
0209
, 157
31)
3935
87
Num
ber o
f dea
ths
Dea
ths
per 1
00 0
00 c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
LMIC
)Th
e fo
rmer
Yug
osla
v Re
publ
ic o
f M
aced
onia
115
239
249
319
823
(663
, 986
)80
64
Sear
Tim
or-L
este
271
1835
2911
0(0
, 216
)20
33
Afr
Togo
252
129
184
270
727
(142
, 116
8)22
43
Wpr
(LM
IC)
Tong
aN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
HIC
)Tr
inid
ad a
nd T
obag
o1
219
140
5221
4(0
, 316
)32
32
Emr (
LMIC
)Tu
nisi
a25
5946
31
454
795
2 79
8(2
246,
335
4)52
57
Eur (
LMIC
)Tu
rkey
139
653
5 63
68
540
4 99
919
967
(164
80, 2
3516
)54
68
Eur (
LMIC
)Tu
rkm
enis
tan
7729
881
388
462
2 04
3(6
32, 2
888)
8013
1
Wpr
(LM
IC)
Tuva
luN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Uga
nda
1 80
695
6096
31
512
4 43
6(3
471,
556
8)25
53
Eur (
LMIC
)U
krai
ne37
192
2 20
518
054
5 34
625
834
(366
, 378
75)
123
89
Emr (
HIC
)U
nite
d Ar
ab E
mira
tes
69
4934
013
453
7(4
64, 6
12)
828
Eur (
HIC
)U
nite
d Ki
ngdo
m7
217
2 63
74
523
1 54
28
926
(300
6, 1
2230
)29
16
Afr
Uni
ted
Repu
blic
of
Tanz
ania
1 07
263
2190
71
128
3 19
0(1
942,
422
7)13
24
Amr (
HIC
)U
nite
d St
ates
of
Amer
ica
1834
34
833
13 2
052
531
20 9
30(8
82, 4
4069
)13
9
Amr (
HIC
)U
rugu
ay2
1013
419
297
434
(118
, 617
)27
20
Eur (
LMIC
)U
zbek
ista
n41
910
633
35
362
2 37
68
597
(422
1, 1
2158
)61
103
Wpr
(LM
IC)
Vanu
atu
00
01
12
(0, 2
8)1
2
Amr (
LMIC
)Ve
nezu
ela,
Bol
ivar
ian
Repu
blic
of
7164
470
2 21
383
43
652
(266
2, 4
521)
2535
Wpr
(LM
IC)
Viet
Nam
361
570
3 65
12
903
8 35
215
838
(114
14, 2
0146
)35
48
Emr (
LMIC
)Ye
men
785
7194
1 78
91
147
3 88
6(1
779,
587
6)31
69
Afr
Zam
bia
523
514
309
475
1 32
7(3
82, 1
968)
1836
Afr
Zim
babw
e35
528
8217
225
188
8(6
4, 1
425)
1223
AAP
: Am
bien
t air
pollu
tion ;
ALR
I : Ac
ute
low
er r
espi
rato
ry d
isea
se ;
CO
PD :
Chr
onic
obs
truct
ive
pulm
onar
y di
seas
e ; IH
D :
Isch
aem
ic h
eart
dise
ase.
Afr
: Afri
ca ;
Amr :
Am
eric
a ; E
mr :
Eas
tern
Med
iterra
nean
; Eu
r : E
urop
e; S
ear :
Sou
th-E
ast A
sia ;
Wpr
: Wes
tern
Pac
ific ;
LM
IC : L
ow- a
nd m
iddl
e-in
com
e co
untri
es ; H
IC : H
igh-
inco
me
coun
tries
; NA
: Not
ava
ilabl
e.a A
ge g
roup
incl
udes
less
than
5 y
ears
old
.b A
ge g
roup
incl
udes
25
year
s an
d ab
ove.
89
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Af
ghan
ista
n34
2 27
84
660
9 76
212
0 81
388
567
566
080
(445
478,
704
450)
1 90
42
456
Eur (
LMIC
)Al
bani
a73
634
64
553
16 5
7514
364
36 5
75(1
5359
, 487
21)
1 27
097
9
Afr
Alge
ria30
968
2 78
819
267
136
594
134
408
324
026
(130
976,
457
620)
865
1 07
2
Eur (
HIC
)An
dorra
04
5723
085
377
(11,
564
)47
526
1
Afr
Ango
la33
4 71
63
243
1 14
746
867
53 6
1443
9 58
7(6
7634
, 731
631)
1 93
81
794
Amr (
HIC
)An
tigua
and
Bar
buda
71
2225
215
944
0(0
, 637
)49
450
8
Amr (
LMIC
)Ar
gent
ina
7 71
03
240
37 2
2310
9 17
857
557
214
908
(633
34, 2
9534
5)51
145
1
Eur (
LMIC
)Ar
men
ia75
092
59
666
30 9
6512
773
55 0
79(2
607,
851
84)
1 84
91
467
Wpr
(HIC
)Au
stra
lia6
1130
01
026
288
1 63
1(2
5, 4
8436
)7
5
Eur (
HIC
)Au
stria
791
023
16 4
2626
617
7 77
451
919
(355
31, 6
4880
)61
433
4
Eur (
LMIC
)Az
erba
ijan
12 2
5393
67
393
60 8
1528
109
109
506
(256
10, 1
6002
5)1
170
1 34
8
Amr (
HIC
)Ba
ham
as27
13
125
627
367
1 39
3(5
, 212
7)37
439
0
Emr (
HIC
)Ba
hrai
n14
614
561
42
221
1 08
04
207
(376
9, 4
651)
315
659
Sear
Bang
lade
sh34
9 66
316
7 79
712
0 66
126
4 73
623
9 16
71
142
024
(938
727,
138
2416
)73
61
007
Amr (
HIC
)Ba
rbad
os58
492
457
361
972
(0, 1
428)
345
254
Eur (
LMIC
)Be
laru
s34
11
195
15 1
4414
4 98
542
857
204
523
(452
8, 2
9617
5)2
155
1 39
9
Eur (
HIC
)Be
lgiu
m12
31
839
27 7
5523
954
11 3
5565
026
(409
25, 8
3926
)58
733
3
Amr (
LMIC
)Be
lize
8419
7835
726
880
6(1
33, 1
216)
239
424
Afr
Beni
n64
834
1 04
556
422
852
31 7
2912
1 02
4(3
7122
, 190
585)
1 20
41
547
Sear
Bhut
an1
854
645
463
2 30
71
412
6 68
2(5
402,
814
0)89
81
195
Amr (
LMIC
)Bo
livia
, Plu
rinat
iona
l St
ates
of
24 0
911
356
2 22
331
861
28 9
0788
439
(688
06, 1
0734
0)86
41
010
Eur (
LMIC
)Bo
snia
and
H
erze
govi
na21
21
875
14 8
4929
104
28 2
6374
303
(577
91, 9
1575
)1
941
1 18
3
Afr
Bots
wan
a3
222
6327
12
245
3 55
19
353
(51,
147
94)
439
657
Amr (
LMIC
)Br
azil
17 9
5310
115
74 3
6035
4 71
623
9 36
769
6 51
1(3
0181
3, 1
0530
85)
344
363
Wpr
HIC
Brun
ei D
arus
sala
m0
01
145
21(0
, 116
0)5
7
Eur (
LMIC
)Bu
lgar
ia1
810
3 46
226
434
79 4
5363
521
174
680
(142
448,
206
211)
2 39
21
302
Afr
Burk
ina
Faso
149
811
1 86
91
412
34 0
0052
792
239
884
(114
860,
370
840)
1 44
61
764
90
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Buru
ndi
125
078
1 26
469
217
513
30 9
4717
5 49
4(7
2493
, 282
653)
1 73
31
684
Afr
Cab
o Ve
rde
28 6
051
172
6 85
035
272
29 6
9710
1 59
6(7
214,
157
893)
685
938
Wpr
(LM
IC)
Cam
bodi
a23
7 84
14
061
2 36
950
212
69 5
1536
3 99
9(2
9447
7, 4
4962
1)1
681
1 79
7
Afr
Cam
eroo
n91
342
10 8
3620
685
4 82
836
782
(667
, 128
437)
105
64
Amr (
HIC
)C
anad
a46
112
041
792
1 62
23
037
(188
3, 4
261)
606
868
Afr
Cen
tral A
frica
n Re
publ
ic41
024
1 38
636
68
325
10 2
3361
334
(287
45, 9
7338
)1
328
1 35
6
Afr
Cha
d22
0 18
41
545
688
21 8
6532
829
277
111
(146
456,
422
581)
2 17
91
906
Amr (
HIC
)C
hile
1 55
01
341
13 4
1626
362
22 2
4364
913
(479
70, 7
9146
)37
331
8
Wpr
(LM
IC)
Chi
na61
1 12
11
487
398
5 19
2 60
55
586
044
10 1
74 9
6423
052
132
(195
4371
6,
2680
7904
)1
691
1 50
7
Amr (
LMIC
)C
olom
bia
14 3
824
440
18 3
7589
424
41 9
8316
8 60
4(1
1775
6, 2
0785
9)36
040
8
Afr
Com
oros
2 87
040
2995
31
691
5 58
3(9
34, 7
945)
761
1 00
8
Afr
Con
go29
392
925
205
10 8
0513
452
54 7
79(2
4516
, 864
06)
1 27
81
490
Wpr
(LM
IC)
Coo
k Is
land
sN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)C
osta
Ric
a16
736
11
489
9 16
23
710
14 8
89(1
0973
, 179
78)
320
319
Eur (
HIC
)C
roat
ia34
821
14 6
1426
245
14 5
3956
253
(396
13, 7
0634
)1
312
706
Amr (
LMIC
)C
uba
593
1 28
823
280
42 3
5422
408
89 9
23(8
044,
133
450)
793
555
Eur (
HIC
)C
ypru
s13
391
327
2 78
472
94
892
(329
1, 6
130)
433
329
Eur (
HIC
)C
zech
Rep
ublic
257
1 58
929
092
65 2
9220
142
116
373
(905
11, 1
3952
2)1
104
618
Afr
Côt
e d’
Ivoi
re12
9 98
21
756
1 29
245
243
66 0
2224
4 29
5(2
6116
, 393
384)
1 15
81
396
Sear
Dem
ocra
tic P
eopl
e’s
Repu
blic
of K
orea
20 9
0723
675
88 1
9096
799
169
397
398
968
(548
84, 6
6268
1)1
611
1 52
8
Afr
Dem
ocra
tic R
epub
lic
of th
e C
ongo
955
030
11 3
642
589
144
887
212
525
1 32
6 39
6(6
1663
6, 2
0801
28)
1 88
71
809
Eur (
HIC
)D
enm
ark
1363
48
768
7 77
14
463
21 6
50(1
208,
355
99)
387
217
Emr (
LMIC
)D
jibou
ti4
895
116
135
1 57
62
398
9 12
0(3
063,
149
57)
1 06
91
296
Amr (
LMIC
)D
omin
ica
73
2714
613
131
4(1
7, 4
60)
439
423
Amr (
LMIC
)D
omin
ican
Rep
ublic
7 68
434
93
958
25 1
5114
794
51 9
36(4
994,
744
10)
511
603
Amr (
LMIC
)Ec
uado
r7
813
634
3 43
818
890
13 9
8144
756
(223
13, 5
8308
)29
033
2
Emr (
LMIC
)Eg
ypt
86 4
3241
035
61 1
7657
9 45
940
5 95
61
174
059
(977
014,
138
9703
)1
371
1 87
6
Amr (
LMIC
)El
Sal
vado
r4
155
1 22
12
280
22 3
937
739
37 7
87(3
0163
, 457
49)
622
694
91
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Equa
toria
l Gui
nea
5 63
618
318
22
279
2 28
110
561
(553
, 183
43)
1 36
51
545
Afr
Eritr
ea32
875
619
588
9 64
415
798
59 5
24(2
3614
, 941
05)
1 21
71
685
Eur (
HIC
)Es
toni
a15
1683
24
190
926
5 97
9(9
4, 1
1818
)45
225
1
Afr
Ethi
opia
505
240
9 51
912
822
64 0
4511
7 45
870
9 08
4(2
3159
4, 1
1343
57)
769
781
Wpr
(LM
IC)
Fiji
20
052
963
(0, 9
613)
79
Eur (
HIC
)Fi
nlan
d11
2068
53
903
983
5 60
1(3
2, 2
7740
)10
352
Eur (
HIC
)Fr
ance
354
1 84
310
4 13
267
410
43 1
6921
6 90
7(7
6667
, 306
566)
341
203
Afr
Gab
on5
279
340
497
3 14
63
452
12 7
14(2
213,
208
86)
788
921
Afr
Gam
bia
10 3
4718
116
13
180
5 07
018
938
(790
, 343
69)
1 04
81
400
Eur (
LMIC
)G
eorg
ia1
109
925
5 10
240
220
25 9
2573
280
(464
65, 9
2862
)1
771
1 15
9
Eur (
HIC
)G
erm
any
462
9 48
215
6 41
822
6 87
884
821
478
060
(230
550,
632
146)
594
292
Afr
Gha
na87
880
1 71
82
304
52 6
1080
135
224
647
(143
698,
295
100)
879
1 18
8
Eur (
HIC
)G
reec
e92
1 03
018
944
43 0
8426
883
90 0
33(3
3231
, 120
529)
810
426
Amr (
LMIC
)G
rena
da3
229
258
204
496
(0, 7
20)
470
554
Amr (
LMIC
)G
uate
mal
a35
958
1 13
14
319
21 1
9211
548
74 1
47(5
8770
, 902
13)
482
570
Afr
Gui
nea
62 6
3082
960
022
249
30 9
7911
7 28
7(1
0043
, 187
988)
1 00
91
211
Afr
Gui
nea-
Biss
au14
444
167
115
3 47
25
041
23 2
39(1
203,
392
55)
1 35
51
493
Amr (
LMIC
)G
uyan
a30
020
120
3 84
53
057
7 34
1(2
, 112
67)
968
1 18
4
Amr (
LMIC
)H
aiti
52 0
2429
32
571
21 3
0040
672
116
861
(110
65, 1
8008
9)1
136
1 38
6
Amr (
LMIC
)H
ondu
ras
8 98
01
326
2 43
720
015
12 2
8645
045
(355
58, 5
4901
)58
283
3
Eur (
LMIC
)H
unga
ry32
33
224
53 1
9182
644
31 8
0617
1 18
8(1
3035
7, 2
0882
4)1
719
1 00
8
Eur (
HIC
)Ic
elan
d0
595
182
6434
6(2
, 109
5)10
772
Sear
Indi
a3
624
190
2 51
6 69
980
5 53
07
412
934
5 23
0 65
119
590
004
(164
6907
1,
2317
9478
)1
550
1 89
9
Sear
Indo
nesi
a22
9 87
019
399
137
053
439
333
905
691
1 73
1 34
6(9
1844
9, 2
2950
02)
698
905
Emr (
LMIC
)Ira
n (Is
lam
ic
Repu
blic
of)
54 4
258
513
37 8
9442
2 10
518
0 27
070
3 20
7(6
0643
7, 8
0205
2)92
31
203
Emr (
LMIC
)Ira
q91
681
3 60
019
790
131
867
80 6
5932
7 59
6(2
1309
0, 4
5221
4)99
41
690
Eur (
HIC
)Ire
land
4117
93
110
7 59
42
016
12 9
41(9
97, 2
0463
)27
720
5
Eur (
HIC
)Is
rael
9252
89
349
8 47
34
408
22 8
50(1
6838
, 282
99)
297
245
Eur (
HIC
)Ita
ly20
96
796
130
442
131
513
79 3
7234
8 33
3(2
3411
0, 4
3969
3)58
327
1
92
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Amr (
LMIC
)Ja
mai
ca71
812
52
131
4 81
76
809
14 5
99(1
0198
, 182
71)
528
524
Wpr
(HIC
)Ja
pan
1 64
83
516
178
246
193
571
178
114
555
095
(219
824,
753
378)
437
206
Emr (
LMIC
)Jo
rdan
5 72
675
74
326
20 8
1013
027
44 6
46(3
8246
, 512
07)
638
1 08
4
Eur (
LMIC
)Ka
zakh
stan
8 04
72
713
19 0
5015
8 91
877
917
266
644
(352
23, 4
1130
7)1
585
1 69
9
Afr
Keny
a18
3 43
678
42
293
36 0
5549
073
271
641
(896
98, 3
8012
5)63
969
6
Wpr
(LM
IC)
Kirib
ati
00
00
00
(0, 8
20)
00
Emr (
HIC
)Ku
wai
t1
112
7485
610
165
3 15
715
363
(136
99, 1
7117
)44
997
0
Eur (
LMIC
)Ky
rgyz
stan
4 39
967
32
148
31 3
2517
023
55 5
69(2
2858
, 730
35)
984
1 39
8
Wpr
(LM
IC)
Lao
Peop
le’s
D
emoc
ratic
Rep
ublic
36 1
6193
03
593
16 9
9715
521
73 2
03(2
6356
, 110
316)
1 13
11
458
Eur (
HIC
)La
tvia
3815
04
812
21 9
649
136
36 1
00(2
6497
, 440
09)
1 77
295
5
Emr (
LMIC
)Le
bano
n51
941
85
274
18 7
655
021
29 9
97(2
4739
, 350
54)
609
631
Afr
Leso
tho
7 45
832
016
32
248
5 16
515
355
(10,
288
99)
746
949
Afr
Libe
ria5
755
107
522
180
2 61
410
708
(2, 2
9331
)25
632
6
Emr (
LMIC
)Li
bya
2 76
11
153
6 88
625
039
15 4
7151
310
(352
43, 6
8435
)81
71
285
Eur (
HIC
)Li
thua
nia
6730
35
763
27 5
1310
720
44 3
67(3
3458
, 535
73)
1 47
185
5
Eur (
HIC
)Lu
xem
bour
g2
5585
471
248
52
109
(136
1, 2
703)
396
259
Afr
Mad
agas
car
82 9
141
179
3 97
533
857
54 7
5117
6 67
7(7
6607
, 243
779)
792
1 11
6
Afr
Mal
awi
67 8
1894
941
318
014
29 5
3811
6 73
2(2
564,
190
738)
743
962
Wpr
(LM
IC)
Mal
aysi
a2
670
2 89
718
812
92 6
5543
660
160
693
(917
43, 2
0624
3)55
473
0
Sear
Mal
dive
s63
2696
515
437
1 13
8(2
90, 1
520)
330
514
Afr
Mal
i20
8 01
63
651
1 70
131
393
45 0
3428
9 79
5(1
4607
5, 4
5053
0)1
799
1 85
6
Eur (
HIC
)M
alta
019
635
1 50
944
12
605
(134
2, 3
308)
627
361
Wpr
(LM
IC)
Mar
shal
l Isl
ands
NA
NA
NA
NA
NA
NA
NA
NA
NA
Afr
Mau
ritan
ia30
826
525
332
6 35
39
893
47 9
30(2
8099
, 738
26)
1 26
91
414
Afr
Mau
ritiu
s18
131
577
3 84
62
071
6 70
7(2
957,
864
4)53
347
7
Amr (
LMIC
)M
exic
o42
444
11 8
4831
617
234
186
102
089
422
185
(315
925,
512
238)
346
419
Wpr
(LM
IC)
Mic
rone
sia
(Fed
erat
ed S
tate
s of
)1
00
21
3(0
, 642
)3
4
Eur (
HIC
)M
onac
o0
131
7226
130
(0, 2
47)
346
193
93
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Wpr
(LM
IC)
Mon
golia
3 56
746
31
690
16 5
3712
529
34 7
87(2
4192
, 429
89)
1 23
91
764
Eur (
LMIC
)M
onte
negr
o30
142
392
3 34
32
758
8 53
7(6
237,
106
02)
1 36
893
7
Emr (
LMIC
)M
oroc
co33
467
1 78
123
822
90 8
7089
658
239
598
(178
845,
291
920)
726
830
Afr
Moz
ambi
que
122
599
1 40
21
609
16 7
1833
533
175
861
(383
0, 2
8909
7)68
368
3
Sear
Mya
nmar
138
885
31 5
2176
488
144
488
299
332
690
714
(574
461,
817
291)
1 31
51
627
Afr
Nam
ibia
3 08
021
924
72
372
4 35
810
276
(117
7, 1
6247
)44
870
0
Wpr
(LM
IC)
Nau
ruN
AN
AN
AN
AN
AN
AN
AN
AN
A
Sear
Nep
al67
160
37 9
4927
843
87 5
6475
614
296
130
(224
082,
383
002)
1 07
71
438
Eur (
HIC
)N
ethe
rland
s11
92
151
41 7
7923
421
13 8
3081
300
(429
01, 1
0977
3)48
527
9
Wpr
(HIC
)N
ew Z
eala
nd3
470
233
6937
9(2
, 815
5)9
6
Amr (
LMIC
)N
icar
agua
6 56
971
71
679
18 1
8610
835
37 9
86(6
041,
569
39)
646
871
Afr
Nig
er28
7 40
42
457
299
30 7
0552
736
373
601
(221
491,
569
811)
2 11
81
879
Afr
Nig
eria
2 01
8 55
117
656
8 85
330
3 54
943
9 41
92
788
027
(222
6669
, 34
1596
4)1
657
1 58
5
Wpr
(LM
IC)
Niu
eN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)N
orw
ay16
185
2 94
75
653
2 26
311
065
(473
, 216
55)
220
132
Emr (
HIC
)O
man
889
128
722
6 96
84
887
13 5
94(9
288,
179
27)
383
750
Emr (
LMIC
)Pa
kist
an1
242
440
115
082
70 5
0753
4 58
338
2 74
82
345
359
(192
3609
, 28
4857
7)1
322
1 51
8
Wpr
(LM
IC)
Pala
uN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Pa
nam
a1
364
8782
45
199
2 96
710
442
(142
6, 1
5150
)27
930
3
Wpr
(LM
IC)
Papu
a N
ew G
uine
a14
990
244
783
6 05
54
354
26 4
28(0
, 632
61)
369
427
Amr (
LMIC
)Pa
ragu
ay3
819
301
2 75
914
263
11 9
0233
044
(154
60, 4
3378
)51
867
2
Amr (
LMIC
)Pe
ru14
797
2 17
215
470
47 7
8734
847
115
073
(891
77, 1
3909
3)38
243
9
Wpr
(LM
IC)
Philip
pine
s15
1 16
413
981
65 4
4544
5 70
831
2 14
698
8 44
3(7
5525
5, 1
1959
18)
1 02
91
356
Eur (
HIC
)Po
land
1 08
98
840
144
742
247
551
157
769
559
991
(447
950,
666
269)
1 45
091
0
Eur (
HIC
)Po
rtuga
l56
280
7 99
012
011
12 4
8632
822
(154
8, 5
4610
)31
216
6
Emr (
HIC
)Q
atar
126
641
211
3 87
51
366
6 64
2(5
902,
740
3)33
069
9
Wpr
(HIC
)Re
publ
ic o
f Kor
ea67
64
051
99 2
1857
125
80 0
2024
1 09
0(1
9013
4, 2
9058
6)48
634
5
Eur (
LMIC
)Re
publ
ic o
f Mol
dova
1 42
449
85
388
40 3
3618
514
66 1
60(0
, 105
853)
1 62
41
298
Eur (
LMIC
)Ro
man
ia7
962
3 26
757
942
142
088
103
680
314
939
(237
754,
382
435)
1 57
998
9
94
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
HIC
)Ru
ssia
n Fe
dera
tion
12 1
1615
103
264
830
1 93
9 66
696
2 21
73
193
932
(138
7484
, 349
265)
2 22
91
511
Afr
Rwan
da66
948
843
622
14 6
2125
587
108
622
(561
63, 1
6732
6)1
004
1 19
5
Amr (
HIC
)Sa
int K
itts
and
Nev
isN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Sa
int L
ucia
848
7833
440
190
5(1
47, 1
308)
500
495
Amr (
LMIC
)Sa
int V
ince
nt a
nd th
e G
rena
dine
s9
121
273
177
482
(0, 6
99)
441
477
Wpr
(LM
IC)
Sam
oaN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)Sa
n M
arin
oN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Sao
Tom
e an
d Pr
inci
pe45
113
2416
931
897
5(0
, 157
7)54
676
4
Emr (
HIC
)Sa
udi A
rabi
a5
322
4 57
810
690
105
918
80 1
8820
6 69
7(1
8063
7, 2
3407
9)70
11
373
Afr
Sene
gal
55 7
111
566
1 14
514
426
20 7
6393
611
(727
49, 1
1574
6)67
983
1
Eur (
LMIC
)Se
rbia
366
1 71
137
806
47 8
9938
856
126
637
(879
89, 1
6038
2)1
410
870
Afr
Seyc
helle
s7
553
266
126
458
(37,
668
)48
450
1
Afr
Sier
ra L
eone
67 6
6242
528
413
264
20 5
0210
2 13
6(0
, 190
034)
1 69
01
782
Wpr
(HIC
)Si
ngap
ore
131
280
6 52
013
343
5 65
725
931
(132
25, 3
4817
)48
937
4
Eur (
HIC
)Sl
ovak
ia41
143
010
779
42 7
9916
506
70 9
25(5
4710
, 850
63)
1 31
087
6
Eur (
HIC
)Sl
oven
ia11
162
5 14
75
133
3 88
614
338
(100
98, 1
7970
)69
538
2
Wpr
(LM
IC)
Solo
mon
Isla
nds
00
00
00
(0, 3
022)
00
Emr (
LMIC
)So
mal
ia12
3 65
240
072
98
353
13 2
4214
6 37
6(6
893,
261
160)
1 45
91
089
Afr
Sout
h Af
rica
105
342
10 1
8644
936
120
850
173
456
454
770
(359
039,
545
313)
861
1 11
6
Emr (
LMIC
)So
uth
Suda
n10
8 89
51
113
983
14 7
5123
942
149
684
(659
42, 2
2753
5)1
363
1 28
7
Eur (
HIC
)Sp
ain
237
1 69
142
769
56 7
2526
621
128
043
(238
35, 2
1005
6)27
515
6
Sear
Sri L
anka
2 98
14
972
10 0
3411
7 18
952
962
188
138
(137
899,
235
835)
921
893
Emr (
LMIC
)Su
dan
261
209
5 12
23
569
52 2
7588
336
410
512
(224
919,
623
811)
1 08
91
190
Amr (
LMIC
)Su
rinam
e15
910
210
948
851
2 17
7(1
, 357
3)41
244
8
Afr
Swaz
iland
4 71
815
810
31
277
2 26
38
520
(0, 1
4612
)69
287
1
Eur (
HIC
)Sw
eden
13
8241
812
562
9(0
, 294
79)
73
Eur (
HIC
)Sw
itzer
land
3341
39
276
12 0
404
266
26 0
28(7
270,
362
08)
324
177
95
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Sy
rian
Arab
Rep
ublic
10 5
331
328
14 5
6895
816
36 7
0515
8 95
0(9
3603
, 218
308)
796
1 39
2
Eur (
LMIC
)Ta
jikis
tan
45 4
941
955
3 00
443
109
30 3
0912
3 87
1(6
6432
, 185
137)
1 56
22
346
Sear
Thai
land
9 44
217
204
114
602
216
933
160
335
518
516
(411
912,
622
205)
772
643
Eur (
LMIC
)Th
e fo
rmer
Yug
osla
v Re
publ
ic o
f M
aced
onia
101
434
8 10
39
960
13 7
0932
306
(262
26, 3
8493
)1
561
1 14
8
Sear
Tim
or-L
este
4 57
347
795
1 91
11
487
8 81
4(0
, 175
45)
800
926
Afr
Togo
43 9
2450
139
911
519
17 5
2373
867
(116
08, 1
2218
2)1
095
1 30
9
Wpr
(LM
IC)
Tong
aN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
HIC
)Tr
inid
ad a
nd T
obag
o25
838
733
5 54
82
284
8 86
2(0
, 130
46)
661
594
Emr (
LMIC
)Tu
nisi
a4
057
1 98
714
135
61 3
2636
037
117
542
(951
77, 1
3994
6)1
080
1 10
6
Eur (
LMIC
)Tu
rkey
21 8
0520
007
196
101
368
778
239
376
846
068
(704
766,
988
251)
1 13
01
208
Eur (
LMIC
)Tu
rkm
enis
tan
11 7
661
531
4 04
674
229
28 6
2112
0 19
3(3
6834
, 171
202)
2 32
33
120
Wpr
(LM
IC)
Tuva
luN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Uga
nda
285
051
4 87
84
194
48 9
8680
384
423
492
(324
787,
543
839)
1 19
61
402
Eur (
LMIC
)U
krai
ne5
734
5 41
173
112
796
790
247
172
1 12
8 21
9(1
7925
, 163
8357
)2
489
1 51
2
Emr (
HIC
)U
nite
d Ar
ab E
mira
tes
829
393
2 08
516
984
7 43
227
723
(239
71, 3
1545
)31
059
5
Eur (
HIC
)U
nite
d Ki
ngdo
m1
135
6 76
097
796
139
234
56 0
5930
0 98
5(1
0383
9, 4
1553
1)47
327
7
Afr
Uni
ted
Repu
blic
of
Tanz
ania
173
615
2 66
71
009
45 5
1655
715
278
521
(158
205,
377
239)
573
651
Amr (
HIC
)U
nite
d St
ates
of
Amer
ica
2 95
912
278
192
562
465
743
110
472
784
015
(353
95, 1
6601
76)
249
168
Amr (
HIC
)U
rugu
ay32
426
14
196
6 47
33
844
15 0
99(4
262,
212
61)
444
326
Eur (
LMIC
)U
zbek
ista
n65
481
4 49
114
596
249
788
125
646
460
001
(221
078,
657
777)
1 60
92
196
Wpr
(LM
IC)
Vanu
atu
80
330
2666
(0, 1
225)
2743
Amr (
LMIC
)Ve
nezu
ela,
Bol
ivar
ian
Repu
blic
of
11 4
072
395
21 6
4594
773
40 1
5317
0 37
3(1
2368
2, 2
1121
2)57
168
9
Wpr
(LM
IC)
Viet
Nam
53 7
6217
575
147
882
111
775
328
906
659
901
(476
947,
835
297)
730
811
Emr (
LMIC
)Ye
men
128
485
3 37
83
389
89 7
0866
717
291
678
(121
702,
458
316)
1 17
21
720
Afr
Zam
bia
90 4
7741
768
314
882
22 4
9012
8 94
9(2
8321
, 198
935)
872
935
Afr
Zim
babw
e63
624
986
2 54
98
822
15 7
9391
774
(380
0, 1
4816
4)63
069
2
YLL :
yea
r of
life
lost
; AA
P :
Ambi
ent
air
pollu
tion ;
ALR
I : Ac
ute
low
er r
espi
rato
ry d
isea
se ;
CO
PD :
Chr
onic
obs
truct
ive
pulm
onar
y di
seas
e ; I
HD
: Is
chae
mic
hea
rt di
seas
e. A
fr :
Afric
a ; A
mr :
Am
eric
a ;
Emr :
Eas
tern
Med
iterra
nean
; Eur
: Eur
ope ;
Sea
r : S
outh
-Eas
t Asi
a ; W
pr : W
este
rn P
acifi
c ; L
MIC
: Low
- and
mid
dle-
inco
me
coun
tries
; HIC
: Hig
h-in
com
e co
untri
es ; N
A : N
ot a
vaila
ble.
a Age
gro
up in
clud
es le
ss th
an 5
yea
rs o
ld.
b Age
gro
up in
clud
es 2
5 ye
ars
and
abov
e.
96
Num
ber o
f YLL
s YL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Af
ghan
ista
n16
3 09
92
231
2 64
856
435
50 5
7027
4 98
3(2
1665
3, 3
4178
1)1
905
2 41
1
Eur (
LMIC
)Al
bani
a31
115
21
506
6 70
37
540
16 2
13(6
722,
215
86)
1 12
981
7
Afr
Alge
ria13
523
945
3 64
148
877
60 9
4012
7 92
5(5
1571
, 180
805)
688
835
Eur (
HIC
)An
dorra
01
1375
4213
2(3
, 196
)32
814
5
Afr
Ango
la13
1 79
71
326
412
18 6
4327
801
179
980
(283
57, 2
9856
1)1
573
1 53
0
Amr (
HIC
)An
tigua
and
Bar
buda
20
710
275
187
(0, 2
70)
401
392
Amr (
LMIC
)Ar
gent
ina
3 27
41
179
10 8
4239
628
25 3
2780
252
(235
07, 1
0973
0)37
329
0
Eur (
LMIC
)Ar
men
ia28
530
51
573
10 7
595
650
18 5
71(7
69, 2
8210
)1
239
814
Wpr
(HIC
)Au
stra
lia3
512
232
615
461
0(9
, 189
58)
53
Eur (
HIC
)Au
stria
5941
05
910
9 85
84
003
20 2
41(1
3832
, 253
22)
468
216
Eur (
LMIC
)Az
erba
ijan
5 42
435
21
479
22 4
7913
611
43 3
45(9
822,
633
92)
920
1 00
2
Amr (
HIC
)Ba
ham
as11
71
3820
916
152
5(2
, 804
)27
627
0
Emr (
HIC
)Ba
hrai
n67
4916
358
038
91
249
(111
3, 1
388)
249
531
Sear
Bang
lade
sh15
6 97
576
788
30 5
7278
697
118
505
461
536
(376
188,
563
712)
601
814
Amr (
HIC
)Ba
rbad
os24
130
164
154
373
(0, 5
49)
255
173
Eur (
LMIC
)Be
laru
s10
920
11
637
55 3
5220
372
77 6
71(1
303,
111
090)
1 52
976
5
Eur (
HIC
)Be
lgiu
m52
642
7 55
27
434
5 53
821
218
(136
38, 2
7183
)37
619
3
Amr (
LMIC
)Be
lize
501
2214
612
834
8(5
4, 5
16)
206
369
Afr
Beni
n29
279
348
199
10 6
2715
582
56 0
34(1
7331
, 879
11)
1 11
11
398
Sear
Bhut
an80
125
423
289
178
22
959
(239
4, 3
597)
860
1 18
8
Amr (
LMIC
)Bo
livia
, Plu
rinat
iona
l St
ates
of
10 9
2868
41
162
13 2
6113
218
39 2
54(3
0416
, 477
82)
768
875
Eur (
LMIC
)Bo
snia
and
H
erze
govi
na89
769
2 92
310
886
14 7
7029
437
(230
46, 3
6220
)1
531
817
Afr
Bots
wan
a1
571
2646
1 13
32
200
4 97
5(2
8, 7
816)
466
679
Amr (
LMIC
)Br
azil
8 13
44
195
30 1
3812
7 19
711
2 01
328
1 67
7(1
2202
8, 4
2817
8)27
427
1
Wpr
HIC
Brun
ei D
arus
sala
m0
01
42
7(0
, 429
)4
5
Eur (
LMIC
)Bu
lgar
ia76
51
326
4 49
230
608
30 5
2267
713
(555
52, 7
9643
)1
805
822
97
Num
ber o
f YLL
s YL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Burk
ina
Faso
69 2
3580
967
916
091
24 8
2011
1 63
3(5
3548
, 172
413)
1 33
41
539
Afr
Buru
ndi
56 7
3657
934
66
009
12 5
3476
204
(309
87, 1
2358
8)1
486
1 40
2
Afr
Cab
o Ve
rde
12 0
5652
32
475
15 3
9514
319
44 7
69(3
168,
694
17)
589
772
Wpr
(LM
IC)
Cam
bodi
a10
5 72
11
423
853
21 7
6533
935
163
697
(132
518,
201
931)
1 51
11
617
Afr
Cam
eroo
n46
163
5 07
36
348
2 48
314
113
(240
, 518
28)
8045
Amr (
HIC
)C
anad
a22
129
1826
270
51
236
(764
, 173
4)48
760
4
Afr
Cen
tral A
frica
n Re
publ
ic16
868
627
127
3 52
15
138
26 2
82(1
2380
, 416
30)
1 12
21
159
Afr
Cha
d93
313
684
289
9 38
414
996
118
666
(627
93, 1
8087
3)1
868
1 65
5
Amr (
HIC
)C
hile
596
548
5 30
17
426
9 59
123
461
(170
99, 2
8858
)26
620
6
Wpr
(LM
IC)
Chi
na25
7 59
567
4 32
31
453
252
2 62
0 15
24
804
159
9 80
9 48
0(8
3499
19, 1
1390
232)
1 48
31
265
Amr (
LMIC
)C
olom
bia
5 99
41
904
7 17
933
582
21 9
7570
635
(491
12, 8
7387
)29
732
0
Afr
Com
oros
1 30
320
037
571
82
417
(388
, 345
0)66
484
1
Afr
Con
go11
128
338
574
314
6 73
022
568
(102
07, 3
5361
)1
053
1 26
4
Wpr
(LM
IC)
Coo
k Is
land
sN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)C
osta
Ric
a70
171
494
2 99
11
757
5 48
2(4
012,
666
1)23
622
4
Eur (
HIC
)C
roat
ia14
271
3 53
610
087
6 98
820
896
(150
57, 2
5987
)94
141
1
Amr (
LMIC
)C
uba
272
572
8 45
715
560
10 1
3634
997
(308
0, 5
2022
)62
040
5
Eur (
HIC
)C
ypru
s12
928
067
935
01
330
(905
, 166
4)24
116
2
Eur (
HIC
)C
zech
Rep
ublic
114
567
8 56
323
933
9 92
543
102
(337
32, 5
1588
)80
337
4
Afr
Côt
e d’
Ivoi
re59
202
513
441
18 1
1228
254
106
521
(110
78, 1
7183
9)1
030
1 27
5
Sear
Dem
ocra
tic P
eopl
e’s
Repu
blic
of K
orea
10 3
259
559
36 3
6838
170
69 8
2016
4 24
2(2
2547
, 273
082)
1 29
71
089
Afr
Dem
ocra
tic R
epub
lic
of th
e C
ongo
423
559
4 61
983
759
455
107
418
595
889
(277
324,
933
537)
1 69
01
626
Eur (
HIC
)D
enm
ark
333
14
361
2 46
72
195
9 35
7(4
13, 1
5866
)33
217
2
Emr (
LMIC
)D
jibou
ti2
060
6068
633
1 02
03
840
(128
1, 6
329)
905
1 08
6
Amr (
LMIC
)D
omin
ica
31
757
6513
2(7
, 192
)36
633
2
Amr (
LMIC
)D
omin
ican
Rep
ublic
3 16
317
91
546
12 0
267
639
24 5
53(2
382,
350
51)
482
558
Amr (
LMIC
)Ec
uado
r3
408
268
1 45
57
167
6 41
418
711
(918
5, 2
4474
)24
326
6
Emr (
LMIC
)Eg
ypt
44 5
0516
469
17 0
4022
7 78
517
3 09
247
8 89
0(3
9744
6, 5
6877
7)1
129
1 45
2
98
Num
ber o
f YLL
s YL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Amr (
LMIC
)El
Sal
vado
r1
823
709
1 05
410
301
4 18
118
067
(143
64, 2
1967
)56
359
5
Afr
Equa
toria
l Gui
nea
2 05
262
4569
298
73
837
(202
, 667
7)1
018
1 20
8
Afr
Eritr
ea13
773
293
287
3 71
26
807
24 8
72(9
802,
394
51)
1 01
71
349
Eur (
HIC
)Es
toni
a0
419
01
535
419
2 14
8(2
6, 4
170)
304
119
Afr
Ethi
opia
185
983
1 14
76
718
22 0
5848
508
264
415
(867
34, 4
2027
7)57
359
0
Wpr
(LM
IC)
Fiji
10
012
317
(0, 2
690)
45
Eur (
HIC
)Fi
nlan
d6
722
11
224
470
1 92
8(9
, 973
9)70
28
Eur (
HIC
)Fr
ance
118
587
27 8
9119
899
21 1
2769
620
(246
25, 9
7125
)21
311
1
Afr
Gab
on1
870
136
179
1 30
51
821
5 31
0(9
60, 8
644)
665
769
Afr
Gam
bia
4 51
357
401
380
2 27
88
267
(350
, 149
48)
906
1 24
1
Eur (
LMIC
)G
eorg
ia39
834
683
716
390
12 8
6530
836
(194
51, 3
8983
)1
421
759
Eur (
HIC
)G
erm
any
188
3 82
852
206
77 7
8542
801
176
808
(844
31, 2
3366
6)43
118
4
Afr
Gha
na40
887
747
499
22 5
1545
407
110
054
(704
01, 1
4458
7)85
41
131
Eur (
HIC
)G
reec
e38
464
3 23
514
852
13 5
8732
175
(116
23, 4
2388
)56
724
4
Amr (
LMIC
)G
rena
da1
17
8986
184
(0, 2
67)
349
364
Amr (
LMIC
)G
uate
mal
a16
147
511
1 90
68
842
5 71
333
119
(262
08, 4
0349
)42
247
9
Afr
Gui
nea
28 4
7530
818
410
740
15 1
6954
875
(478
2, 8
7626
)94
61
148
Afr
Gui
nea-
Biss
au6
300
5851
1 63
32
357
10 3
99(5
57, 1
7488
)1
204
1 34
6
Amr (
LMIC
)G
uyan
a14
17
571
497
1 34
73
049
(1, 4
706)
806
1 00
3
Amr (
LMIC
)H
aiti
23 9
3111
91
425
10 3
7121
027
56 8
73(5
454,
874
58)
1 09
31
308
Amr (
LMIC
)H
ondu
ras
4 08
853
298
57
345
5 48
618
435
(144
79, 2
2554
)47
664
7
Eur (
LMIC
)H
unga
ry14
21
265
18 7
0133
186
14 2
7667
570
(516
99, 8
2224
)1
293
639
Eur (
HIC
)Ic
elan
d0
250
5532
139
(0, 4
72)
8750
Sear
Indi
a1
857
079
1 02
3 75
919
8 70
62
306
544
2 41
4 82
27
800
910
(651
7074
, 929
3312
)1
282
1 52
0
Sear
Indo
nesi
a98
053
5 40
538
394
130
612
416
064
688
528
(362
860,
912
704)
560
706
Emr (
LMIC
)Ira
n (Is
lam
ic
Repu
blic
of)
26 2
083
380
13 1
5915
7 16
779
310
279
224
(240
070,
319
522)
740
1 03
3
Emr (
LMIC
)Ira
q42
264
1 28
75
539
42 6
8031
022
122
792
(790
44, 1
7159
0)75
41
156
Eur (
HIC
)Ire
land
2180
1 26
92
504
1 04
44
917
(339
, 791
5)21
014
0
99
Num
ber o
f YLL
s YL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
HIC
)Is
rael
2219
12
982
2 64
41
999
7 83
7(5
787,
970
7)20
214
1
Eur (
HIC
)Ita
ly14
22
489
34 3
7146
326
41 1
2712
4 45
5(8
5411
, 155
902)
405
157
Amr (
LMIC
)Ja
mai
ca28
531
416
1 89
33
232
5 85
8(4
160,
727
0)42
238
7
Wpr
(HIC
)Ja
pan
792
675
44 8
3157
353
69 7
1017
3 36
1(6
8199
, 233
248)
266
106
Emr (
LMIC
)Jo
rdan
2 50
019
165
07
237
6 18
916
767
(144
05, 1
9191
)49
380
1
Eur (
LMIC
)Ka
zakh
stan
3 47
288
43
294
59 7
8638
564
106
000
(138
55, 1
6255
5)1
218
1 15
6
Afr
Keny
a80
928
345
917
12 5
2120
579
115
291
(372
21, 1
6193
6)54
256
9
Wpr
(LM
IC)
Kirib
ati
00
00
00
(0, 2
66)
00
Emr (
HIC
)Ku
wai
t42
424
220
2 04
01
106
3 81
5(3
377,
428
3)25
467
7
Eur (
LMIC
)Ky
rgyz
stan
1 86
226
048
811
953
7 25
721
820
(882
9, 2
8663
)76
31
000
Wpr
(LM
IC)
Lao
Peop
le’s
D
emoc
ratic
Rep
ublic
15 1
5246
11
109
7 54
37
234
31 4
99(1
1532
, 473
52)
967
1 21
7
Eur (
HIC
)La
tvia
1533
731
8 80
74
591
14 1
76(1
0520
, 171
64)
1 28
251
0
Emr (
LMIC
)Le
bano
n23
014
91
627
4 73
72
721
9 46
3(7
740,
111
46)
389
399
Afr
Leso
tho
3 41
512
838
1 13
33
037
7 75
1(5
, 144
03)
743
887
Afr
Libe
ria2
797
4418
1 00
91
274
5 14
1(1
, 140
82)
247
308
Emr (
LMIC
)Li
bya
1 16
542
393
09
671
7 26
319
452
(135
55, 2
5798
)62
993
6
Eur (
HIC
)Li
thua
nia
4162
844
11 0
355
576
17 5
58(1
3377
, 210
57)
1 07
946
6
Eur (
HIC
)Lu
xem
bour
g2
2427
019
824
173
5(4
75, 9
46)
276
157
Afr
Mad
agas
car
37 1
7357
969
513
221
26 5
4678
214
(336
71, 1
0799
6)69
997
9
Afr
Mal
awi
34 7
4238
315
38
793
15 3
4559
415
(123
7, 9
7031
)75
592
5
Wpr
(LM
IC)
Mal
aysi
a1
175
810
6 37
030
873
19 1
1358
341
(332
13, 7
4942
)39
855
3
Sear
Mal
dive
s27
1416
193
111
362
(89,
483
)21
034
6
Afr
Mal
i94
987
1 11
071
017
242
25 2
2313
9 27
3(7
1065
, 214
508)
1 74
41
844
Eur (
HIC
)M
alta
05
165
526
187
883
(462
, 111
0)42
222
1
Wpr
(LM
IC)
Mar
shal
l Isl
ands
NA
NA
NA
NA
NA
NA
NA
NA
NA
Afr
Mau
ritan
ia11
696
212
107
3 02
24
847
19 8
83(1
1770
, 303
74)
1 05
91
224
Afr
Mau
ritiu
s63
615
71
168
766
2 16
0(9
44, 2
783)
340
289
Amr (
LMIC
)M
exic
o18
624
5 32
312
182
85 5
9350
304
172
027
(127
788,
209
804)
280
324
Wpr
(LM
IC)
Mic
rone
sia
(Fed
erat
ed S
tate
s of
)0
00
00
1(0
, 229
)2
3
100
Num
ber o
f YLL
s YL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
HIC
)M
onac
o0
08
2413
45(0
, 85)
235
101
Wpr
(LM
IC)
Mon
golia
1 39
316
429
85
370
5 18
312
408
(860
6, 1
5357
)87
61
226
Eur (
LMIC
)M
onte
negr
o12
356
776
31
039
2 38
4(1
744,
296
8)75
545
6
Emr (
LMIC
)M
oroc
co14
418
539
2 61
136
185
46 7
7510
0 52
8(7
5973
, 121
784)
601
675
Afr
Moz
ambi
que
51 4
6377
360
27
904
15 5
3776
279
(179
6, 1
2523
8)57
857
9
Sear
Mya
nmar
58 4
0917
927
33 7
6281
429
140
657
332
184
(276
447,
393
004)
1 23
51
461
Afr
Nam
ibia
1 41
797
881
225
2 71
65
543
(657
, 869
9)47
069
9
Wpr
(LM
IC)
Nau
ruN
AN
AN
AN
AN
AN
AN
AN
AN
A
Sear
Nep
al32
168
19 5
0914
486
36 2
7237
045
139
481
(104
679,
181
830)
985
1 31
5
Eur (
HIC
)N
ethe
rland
s52
1 02
416
884
7 48
37
307
32 7
50(1
7038
, 444
84)
388
212
Wpr
(HIC
)N
ew Z
eala
nd2
237
7139
151
(1, 3
452)
74
Amr (
LMIC
)N
icar
agua
2 71
932
366
46
966
4 91
715
591
(248
5, 2
3519
)52
367
1
Afr
Nig
er11
9 15
81
041
4614
942
25 6
8316
0 87
0(9
5851
, 244
409)
1 83
81
774
Afr
Nig
eria
864
235
7 18
44
557
128
099
211
378
1 21
5 45
3(9
7139
3, 1
4878
89)
1 47
11
441
Wpr
(LM
IC)
Niu
eN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)N
orw
ay5
921
254
1 88
71
135
4 37
3(1
64, 8
766)
175
90
Emr (
HIC
)O
man
469
3915
21
986
1 45
14
096
(278
1, 5
459)
314
620
Emr (
LMIC
)Pa
kist
an53
4 05
927
645
11 6
6623
5 71
720
3 29
31
012
379
(836
044,
122
0982
)1
174
1 36
3
Wpr
(LM
IC)
Pala
uN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Pa
nam
a73
039
270
1 60
71
352
3 99
8(5
25, 5
875)
214
222
Wpr
(LM
IC)
Papu
a N
ew G
uine
a6
763
7626
52
433
1 24
810
785
(0, 2
5810
)30
833
5
Amr (
LMIC
)Pa
ragu
ay1
679
9652
64
731
4 92
911
961
(556
1, 1
5661
)38
147
8
Amr (
LMIC
)Pe
ru6
541
1 11
67
660
18 6
8116
256
50 2
54(3
8661
, 610
80)
333
366
Wpr
(LM
IC)
Philip
pine
s68
621
3 45
718
623
143
385
120
160
354
247
(269
559,
429
507)
746
940
Eur (
HIC
)Po
land
413
2 61
243
455
81 4
0871
253
199
140
(159
581,
236
994)
999
525
Eur (
HIC
)Po
rtuga
l26
791
588
4 01
85
752
11 4
63(4
95, 1
8432
)20
891
Emr (
HIC
)Q
atar
5218
188
525
183
966
(851
, 108
8)18
956
6
Wpr
(HIC
)Re
publ
ic o
f Kor
ea25
41
067
25 8
8017
101
33 2
8477
586
(617
70, 9
3155
)31
119
2
Eur (
LMIC
)Re
publ
ic o
f Mol
dova
661
141
988
17 4
868
838
28 1
14(0
, 442
76)
1 32
992
1
101
Num
ber o
f YLL
s YL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
LMIC
)Ro
man
ia3
602
861
10 9
9951
272
47 6
3811
4 37
2(8
7652
, 137
810)
1 11
459
9
Eur (
HIC
)Ru
ssia
n Fe
dera
tion
5 61
23
421
40 1
7169
9 14
946
9 39
21
217
745
(520
667,
165
2256
)1
585
864
Afr
Rwan
da29
859
378
227
5 77
711
399
47 6
40(2
4511
, 736
23)
844
963
Amr (
HIC
)Sa
int K
itts
and
Nev
isN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Sa
int L
ucia
332
2112
117
535
3(5
7, 5
08)
383
362
Amr (
LMIC
)Sa
int V
ince
nt a
nd th
e G
rena
dine
s4
06
118
9021
8(0
, 316
)40
341
5
Wpr
(LM
IC)
Sam
oaN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)Sa
n M
arin
oN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Sao
Tom
e an
d Pr
inci
pe20
34
692
173
479
(0, 7
65)
534
733
Emr (
HIC
)Sa
udi A
rabi
a2
612
1 55
22
877
30 8
5132
992
70 8
84(6
1575
, 807
67)
552
1 06
9
Afr
Sene
gal
24 0
9253
643
46
568
10 1
1941
749
(325
42, 5
1479
)59
472
1
Eur (
LMIC
)Se
rbia
130
584
10 1
1315
556
19 3
5045
734
(322
84, 5
7582
)99
554
1
Afr
Seyc
helle
s2
29
7842
134
(10,
193
)28
926
8
Afr
Sier
ra L
eone
32 0
4916
410
16
434
10 4
5549
203
(0, 9
1290
)1
610
1 74
5
Wpr
(HIC
)Si
ngap
ore
4962
2 14
93
911
2 52
58
695
(438
6, 1
1710
)32
423
8
Eur (
HIC
)Sl
ovak
ia21
513
92
838
16 1
857
209
26 5
86(2
0620
, 318
09)
953
532
Eur (
HIC
)Sl
oven
ia11
531
467
1 56
51
852
4 94
8(3
517,
618
9)47
621
7
Wpr
(LM
IC)
Solo
mon
Isla
nds
00
00
00
(0, 1
028)
00
Emr (
LMIC
)So
mal
ia56
878
238
347
3 00
25
622
66 0
86(3
022,
118
382)
1 31
094
9
Afr
Sout
h Af
rica
46 2
323
244
14 6
2746
663
92 6
0420
3 36
9(1
6088
2, 2
4338
8)75
686
3
Emr (
LMIC
)So
uth
Suda
n47
572
403
426
5 79
810
960
65 1
59(2
8646
, 990
84)
1 18
71
112
Eur (
HIC
)Sp
ain
7831
48
154
16 6
5512
742
37 9
43(6
952,
599
88)
160
75
Sear
Sri L
anka
1 20
81
644
2 74
135
253
19 8
4660
692
(442
72, 7
6426
)57
653
4
Emr (
LMIC
)Su
dan
111
077
1 86
71
174
20 7
1940
639
175
475
(961
65, 2
6640
3)93
41
024
Amr (
LMIC
)Su
rinam
e11
646
367
380
810
(0, 1
312)
307
318
Afr
Swaz
iland
2 07
183
3673
31
558
4 48
1(0
, 759
2)71
792
3
Eur (
HIC
)Sw
eden
12
4015
065
258
(0, 1
2682
)5
2
Eur (
HIC
)Sw
itzer
land
1517
13
442
3 95
02
243
9 82
1(2
578,
137
45)
242
115
Emr (
LMIC
)Sy
rian
Arab
Rep
ublic
4 39
442
52
703
33 7
2412
004
53 2
50(3
1883
, 726
63)
539
906
102
Num
ber o
f YLL
s YL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
LMIC
)Ta
jikis
tan
19 4
171
024
1 17
520
221
17 2
9759
134
(319
10, 8
8088
)1
505
2 30
6
Sear
Thai
land
3 85
33
690
37 8
2285
872
69 1
9120
0 42
8(1
6061
1, 2
3859
9)58
946
7
Eur (
LMIC
)Th
e fo
rmer
Yug
osla
v Re
publ
ic o
f M
aced
onia
4814
01
481
3 10
66
440
11 2
16(9
174,
133
31)
1 08
072
6
Sear
Tim
or-L
este
2 12
120
259
916
699
4 01
5(0
, 791
8)74
083
4
Afr
Togo
21 0
2117
711
35
493
8 82
635
630
(563
8, 5
8792
)1
042
1 23
2
Wpr
(LM
IC)
Tong
aN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
HIC
)Tr
inid
ad a
nd T
obag
o12
95
187
1 71
493
62
971
(0, 4
369)
438
375
Emr (
LMIC
)Tu
nisi
a1
750
754
853
21 4
8215
248
40 0
87(3
2733
, 475
28)
730
722
Eur (
LMIC
)Tu
rkey
9 14
26
887
24 9
3213
0 95
810
3 45
727
5 37
5(2
3271
9, 3
1889
4)72
371
8
Eur (
LMIC
)Tu
rkm
enis
tan
4 80
164
287
726
246
13 1
8045
746
(139
26, 6
5576
)1
741
2 30
2
Wpr
(LM
IC)
Tuva
luN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Uga
nda
121
133
2 38
82
071
17 6
7336
036
179
301
(137
192,
230
643)
1 01
21
153
Eur (
LMIC
)U
krai
ne2
342
1 26
711
243
349
292
126
850
490
993
(628
6, 7
0517
1)2
015
968
Emr (
HIC
)U
nite
d Ar
ab E
mira
tes
311
9647
71
867
1 20
73
959
(336
8, 4
580)
173
535
Eur (
HIC
)U
nite
d Ki
ngdo
m53
73
256
43 5
7942
355
29 2
9911
9 02
7(3
8097
, 167
686)
369
192
Afr
Uni
ted
Repu
blic
of
Tanz
ania
76 3
071
083
420
17 3
0523
795
118
910
(670
53, 1
6146
2)48
654
7
Amr (
HIC
)U
nite
d St
ates
of
Amer
ica
1 32
36
262
85 5
3915
8 08
255
912
307
117
(134
18, 6
6858
0)19
311
8
Amr (
HIC
)U
rugu
ay16
669
893
1 89
71
934
4 95
9(1
432,
685
3)28
217
8
Eur (
LMIC
)U
zbek
ista
n27
448
1 89
73
746
100
577
60 6
0819
4 27
6(9
2850
, 278
471)
1 33
71
712
Wpr
(LM
IC)
Vanu
atu
30
19
821
(0, 3
94)
1728
Amr (
LMIC
)Ve
nezu
ela,
Bol
ivar
ian
Repu
blic
of
4 94
31
126
9 25
630
067
17 6
8363
075
(451
19, 7
9002
)42
148
6
Wpr
(LM
IC)
Viet
Nam
20 9
147
587
35 9
3034
617
118
649
217
697
(157
770,
276
307)
476
465
Emr (
LMIC
)Ye
men
57 2
481
578
893
31 4
9629
396
120
610
(491
71, 1
9164
4)98
01
380
Afr
Zam
bia
42 9
6228
528
55
156
9 02
357
711
(120
02, 8
9782
)77
975
4
Afr
Zim
babw
e31
355
405
940
4 11
28
510
45 3
23(1
868,
730
01)
614
659
YLL :
yea
r of l
ife lo
st ; A
AP : A
mbi
ent a
ir po
llutio
n ; A
LRI :
Acut
e lo
wer
resp
irato
ry d
isea
se ; C
OPD
: Chr
onic
obs
truct
ive
pulm
onar
y di
seas
e ; IH
D : I
scha
emic
hea
rt di
seas
e. A
fr : A
frica
; Am
r : A
mer
ica ;
Em
r : E
aste
rn
Med
iterra
nean
; Eur
: Eur
ope ;
Sea
r : S
outh
-Eas
t Asi
a ; W
pr : W
este
rn P
acifi
c ; L
MIC
: Low
- and
mid
dle-
inco
me
coun
tries
; HIC
: Hig
h-in
com
e co
untri
es ; N
A : N
ot a
vaila
ble.
a Age
gro
up in
clud
es le
ss th
an 5
yea
rs o
ld.
b Age
gro
up in
clud
es 2
5 ye
ars
and
abov
e.
103
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Af
ghan
ista
n17
9 17
92
429
7 11
564
378
37 9
9729
1 09
7(2
2882
9, 3
6267
8)1
904
2 49
8
Eur (
LMIC
)Al
bani
a42
519
43
047
9 87
26
824
20 3
62(8
611,
271
65)
1 41
01
142
Afr
Alge
ria17
446
1 84
315
626
87 7
1773
469
196
101
(791
30, 2
7700
4)1
040
1 31
1
Eur (
HIC
)An
dorra
03
4415
543
245
(8, 3
69)
627
388
Afr
Ango
la20
2 91
81
917
735
28 2
2425
812
259
607
(391
70, 4
3307
0)2
308
2 06
7
Amr (
HIC
)An
tigua
and
Bar
buda
41
1515
083
254
(0, 3
67)
597
640
Amr (
LMIC
)Ar
gent
ina
4 43
62
061
26 3
8069
550
32 2
3013
4 65
7(3
9258
, 185
786)
654
644
Eur (
LMIC
)Ar
men
ia46
562
18
093
20 2
067
124
36 5
08(1
714,
570
14)
2 46
72
255
Wpr
(HIC
)Au
stra
lia3
617
970
013
51
022
(16,
296
38)
96
Eur (
HIC
)Au
stria
2061
310
516
16 7
593
771
31 6
79(2
1683
, 395
95)
767
466
Eur (
LMIC
)Az
erba
ijan
6 82
958
35
914
38 3
3714
498
66 1
61(1
5454
, 966
50)
1 42
31
751
Amr (
HIC
)Ba
ham
as15
42
8741
920
686
8(3
, 132
2)47
653
9
Emr (
HIC
)Ba
hrai
n79
9645
11
641
692
2 95
8(2
655,
326
3)35
675
2
Sear
Bang
lade
sh19
2 68
891
010
90 0
8818
6 03
912
0 66
268
0 48
8(5
6266
8, 8
1862
1)86
81
192
Amr (
HIC
)Ba
rbad
os34
362
294
206
598
(0, 8
79)
443
349
Eur (
LMIC
)Be
laru
s23
299
413
507
89 6
3322
486
126
852
(291
4, 1
8545
3)2
876
2 27
0
Eur (
HIC
)Be
lgiu
m71
1 19
820
203
16 5
205
817
43 8
08(2
7226
, 567
71)
806
491
Amr (
LMIC
)Be
lize
3418
5621
114
045
8(7
3, 7
02)
273
474
Afr
Beni
n35
556
697
365
12 2
2516
147
64 9
90(1
9753
, 102
678)
1 29
81
706
Sear
Bhut
an1
053
391
231
1 41
663
13
723
(300
8, 4
544)
932
1 20
6
Amr (
LMIC
)Bo
livia
, Plu
rinat
iona
l St
ates
of
13 1
6367
21
061
18 6
0015
689
49 1
85(3
8356
, 595
65)
959
1 15
0
Eur (
LMIC
)Bo
snia
and
H
erze
govi
na12
31
106
11 9
2618
218
13 4
9344
866
(346
54, 5
5437
)2
354
1 58
6
Afr
Bots
wan
a1
651
3822
51
112
1 35
24
378
(23,
697
8)41
162
0
Amr (
LMIC
)Br
azil
9 81
95
920
44 2
2222
7 51
912
7 35
341
4 83
4(1
7974
8, 6
2515
1)41
647
1
Wpr
HIC
Brun
ei D
arus
sala
m0
01
103
13(0
, 734
)6
9
Eur (
LMIC
)Bu
lgar
ia1
045
2 13
621
942
48 8
4532
999
106
967
(866
78, 1
2665
5)3
011
1 84
8
104
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Burk
ina
Faso
80 5
751
060
734
17 9
1027
972
128
251
(613
63, 1
9842
7)1
560
2 04
2
Afr
Buru
ndi
68 3
4268
534
611
504
18 4
1499
290
(414
94, 1
5906
7)1
987
1 97
1
Afr
Cab
o Ve
rde
16 5
4864
94
375
19 8
7615
378
56 8
27(3
900,
884
70)
786
1 14
4
Wpr
(LM
IC)
Cam
bodi
a13
2 12
12
639
1 51
628
446
35 5
8020
0 30
2(1
6193
5, 2
4771
2)1
850
1 98
1
Afr
Cam
eroo
n45
178
5 76
414
337
2 34
522
669
(449
, 767
99)
131
86
Amr (
HIC
)C
anad
a23
991
2353
191
71
800
(111
8, 2
532)
729
1 22
3
Afr
Cen
tral A
frica
n Re
publ
ic24
156
759
238
4 80
45
096
35 0
52(1
6358
, 557
11)
1 54
01
563
Afr
Cha
d12
6 87
186
139
812
481
17 8
3315
8 44
5(8
3654
, 241
698)
2 49
02
163
Amr (
HIC
)C
hile
955
793
8 11
518
937
12 6
5341
452
(308
41, 5
0306
)48
344
8
Wpr
(LM
IC)
Chi
na35
3 52
781
3 07
53
739
353
2 96
5 89
25
370
805
13 2
42 6
51(1
1194
228,
15
4250
25)
1 88
81
755
Amr (
LMIC
)C
olom
bia
8 38
72
536
11 1
9755
842
20 0
0897
970
(683
69, 1
2045
1)42
451
1
Afr
Com
oros
1 56
720
2957
897
33
166
(545
, 449
5)85
61
183
Afr
Con
go18
264
586
148
6 49
16
722
32 2
11(1
4300
, 510
58)
1 50
31
722
Wpr
(LM
IC)
Coo
k Is
land
sN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)C
osta
Ric
a97
191
995
6 17
11
953
9 40
8(6
962,
113
15)
404
418
Eur (
HIC
)C
roat
ia20
550
11 0
7816
158
7 55
135
357
(245
23, 4
4731
)1
711
1 05
2
Amr (
LMIC
)C
uba
320
716
14 8
2426
794
12 2
7354
927
(501
2, 8
1450
)96
371
0
Eur (
HIC
)C
ypru
s0
301
047
2 10
537
93
562
(238
3, 4
474)
618
504
Eur (
HIC
)C
zech
Rep
ublic
143
1 02
220
530
41 3
5910
216
73 2
71(5
6758
, 880
46)
1 41
490
1
Afr
Côt
e d’
Ivoi
re70
780
1 24
485
127
131
37 7
6913
7 77
4(1
5084
, 221
544)
1 28
11
503
Sear
Dem
ocra
tic P
eopl
e’s
Repu
blic
of K
orea
10 5
8214
116
51 8
2258
629
99 5
7723
4 72
6(3
1916
, 389
541)
1 94
02
148
Afr
Dem
ocra
tic R
epub
lic
of th
e C
ongo
531
472
6 74
51
752
85 4
3210
5 10
773
0 50
7(3
3954
7, 1
1464
26)
2 08
61
993
Eur (
HIC
)D
enm
ark
1030
34
408
5 30
42
268
12 2
93(7
43, 1
9728
)44
226
6
Emr (
LMIC
)D
jibou
ti2
836
5667
943
1 37
85
280
(178
3, 8
628)
1 23
21
514
Amr (
LMIC
)D
omin
ica
52
2089
6618
2(1
0, 2
68)
512
517
Amr (
LMIC
)D
omin
ican
Rep
ublic
4 52
117
02
412
13 1
257
155
27 3
83(2
582,
393
79)
541
648
Amr (
LMIC
)Ec
uado
r4
405
366
1 98
311
724
7 56
726
045
(130
93, 3
3841
)33
840
4
Emr (
LMIC
)Eg
ypt
41 9
2724
566
44 1
3635
1 67
523
2 86
469
5 16
9(5
7914
2, 8
2094
9)1
607
2 33
5
105
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Amr (
LMIC
)El
Sal
vado
r2
332
513
1 22
612
092
3 55
819
720
(157
96, 2
3782
)68
981
9
Afr
Equa
toria
l Gui
nea
3 58
412
113
81
587
1 29
46
724
(353
, 116
63)
1 69
41
852
Afr
Eritr
ea19
103
326
301
5 93
18
991
34 6
53(1
3804
, 546
57)
1 41
62
082
Eur (
HIC
)Es
toni
a15
1264
22
655
507
3 83
1(6
7, 7
669)
620
432
Afr
Ethi
opia
319
258
8 37
16
104
41 9
8768
949
444
669
(144
873,
714
179)
966
982
Wpr
(LM
IC)
Fiji
10
040
647
(0, 6
924)
1013
Eur (
HIC
)Fi
nlan
d5
1346
42
679
513
3 67
3(2
2, 1
8053
)13
879
Eur (
HIC
)Fr
ance
237
1 25
676
241
47 5
1122
042
147
287
(515
58, 2
0982
1)47
630
5
Afr
Gab
on3
410
204
318
1 84
11
631
7 40
4(1
235,
122
41)
908
1 07
6
Afr
Gam
bia
5 83
312
412
11
800
2 79
210
671
(442
, 194
18)
1 19
31
557
Eur (
LMIC
)G
eorg
ia71
057
94
265
23 8
3013
060
42 4
44(2
6861
, 539
10)
2 15
51
667
Eur (
HIC
)G
erm
any
274
5 65
310
4 21
314
9 09
242
019
301
252
(146
398,
398
718)
763
411
Afr
Gha
na46
994
972
1 80
530
095
34 7
2711
4 59
3(7
3314
, 150
588)
905
1 24
2
Eur (
HIC
)G
reec
e54
567
15 7
0928
232
13 2
9657
858
(212
06, 7
8220
)1
064
627
Amr (
LMIC
)G
rena
da2
221
170
118
312
(0, 4
54)
592
778
Amr (
LMIC
)G
uate
mal
a19
811
620
2 41
212
350
5 83
541
028
(325
68, 4
9874
)54
667
4
Afr
Gui
nea
34 1
5552
141
711
509
15 8
1062
411
(522
4, 1
0036
0)1
071
1 27
2
Afr
Gui
nea-
Biss
au8
144
109
641
839
2 68
412
840
(636
, 217
66)
1 50
91
641
Amr (
LMIC
)G
uyan
a15
813
632
347
1 71
04
292
(1, 6
562)
1 13
01
375
Amr (
LMIC
)H
aiti
28 0
9217
41
147
10 9
2919
645
59 9
87(5
457,
926
22)
1 17
91
469
Amr (
LMIC
)H
ondu
ras
4 89
279
41
452
12 6
716
801
26 6
10(2
1079
, 323
52)
688
1 02
8
Eur (
LMIC
)H
unga
ry18
11
959
34 4
9049
458
17 5
3010
3 61
8(7
8527
, 126
682)
2 18
91
479
Eur (
HIC
)Ic
elan
d0
345
127
3220
7(1
, 623
)12
793
Sear
Indi
a1
767
111
1 49
2 94
060
6 82
55
106
390
2 81
5 82
911
789
093
(994
6795
, 138
9327
0)1
799
2 27
2
Sear
Indo
nesi
a13
1 81
713
994
98 6
5930
8 72
148
9 62
71
042
818
(553
692,
138
1328
)83
41
116
Emr (
LMIC
)Ira
n (Is
lam
ic
Repu
blic
of)
28 2
175
134
24 7
3526
4 93
910
0 96
042
3 98
4(3
6633
7, 4
8256
5)1
104
1 37
2
Emr (
LMIC
)Ira
q49
417
2 31
314
251
89 1
8749
637
204
804
(134
138,
280
733)
1 22
92
289
Eur (
HIC
)Ire
land
2010
01
842
5 09
097
28
024
(625
, 125
50)
345
273
Eur (
HIC
)Is
rael
7133
76
368
5 82
92
409
15 0
14(1
1058
, 186
04)
395
363
Eur (
HIC
)Ita
ly67
4 30
796
071
85 1
8738
245
223
878
(148
539,
284
331)
772
402
106
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Amr (
LMIC
)Ja
mai
ca43
394
1 71
42
924
3 57
68
742
(601
5, 1
1014
)63
666
4
Wpr
(HIC
)Ja
pan
856
2 84
113
3 41
513
6 21
710
8 40
438
1 73
4(1
5066
5, 5
2111
1)61
731
8
Emr (
LMIC
)Jo
rdan
3 22
656
63
677
13 5
736
838
27 8
79(2
3823
, 320
44)
776
1 37
0
Eur (
LMIC
)Ka
zakh
stan
4 57
51
829
15 7
5599
132
39 3
5316
0 64
4(2
1034
, 248
898)
1 97
92
410
Afr
Keny
a10
2 50
943
91
375
23 5
3428
494
156
350
(525
73, 2
1819
0)73
583
0
Wpr
(LM
IC)
Kirib
ati
00
00
00
(0, 5
54)
01
Emr (
HIC
)Ku
wai
t68
750
636
8 12
52
050
11 5
48(1
0319
, 128
34)
602
1 17
2
Eur (
LMIC
)Ky
rgyz
stan
2 53
741
21
659
19 3
729
767
33 7
48(1
3887
, 443
70)
1 21
01
881
Wpr
(LM
IC)
Lao
Peop
le’s
D
emoc
ratic
Rep
ublic
21 0
0946
92
484
9 45
58
287
41 7
04(1
4831
, 629
64)
1 29
71
727
Eur (
HIC
)La
tvia
2411
74
081
13 1
574
545
21 9
24(1
5868
, 269
07)
2 35
31
591
Emr (
LMIC
)Le
bano
n29
026
93
647
14 0
282
300
20 5
34(1
6998
, 239
14)
823
845
Afr
Leso
tho
4 04
319
212
51
115
2 12
87
603
(5, 1
4504
)75
01
032
Afr
Libe
ria2
958
6335
1 17
11
340
5 56
7(1
, 152
58)
264
344
Emr (
LMIC
)Li
bya
1 59
672
95
956
15 3
688
209
31 8
58(2
1655
, 426
41)
998
1 65
2
Eur (
HIC
)Li
thua
nia
2624
14
919
16 4
785
145
26 8
09(1
9974
, 325
84)
1 93
01
367
Eur (
HIC
)Lu
xem
bour
g0
3158
451
424
41
373
(884
, 176
0)51
736
7
Afr
Mad
agas
car
45 7
4160
13
280
20 6
3628
204
98 4
63(4
2789
, 135
764)
886
1 25
9
Afr
Mal
awi
33 0
7656
626
09
221
14 1
9357
317
(126
8, 9
3704
)73
299
9
Wpr
(LM
IC)
Mal
aysi
a1
495
2 08
712
441
61 7
8224
547
102
352
(581
83, 1
3127
2)71
291
4
Sear
Mal
dive
s36
1279
322
326
776
(200
, 103
8)44
968
0
Afr
Mal
i11
3 02
82
541
990
14 1
5119
811
150
522
(749
60, 2
3606
2)1
852
1 85
9
Eur (
HIC
)M
alta
015
470
984
255
1 72
2(8
79, 2
202)
833
514
Wpr
(LM
IC)
Mar
shal
l Isl
ands
NA
NA
NA
NA
NA
NA
NA
NA
NA
Afr
Mau
ritan
ia19
130
314
225
3 33
25
046
28 0
47(1
6326
, 434
64)
1 47
71
604
Afr
Mau
ritiu
s11
826
420
2 67
91
305
4 54
7(1
984,
586
3)73
068
7
Amr (
LMIC
)M
exic
o23
819
6 52
619
435
148
593
51 7
8525
0 15
9(1
8808
8, 3
0242
0)41
252
1
Wpr
(LM
IC)
Mic
rone
sia
(Fed
erat
ed S
tate
s of
)0
00
11
2(0
, 413
)4
6
Eur (
HIC
)M
onac
o0
122
4813
84(0
, 163
)46
329
2
Wpr
(LM
IC)
Mon
golia
2 17
430
01
392
11 1
677
346
22 3
79(1
5576
, 276
40)
1 60
82
382
107
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
LMIC
)M
onte
negr
o18
111
826
2 57
91
719
6 15
3(4
488,
763
5)1
997
1 48
4
Emr (
LMIC
)M
oroc
co19
049
1 24
221
211
54 6
8442
883
139
069
(102
817,
170
336)
856
991
Afr
Moz
ambi
que
71 1
3662
81
007
8 81
417
996
99 5
82(2
079,
163
848)
795
804
Sear
Mya
nmar
80 4
7613
594
42 7
2663
058
158
676
358
529
(297
718,
424
251)
1 39
81
820
Afr
Nam
ibia
1 66
212
215
91
147
1 64
24
733
(510
, 755
4)42
569
9
Wpr
(LM
IC)
Nau
ruN
AN
AN
AN
AN
AN
AN
AN
AN
A
Sear
Nep
al34
992
18 4
4013
357
51 2
9138
569
156
649
(119
368,
201
233)
1 17
41
566
Eur (
HIC
)N
ethe
rland
s66
1 12
824
895
15 9
386
523
48 5
50(2
5883
, 653
43)
585
355
Wpr
(HIC
)N
ew Z
eala
nd2
234
161
3022
8(2
, 474
5)11
8
Amr (
LMIC
)N
icar
agua
3 85
039
41
014
11 2
205
918
22 3
96(3
551,
334
21)
773
1 10
5
Afr
Nig
er16
8 24
61
416
254
15 7
6227
053
212
731
(125
664,
325
508)
2 39
51
969
Afr
Nig
eria
1 15
4 31
610
471
4 29
517
5 45
122
8 04
11
572
574
(125
5275
, 19
2813
4)1
837
1 72
4
Wpr
(LM
IC)
Niu
eN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)N
orw
ay11
931
694
3 76
71
127
6 69
1(2
98, 1
2905
)26
617
6
Emr (
HIC
)O
man
420
8957
04
982
3 43
79
498
(650
0, 1
2470
)42
485
1
Emr (
LMIC
)Pa
kist
an70
8 38
187
437
58 8
4129
8 86
617
9 45
51
332
980
(108
7099
, 16
2762
4)1
462
1 66
5
Wpr
(LM
IC)
Pala
uN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Pa
nam
a63
548
554
3 59
21
615
6 44
4(8
93, 9
278)
343
388
Wpr
(LM
IC)
Papu
a N
ew G
uine
a8
227
169
518
3 62
33
107
15 6
43(0
, 374
28)
429
525
Amr (
LMIC
)Pa
ragu
ay2
140
206
2 23
39
532
6 97
321
084
(981
2, 2
7736
)65
186
6
Amr (
LMIC
)Pe
ru8
255
1 05
67
810
29 1
0718
591
64 8
19(5
0539
, 780
13)
430
521
Wpr
(LM
IC)
Philip
pine
s82
543
10 5
2446
822
302
322
191
986
634
196
(485
332,
766
829)
1 30
61
806
Eur (
HIC
)Po
land
677
6 22
910
1 28
716
6 14
386
516
360
851
(287
762,
429
651)
1 93
21
376
Eur (
HIC
)Po
rtuga
l29
201
6 40
27
993
6 73
421
359
(973
, 362
42)
427
253
Emr (
HIC
)Q
atar
7345
1 02
43
350
1 18
35
676
(505
0, 6
317)
377
736
Wpr
(HIC
)Re
publ
ic o
f Kor
ea42
22
984
73 3
3840
024
46 7
3616
3 50
4(1
2816
1, 1
9768
4)66
353
5
Eur (
LMIC
)Re
publ
ic o
f Mol
dova
764
357
4 40
022
849
9 67
638
046
(0, 6
1639
)1
941
1 77
3
Eur (
LMIC
)Ro
man
ia4
360
2 40
646
943
90 8
1656
042
200
568
(149
781,
244
879)
2 07
31
437
Eur (
HIC
)Ru
ssia
n Fe
dera
tion
6 50
511
682
224
659
1 24
0 51
649
2 82
41
976
187
(855
234,
269
9613
)2
973
2 40
3
108
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Rwan
da37
090
465
395
8 84
414
188
60 9
82(3
1633
, 936
98)
1 17
91
503
Amr (
HIC
)Sa
int K
itts
and
Nev
isN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Sa
int L
ucia
516
5721
322
555
2(9
0, 8
00)
621
639
Amr (
LMIC
)Sa
int V
ince
nt a
nd th
e G
rena
dine
s5
115
156
8726
4(0
, 383
)47
854
0
Wpr
(LM
IC)
Sam
oaN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)Sa
n M
arin
oN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Sao
Tom
e an
d Pr
inci
pe24
89
1877
144
496
(0, 8
12)
558
802
Emr (
HIC
)Sa
udi A
rabi
a2
711
3 02
57
813
75 0
6747
197
135
813
(119
012,
153
380)
815
1 64
9
Afr
Sene
gal
31 6
191
030
711
7 85
710
644
51 8
61(4
0207
, 642
67)
768
960
Eur (
LMIC
)Se
rbia
235
1 12
627
692
32 3
4419
506
80 9
03(5
5695
, 102
887)
1 84
41
235
Afr
Seyc
helle
s5
443
188
8432
4(2
4, 4
75)
672
742
Afr
Sier
ra L
eone
35 6
1326
118
36
829
10 0
4652
933
(0, 9
8733
)1
772
1 81
9
Wpr
(HIC
)Si
ngap
ore
8221
84
371
9 43
33
132
17 2
36(8
807,
231
10)
659
521
Eur (
HIC
)Sl
ovak
ia19
729
27
941
26 6
139
297
44 3
39(3
4039
, 533
29)
1 68
91
302
Eur (
HIC
)Sl
oven
ia0
109
3 68
13
568
2 03
49
391
(657
3, 1
1794
)91
856
9
Wpr
(LM
IC)
Solo
mon
Isla
nds
00
00
00
(0, 1
994)
00
Emr (
LMIC
)So
mal
ia66
774
163
382
5 35
17
621
80 2
89(3
850,
142
755)
1 60
91
235
Afr
Sout
h Af
rica
59 1
106
942
30 3
1074
187
80 8
5325
1 40
1(1
9807
5, 3
0217
0)96
91
520
Emr (
LMIC
)So
uth
Suda
n61
323
710
557
8 95
312
982
84 5
25(3
7287
, 128
451)
1 53
91
467
Eur (
HIC
)Sp
ain
159
1 37
734
615
40 0
7013
879
90 1
00(1
6480
, 150
243)
392
245
Sear
Sri L
anka
1 77
33
328
7 29
381
936
33 1
1612
7 44
6(9
3595
, 159
445)
1 28
81
312
Emr (
LMIC
)Su
dan
150
132
3 25
62
395
31 5
5647
697
235
036
(128
740,
357
480)
1 24
21
359
Amr (
LMIC
)Su
rinam
e14
83
164
582
471
1 36
7(0
, 226
4)51
658
5
Afr
Swaz
iland
2 64
774
6854
470
54
039
(0, 7
019)
665
799
Eur (
HIC
)Sw
eden
01
4126
860
371
(0, 1
6816
)8
4
Eur (
HIC
)Sw
itzer
land
1824
25
834
8 09
02
023
16 2
07(4
634,
224
82)
409
246
Emr (
LMIC
)Sy
rian
Arab
Rep
ublic
6 13
990
311
866
62 0
9224
701
105
700
(617
40, 1
4568
1)1
046
1 89
5
Eur (
LMIC
)Ta
jikis
tan
26 0
7793
11
828
22 8
8813
012
64 7
37(3
4560
, 970
55)
1 61
82
378
Sear
Thai
land
5 58
913
514
76 7
8013
1 06
191
144
318
088
(250
916,
383
741)
960
841
109
Num
ber o
f YLL
sYL
Ls 1
00 0
00 p
er c
apita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
LMIC
)Th
e fo
rmer
Yug
osla
v Re
publ
ic o
f M
aced
onia
5329
46
622
6 85
47
268
21 0
90(1
7019
, 251
88)
2 04
61
611
Sear
Tim
or-L
este
2 45
227
537
995
788
4 79
9(0
, 963
0)85
71
016
Afr
Togo
22 9
0332
528
76
025
8 69
738
237
(597
2, 6
3385
)1
149
1 39
4
Wpr
(LM
IC)
Tong
aN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
HIC
)Tr
inid
ad a
nd T
obag
o12
934
546
3 83
41
348
5 89
1(0
, 867
8)88
883
6
Emr (
LMIC
)Tu
nisi
a2
307
1 23
313
282
39 8
4520
789
77 4
55(6
2330
, 924
90)
1 43
81
517
Eur (
LMIC
)Tu
rkey
12 6
6413
120
171
170
237
820
135
919
570
692
(471
676,
669
656)
1 55
21
780
Eur (
LMIC
)Tu
rkm
enis
tan
6 96
489
03
168
47 9
8315
442
74 4
47(2
2665
, 105
624)
2 92
54
029
Wpr
(LM
IC)
Tuva
luN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Uga
nda
163
918
2 49
02
123
31 3
1344
348
244
191
(187
570,
313
203)
1 38
11
677
Eur (
LMIC
)U
krai
ne3
392
4 14
461
870
447
498
120
322
637
226
(111
22, 9
3365
9)3
041
2 25
5
Emr (
HIC
)U
nite
d Ar
ab E
mira
tes
518
296
1 60
815
118
6 22
523
765
(205
91, 2
6974
)35
662
0
Eur (
HIC
)U
nite
d Ki
ngdo
m59
93
504
54 2
1796
879
26 7
6018
1 95
9(6
4682
, 247
933)
582
371
Afr
Uni
ted
Repu
blic
of
Tanz
ania
97 3
081
584
588
28 2
1131
919
159
610
(910
61, 2
1577
5)66
176
1
Amr (
HIC
)U
nite
d St
ates
of
Amer
ica
1 63
66
016
107
023
307
662
54 5
6047
6 89
8(2
1813
, 992
433)
306
222
Amr (
HIC
)U
rugu
ay15
819
33
303
4 57
71
910
10 1
40(2
771,
144
46)
619
509
Eur (
LMIC
)U
zbek
ista
n38
033
2 59
410
850
149
210
65 0
3826
5 72
5(1
2791
2, 3
7950
4)1
889
2 76
4
Wpr
(LM
IC)
Vanu
atu
40
221
1845
(0, 8
31)
3659
Amr (
LMIC
)Ve
nezu
ela,
Bol
ivar
ian
Repu
blic
of
6 46
51
269
12 3
8964
706
22 4
7010
7 29
8(7
8529
, 132
226)
721
914
Wpr
(LM
IC)
Viet
Nam
32 8
489
988
111
953
77 1
5821
0 25
744
2 20
4(3
1831
5, 5
5936
3)99
11
239
Emr (
LMIC
)Ye
men
71 2
371
800
2 49
658
212
37 3
2117
1 06
8(7
2537
, 266
686)
1 36
12
079
Afr
Zam
bia
47 5
1413
339
89
726
13 4
6771
237
(163
39, 1
0915
3)96
51
141
Afr
Zim
babw
e32
269
581
1 60
94
709
7 28
346
452
(191
0, 7
5197
)64
672
5
YLL :
yea
r of l
ife lo
st ;
AAP
: Am
bien
t air
pollu
tion ;
ALR
I : Ac
ute
low
er re
spira
tory
dis
ease
; C
OPD
: C
hron
ic o
bstru
ctiv
e pu
lmon
ary
dise
ase ;
IHD
: Is
chae
mic
hea
rt di
seas
e. A
fr : A
frica
; Am
r : A
mer
ica ;
Em
r : E
aste
rn M
edite
rrane
an ; E
ur : E
urop
e ; S
ear :
Sou
th-E
ast A
sia ;
Wpr
: Wes
tern
Pac
ific ;
LM
IC : L
ow- a
nd m
iddl
e-in
com
e co
untri
es ; H
IC : H
igh-
inco
me
coun
tries
; NA
: Not
ava
ilabl
e.a A
ge g
roup
incl
udes
less
than
5 y
ears
old
.b A
ge g
roup
incl
udes
25
year
s an
d ab
ove.
111
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Af
ghan
ista
n34
3 35
89
245
9 91
512
1 75
788
934
573
208
(450
258,
714
931)
1 92
82
501
Eur (
LMIC
)Al
bani
a74
560
44
593
16 7
2314
504
37 1
69(1
5554
, 497
30)
1 29
099
6
Afr
Alge
ria31
601
7 53
719
433
138
062
135
436
332
068
(133
038,
474
968)
887
1 09
7
Eur (
HIC
)An
dorra
07
5823
491
390
(11,
588
)49
227
1
Afr
Ango
la33
5 54
36
552
1 18
647
195
53 9
0044
4 37
5(6
8199
, 744
254)
1 95
91
833
Amr (
HIC
)An
tigua
and
Bar
buda
84
2225
416
345
1(0
, 657
)50
652
1
Amr (
LMIC
)Ar
gent
ina
7 91
05
339
37 5
4611
0 61
759
090
220
501
(646
76, 3
0496
1)52
446
3
Eur (
LMIC
)Ar
men
ia76
21
391
9 71
331
157
12 9
7856
001
(263
4, 8
7447
)1
880
1 49
3
Wpr
(HIC
)Au
stra
lia8
2230
41
050
318
1 70
2(2
7, 5
0732
)7
5
Eur (
HIC
)Au
stria
992
110
16 5
8127
161
8 73
054
681
(371
86, 6
8807
)64
735
4
Eur (
LMIC
)Az
erba
ijan
12 2
832
214
7 45
061
409
28 5
7911
1 93
5(2
5959
, 165
568)
1 19
61
375
Amr (
HIC
)Ba
ham
as27
415
126
636
393
1 44
4(5
, 222
3)38
840
4
Emr (
HIC
)Ba
hrai
n16
151
162
02
277
1 16
14
731
(415
2, 5
354)
355
708
Sear
Bang
lade
sh35
3 83
527
1 66
212
1 86
527
0 58
324
9 31
01
267
255
(101
9971
, 156
5478
)81
61
114
Amr (
HIC
)Ba
rbad
os60
1992
467
381
1 01
9(0
, 151
8)36
226
7
Eur (
LMIC
)Be
laru
s37
22
086
15 3
0014
5 78
143
834
207
374
(458
6, 3
0211
8)2
185
1 42
0
Eur (
HIC
)Be
lgiu
m15
52
955
28 0
4524
910
12 5
3968
602
(431
93, 8
8932
)61
935
3
Amr (
LMIC
)Be
lize
9339
7936
428
185
6(1
39, 1
322)
254
445
Afr
Beni
n65
079
2 76
557
423
087
31 8
4212
3 34
8(3
7519
, 196
565)
1 22
71
587
Sear
Bhut
an1
876
1 00
546
52
333
1 45
27
132
(567
9, 8
840)
959
1 27
4
Amr (
LMIC
)Bo
livia
, Plu
rinat
iona
l St
ates
of
24 3
332
468
2 25
332
124
29 1
0090
278
(699
20, 1
1014
1)88
21
033
Eur (
LMIC
)Bo
snia
and
H
erze
govi
na22
73
084
14 9
9529
394
28 5
9376
293
(590
30, 9
4725
)1
993
1 21
9
Afr
Bots
wan
a3
245
296
277
2 28
23
578
9 67
8(5
2, 1
5664
)45
468
0
Amr (
LMIC
)Br
azil
18 9
8216
749
74 9
2136
0 29
824
4 53
271
5 48
2(3
0880
4, 1
0873
05)
353
372
Wpr
HIC
Brun
ei D
arus
sala
m0
01
155
21(0
, 118
4)5
7
Eur (
LMIC
)Bu
lgar
ia1
844
5 24
526
629
80 1
3864
096
177
952
(144
728,
210
701)
2 43
61
329
Afr
Burk
ina
Faso
150
221
4 87
21
426
34 4
3352
956
243
908
(116
116,
380
407)
1 47
01
810
112
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Buru
ndi
125
544
3 40
470
417
749
31 0
1417
8 41
5(7
3231
, 290
149)
1 76
21
734
Afr
Cab
o Ve
rde
28 9
003
427
6 92
935
678
30 3
2710
5 26
1(7
373,
166
998)
710
976
Wpr
(LM
IC)
Cam
bodi
a23
8 43
411
197
2 40
250
839
69 8
3737
2 70
9(3
0010
0, 4
6259
0)1
721
1 86
9
Afr
Cam
eroo
n92
600
10 9
6821
070
6 17
838
908
(742
, 136
028)
112
68
Amr (
HIC
)C
anad
a47
026
943
808
1 63
13
220
(194
7, 4
671)
643
919
Afr
Cen
tral A
frica
n Re
publ
ic41
185
2 67
637
98
431
10 3
0762
979
(292
01, 1
0138
1)1
363
1 41
2
Afr
Cha
d22
0 46
63
830
698
22 1
1132
959
280
064
(147
516,
429
122)
2 20
31
953
Amr (
HIC
)C
hile
1 64
72
848
13 5
3026
963
23 2
2768
215
(500
86, 8
3865
)39
233
4
Wpr
(LM
IC)
Chi
na62
7 49
31
814
679
5 24
3 32
75
662
869
10 3
27 2
3523
675
602
(200
0745
2, 2
7642
228)
1 73
71
546
Amr (
LMIC
)C
olom
bia
15 1
966
759
18 5
6190
746
43 3
1817
4 58
0(1
2124
9, 2
1661
8)37
242
2
Afr
Com
oros
2 88
910
629
965
1 69
55
684
(944
, 814
6)77
51
029
Afr
Con
go29
494
2 15
421
810
900
13 5
2156
287
(248
57, 9
0402
)1
313
1 54
7
Wpr
(LM
IC)
Coo
k Is
land
sN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)C
osta
Ric
a22
564
11
502
9 30
63
908
15 5
82(1
1394
, 189
78)
335
334
Eur (
HIC
)C
roat
ia43
1 45
714
733
26 5
1614
899
57 6
47(4
0452
, 727
60)
1 34
572
6
Amr (
LMIC
)C
uba
699
2 32
323
481
42 8
4623
308
92 6
58(8
281,
138
762)
817
573
Eur (
HIC
)C
ypru
s13
991
336
2 81
979
25
059
(339
1, 6
374)
448
341
Eur (
HIC
)C
zech
Rep
ublic
291
3 12
829
383
65 9
0821
071
119
780
(928
27, 1
4428
2)1
136
639
Afr
Côt
e d’
Ivoi
re13
0 37
84
355
1 31
445
623
66 2
0424
7 87
4(2
6334
, 402
957)
1 17
51
424
Sear
Dem
ocra
tic P
eopl
e’s
Repu
blic
of K
orea
21 1
2328
316
88 7
8498
002
171
148
407
373
(555
92, 6
8401
5)1
645
1 55
9
Afr
Dem
ocra
tic R
epub
lic
of th
e C
ongo
957
459
26 2
092
700
146
091
213
509
1 34
5 96
7(6
2222
4, 2
1272
57)
1 91
51
859
Eur (
HIC
)D
enm
ark
2697
08
864
8 00
04
818
22 6
79(1
269,
375
51)
405
228
Emr (
LMIC
)D
jibou
ti4
922
357
136
1 60
42
408
9 42
7(3
114,
158
28)
1 10
51
348
Amr (
LMIC
)D
omin
ica
86
2814
813
532
5(1
8, 4
79)
453
437
Amr (
LMIC
)D
omin
ican
Rep
ublic
7 81
189
73
995
25 4
1715
179
53 3
00(5
078,
771
06)
525
619
Amr (
LMIC
)Ec
uado
r7
979
1 36
63
463
19 1
6114
295
46 2
64(2
2877
, 608
02)
300
344
Emr (
LMIC
)Eg
ypt
88 0
5775
577
61 5
8458
6 04
840
9 09
01
220
357
(100
5641
, 146
0546
)1
425
1 94
7
Amr (
LMIC
)El
Sal
vado
r4
305
1 85
42
299
22 6
038
025
39 0
87(3
0999
, 477
07)
644
718
113
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Equa
toria
l Gui
nea
5 65
335
918
42
297
2 29
610
788
(563
, 190
51)
1 39
41
589
Afr
Eritr
ea33
084
1 85
859
59
785
15 8
4061
162
(239
67, 9
8360
)1
250
1 74
5
Eur (
HIC
)Es
toni
a16
2983
94
235
1 00
36
122
(99,
121
39)
462
258
Afr
Ethi
opia
507
048
26 5
6412
909
65 8
9511
8 25
373
0 67
0(2
3606
9, 1
1892
41)
793
823
Wpr
(LM
IC)
Fiji
20
052
964
(0, 9
832)
79
Eur (
HIC
)Fi
nlan
d14
3569
23
969
1 06
45
774
(33,
287
07)
106
54
Eur (
HIC
)Fr
ance
507
4 71
610
4 98
169
974
49 5
7822
9 75
6(8
2127
, 325
137)
361
215
Afr
Gab
on5
313
735
503
3 18
73
484
13 2
22(2
248,
223
04)
819
966
Afr
Gam
bia
10 4
2452
216
33
219
5 08
819
416
(803
, 360
06)
1 07
41
449
Eur (
LMIC
)G
eorg
ia1
119
1 61
15
139
40 6
1826
204
74 6
92(4
7163
, 951
43)
1 80
51
184
Eur (
HIC
)G
erm
any
723
14 9
0415
8 01
323
2 05
593
848
499
543
(240
916,
663
000)
621
307
Afr
Gha
na88
159
5 67
42
324
53 3
3980
391
229
888
(146
097,
304
536)
900
1 22
1
Eur (
HIC
)G
reec
e11
61
725
19 1
6043
631
27 6
2992
262
(340
43, 1
2390
6)83
043
8
Amr (
LMIC
)G
rena
da4
629
261
208
508
(0, 7
44)
482
567
Amr (
LMIC
)G
uate
mal
a36
351
2 11
84
350
21 4
9311
989
76 3
02(6
0240
, 931
77)
496
590
Afr
Gui
nea
62 8
802
172
610
22 4
9031
085
119
237
(101
57, 1
9309
9)1
025
1 23
9
Afr
Gui
nea-
Biss
au14
488
426
117
3 51
15
057
23 5
99(1
221,
402
73)
1 37
61
526
Amr (
LMIC
)G
uyan
a31
850
120
3 86
43
072
7 42
3(2
, 114
55)
979
1 19
7
Amr (
LMIC
)H
aiti
52 2
9886
22
590
21 5
3940
891
118
179
(111
82, 1
8281
9)1
149
1 40
3
Amr (
LMIC
)H
ondu
ras
9 11
02
082
2 45
520
255
12 4
6246
363
(363
78, 5
6936
)59
985
8
Eur (
LMIC
)H
unga
ry35
45
035
53 5
6883
414
32 6
6517
5 03
5(1
3290
4, 2
1425
3)1
758
1 03
3
Eur (
HIC
)Ic
elan
d0
796
187
7336
3(2
, 115
3)11
276
Sear
Indi
a3
663
274
3 28
2 84
181
3 67
47
455
375
5 29
0 85
120
506
014
(170
4620
4, 2
4531
628)
1 62
31
986
Sear
Indo
nesi
a23
1 72
741
378
138
292
444
628
913
075
1 76
9 10
0(9
3395
9, 2
3580
64)
713
923
Emr (
LMIC
)Ira
n (Is
lam
ic
Repu
blic
of)
55 6
6023
441
38 2
5842
5 11
418
3 55
472
6 02
7(6
2254
8, 8
3416
1)95
31
239
Emr (
LMIC
)Ira
q92
673
8 82
819
894
133
068
81 4
3733
5 90
0(2
1681
0, 4
6825
8)1
019
1 73
2
Eur (
HIC
)Ire
land
5030
63
145
7 74
52
229
13 4
75(1
051,
214
35)
289
213
Eur (
HIC
)Is
rael
126
1 17
89
436
8 87
65
075
24 6
90(1
8152
, 308
09)
321
266
Eur (
HIC
)Ita
ly31
412
191
131
947
136
139
86 6
6336
7 25
3(2
4672
5, 4
6537
7)61
528
8
114
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Amr (
LMIC
)Ja
mai
ca76
628
32
143
4 88
86
927
15 0
07(1
0442
, 188
56)
543
539
Wpr
(HIC
)Ja
pan
1 86
87
141
180
791
199
245
197
984
587
030
(233
989,
798
287)
462
219
Emr (
LMIC
)Jo
rdan
5 78
11
722
4 35
321
028
13 2
1846
102
(392
83, 5
3271
)65
91
117
Eur (
LMIC
)Ka
zakh
stan
8 09
94
387
19 2
0515
9 61
878
448
269
757
(354
69, 4
1925
4)1
604
1 71
8
Afr
Keny
a18
4 20
03
767
2 30
836
802
49 3
5227
6 42
8(9
1167
, 388
740)
650
715
Wpr
(LM
IC)
Kirib
ati
00
00
00
(0, 8
39)
00
Emr (
HIC
)Ku
wai
t1
138
903
870
10 3
253
307
16 5
43(1
4565
, 187
08)
484
1 02
0
Eur (
LMIC
)Ky
rgyz
stan
4 42
31
095
2 16
331
545
17 1
5356
379
(231
19, 7
4453
)99
81
417
Wpr
(LM
IC)
Lao
Peop
le’s
D
emoc
ratic
Rep
ublic
36 2
071
925
3 62
217
135
15 7
5274
641
(266
80, 1
1355
4)1
153
1 49
4
Eur (
HIC
)La
tvia
4535
54
852
22 1
559
388
36 7
95(2
6937
, 449
74)
1 80
697
7
Emr (
LMIC
)Le
bano
n56
31
197
5 32
219
015
5 29
531
392
(257
07, 3
7039
)63
766
0
Afr
Leso
tho
7 48
859
817
02
287
5 18
915
731
(10,
302
74)
765
978
Afr
Libe
ria5
781
172
532
210
2 62
610
842
(2, 2
9905
)25
933
1
Emr (
LMIC
)Li
bya
2 87
32
782
6 91
625
355
15 7
1153
638
(362
73, 7
3079
)85
41
333
Eur (
HIC
)Li
thua
nia
8961
55
811
27 7
6311
126
45 4
04(3
4144
, 550
14)
1 50
587
9
Eur (
HIC
)Lu
xem
bour
g2
102
865
740
533
2 24
2(1
445,
289
4)42
127
6
Afr
Mad
agas
car
83 2
403
440
3 98
734
331
54 8
5517
9 85
3(7
7621
, 249
698)
807
1 14
1
Afr
Mal
awi
68 2
972
764
426
18 3
3129
624
119
442
(260
4, 1
9787
9)76
199
3
Wpr
(LM
IC)
Mal
aysi
a2
810
5 68
818
970
93 3
1445
039
165
821
(937
72, 2
1482
1)57
175
1
Sear
Mal
dive
s66
5496
521
457
1 19
4(3
00, 1
623)
346
537
Afr
Mal
i20
8 35
46
954
1 71
631
584
45 1
9229
3 80
0(1
4730
4, 4
6029
9)1
823
1 90
4
Eur (
HIC
)M
alta
149
641
1 53
247
72
700
(138
8, 3
448)
650
375
Wpr
(LM
IC)
Mar
shal
l Isl
ands
NA
NA
NA
NA
NA
NA
NA
NA
NA
Afr
Mau
ritan
ia30
906
1 87
633
96
466
9 95
349
540
(286
63, 7
7709
)1
312
1 48
4
Afr
Mau
ritiu
s18
815
958
33
892
2 15
26
974
(304
2, 9
097)
554
496
Amr (
LMIC
)M
exic
o44
235
16 4
3832
017
237
465
106
252
436
407
(325
031,
532
267)
358
432
Wpr
(LM
IC)
Mic
rone
sia
(Fed
erat
ed S
tate
s of
)1
00
21
3(0
, 664
)3
5
Eur (
HIC
)M
onac
o0
231
7328
135
(0, 2
59)
360
200
Wpr
(LM
IC)
Mon
golia
3 60
579
71
714
16 6
7012
598
35 3
84(2
4539
, 439
02)
1 26
01
791
115
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
LMIC
)M
onte
negr
o34
842
409
3 40
22
797
8 72
6(6
362,
108
66)
1 39
995
9
Emr (
LMIC
)M
oroc
co33
877
4 68
923
994
92 0
6990
543
245
171
(182
357,
300
280)
743
849
Afr
Moz
ambi
que
123
049
3 42
91
645
17 0
7833
718
178
918
(397
3, 2
9674
4)69
570
4
Sear
Mya
nmar
139
242
54 0
7176
965
145
603
302
550
718
432
(592
047,
858
889)
1 36
71
689
Afr
Nam
ibia
3 11
055
125
52
414
4 38
710
716
(121
2, 1
7457
)46
873
1
Wpr
(LM
IC)
Nau
ruN
AN
AN
AN
AN
AN
AN
AN
AN
A
Sear
Nep
al68
013
53 7
3927
934
88 4
7977
065
315
230
(234
391,
415
553)
1 14
61
533
Eur (
HIC
)N
ethe
rland
s13
63
703
42 1
6824
287
15 5
3585
829
(453
88, 1
1645
0)51
229
5
Wpr
(HIC
)N
ew Z
eala
nd4
771
238
7439
4(2
, 848
7)9
6
Amr (
LMIC
)N
icar
agua
6 67
31
080
1 69
018
339
10 9
6638
748
(612
4, 5
8700
)65
988
9
Afr
Nig
er28
8 09
17
262
317
31 1
2052
962
379
751
(223
946,
583
674)
2 15
31
945
Afr
Nig
eria
2 02
2 04
542
132
8 98
830
7 25
944
1 65
02
822
073
(225
0524
, 346
6303
)1
677
1 62
0
Wpr
(LM
IC)
Niu
eN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)N
orw
ay24
278
2 98
05
787
2 48
911
558
(497
, 227
33)
230
138
Emr (
HIC
)O
man
929
631
727
7 07
14
967
14 3
25(9
601,
194
12)
404
780
Emr (
LMIC
)Pa
kist
an1
246
970
203
138
71 7
0354
0 88
639
0 11
22
452
808
(199
2965
, 300
3450
)1
383
1 60
5
Wpr
(LM
IC)
Pala
uN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Pa
nam
a1
406
188
833
5 28
13
050
10 7
59(1
478,
157
38)
287
312
Wpr
(LM
IC)
Papu
a N
ew G
uine
a15
096
477
791
6 17
24
455
26 9
92(0
, 657
34)
377
439
Amr (
LMIC
)Pa
ragu
ay3
939
601
2 78
214
433
12 0
7033
825
(157
64, 4
4631
)53
068
8
Amr (
LMIC
)Pe
ru15
256
5 58
615
578
48 5
9535
789
120
804
(928
34, 1
4777
8)40
146
1
Wpr
(LM
IC)
Philip
pine
s15
2 42
931
229
66 0
5344
9 53
531
5 92
81
015
174
(771
359,
123
7902
)1
057
1 39
4
Eur (
HIC
)Po
land
1 26
414
825
145
980
249
921
160
893
572
883
(456
917,
683
994)
1 48
493
4
Eur (
HIC
)Po
rtuga
l65
480
8 05
212
354
12 9
7833
929
(160
9, 5
6590
)32
317
2
Emr (
HIC
)Q
atar
131
749
1 21
73
975
1 55
67
627
(660
5, 8
757)
378
759
Wpr
(HIC
)Re
publ
ic o
f Kor
ea84
77
319
100
350
59 4
8885
509
253
512
(199
622,
306
641)
511
364
Eur (
LMIC
)Re
publ
ic o
f Mol
dova
1 43
580
25
422
40 5
6918
817
67 0
46(0
, 108
018)
1 64
51
316
Eur (
LMIC
)Ro
man
ia8
053
6 09
358
336
143
543
104
935
320
959
(241
726,
390
976)
1 60
91
009
Eur (
HIC
)Ru
ssia
n Fe
dera
tion
12 5
7626
139
266
721
1 95
0 24
397
3 21
73
228
897
(140
0443
, 440
8243
)2
253
1 52
9
116
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Rwan
da67
395
3 58
263
314
892
25 6
8311
2 18
6(5
7267
, 175
976)
1 03
71
251
Amr (
HIC
)Sa
int K
itts
and
Nev
isN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Sa
int L
ucia
8618
7933
940
993
1(1
50, 1
358)
515
510
Amr (
LMIC
)Sa
int V
ince
nt a
nd th
e G
rena
dine
s11
521
276
181
495
(0, 7
23)
452
489
Wpr
(LM
IC)
Sam
oaN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)Sa
n M
arin
oN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Sao
Tom
e an
d Pr
inci
pe45
325
2417
131
999
3(0
, 162
3)55
678
1
Emr (
HIC
)Sa
udi A
rabi
a5
842
15 1
5210
749
107
302
81 5
3722
0 58
3(1
9029
0, 2
5357
1)74
81
438
Afr
Sene
gal
56 0
724
088
1 16
314
689
20 9
5396
965
(748
92, 1
2081
6)70
487
4
Eur (
LMIC
)Se
rbia
409
2 98
738
000
48 4
6339
455
129
313
(896
74, 1
6449
4)1
440
891
Afr
Seyc
helle
s8
1053
268
128
467
(37,
689
)49
451
1
Afr
Sier
ra L
eone
67 7
5694
828
813
372
20 5
4510
2 90
9(0
, 192
638)
1 70
31
804
Wpr
(HIC
)Si
ngap
ore
139
373
6 57
513
533
5 98
026
600
(135
53, 3
5797
)50
238
3
Eur (
HIC
)Sl
ovak
ia42
91
077
10 8
8643
118
16 9
0772
417
(556
87, 8
7238
)1
337
896
Eur (
HIC
)Sl
oven
ia17
441
5 19
65
232
4 10
514
990
(105
17, 1
8898
)72
740
2
Wpr
(LM
IC)
Solo
mon
Isla
nds
00
00
00
(0, 3
114)
00
Emr (
LMIC
)So
mal
ia12
3 95
11
234
735
8 52
113
293
147
735
(696
1, 2
6486
7)1
472
1 11
2
Afr
Sout
h Af
rica
105
724
26 6
8945
262
122
366
174
714
474
754
(371
260,
576
900)
899
1 16
5
Emr (
LMIC
)So
uth
Suda
n10
9 25
32
819
991
14 9
7024
060
152
094
(667
40, 2
3276
6)1
385
1 32
3
Eur (
HIC
)Sp
ain
272
2 57
843
157
58 2
3729
352
133
596
(249
74, 2
1925
7)28
616
2
Sear
Sri L
anka
3 13
29
962
10 0
8311
8 06
554
977
196
219
(141
976,
249
981)
961
931
Emr (
LMIC
)Su
dan
262
610
13 8
443
600
53 1
4888
820
422
022
(228
768,
650
658)
1 11
91
240
Amr (
LMIC
)Su
rinam
e16
735
211
962
871
2 24
6(1
, 374
5)42
546
2
Afr
Swaz
iland
4 73
731
310
81
301
2 27
78
735
(0, 1
5241
)70
990
1
Eur (
HIC
)Sw
eden
16
8342
413
765
0(0
, 305
58)
73
Eur (
HIC
)Sw
itzer
land
411
295
9 38
712
379
5 05
528
158
(784
1, 3
9714
)35
119
3
Emr (
LMIC
)Sy
rian
Arab
Rep
ublic
10 9
534
291
14 5
8896
682
37 3
4016
3 85
4(9
5388
, 228
829)
820
1 42
9
Eur (
LMIC
)Ta
jikis
tan
45 5
923
397
3 02
943
484
30 5
6812
6 06
9(6
7187
, 190
103)
1 59
02
390
Sear
Thai
land
9 61
029
447
115
769
219
454
167
934
542
214
(427
557,
656
102)
807
672
117
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
LMIC
)Th
e fo
rmer
Yug
osla
v Re
publ
ic o
f M
aced
onia
115
938
8 14
910
109
13 8
4033
150
(268
10, 3
9716
)1
602
1 18
0
Sear
Tim
or-L
este
4 58
310
579
71
927
1 51
28
924
(0, 1
7939
)81
094
2
Afr
Togo
44 1
021
506
405
11 6
6417
590
75 2
67(1
1746
, 126
011)
1 11
61
345
Wpr
(LM
IC)
Tong
aN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
HIC
)Tr
inid
ad a
nd T
obag
o26
999
739
5 59
72
346
9 04
9(0
, 134
24)
675
607
Emr (
LMIC
)Tu
nisi
a4
130
4 33
314
246
62 0
4636
526
121
282
(975
77, 1
4557
6)1
115
1 14
1
Eur (
LMIC
)Tu
rkey
23 0
3833
004
197
655
371
760
242
166
867
624
(720
077,
101
8543
)1
159
1 23
9
Eur (
LMIC
)Tu
rkm
enis
tan
11 7
992
224
4 06
874
505
28 8
0812
1 40
4(3
7051
, 173
952)
2 34
73
151
Wpr
(LM
IC)
Tuva
luN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Uga
nda
287
096
14 1
924
228
49 7
7280
711
435
999
(332
422,
563
596)
1 23
21
472
Eur (
LMIC
)U
krai
ne5
780
9 57
173
745
800
250
252
438
1 14
1 78
5(1
8112
, 166
5776
)2
519
1 53
2
Emr (
HIC
)U
nite
d Ar
ab E
mira
tes
866
2 53
92
102
17 2
507
722
30 4
79(2
5728
, 357
15)
340
624
Eur (
HIC
)U
nite
d Ki
ngdo
m1
247
11 6
1798
923
141
450
61 2
6031
4 49
7(1
0826
0, 4
3723
2)49
529
1
Afr
Uni
ted
Repu
blic
of
Tanz
ania
174
605
8 07
01
037
46 3
4056
141
286
193
(161
705,
391
100)
588
679
Amr (
HIC
)U
nite
d St
ates
of
Amer
ica
3 28
320
221
195
036
473
323
129
932
821
795
(372
19, 1
7525
38)
261
176
Amr (
HIC
)U
rugu
ay33
340
64
233
6 58
63
964
15 5
23(4
369,
219
75)
457
336
Eur (
LMIC
)U
zbek
ista
n65
552
9 03
914
709
251
377
126
711
467
389
(223
133,
674
971)
1 63
52
230
Wpr
(LM
IC)
Vanu
atu
81
330
2668
(0, 1
282)
2744
Amr (
LMIC
)Ve
nezu
ela,
Bol
ivar
ian
Repu
blic
of
11 9
184
212
21 8
4395
764
41 1
0817
4 84
5(1
2630
2, 2
1802
3)58
670
7
Wpr
(LM
IC)
Viet
Nam
54 5
7637
308
149
065
113
987
333
882
688
818
(493
511,
882
658)
763
845
Emr (
LMIC
)Ye
men
129
343
6 71
53
472
90 4
1567
112
297
057
(123
087,
471
950)
1 19
41
759
Afr
Zam
bia
90 8
212
071
694
15 1
1322
568
131
267
(287
30, 2
0440
3)88
896
4
Afr
Zim
babw
e63
863
2 81
52
578
9 05
115
960
94 2
67(3
907,
154
648)
647
725
DAL
Y : D
isab
ility-
adju
sted
life
year
s ; A
AP : A
mbi
ent a
ir po
llutio
n ; A
LRI :
Acut
e lo
wer
resp
irato
ry d
isea
se ; C
OPD
: Chr
onic
obs
truct
ive
pulm
onar
y di
seas
e ; IH
D : I
scha
emic
hea
rt di
seas
e. A
fr : A
frica
; Am
r : A
mer
ica ;
Em
r: Ea
ster
n M
edite
rrane
an ; E
ur : E
urop
e ; S
ear :
Sou
th-E
ast A
sia ;
Wpr
: Wes
tern
Pac
ific ;
LM
IC : L
ow- a
nd m
iddl
e-in
com
e co
untri
es ; H
IC : H
igh-
inco
me
coun
tries
; NA:
Not
ava
ilabl
e.a A
ge g
roup
incl
udes
less
than
5 y
ears
old
.b A
ge g
roup
incl
udes
25
year
s an
d ab
ove.
118
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
IaC
OPD
bLu
ng c
ance
rbIH
Db
Stro
keb
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Af
ghan
ista
n16
3 61
14
545
2 69
656
907
50 7
0627
8 46
5(2
1897
9, 3
4686
8)1
929
2 45
6
Eur (
LMIC
)Al
bani
a31
527
91
514
6 76
87
599
16 4
77(6
807,
220
37)
1 14
783
2
Afr
Alge
ria13
818
3 17
13
666
49 5
3161
381
131
566
(525
25, 1
8862
7)70
885
8
Eur (
HIC
)An
dorra
03
1377
4513
8(3
, 207
)34
315
4
Afr
Ango
la13
2 21
42
860
420
18 7
7727
952
182
222
(285
88, 3
0445
1)1
593
1 56
6
Amr (
HIC
)An
tigua
and
Bar
buda
32
710
377
192
(0, 2
79)
412
403
Amr (
LMIC
)Ar
gent
ina
3 36
82
259
10 9
1940
289
26 1
2482
959
(241
29, 1
1429
7)38
630
0
Eur (
LMIC
)Ar
men
ia29
053
81
579
10 8
455
753
19 0
05(7
93, 2
9275
)1
268
836
Wpr
(HIC
)Au
stra
lia4
1112
333
716
764
1(9
, 199
20)
63
Eur (
HIC
)Au
stria
6998
15
960
10 1
124
482
21 6
03(1
4672
, 272
69)
500
234
Eur (
LMIC
)Az
erba
ijan
5 43
81
011
1 48
922
749
13 8
3844
525
(997
9, 6
6106
)94
51
027
Amr (
HIC
)Ba
ham
as11
86
3821
217
755
1(2
, 852
)29
028
2
Emr (
HIC
)Ba
hrai
n74
169
164
598
413
1 41
8(1
236,
161
5)28
257
5
Sear
Bang
lade
sh15
8 98
212
4 06
130
763
81 0
1012
2 60
351
7 41
8(4
1193
8, 6
4578
9)67
391
0
Amr (
HIC
)Ba
rbad
os25
830
168
164
396
(0, 5
92)
270
184
Eur (
LMIC
)Be
laru
s12
562
81
657
55 7
4320
908
79 0
62(1
328,
113
898)
1 55
678
2
Eur (
HIC
)Be
lgiu
m68
1 20
67
617
7 86
96
098
22 8
59(1
4658
, 294
78)
405
210
Amr (
LMIC
)Be
lize
5510
2314
913
437
0(5
7, 5
62)
220
388
Afr
Beni
n29
398
1 13
720
110
737
15 6
4157
113
(175
30, 9
0675
)1
132
1 43
4
Sear
Bhut
an81
239
723
290
079
53
137
(250
4, 3
873)
911
1 26
0
Amr (
LMIC
)Bo
livia
, Plu
rinat
iona
l St
ates
of
11 0
441
272
1 17
513
393
13 3
0640
189
(309
90, 4
9214
)78
789
8
Eur (
LMIC
)Bo
snia
and
H
erze
govi
na96
1 39
32
949
11 0
2414
913
30 3
75(2
3611
, 376
99)
1 58
084
9
Afr
Bots
wan
a1
582
128
471
149
2 21
65
121
(28,
820
0)48
069
9
Amr (
LMIC
)Br
azil
8 61
27
641
30 3
1912
9 83
611
4 39
529
0 80
3(1
2563
2, 4
4460
0)28
328
0
Wpr
HIC
Brun
ei D
arus
sala
m0
01
52
8(0
, 440
)4
5
Eur (
LMIC
)Bu
lgar
ia78
12
248
4 52
730
936
30 8
0169
294
(566
79, 8
1887
)1
847
846
Afr
Burk
ina
Faso
69 4
352
293
682
16 3
0724
911
113
627
(542
19, 1
7720
4)1
357
1 58
2
119
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
IaC
OPD
bLu
ng c
ance
rbIH
Db
Stro
keb
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Buru
ndi
56 9
661
679
352
6 11
912
565
77 6
80(3
1354
, 127
378)
1 51
51
452
Afr
Cab
o Ve
rde
12 1
981
742
2 50
315
599
14 6
4446
687
(328
8, 7
4301
)61
480
7
Wpr
(LM
IC)
Cam
bodi
a10
6 01
04
751
860
22 0
5834
090
167
768
(135
168,
208
012)
1 54
91
683
Afr
Cam
eroo
n46
295
5 12
86
519
3 14
815
136
(275
, 554
44)
8648
Amr (
HIC
)C
anad
a22
699
1926
871
01
323
(794
, 192
3)52
164
9
Afr
Cen
tral A
frica
n Re
publ
ic16
947
1 24
813
13
569
5 17
627
070
(125
97, 4
3574
)1
155
1 21
0
Afr
Cha
d93
449
1 76
529
29
499
15 0
5912
0 06
4(6
3304
, 183
941)
1 89
01
698
Amr (
HIC
)C
hile
640
1 31
75
340
7 68
910
058
25 0
44(1
8119
, 311
54)
284
221
Wpr
(LM
IC)
Chi
na26
5 08
582
7 72
51
467
555
2 65
3 78
44
871
317
10 0
85 4
65(8
5506
89, 1
1763
242)
1 52
51
300
Amr (
LMIC
)C
olom
bia
6 38
33
132
7 24
734
217
22 5
6873
547
(507
91, 9
1728
)30
933
3
Afr
Com
oros
1 31
255
038
172
02
468
(394
, 355
1)67
886
3
Afr
Con
go11
178
914
614
355
6 76
423
271
(103
63, 3
7219
)1
086
1 31
6
Wpr
(LM
IC)
Coo
k Is
land
sN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)C
osta
Ric
a97
310
498
3 05
61
841
5 80
2(4
206,
713
5)25
023
8
Eur (
HIC
)C
roat
ia18
599
3 56
110
216
7 16
321
558
(154
45, 2
6983
)97
142
8
Amr (
LMIC
)C
uba
323
1 06
18
518
15 7
8410
543
36 2
29(3
171,
544
29)
642
421
Eur (
HIC
)C
ypru
s13
3928
169
537
91
406
(949
, 177
4)25
417
2
Eur (
HIC
)C
zech
Rep
ublic
130
1 34
28
638
24 2
1610
366
44 6
92(3
4810
, 538
13)
833
392
Afr
Côt
e d’
Ivoi
re59
397
1 56
844
418
265
28 3
3910
8 01
3(1
1168
, 175
802)
1 04
41
300
Sear
Dem
ocra
tic P
eopl
e’s
Repu
blic
of K
orea
10 4
3111
985
36 6
1338
787
70 7
2816
8 54
4(2
2900
, 284
130)
1 33
11
118
Afr
Dem
ocra
tic R
epub
lic
of th
e C
ongo
424
752
11 8
0087
160
000
107
876
605
299
(280
122,
956
296)
1 71
61
673
Eur (
HIC
)D
enm
ark
951
14
403
2 56
82
355
9 84
7(4
51, 1
6835
)34
918
2
Emr (
LMIC
)D
jibou
ti2
073
184
6964
61
024
3 99
5(1
306,
676
2)94
11
137
Amr (
LMIC
)D
omin
ica
32
758
6713
7(7
, 201
)37
934
4
Amr (
LMIC
)D
omin
ican
Rep
ublic
3 22
543
21
558
12 1
477
817
25 1
79(2
416,
362
84)
495
573
Amr (
LMIC
)Ec
uado
r3
487
642
1 46
47
291
6 55
919
444
(946
6, 2
5696
)25
227
7
Emr (
LMIC
)Eg
ypt
45 2
8133
741
17 1
6223
0 91
117
4 59
950
1 69
3(4
1172
8, 6
0373
6)1
183
1 51
9
Amr (
LMIC
)El
Sal
vado
r1
896
1 08
11
063
10 4
134
319
18 7
73(1
4805
, 230
50)
585
618
120
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
IaC
OPD
bLu
ng c
ance
rbIH
Db
Stro
keb
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Equa
toria
l Gui
nea
2 06
013
845
698
994
3 93
5(2
06, 6
985)
1 04
41
249
Afr
Eritr
ea13
873
956
290
3 78
26
828
25 7
29(9
977,
416
92)
1 05
21
409
Eur (
HIC
)Es
toni
a0
1019
21
557
462
2 22
1(2
8, 4
329)
314
125
Afr
Ethi
opia
186
856
8 50
46
760
22 9
0448
890
273
914
(887
17, 4
4427
5)59
362
5
Wpr
(LM
IC)
Fiji
10
013
317
(0, 2
792)
45
Eur (
HIC
)Fi
nlan
d8
1422
31
252
512
2 00
8(1
0, 1
0191
)73
30
Eur (
HIC
)Fr
ance
191
2 08
228
077
21 0
8024
400
75 8
30(2
7007
, 106
138)
233
121
Afr
Gab
on1
886
319
181
1 32
21
837
5 54
5(9
77, 9
312)
694
810
Afr
Gam
bia
4 55
121
240
1 39
82
287
8 48
8(3
55, 1
5697
)93
01
285
Eur (
LMIC
)G
eorg
ia40
373
084
316
583
13 0
2231
582
(198
37, 4
0182
)1
456
782
Eur (
HIC
)G
erm
any
314
6 63
952
661
80 0
5747
119
186
789
(891
54, 2
4808
6)45
619
6
Afr
Gha
na41
021
2 67
950
322
854
45 5
3111
2 58
9(7
1527
, 149
172)
874
1 16
1
Eur (
HIC
)G
reec
e50
836
3 27
315
109
13 9
2633
195
(119
41, 4
3983
)58
525
3
Amr (
LMIC
)G
rena
da2
28
9088
190
(0, 2
78)
360
376
Amr (
LMIC
)G
uate
mal
a16
336
1 04
81
919
8 99
05
912
34 2
05(2
6949
, 418
43)
435
498
Afr
Gui
nea
28 5
9794
718
610
860
15 2
1855
808
(483
9, 9
0054
)96
21
174
Afr
Gui
nea-
Biss
au6
321
181
521
652
2 36
510
570
(563
, 179
70)
1 22
41
377
Amr (
LMIC
)G
uyan
a15
021
571
506
1 35
53
089
(1, 4
795)
816
1 01
6
Amr (
LMIC
)H
aiti
24 0
6439
81
433
10 4
9121
126
57 5
12(5
526,
887
94)
1 10
61
324
Amr (
LMIC
)H
ondu
ras
4 15
192
499
37
456
5 55
919
083
(148
79, 2
3560
)49
367
0
Eur (
LMIC
)H
unga
ry15
62
235
18 8
1633
555
14 7
2069
483
(529
92, 8
4973
)1
330
660
Eur (
HIC
)Ic
elan
d0
351
5736
147
(1, 4
99)
9154
Sear
Indi
a1
875
402
1 38
5 38
620
0 79
12
324
770
2 44
1 64
28
227
991
(679
1629
, 991
6369
)1
352
1 60
3
Sear
Indo
nesi
a98
944
15 7
2538
802
132
955
419
319
705
745
(369
868,
942
950)
574
722
Emr (
LMIC
)Ira
n
(Isla
mic
Rep
ublic
of)
26 7
9410
461
13 2
5715
8 46
480
783
289
758
(247
234,
334
417)
768
1 06
7
Emr (
LMIC
)Ira
q42
735
3 90
75
576
43 2
7931
377
126
874
(808
50, 1
7947
1)77
91
196
Eur (
HIC
)Ire
land
2514
41
282
2 57
01
140
5 16
2(3
60, 8
373)
220
148
Eur (
HIC
)Is
rael
3852
33
008
2 82
52
320
8 71
4(6
403,
109
16)
224
160
Eur (
HIC
)Ita
ly19
45
208
34 7
3048
418
44 6
8013
3 23
1(9
1124
, 167
870)
434
171
121
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
IaC
OPD
bLu
ng c
ance
rbIH
Db
Stro
keb
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Amr (
LMIC
)Ja
mai
ca30
910
341
91
927
3 28
96
047
(427
3, 7
536)
436
401
Wpr
(HIC
)Ja
pan
900
2 52
245
592
59 9
8379
696
188
692
(741
86, 2
5446
5)28
911
7
Emr (
LMIC
)Jo
rdan
2 52
763
565
57
338
6 26
217
416
(148
69, 2
0090
)51
283
0
Eur (
LMIC
)Ka
zakh
stan
3 49
71
748
3 32
260
090
38 8
5110
7 50
8(1
3978
, 166
466)
1 23
51
172
Afr
Keny
a81
300
1 83
392
412
858
20 7
2411
7 63
9(3
7893
, 166
207)
553
588
Wpr
(LM
IC)
Kirib
ati
00
00
00
(0, 2
75)
00
Emr (
HIC
)Ku
wai
t43
730
122
22
087
1 15
04
197
(365
4, 4
806)
280
718
Eur (
LMIC
)Ky
rgyz
stan
1 87
447
549
112
051
7 32
222
213
(896
1, 2
9373
)77
71
017
Wpr
(LM
IC)
Lao
Peop
le’s
D
emoc
ratic
Rep
ublic
15 1
7497
81
119
7 61
17
343
32 2
26(1
1699
, 490
33)
989
1 25
1
Eur (
HIC
)La
tvia
1813
373
88
902
4 72
714
519
(107
40, 1
7627
)1
313
528
Emr (
LMIC
)Le
bano
n25
051
01
640
4 83
92
812
10 0
50(8
138,
119
94)
414
424
Afr
Leso
tho
3 43
026
640
1 15
33
051
7 94
0(5
, 150
94)
761
913
Afr
Libe
ria2
809
7518
1 02
41
279
5 20
5(1
, 143
50)
250
313
Emr (
LMIC
)Li
bya
1 21
91
221
937
9 81
67
367
20 5
60(1
4039
, 280
32)
665
982
Eur (
HIC
)Li
thua
nia
5221
485
311
156
5 79
518
070
(137
16, 2
1749
)1
110
485
Eur (
HIC
)Lu
xem
bour
g2
4827
321
126
379
7(5
13, 1
034)
299
172
Afr
Mad
agas
car
37 3
321
736
700
13 4
3726
596
79 8
00(3
4195
, 111
029)
713
1 00
3
Afr
Mal
awi
34 9
761
297
158
8 95
215
385
60 7
68(1
252,
100
625)
772
955
Wpr
(LM
IC)
Mal
aysi
a1
244
2 16
06
419
31 1
7319
671
60 6
67(3
4118
, 788
86)
414
573
Sear
Mal
dive
s28
2816
196
121
390
(94,
535
)22
736
9
Afr
Mal
i95
151
2 68
671
617
343
25 2
9414
1 18
9(7
1709
, 219
164)
1 76
81
890
Eur (
HIC
)M
alta
118
166
536
204
924
(482
, 117
1)44
323
3
Wpr
(LM
IC)
Mar
shal
l Isl
ands
NA
NA
NA
NA
NA
NA
NA
NA
NA
Afr
Mau
ritan
ia11
735
851
108
3 07
64
875
20 6
45(1
2030
, 321
97)
1 09
91
289
Afr
Mau
ritiu
s67
6815
91
189
805
2 28
7(9
82, 3
001)
360
306
Amr (
LMIC
)M
exic
o19
473
7 80
412
314
87 1
7652
245
179
012
(132
184,
219
783)
292
337
Wpr
(LM
IC)
Mic
rone
sia
(Fed
erat
ed S
tate
s of
)0
00
00
1(0
, 239
)2
3
Eur (
HIC
)M
onac
o0
18
2414
48(0
, 90)
248
108
122
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
IaC
OPD
bLu
ng c
ance
rbIH
Db
Stro
keb
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Wpr
(LM
IC)
Mon
golia
1 41
133
230
45
429
5 21
712
692
(877
3, 1
5800
)89
61
251
Eur (
LMIC
)M
onte
negr
o14
4257
080
01
058
2 48
5(1
811,
310
7)78
747
9
Emr (
LMIC
)M
oroc
co14
612
1 96
02
641
36 7
6247
169
103
143
(775
55, 1
2555
9)61
769
2
Afr
Moz
ambi
que
51 6
821
885
613
8 08
315
641
77 9
04(1
852,
129
366)
590
599
Sear
Mya
nmar
58 5
8630
229
33 9
2882
007
142
251
347
000
(285
845,
415
517)
1 29
01
524
Afr
Nam
ibia
1 43
226
290
1 24
52
732
5 76
1(6
71, 9
291)
489
727
Wpr
(LM
IC)
Nau
ruN
AN
AN
AN
AN
AN
AN
AN
AN
A
Sear
Nep
al32
578
27 3
8514
513
36 7
0237
666
148
843
(109
737,
197
727)
1 05
21
403
Eur (
HIC
)N
ethe
rland
s61
1 82
317
011
7 86
28
069
34 8
26(1
8165
, 476
13)
412
226
Wpr
(HIC
)N
ew Z
eala
nd2
437
7441
157
(1, 3
598)
74
Amr (
LMIC
)N
icar
agua
2 76
950
966
87
037
4 97
715
961
(252
9, 2
4390
)53
568
7
Afr
Nig
er11
9 48
73
201
4915
138
25 7
8116
3 65
6(9
6959
, 250
625)
1 87
01
834
Afr
Nig
eria
865
909
18 7
434
587
129
845
212
374
1 23
1 45
8(9
8255
7, 1
5118
46)
1 49
01
474
Wpr
(LM
IC)
Niu
eN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)N
orw
ay9
141
1 26
61
944
1 24
34
603
(177
, 927
6)18
495
Emr (
HIC
)O
man
488
207
153
2 01
91
479
4 34
7(2
890,
596
4)33
365
0
Emr (
LMIC
)Pa
kist
an53
6 18
864
594
11 8
1323
8 54
020
6 18
81
057
323
(865
895,
128
6013
)1
226
1 43
8
Wpr
(LM
IC)
Pala
uN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Pa
nam
a74
989
272
1 64
21
391
4 14
3(5
43, 6
148)
222
231
Wpr
(LM
IC)
Papu
a N
ew G
uine
a6
811
191
268
2 48
41
293
11 0
48(0
, 269
94)
315
346
Amr (
LMIC
)Pa
ragu
ay1
734
245
530
4 80
74
999
12 3
16(5
690,
162
31)
392
492
Amr (
LMIC
)Pe
ru6
762
2 91
97
709
19 0
5816
694
53 1
42(4
0460
, 655
42)
352
387
Wpr
(LM
IC)
Philip
pine
s69
227
11 7
5718
781
145
146
121
997
366
909
(276
926,
449
216)
773
974
Eur (
HIC
)Po
land
496
5 65
143
761
82 5
0472
796
205
208
(163
918,
245
221)
1 03
054
4
Eur (
HIC
)Po
rtuga
l31
183
1 60
24
182
6 00
111
999
(520
, 193
90)
218
96
Emr (
HIC
)Q
atar
5515
218
854
221
61
152
(982
, 134
5)22
662
3
Wpr
(HIC
)Re
publ
ic o
f Kor
ea34
02
706
26 2
1618
267
35 8
5483
383
(661
74, 1
0056
4)33
420
8
Eur (
LMIC
)Re
publ
ic o
f Mol
dova
666
291
994
17 6
028
993
28 5
46(0
, 453
40)
1 35
093
7
Eur (
LMIC
)Ro
man
ia3
646
2 27
211
074
51 9
7448
246
117
212
(894
67, 1
4178
3)1
141
617
123
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
IaC
OPD
bLu
ng c
ance
rbIH
Db
Stro
keb
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
HIC
)Ru
ssia
n Fe
dera
tion
5 83
99
006
40 5
1070
4 44
047
5 18
91
234
984
(527
150,
168
0821
)1
608
878
Afr
Rwan
da30
079
1 80
223
15
904
11 4
4949
465
(250
80, 7
8080
)87
61
014
Amr (
HIC
)Sa
int K
itts
and
Nev
isN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Sa
int L
ucia
347
2112
317
936
5(5
8, 5
30)
396
375
Amr (
LMIC
)Sa
int V
ince
nt a
nd th
e G
rena
dine
s5
26
119
9222
4(0
, 327
)41
342
5
Wpr
(LM
IC)
Sam
oaN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)Sa
n M
arin
oN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Sao
Tom
e an
d Pr
inci
pe20
410
793
174
488
(0, 7
88)
544
749
Emr (
HIC
)Sa
udi A
rabi
a2
853
5 53
82
890
31 3
3233
455
76 0
67(6
5190
, 879
50)
592
1 12
9
Afr
Sene
gal
24 2
671
792
438
6 70
010
217
43 4
14(3
3590
, 539
83)
618
761
Eur (
LMIC
)Se
rbia
151
1 22
910
159
15 8
1819
624
46 9
80(3
3048
, 594
79)
1 02
355
9
Afr
Seyc
helle
s3
49
7943
138
(10,
202
)29
827
6
Afr
Sier
ra L
eone
32 0
9540
610
26
485
10 4
7749
564
(0, 9
2534
)1
622
1 76
5
Wpr
(HIC
)Si
ngap
ore
5310
52
167
3 99
72
662
8 98
4(4
528,
121
30)
335
246
Eur (
HIC
)Sl
ovak
ia22
346
12
860
16 3
357
413
27 2
93(2
1087
, 328
09)
978
549
Eur (
HIC
)Sl
oven
ia13
189
1 47
91
609
1 95
55
246
(370
7, 6
608)
505
234
Wpr
(LM
IC)
Solo
mon
Isla
nds
00
00
00
(0, 1
070)
00
Emr (
LMIC
)So
mal
ia57
026
680
350
3 08
25
647
66 7
83(3
053,
120
293)
1 32
497
2
Afr
Sout
h Af
rica
46 4
1811
699
14 7
3747
429
93 2
8121
3 56
4(1
6718
8, 2
5912
7)79
490
8
Emr (
LMIC
)So
uth
Suda
n47
751
1 27
142
95
899
11 0
1866
368
(290
30, 1
0171
5)1
209
1 14
7
Eur (
HIC
)Sp
ain
9573
78
211
17 3
2914
080
40 4
52(7
494,
641
93)
171
80
Sear
Sri L
anka
1 28
14
155
2 75
635
646
20 8
6864
706
(462
74, 8
3474
)61
456
9
Emr (
LMIC
)Su
dan
111
778
6 27
21
187
21 1
1840
873
181
229
(980
58, 2
7984
8)96
51
073
Amr (
LMIC
)Su
rinam
e15
1847
373
390
842
(0, 1
391)
319
331
Afr
Swaz
iland
2 08
015
937
745
1 56
54
586
(0, 7
901)
734
951
Eur (
HIC
)Sw
eden
13
4115
271
267
(0, 1
3190
)6
2
Eur (
HIC
)Sw
itzer
land
1962
43
478
4 10
22
621
10 8
44(2
860,
154
47)
267
130
Emr (
LMIC
)Sy
rian
Arab
Rep
ublic
4 60
41
834
2 70
734
104
12 3
2055
568
(327
06, 7
7627
)56
394
1
Eur (
LMIC
)Ta
jikis
tan
19 4
631
764
1 18
220
390
17 4
1260
211
(322
52, 9
0532
)1
532
2 34
9
124
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
IaC
OPD
bLu
ng c
ance
rbIH
Db
Stro
keb
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Sear
Thai
land
3 93
49
545
38 2
1087
104
72 6
9421
1 48
6(1
6814
0, 2
5434
1)62
249
2
Eur (
LMIC
)Th
e fo
rmer
Yug
osla
v Re
publ
ic o
f M
aced
onia
5539
51
489
3 17
36
495
11 6
06(9
434,
138
86)
1 11
775
4
Sear
Tim
or-L
este
2 12
649
259
924
710
4 06
8(0
, 810
3)75
084
9
Afr
Togo
21 1
0965
711
45
565
8 86
036
305
(571
1, 6
0632
)1
062
1 26
5
Wpr
(LM
IC)
Tong
aN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
HIC
)Tr
inid
ad a
nd T
obag
o13
430
188
1 73
597
13
057
(0, 4
540)
451
386
Emr (
LMIC
)Tu
nisi
a1
785
1 89
786
121
809
15 4
8341
833
(338
29, 5
0181
)76
175
3
Eur (
LMIC
)Tu
rkey
9 73
413
423
25 1
7813
2 38
610
4 84
028
5 56
1(2
3971
2, 3
3343
0)75
074
5
Eur (
LMIC
)Tu
rkm
enis
tan
4 81
71
001
882
26 3
7013
273
46 3
43(1
4031
, 669
68)
1 76
42
330
Wpr
(LM
IC)
Tuva
luN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Uga
nda
122
133
7 02
42
085
18 0
1736
198
185
457
(140
980,
240
534)
1 04
71
220
Eur (
LMIC
)U
krai
ne2
365
3 32
511
354
351
024
129
729
497
797
(637
5, 7
1894
1)2
043
984
Emr (
HIC
)U
nite
d Ar
ab E
mira
tes
329
599
480
1 92
61
267
4 60
1(3
773,
555
8)20
257
0
Eur (
HIC
)U
nite
d Ki
ngdo
m59
15
841
44 0
5343
328
31 6
6612
5 48
0(4
0268
, 178
286)
389
204
Afr
Uni
ted
Repu
blic
of
Tanz
ania
76 7
903
874
433
17 6
8624
012
122
794
(687
71, 1
6858
5)50
257
4
Amr (
HIC
)U
nite
d St
ates
of
Amer
ica
1 46
710
443
86 6
5516
1 52
465
810
325
901
(145
81, 7
1501
6)20
512
6
Amr (
HIC
)U
rugu
ay17
114
089
91
949
1 99
65
155
(147
8, 7
170)
293
186
Eur (
LMIC
)U
zbek
ista
n27
482
4 22
83
773
101
309
61 1
1519
7 90
6(9
3815
, 286
989)
1 36
21
742
Wpr
(LM
IC)
Vanu
atu
40
19
822
(0, 4
21)
1829
Amr (
LMIC
)Ve
nezu
ela,
Bol
ivar
ian
Repu
blic
of
5 19
02
044
9 31
930
503
18 1
2365
179
(463
43, 8
2205
)43
550
1
Wpr
(LM
IC)
Viet
Nam
21 2
9318
044
36 2
7835
674
121
354
232
643
(166
229,
300
933)
509
497
Emr (
LMIC
)Ye
men
57 6
593
237
913
31 8
3229
562
123
202
(497
69, 1
9827
0)1
001
1 41
7
Afr
Zam
bia
43 1
311
127
290
5 26
29
062
58 8
70(1
2202
, 925
38)
795
782
Afr
Zim
babw
e31
471
1 32
095
04
229
8 59
546
566
(193
5, 7
6231
)63
169
1
DAL
Y : D
isab
ility-
adju
sted
life
yea
rs ; A
AP : A
mbi
ent a
ir po
llutio
n ; A
LRI :
Acut
e lo
wer
resp
irato
ry d
isea
se ; C
OPD
: Chr
onic
obs
truct
ive
pulm
onar
y di
seas
e ; IH
D : I
scha
emic
hea
rt di
seas
e. A
fr : A
frica
; Am
r :
Amer
ica ;
Em
r: Ea
ster
n M
edite
rrane
an ; E
ur: E
urop
e ; S
ear :
Sou
th-E
ast A
sia ;
Wpr
: Wes
tern
Pac
ific ;
LM
IC : L
ow- a
nd m
iddl
e-in
com
e co
untri
es ; H
IC: H
igh-
inco
me
coun
tries
; NA
: Not
ava
ilabl
e.a A
ge g
roup
incl
udes
less
than
5 y
ears
old
.b A
ge g
roup
incl
udes
25
year
s an
d ab
ove.
125
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Af
ghan
ista
n17
9 74
74
700
7 21
964
849
38 2
2829
4 74
3(2
3128
5, 3
6806
4)1
928
2 54
3
Eur (
LMIC
)Al
bani
a43
032
53
078
9 95
56
905
20 6
92(8
739,
277
12)
1 43
31
161
Afr
Alge
ria17
783
4 36
715
767
88 5
3174
055
200
502
(802
65, 2
8638
5)1
064
1 33
9
Eur (
HIC
)An
dorra
04
4515
746
252
(8, 3
81)
644
399
Afr
Ango
la20
3 33
03
692
765
28 4
1925
948
262
154
(395
17, 4
3980
3)2
331
2 11
0
Amr (
HIC
)An
tigua
and
Bar
buda
52
1515
286
259
(0, 3
78)
610
655
Amr (
LMIC
)Ar
gent
ina
4 54
23
080
26 6
2770
328
32 9
6613
7 54
3(3
9993
, 190
704)
668
658
Eur (
LMIC
)Ar
men
ia47
285
28
134
20 3
137
225
36 9
96(1
732,
582
07)
2 50
02
286
Wpr
(HIC
)Au
stra
lia4
1218
171
315
11
060
(17,
308
51)
97
Eur (
HIC
)Au
stria
301
130
10 6
2117
049
4 24
833
078
(225
48, 4
1572
)80
048
8
Eur (
LMIC
)Az
erba
ijan
6 84
51
202
5 96
138
661
14 7
4167
410
(156
13, 9
9461
)1
450
1 78
1
Amr (
HIC
)Ba
ham
as15
69
8842
421
689
3(3
, 137
1)49
055
4
Emr (
HIC
)Ba
hrai
n87
342
456
1 67
974
93
313
(291
5, 3
739)
398
803
Sear
Bang
lade
sh19
4 85
314
7 60
191
102
189
574
126
707
749
837
(607
961,
919
646)
956
1 30
9
Amr (
HIC
)Ba
rbad
os35
1162
299
217
623
(0, 9
27)
462
364
Eur (
LMIC
)Be
laru
s24
71
458
13 6
4390
038
22 9
2612
8 31
2(2
936,
188
471)
2 90
92
297
Eur (
HIC
)Be
lgiu
m87
1 74
920
428
17 0
406
440
45 7
44(2
8453
, 594
54)
842
514
Amr (
LMIC
)Be
lize
3829
5721
514
748
5(7
6, 7
62)
289
496
Afr
Beni
n35
681
1 62
837
312
350
16 2
0266
234
(199
71, 1
0587
9)1
323
1 75
0
Sear
Bhut
an1
064
608
233
1 43
365
73
995
(317
5, 4
967)
1 00
01
292
Amr (
LMIC
)Bo
livia
, Plu
rinat
iona
l St
ates
of
13 2
891
197
1 07
818
732
15 7
9450
089
(389
42, 6
0930
)97
61
173
Eur (
LMIC
)Bo
snia
and
H
erze
govi
na13
11
691
12 0
4618
370
13 6
8045
918
(353
06, 5
7027
)2
409
1 62
6
Afr
Bots
wan
a1
663
168
230
1 13
31
363
4 55
7(2
3, 7
471)
428
645
Amr (
LMIC
)Br
azil
10 3
709
108
44 6
0223
0 46
213
0 13
742
4 67
9(1
8350
8, 6
4289
0)42
648
2
Wpr
HIC
Brun
ei D
arus
sala
m0
01
103
13(0
, 749
)6
9
Eur (
LMIC
)Bu
lgar
ia1
063
2 99
722
101
49 2
0233
295
108
658
(878
55, 1
2899
3)3
058
1 88
0
126
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Afr
Burk
ina
Faso
80 7
862
579
744
18 1
2628
045
130
281
(619
61, 2
0325
5)1
585
2 09
3
Afr
Buru
ndi
68 5
781
725
352
11 6
3118
449
100
735
(418
65, 1
6277
1)2
016
2 02
1
Afr
Cab
o Ve
rde
16 7
021
685
4 42
620
078
15 6
8258
574
(398
7, 9
2741
)81
01
184
Wpr
(LM
IC)
Cam
bodi
a13
2 42
46
446
1 54
228
781
35 7
4720
4 94
1(1
6495
9, 2
5460
0)1
893
2 05
9
Afr
Cam
eroo
n45
305
5 84
014
552
3 03
023
772
(484
, 807
16)
137
90
Amr (
HIC
)C
anad
a24
416
924
539
920
1 89
7(1
151,
274
9)76
91
282
Afr
Cen
tral A
frica
n Re
publ
ic24
238
1 42
824
84
862
5 13
235
909
(166
13, 5
7810
)1
578
1 62
4
Afr
Cha
d12
7 01
72
065
407
12 6
1217
900
160
001
(842
19, 2
4518
0)2
515
2 21
3
Amr (
HIC
)C
hile
1 00
71
531
8 19
019
274
13 1
7043
171
(319
45, 5
2726
)50
346
6
Wpr
(LM
IC)
Chi
na36
2 40
898
6 95
43
775
771
3 00
9 08
55
455
918
13 5
90 1
37(1
1453
348,
15
8950
66)
1 93
71
800
Amr (
LMIC
)C
olom
bia
8 81
33
626
11 3
1456
529
20 7
5010
1 03
3(7
0274
, 124
947)
437
526
Afr
Com
oros
1 57
751
2958
597
53
217
(553
, 459
4)86
91
205
Afr
Con
go18
315
1 24
115
76
545
6 75
733
016
(144
82, 5
3167
)1
540
1 78
4
Wpr
(LM
IC)
Coo
k Is
land
sN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)C
osta
Ric
a12
833
11
004
6 25
02
068
9 78
0(7
184,
118
48)
420
435
Eur (
HIC
)C
roat
ia25
857
11 1
7216
300
7 73
636
090
(249
65, 4
5828
)1
746
1 07
6
Amr (
LMIC
)C
uba
377
1 26
214
963
27 0
6212
765
56 4
28(5
158,
843
32)
990
731
Eur (
HIC
)C
ypru
s0
601
055
2 12
541
33
653
(243
8, 4
604)
633
517
Eur (
HIC
)C
zech
Rep
ublic
161
1 78
620
745
41 6
9110
706
75 0
89(5
7985
, 905
84)
1 45
092
6
Afr
Côt
e d’
Ivoi
re70
981
2 78
787
027
358
37 8
6413
9 86
1(1
5190
, 227
195)
1 30
01
535
Sear
Dem
ocra
tic P
eopl
e’s
Repu
blic
of K
orea
10 6
9216
331
52 1
7159
216
100
420
238
829
(323
56, 3
9993
7)1
973
2 18
2
Afr
Dem
ocra
tic R
epub
lic
of th
e C
ongo
532
707
14 4
091
828
86 0
9110
5 63
374
0 66
8(3
4250
1, 1
1711
49)
2 11
52
046
Eur (
HIC
)D
enm
ark
1745
94
460
5 43
22
463
12 8
32(7
81, 2
0723
)46
227
9
Emr (
LMIC
)D
jibou
ti2
850
173
6895
81
383
5 43
2(1
806,
906
0)1
268
1 56
5
Amr (
LMIC
)D
omin
ica
54
2190
6818
8(1
0, 2
78)
528
533
Amr (
LMIC
)D
omin
ican
Rep
ublic
4 58
746
52
437
13 2
707
362
28 1
21(2
633,
408
40)
555
666
Amr (
LMIC
)Ec
uado
r4
492
724
1 99
911
870
7 73
626
820
(133
93, 3
5088
)34
841
6
127
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Emr (
LMIC
)Eg
ypt
42 7
7641
837
44 4
2235
5 13
723
4 49
271
8 66
4(5
9380
4, 8
5661
9)1
661
2 40
9
Amr (
LMIC
)El
Sal
vado
r2
409
773
1 23
612
190
3 70
620
314
(161
84, 2
4659
)71
084
3
Afr
Equa
toria
l Gui
nea
3 59
322
113
91
599
1 30
26
854
(356
, 120
68)
1 72
71
900
Afr
Eritr
ea19
211
902
305
6 00
39
012
35 4
33(1
3988
, 566
67)
1 44
82
141
Eur (
HIC
)Es
toni
a15
1964
72
678
541
3 90
1(7
0, 7
830)
632
440
Afr
Ethi
opia
320
192
18 0
606
149
42 9
9169
363
456
756
(147
255,
745
078)
993
1 02
9
Wpr
(LM
IC)
Fiji
10
040
647
(0, 7
043)
1113
Eur (
HIC
)Fi
nlan
d6
2146
92
717
553
3 76
6(2
3, 1
8586
)14
181
Eur (
HIC
)Fr
ance
316
2 63
376
905
48 8
9425
178
153
926
(544
70, 2
1928
8)49
731
9
Afr
Gab
on3
427
417
322
1 86
51
647
7 67
8(1
255,
130
05)
942
1 12
6
Afr
Gam
bia
5 87
330
912
31
821
2 80
210
928
(448
, 203
09)
1 22
11
610
Eur (
LMIC
)G
eorg
ia71
688
14
296
24 0
3513
182
43 1
10(2
7173
, 549
89)
2 18
91
695
Eur (
HIC
)G
erm
any
409
8 26
510
5 35
315
1 99
846
729
312
754
(152
163,
415
287)
792
429
Afr
Gha
na47
138
2 99
51
821
30 4
8534
860
117
299
(744
56, 1
5543
7)92
71
277
Eur (
HIC
)G
reec
e66
889
15 8
8728
522
13 7
0359
067
(216
33, 8
0081
)1
086
641
Amr (
LMIC
)G
rena
da3
422
171
120
319
(0, 4
66)
604
793
Amr (
LMIC
)G
uate
mal
a20
016
1 07
02
431
12 5
036
077
42 0
97(3
3300
, 513
35)
560
696
Afr
Gui
nea
34 2
821
224
424
11 6
3015
867
63 4
29(5
271,
103
042)
1 08
91
301
Afr
Gui
nea-
Biss
au8
167
245
651
859
2 69
213
029
(648
, 223
02)
1 53
11
677
Amr (
LMIC
)G
uyan
a16
829
632
358
1 71
74
335
(1, 6
661)
1 14
11
389
Amr (
LMIC
)H
aiti
28 2
3446
31
157
11 0
4819
766
60 6
67(5
505,
940
26)
1 19
21
488
Amr (
LMIC
)H
ondu
ras
4 96
01
158
1 46
212
798
6 90
327
280
(214
99, 3
3372
)70
51
054
Eur (
LMIC
)H
unga
ry19
72
800
34 7
5249
859
17 9
4510
5 55
2(7
9789
, 129
379)
2 23
01
508
Eur (
HIC
)Ic
elan
d0
445
130
3721
6(2
, 655
)13
398
Sear
Indi
a1
787
871
1 89
7 45
661
2 88
35
130
605
2 84
9 20
912
278
024
(102
6216
6,
1460
6630
)1
874
2 36
3
Sear
Indo
nesi
a13
2 78
325
653
99 4
9031
1 67
349
3 75
61
063
355
(561
844,
141
5551
)85
11
136
Emr (
LMIC
)Ira
n (Is
lam
ic
Repu
blic
of)
28 8
6612
981
25 0
0126
6 65
010
2 77
143
6 26
9(3
7512
6, 4
9963
8)1
136
1 40
9
Emr (
LMIC
)Ira
q49
938
4 92
114
319
89 7
8850
060
209
026
(135
965,
288
780)
1 25
42
333
Eur (
HIC
)Ire
land
2516
11
863
5 17
61
090
8 31
4(6
48, 1
3074
)35
728
4
128
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
HIC
)Is
rael
8865
56
429
6 05
02
755
15 9
76(1
1742
, 198
91)
420
387
Eur (
HIC
)Ita
ly11
96
983
97 2
1787
721
41 9
8323
4 02
3(1
5531
5, 2
9820
2)80
742
2
Amr (
LMIC
)Ja
mai
ca45
718
01
724
2 96
13
638
8 96
1(6
146,
113
37)
652
681
Wpr
(HIC
)Ja
pan
968
4 62
013
5 19
913
9 26
211
8 28
839
8 33
7(1
5771
5, 5
4435
2)64
433
2
Emr (
LMIC
)Jo
rdan
3 25
51
087
3 69
713
691
6 95
628
686
(244
04, 3
3165
)79
81
405
Eur (
LMIC
)Ka
zakh
stan
4 60
32
639
15 8
8399
528
39 5
9716
2 24
9(2
1184
, 252
935)
1 99
92
433
Afr
Keny
a10
2 90
01
934
1 38
423
944
28 6
2815
8 79
0(5
3320
, 222
532)
747
850
Wpr
(LM
IC)
Kirib
ati
00
00
00
(0, 5
65)
01
Emr (
HIC
)Ku
wai
t70
160
264
88
238
2 15
712
346
(109
09, 1
3904
)64
31
227
Eur (
LMIC
)Ky
rgyz
stan
2 55
062
01
672
19 4
949
831
34 1
66(1
4021
, 450
95)
1 22
51
902
Wpr
(LM
IC)
Lao
Peop
le’s
D
emoc
ratic
Rep
ublic
21 0
3294
72
503
9 52
38
409
42 4
15(1
5025
, 645
45)
1 31
91
764
Eur (
HIC
)La
tvia
2722
24
113
13 2
534
661
22 2
76(1
6099
, 274
05)
2 39
11
618
Emr (
LMIC
)Le
bano
n31
368
73
682
14 1
772
483
21 3
42(1
7553
, 250
44)
856
878
Afr
Leso
tho
4 05
833
213
01
134
2 13
87
791
(5, 1
5185
)76
91
065
Afr
Libe
ria2
972
9735
1 18
61
347
5 63
7(1
, 155
53)
267
349
Emr (
LMIC
)Li
bya
1 65
41
561
5 97
915
540
8 34
533
079
(222
09, 4
5072
)1
036
1 70
3
Eur (
HIC
)Li
thua
nia
3740
14
958
16 6
075
331
27 3
35(2
0321
, 333
13)
1 96
81
396
Eur (
HIC
)Lu
xem
bour
g0
5359
253
027
01
445
(929
, 185
9)54
438
6
Afr
Mad
agas
car
45 9
081
704
3 28
720
894
28 2
6010
0 05
3(4
3326
, 138
723)
901
1 28
5
Afr
Mal
awi
33 3
211
467
268
9 37
914
239
58 6
74(1
292,
972
77)
750
1 03
1
Wpr
(LM
IC)
Mal
aysi
a1
566
3 52
912
551
62 1
4125
368
105
154
(593
44, 1
3595
9)73
193
7
Sear
Mal
dive
s38
2580
325
336
804
(205
, 108
8)46
570
3
Afr
Mal
i11
3 20
34
269
1 00
014
241
19 8
9915
2 61
1(7
5546
, 241
047)
1 87
81
912
Eur (
HIC
)M
alta
131
475
997
273
1 77
6(9
03, 2
280)
859
531
Wpr
(LM
IC)
Mar
shal
l Isl
ands
NA
NA
NA
NA
NA
NA
NA
NA
NA
Afr
Mau
ritan
ia19
171
1 02
623
03
390
5 07
828
895
(166
24, 4
5511
)1
521
1 68
0
Afr
Mau
ritiu
s12
191
424
2 70
31
347
4 68
6(2
032,
609
8)75
270
8
Amr (
LMIC
)M
exic
o24
762
8 63
419
703
150
289
54 0
0725
7 39
5(1
9280
3, 3
1252
2)42
453
5
Wpr
(LM
IC)
Mic
rone
sia
(Fed
erat
ed S
tate
s of
)0
00
11
2(0
, 425
)4
6
129
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
HIC
)M
onac
o0
123
4914
87(0
, 169
)47
730
1
Wpr
(LM
IC)
Mon
golia
2 19
446
51
410
11 2
417
382
22 6
92(1
5755
, 281
08)
1 63
02
413
Eur (
LMIC
)M
onte
negr
o20
421
838
2 60
21
739
6 24
1(4
548,
776
0)2
026
1 50
6
Emr (
LMIC
)M
oroc
co19
265
2 72
921
354
55 3
0743
374
142
028
(104
639,
174
822)
874
1 01
2
Afr
Moz
ambi
que
71 3
661
545
1 03
28
995
18 0
7710
1 01
4(2
118,
167
374)
806
824
Sear
Mya
nmar
80 6
5723
843
43 0
3763
596
160
299
371
432
(306
289,
443
553)
1 44
81
882
Afr
Nam
ibia
1 67
828
916
41
168
1 65
54
955
(527
, 816
6)44
573
3
Wpr
(LM
IC)
Nau
ruN
AN
AN
AN
AN
AN
AN
AN
AN
A
Sear
Nep
al35
435
26 3
5413
421
51 7
7839
398
166
387
(124
723,
217
702)
1 24
71
666
Eur (
HIC
)N
ethe
rland
s75
1 87
925
158
16 4
257
466
51 0
03(2
7229
, 689
19)
614
375
Wpr
(HIC
)N
ew Z
eala
nd2
334
164
3323
6(2
, 491
5)11
8
Amr (
LMIC
)N
icar
agua
3 90
357
11
022
11 3
025
989
22 7
87(3
599,
343
18)
787
1 12
4
Afr
Nig
er16
8 60
44
061
267
15 9
8227
181
216
095
(126
988,
333
049)
2 43
32
040
Afr
Nig
eria
1 15
6 13
623
389
4 40
017
7 41
422
9 27
61
590
615
(126
8077
, 195
4374
)1
858
1 76
1
Wpr
(LM
IC)
Niu
eN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)N
orw
ay15
137
1 71
43
843
1 24
66
955
(310
, 134
68)
276
183
Emr (
HIC
)O
man
441
424
574
5 05
13
488
9 97
8(6
705,
134
52)
445
881
Emr (
LMIC
)Pa
kist
an71
0 78
113
8 54
359
890
302
346
183
925
1 39
5 48
6(1
1271
21,
1716
701)
1 53
11
765
Wpr
(LM
IC)
Pala
uN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Pa
nam
a65
799
562
3 63
91
659
6 61
5(9
11, 9
593)
352
398
Wpr
(LM
IC)
Papu
a N
ew G
uine
a8
285
286
524
3 68
83
162
15 9
44(0
, 387
48)
437
538
Amr (
LMIC
)Pa
ragu
ay2
205
356
2 25
29
625
7 07
121
509
(996
1, 2
8424
)66
488
3
Amr (
LMIC
)Pe
ru8
494
2 66
77
869
29 5
3719
096
67 6
63(5
2367
, 822
70)
449
543
Wpr
(LM
IC)
Philip
pine
s83
202
19 4
7147
272
304
389
193
931
648
265
(493
810,
788
684)
1 33
51
847
Eur (
HIC
)Po
land
768
9 17
410
2 21
916
7 41
788
097
367
674
(292
598,
439
065)
1 96
81
404
Eur (
HIC
)Po
rtuga
l34
297
6 45
18
171
6 97
721
930
(100
4, 3
7264
)43
826
0
Emr (
HIC
)Q
atar
7659
71
028
3 43
31
340
6 47
5(5
621,
741
2)43
079
6
Wpr
(HIC
)Re
publ
ic o
f Kor
ea50
64
613
74 1
3441
221
49 6
5517
0 12
9(1
3326
1, 2
0629
2)69
055
7
Eur (
LMIC
)Re
publ
ic o
f Mol
dova
769
511
4 42
822
968
9 82
438
500
(0, 6
2769
)1
964
1 79
4
130
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
LMIC
)Ro
man
ia4
406
3 82
047
262
91 5
6856
690
203
747
(151
783,
249
488)
2 10
61
461
Eur (
HIC
)Ru
ssia
n Fe
dera
tion
6 73
817
133
226
211
1 24
5 80
349
8 02
81
993
913
(861
636,
272
9202
)2
999
2 42
5
Afr
Rwan
da37
317
1 78
040
28
988
14 2
3462
721
(321
79, 9
7908
)1
213
1 56
6
Amr (
HIC
)Sa
int K
itts
and
Nev
isN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
LMIC
)Sa
int L
ucia
5211
5821
622
956
6(9
2, 8
28)
637
655
Amr (
LMIC
)Sa
int V
ince
nt a
nd th
e G
rena
dine
s6
315
157
8927
1(0
, 397
)49
155
4
Wpr
(LM
IC)
Sam
oaN
AN
AN
AN
AN
AN
AN
AN
AN
A
Eur (
HIC
)Sa
n M
arin
oN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Sao
Tom
e an
d Pr
inci
pe24
915
1878
145
505
(0, 8
36)
568
821
Emr (
HIC
)Sa
udi A
rabi
a2
989
9 61
47
860
75 9
7148
082
144
516
(125
044,
165
703)
868
1 71
8
Afr
Sene
gal
31 8
062
296
726
7 98
810
735
53 5
51(4
1279
, 668
17)
793
1 00
7
Eur (
LMIC
)Se
rbia
258
1 75
827
841
32 6
4519
832
82 3
33(5
6535
, 105
013)
1 87
61
258
Afr
Seyc
helle
s5
644
189
8532
9(2
4, 4
87)
682
753
Afr
Sier
ra L
eone
35 6
6154
218
66
887
10 0
6953
345
(0, 1
0010
4)1
786
1 84
2
Wpr
(HIC
)Si
ngap
ore
8626
84
408
9 53
63
317
17 6
16(8
985,
236
66)
674
532
Eur (
HIC
)Sl
ovak
ia20
661
68
026
26 7
839
494
45 1
25(3
4565
, 544
31)
1 71
91
326
Eur (
HIC
)Sl
oven
ia3
252
3 71
73
623
2 15
09
744
(679
8, 1
2304
)95
259
2
Wpr
(LM
IC)
Solo
mon
Isla
nds
00
00
00
(0, 2
046)
00
Emr (
LMIC
)So
mal
ia66
926
555
385
5 44
07
646
80 9
52(3
884,
144
582)
1 62
21
258
Afr
Sout
h Af
rica
59 3
0614
990
30 5
2574
937
81 4
3326
1 19
0(2
0399
6, 3
1762
0)1
007
1 57
5
Emr (
LMIC
)So
uth
Suda
n61
502
1 54
956
19
072
13 0
4385
726
(377
23, 1
3105
0)1
561
1 50
3
Eur (
HIC
)Sp
ain
177
1 84
034
946
40 9
0915
272
93 1
44(1
7124
, 155
444)
405
254
Sear
Sri L
anka
1 85
15
807
7 32
682
420
34 1
0913
1 51
3(9
5676
, 166
551)
1 33
01
354
Emr (
LMIC
)Su
dan
150
832
7 57
22
413
32 0
3047
946
240
793
(130
714,
370
769)
1 27
21
410
Amr (
LMIC
)Su
rinam
e15
217
164
589
482
1 40
5(0
, 235
6)53
060
1
Afr
Swaz
iland
2 65
715
471
556
711
4 14
9(0
, 734
5)68
483
2
Eur (
HIC
)Sw
eden
13
4227
166
382
(0, 1
7361
)8
5
Eur (
HIC
)Sw
itzer
land
2267
15
909
8 27
72
435
17 3
14(4
982,
242
68)
437
264
Emr (
LMIC
)Sy
rian
Arab
Rep
ublic
6 34
92
457
11 8
8162
579
25 0
2010
8 28
6(6
2671
, 151
214)
1 07
21
935
131
Num
ber o
f DAL
YsD
ALYs
100
000
per
cap
ita
Reg
ion
Cou
ntry
ALR
I aC
OPD
bLu
ng c
ance
r bIH
D b
Stro
ke b
Tota
l U
ncer
tain
ty in
terv
alC
rude
rate
Age-
stan
dard
ized
rate
Eur (
LMIC
)Ta
jikis
tan
26 1
281
634
1 84
723
094
13 1
5565
858
(349
33, 9
9535
)1
646
2 42
4
Sear
Thai
land
5 67
619
903
77 5
5913
2 35
095
240
330
728
(259
399,
401
893)
998
874
Eur (
LMIC
)Th
e fo
rmer
Yug
osla
v Re
publ
ic o
f M
aced
onia
6054
36
661
6 93
67
345
21 5
44(1
7335
, 258
32)
2 09
11
647
Sear
Tim
or-L
este
2 45
756
538
1 00
380
24
857
(0, 9
831)
868
1 03
3
Afr
Togo
22 9
9384
929
16
099
8 73
038
962
(604
8, 6
5378
)1
171
1 43
2
Wpr
(LM
IC)
Tong
aN
AN
AN
AN
AN
AN
AN
AN
AN
A
Amr (
HIC
)Tr
inid
ad a
nd T
obag
o13
469
551
3 86
31
375
5 99
2(0
, 888
6)90
385
0
Emr (
LMIC
)Tu
nisi
a2
345
2 43
713
386
40 2
3721
044
79 4
48(6
3618
, 954
45)
1 47
51
555
Eur (
LMIC
)Tu
rkey
13 3
0419
581
172
478
239
374
137
326
582
063
(479
717,
685
447)
1 58
31
815
Eur (
LMIC
)Tu
rkm
enis
tan
6 98
21
223
3 18
648
135
15 5
3575
061
(227
82, 1
0701
2)2
949
4 06
3
Wpr
(LM
IC)
Tuva
luN
AN
AN
AN
AN
AN
AN
AN
AN
A
Afr
Uga
nda
164
963
7 16
92
143
31 7
5544
513
250
542
(191
462,
323
201)
1 41
71
751
Eur (
LMIC
)U
krai
ne3
416
6 24
662
391
449
226
122
709
643
988
(112
07, 9
4780
9)3
074
2 27
9
Emr (
HIC
)U
nite
d Ar
ab E
mira
tes
537
1 94
01
623
15 3
246
454
25 8
78(2
1954
, 301
59)
388
648
Eur (
HIC
)U
nite
d Ki
ngdo
m65
65
776
54 8
7098
122
29 5
9418
9 01
7(6
7307
, 259
080)
604
386
Afr
Uni
ted
Repu
blic
of
Tanz
ania
97 8
154
196
604
28 6
5432
129
163
399
(926
71, 2
2255
4)67
678
8
Amr (
HIC
)U
nite
d St
ates
of
Amer
ica
1 81
59
778
108
381
311
799
64 1
2249
5 89
4(2
2891
, 103
8384
)31
823
2
Amr (
HIC
)U
rugu
ay16
326
63
334
4 63
71
968
10 3
68(2
830,
148
24)
633
521
Eur (
LMIC
)U
zbek
ista
n38
070
4 81
210
936
150
068
65 5
9626
9 48
2(1
2902
3, 3
8799
5)1
916
2 80
1
Wpr
(LM
IC)
Vanu
atu
50
221
1846
(0, 8
62)
3760
Amr (
LMIC
)Ve
nezu
ela,
Bol
ivar
ian
Repu
blic
of
6 72
72
168
12 5
2465
261
22 9
8510
9 66
6(7
9967
, 135
829)
737
934
Wpr
(LM
IC)
Viet
Nam
33 2
8319
264
112
787
78 3
1321
2 52
845
6 17
5(3
2644
6, 5
8234
3)1
022
1 27
5
Emr (
LMIC
)Ye
men
71 6
843
478
2 56
058
582
37 5
5017
3 85
5(7
3256
, 273
680)
1 38
32
120
Afr
Zam
bia
47 6
9194
440
49
851
13 5
0672
396
(165
19, 1
1187
1)98
11
171
Afr
Zim
babw
e32
392
1 49
61
628
4 82
27
364
47 7
01(1
966,
783
93)
664
760
DAL
Y : D
isab
ility-
adju
sted
life
yea
rs ;
AAP
: Am
bien
t air
pollu
tion ;
ALR
I : Ac
ute
low
er re
spira
tory
dis
ease
; C
OPD
: C
hron
ic o
bstru
ctiv
e pu
lmon
ary
dise
ase ;
IHD
: Is
chae
mic
hea
rt di
seas
e. A
fr : A
frica
; Am
r :
Amer
ica ;
Em
r: Ea
ster
n M
edite
rrane
an ; E
ur: E
urop
e ; S
ear :
Sou
th-E
ast A
sia ;
Wpr
: Wes
tern
Pac
ific ;
LM
IC : L
ow- a
nd m
iddl
e-in
com
e co
untri
es ; H
IC : H
igh-
inco
me
coun
tries
; NA:
Not
ava
ilabl
e.a A
ge g
roup
incl
udes
less
than
5 y
ears
old
.b A
ge g
roup
incl
udes
25
year
s an
d ab
ove.