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Tackling the health burden of air pollution in South Asia

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Air pollution exposure is the second most important risk factor for ill health in South Asia, contributing to between 13% and 21.7% of all deaths and approximately 58 million disability adjusted life years (DALYs) through chronic and acute respiratory and cardiovascular illnesses.1 Of the top 30 cities in the world with the poorest air quality in 2016, 17 are in South Asia.2 The impact of air pollution transcends boundaries. The “brown cloud”—caused by pollution from carbon aerosols—is a phenomenon captured in satellite images of atmospheric haze over South Asia, as well as China. South Asia has one of the highest concentrations of black carbon emissions from cars and trucks, cooking stoves, and industrial facilities. In addition to their effect on health, black carbon particles are a short lived climate pollutant with a possible impact on precipitation patterns and on the Himalayan glacier system, which threatens water resources in the region.3 Collective regional action to monitor air quality and implement evidence based policies and interventions is needed. While countries have introduced promising initiatives in recent years, comprehensive health centred strategies are lacking. We present the status of air pollution and health effects in South Asia, and propose urgent, concerted action across sectors to achieve recommended air quality standards for the people of the region.
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thebmj
BMJ
2017;359:j5209 | doi: 10.1136/bmj.j5209 1
ANALYSIS
Tackling the health burden of air pollution
inSouth Asia
Bhargav Krishna and colleagues call for health driven, multisectoral policy making with defined
air quality targets to curb the impact of air pollution exposure in South Asia
KEY MESSAGES
•  
Air pollution is a major risk factor for
ill health in South Asia
•  
The interconnected nature of the
South Asian airshed necessitates
regional cooperation
•  
Tackling the sources of air pollution
requires systematic collection of air
quality data and a scientic approach
to air quality management
•  
Tackling the health burden of air pol-
lution will require coordinated, multi-
sectoral response, using a “health in
all policies” framework
A
ir pollution exposure is the sec-
ond most important risk factor for 
ill health in South Asia, contrib-
uting to between 13% and 21.7% 
of all deaths and approximately 
58 million disability adjusted life years 
(DALYs) through chronic and acute respir-
atory and cardiovascular illnesses.1Of the 
top 30 cities in the world with the poorest 
air quality in 2016, 17 are in South Asia.
2
The impact of air pollution transcends 
boundaries. The “brown cloud”—caused 
by pollution from carbon aerosols—is a 
phenomenon captured in satellite images of 
atmospheric haze over South Asia, as well 
as China. South Asia has one of the highest 
concentrations of black carbon emissions 
from cars and trucks, cooking stoves, and 
industrial facilities. In addition to their 
eect on health, black carbon particles are 
a short lived climate pollutant with a pos-
sible impact on precipitation patterns and 
on the Himalayan glacier system, which 
threatens water resources in the region.3
Collective regional action to monitor air 
quality and implement evidence based 
policies and interventions is needed. 
While countries have introduced promising 
initiatives in recent years, comprehensive 
health centred strategies are lacking. We 
present the status of air pollution and 
health eects in South Asia, and propose 
urgent, concerted action across sectors to 
achieve recommended air quality standards 
for the people of the region.
Air pollution exposure and trends
Household (indoor) and ambient (outdoor) 
air pollution both contribute to ill health. 
Rural and urban areas are both aected 
by poor air quality. However, the sources 
and pollutant proles vary. For instance, 
use of cooking fuels varies between urban 
and rural households, vehicular density is 
higher in cities, and dierent climate and 
geography across the region aect levels of 
air pollution.
Household air pollution
Approximately 74% of South Asian house-
holds use solid fuels such as wood, dung, 
or coal for cooking and heating.4-6 These 
are inecient fuels and their use in open 
fires or leaky stoves contributes to high 
levels of indoor smoke. Studies on indoor 
air pollution in South Asia show average 
daily PM
2.5
 concentrations range from 300 
μg/m3 to 3000 μg/m3, 5 7 8 which is much 
higher than is recommended by the World 
Health Organization (box 1).9 The propor-
tion of households relying on solid fuels 
has decreased over the past few decades 
(g 1); however this decrease has largely 
been oset by the increase in population.
10
The type of fuel and stove, kitchen area 
ventilation, quantity of fuel, age, gender, 
and time  spent near the cooking area 
influence exposure within and between 
households. Women and children tend 
to have higher exposure. Use of solid 
cooking fuels also contributes to ambient 
air pollution as  a result of  emissions 
carried outdoors. In densely populated 
communities of India,  household  air 
pollution has been estimated to contribute 
to nearly 27% of ambient air pollution.11
Since few studies report direct measures 
of household air pollution,7 trends are 
estimated (for purposes of comparative 
risk assessment) using spatiotemporal 
Gaussian process regression modelling that 
incorporates data on the proportion of solid 
fuel use in each country from nationally 
representative household surveys and 
select co-variates, including maternal 
education and proportion of population 
living in urban areas12
Ambient air pollution
The population in South Asia, with the 
exception of  Sri Lanka, is  among the 
most highly exposed to PM
2.5
 in the world 
(table1). Estimates from the Global Burden 
of Disease Study 2015 (GBD) indicate that 
the population weighted mean ambient 
PM2.5 concentration in South Asia* was 73 
μg/m
3
, compared with the global average of 
44 µg/m
3
. Nearly 99.9% of the South Asian 
population is living in areas with poorer air 
quality than the minimum standards rec-
ommended by WHO (box 1).
Population  weighted  PM2.5
concentrations have increased by 24% in 
South Asia between 1990 and 2015, with 
an increase in all countries except Pakistan 
and Sri Lanka (g 2). Ozone concentrations 
Box: Air quality standards recommended by WHO
PM (g/m)PM. (g/m)
Annual mean
concentration
 h
concentration
Annual mean
concentration
 h
concentration
Interim target-1 70 150 35 75
Interim target-2 50 100 25 50
Interim target-3 30 75 15 37.5
Air quality guideline* 20 50 10 25
1 PM10: Airborne particulate matter smaller than 10 μm (includes both coarse and ne particles that enter the respiratory tract).
2 PM2.5: Airborne particulate matter smaller than 2.5 μm.
3 Interim targets represent incremental steps in a progressive reduction of air pollution. Annual mean concentrations
provide an estimate of long term exposure for comparison.
4 *Lowest levels at which total, cardiopulmonary, and lung cancer mortality have been shown to increase in response to
long term exposure to PM2.5.
Fig1 | Trends in estimated percentage of
households using solid fuels in South Asian
countries
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ANALYSIS
have also increased across the region at a 
rate exceeding the global increase.
The sources of ambient air pollution 
vary across the region, and across rural 
and urban settings. Vehicular emissions, 
construction and road dust, residential 
biomass use, and industrial emissions are 
major contributors.13-16 The main sources 
of fuel used for power generation such as 
coal, natural gas, and oil can influence 
air quality. In Bangladesh, localised 
sources like brick kilns and  motorised 
transport contribute to the base pollution 
load throughout the year. Additionally,
in winter, transboundary transport  of 
particulate matter across the Indo-Gangetic 
Plain  airshed  contributes  to  higher
levels of PM2.5.14Similarly, in Pakistan, 
transboundary transport of dust  and 
pollutants from the Arabian Peninsula
15 16
and from India17is noted to cause episodic 
spikes in PM10and PM2.5 levels.
Impact on health
Exposure to ambient PM2.5 was the third 
ranking risk factor for mortality (1.4 mil-
lion deaths, 10.6% of total deaths) and 
DALYs (5.8% of total DALYs) in South Asia 
in 2015. Household air pollution ranks 
fourth (5.5% of DALYs and 1.2 million 
deaths, 9.6% of total deaths).
18
 No studies 
to date have evaluated the health impacts 
of co-exposure to household and ambient 
air pollution.
Over  the  past  25  years,  deaths
attributable to ambient  PM2.5 exposure 
have increased, with some acceleration 
since 2010 (g 3). Increase in PM
2.5
 levels, 
population growth, and ageing contribute 
to this  trend. Bangladesh, India,  and 
Pakistan have a higher burden because 
of larger populations,  high exposures, 
and  increasing  numbers  of  people
affected by chronic diseases. Common 
diseases aected by air pollution include 
ischaemic heart disease, stroke, acute 
lower respiratory infections,  chronic 
obstructive pulmonary disease, and lung 
cancer. Deaths attributable to household air 
pollution have remained high and relatively 
stable with only a modest increase from 1.1 
million to 1.2 million between 1990 and 
2015.
The  age  standardised  attributable
death rates  indicate a  small decrease, 
from 158  deaths per  100 000 in 1990 
to 133 per 100 000 in 2015, while there 
has been a large decrease in the rate of 
attributable DALYs (g 4) between 1990 
and 2010, possibly driven by a decrease 
in the incidence of acute lower respiratory 
infections. Deaths attributable to ozone 
exposure, while much lower than those 
attributable to PM2.5exposure, have 
increased sharply throughout South Asia 
from 48 000 in 1990 to 122 000 in 2015 
(a 154% increase) driven by increased 
exposure and increasing rates of chronic 
obstructive pulmonary disease in  the 
region, and in India especially.
Air  pollution  propagates  existing
environmental vulnerabilities.19 Children 
and  older  people  are  particularly
vulnerable.  Air  pollution  exposure
results in low birth weight,20 poor lung 
development in children,
21
 mortality from 
respiratory infections,
22
 and may also aect 
cognitive development.23 Older people are 
more likely to develop chronic respiratory 
and cardiac illnesses, and are more
susceptible to heart attacks and strokes 
from long  term exposure, and  during 
episodic high pollution events.24 Lower 
socioeconomic groups are more susceptible 
to insults from air pollution exposure for a 
variety of reasons including occupation and 
housing.2 5 19
Fragmented efforts to reduce air pollution
With the lack of high quality data on air pol-
lution and on health eects in South Asian 
countries, interventions are usually ad hoc, 
and their impact cannot be assessed. Public 
Table | GBD  estimates of exposure to ambient air pollution in South Asia
Country
Population
(millions)
Population weighted
mean annual
ambient PM. ()
Percentage increase in
population weighted mean
annual PM. ( to )
Percentage of population
in  living in areas
exceeding WHO IT-
Population weighted
seasonal mean
ozone ()
Percentage increase in
population weighted seasonal
mean ozone ( to )
India 1282.3 74 23 89.9 76 23
Bangladesh 148.9 89 39 99.9 74 25
Pakistan 202.8 65 −4 94.5 69 17
Nepal 31.3 75 34 90.6 78 26
Bhutan 0.9 56 40 81.6 69 25
Sri Lanka 19.5 28 −7 21.9 54 17
South Asia* 1693.8 73 24 91.2 74 21
Global 7155.5 44 10 50.2 61 7
* Here and elsewhere South Asia refers to the GBD regional denition which includes Bangladesh, Bhutan, India, Nepal, and Pakistan. Data for Sri Lanka added separately. WHO IT-1 is
World Health Organization PM2.5 Interim Target −1 of 35 μg/m3 (annual average).
Fig2 | Trends in annual average population
weighted PM2.5 exposure in South Asia, 1990
to 2015. These gures were adapted from
estimates developed for the Global Burden of
Disease (2015) study
Fig3 | Trends in deaths attributable to
ambient PM2.5 in South Asia, 1990 to 2015.
These gures were adapted from estimates
developed for the Global Burden of Disease
(2015) study.
Fig4 | Trends in age standardised
DALYs/100 000 attributable to ambient
PM2.5 exposure in South Asia, 1990 to 2015.
These gures were adapted from estimates
developed for the Global Burden of Disease
(2015) study
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ANALYSIS
and media attention on levels of air pollu-
tion in South Asian cities have led to spo-
radic measures; however, a robust strategy 
with targeted reductions in pollutant levels 
is lacking.
Availability and quality of air pollution data
Continuous ground monitoring of air qual-
ity across a range of locations is essential to 
understand the concentration of pollutants 
at dierent time points and implement con-
trol strategies. South Asian countries lag far 
behind global standards in the density and 
coverage of air quality monitoring networks. 
Routine monitoring of PM2.5 and ozone in 
the region is minimal. Epidemiological 
studies currently rely on modelled exposure 
estimates based on satellite data.
In India, for  example, the National 
Air Quality Monitoring Program collects 
pollutant data  twice a week from 629 
stations across 264 cities, with 35 cities also 
hosting continuous air quality monitoring 
stations.
26
 Monitoring is restricted to urban 
areas with virtually none carried out in rural 
areas. There are also challenges with the 
data collected, including calibration errors, 
gaps in data, and wide variation in uptime 
of monitoring stations.
Research on health outcomes
A growing body of literature from South 
Asia indicates an association between short 
term exposure to air pollution and a range 
of health outcomes such as decrease in 
lung function, respiratory symptoms, emer-
gency department visits, and mortality. To 
date, however, no direct epidemiological 
studies of long term exposure to ambient 
PM2.5 and mortality from chronic diseases 
in South Asia have been published. The evi-
dence on acute and chronic health eects 
at the high levels of exposures commonly 
encountered in South Asian countries 
needs to be strengthened.27 28
Large scale household surveys, census, 
and vital  registration systems are the 
primary sources of data on mortality in 
South Asia. Incomplete or inconsistent 
recording of cause of death, and structural 
deficiencies in data collection result in 
under-reporting of  deaths, especially
in  rural  areas,  and  thereby  provide
little understanding of the impact of air 
pollution.
Air quality management and exposure
reductions
South Asian countries have taken some 
steps to address specic categories of emis-
sions and exposures (table 2) and improve 
air quality. There is no coherent strategy, 
however, with dened targets for air qual-
ity and regular monitoring to understand 
the impact of these measures.29 Political 
will and eective governance are central to 
tackling the problem.
Health centred environmental policy making
is required
With the multiplicity of sources, modes of 
exposure, and complexity of outcomes, 
there is  no easy solution to the  prob-
lem of air pollution in South Asia. While 
household air pollution needs targeted 
interventions with substitute fuels, tack-
ling ambient air pollution, with its varied 
sources, requires a broader approach. Sys-
tematic collection of air quality data and 
a scientic approach to air quality man-
agement are essential to tackle the varied 
sources of emissions. South Asian countries 
can learn from and adapt evidence based 
initiatives implemented in  other parts 
of the world such as the Clean Air Act in 
the US
46
 and China’s ve year, targeted 10 
point action plan to improve air quality 
in three provinces.47 Local solutions and 
policies must be designed to tackle the 
major sources and contributors. Box 2 pro-
vides an example of a recent programme 
launched in India to reduce household air 
pollutionby expanding access to clean 
cooking fuel.
An evidence informed,  multisectoral 
approach to policy making is required.54
While  the  health  sector  can  play  a
convening role on initiatives to minimise 
exposure and ameliorate health impacts, 
the onus of  action  lies  outside, with 
the  implementation  of  policies  and 
programmes across the  ministries  of 
environment,  energy,  industry,  and
nance, among others.
The emphasis on “health in all policies” 
laid  out  in  the  68th  World  Health 
Assembly’s resolution on air pollution 
provides a  roadmap to tackle  a  cross 
sectoral issue like air pollution where 
health is adversely aected as a result of 
ineective policy making across sectors.
The resolution emphasised the need for 
health related benchmarks of progress 
in air pollution control measures, and 
advocated health impact assessments 
in policy design, implementation, and 
evaluation related to air pollution.55 In 
the context of growing energy use, rapid 
urbanisation, and increased demand for 
personal and public transport, the health 
Table | Sector specic policies and interventions undertaken to reduce emissions and
exposures
Country Target sector Policies or interventions
Pakistan30-34 Transport Introduction of Euro IV standards for exhaust emissions from passenger cars
Retrofitting diesel buses and trucks with PM emission controls
Power Coal gasification, carbon sequestration
Industry Gas to replace fuel oil and coal
Low sulphur furnace oil and diesel
Domestic Promote cleaner cooking and increased use of natural gas
India35-40 Transport Introduction of Euro VI equivalent standards for vehicles and fuels
Industry and power Emissions standards for various industries
Domestic LPG connections to 50 million rural households by 2019
Localised
action plans
Graded Response Action Plan for Delhi
Comprehensive Action Plan for pollution control in the National Capital Territory
Brick kilns Transition to “induced draft zig-zag” technology
Bangladesh41-43 Transport Ban on 2-stroke engines, introduction of compressed natural gas vehicles in Dhaka
Brick kilns Introduction of Hybrid Hoffman kilns
Multiple sectors Air Pollution Reduction Strategy for Bangladesh
Sri Lanka44 Transport Phasing out 2-stroke engines
Introduction of vehicular testing programmes
Nepal45 Transport Vehicle inspection and emissions testing
Ban on 2-stroke engines
Pollution cess on fuel
Brick kilns Ban on movable bull trench kilns
Dust control Road improvement and footpath development in Kathmandu
Box: Increasing access to clean cooking fuel in India
The Indian government has historically provided a subsidy for liquefied petroleum gas (LPG).
Access to this subsidy, however, was skewed heavily in favour of the urban population.48
To tackle this imbalance, the Pradhan Mantri Ujjwala Yojana was launched in May 2016 with
the aim of providing 50 million rural households with subsidised LPG connections by 2019,
where hitherto they had been using solid fuels for cooking (fig 5).
This was coupled with a campaign to encourage urban recipients to give up their subsidy, and
the PAHAL scheme for direct transfer of LPG subsidies to beneficiaries’ bank accounts.49 50 The
programme exceeded its connection targets in the first year.51 The investment both by way
of political will and finances is vital. The question, however, of whether access equates with
usage remains—newspapers have recently reported on beneficiaries dropping out after initial
refills.52 53
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ANALYSIS
impacts of air pollution can be a conscience 
keeper for the principles of sustainable 
urbanisation and development.
While localised sources and emissions 
are important to tackle exposure, it is 
also vital to recognise the role of long 
distance and transboundary transport of 
air pollution in an interconnected airshed 
like the Indo-Gangetic Plain which links 
Bangladesh, India, and Pakistan. Existing 
political platforms, such as the South Asian 
Association for Regional Cooperation, 
must be leveraged to drive action on air 
quality. WHO’s multisectoral action plan 
on non-communicable diseases provides 
a platform through which national and 
regional consensus can  be fostered on 
the health impacts of air pollution. In 
addition to the nine traditional risk factors 
outlined in the action plan, member states 
of WHO’s South East Asia region included 
the reduction of exposure to household air 
pollution from biomass as a target for the 
region. This platform can be the basis for 
coordinated and innovative regional action 
to reduce exposures and improve health 
outcomes.
Sources and methods
We used data from the Global Burden of 
Disease Study (GBD) 2015 on ambient 
and household exposure to air pollution 
and health burden estimates. Details on 
the methods for exposure estimation are 
described elsewhere.29 30
We do not know  of any other study
that provides  national level estimates 
for the  purpose of comparison  across 
different countries. In this context, we 
acknowledge the need to strengthen the 
local evidence base by conducting more 
direct epidemiological  studies on the 
health eects of ambient and household 
air pollution which would accord greater 
condence to the burden estimates.
During  the  preparation  of  this
manuscript, the GBD estimates for 2016 
were released. We believe that the minor 
revision  in  overall  numbers  did  not
necessitate shifting to the 2016 estimates 
for this article.
For other information covered in this 
article, we conducted searches on PubMed, 
Google Scholar, and Science Direct for 
relevant reviews and reports published 
in the region, and drew on our collective 
experience in this eld.
Contributors and sources: BK and DB developed
the outline for the paper, to which all other
authors contributed. BK, MB, KB, ARS, DB, and BAB
contributed sections to the paper, drawing on their
previous work and research from their respective
countries. BK consolidated dras. BK and MB
coordinated revisions. All authors reviewed and
approved the nal manuscript.
Competing interests: We have read and understood
BMJ policy on declaration of interests and have no
relevant interests to declare.
Bhargav Krishna, manager (technical)
Kalpana Balakrishnan, associate dean (research)
and director
Amna R Siddiqui, associate professor
Bilkis A Begum, chief scientic ocer
Damodar Bachani, director
Michael Brauer, professor
1Centre for Environmental Health, Public Health
Foundation of India, Gurgaon, India
2Department of Environmental Health Engineering, Sri
Ramachandra University, Chennai, India
3Department of Community Health Sciences, Aga Khan
University, Karachi, Pakistan
4Chemistry division, Atomic Energy Centre, Dhaka
(AECD), Dhaka, Bangladesh
5School of Population and Public Health, University of
British Columbia, Vancouver, Canada
Correspondence to: Bhargav Krishna
bhargavkrishna@gmail.com
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Cite this as: BMJ ;:j
http://dx.doi.org/10.1136/bmj.j5209
... However, a comparatively moderate AQI has been observed for Chennai and Colombo (58%); AQI is observed to be unhealthy (including unhealthy for sensitive groups) for 27-28.50% of the duration of each day and is found to be good for 14-15.20% of the duration of the day (Table 6). Krishna et al. (2017) reported that more than 99% of South Asia's population lives in areas with air quality worse than WHO's recommended minimum standards and is heavily exposed to PM 2.5 emissions [13]. Therefore, this study indicates alarming AQI conditions for almost half of the day in New Delhi, Dhaka, Kolkata, Mumbai, and Hyderabad. ...
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This study aims to assess the current and future air pollution and associated health impacts in Pakistan. In this study, the Pakistan Integrated Energy Model (Pak-IEM) is used to assess current and future energy consumption in Pakistan. To assess air pollution levels and associated health impacts, we used the Greenhouse gas and Air pollution INteractions and Synergies (GAINS) model. A linkage has been established between both the models to feed the energy outputs from Pak-IEM into GAINS for exploring different scenarios. Mainly, the emissions of three air pollutants (SO2, NOx, and PM2.5) as well as the associated health impacts of increased emissions are assessed. Baseline emission scenario (BES) shows a growth in emissions of SO2, NOx, and PM2.5 by a factor of 2.4, 2.2, and 2.5 between 2007 and 2030. In terms of health impacts, by 2030, annual mean concentrations of fine particles (PM2.5) would increase to more than 150 μg/m3 in some parts of Punjab region of Pakistan, for which loss in statistical life expectancy is calculated to increase from 30 to 60 months in 2007 up to 60–100 months in 2030 on average.
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Background: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods: Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings: All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5–89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation: Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.
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Implications: The field of air pollution accountability continues to grow in importance to a number of stakeholders. Two frameworks, the classical accountability chain and direct accountability, have been used to estimate impacts of regulatory actions, and both require careful attention to confounders and uncertainties. Researchers should continue to be develop and evaluate both methods as they investigate current and future air pollution regulations.
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A mass balance method is applied to assess main source contributions to PM2.5 and PM10 levels in Karachi. Carbonaceous species (elemental carbon, organic carbon, carbonate carbon), soluble ions (Ca++, Mg++, Na+, K+, NH4+, Cl−, NO3−, SO4−), saccharides (levoglucosan, galactosan, mannosan, sucrose, fructose, glucose, arabitol and mannitol) were determined in atmospheric fine (PM2.5) and coarse (PM10) aerosol samples collected under pre-monsoon conditions (March–April 2009) at an urban site in Karachi (Pakistan). The concentrations of PM2.5 and PM10 were found to be 75 μg/m3 and 437 μg/m3 respectively. The large difference between PM10 and PM2.5 originated predominantly from mineral dust. “Calcareous dust” and „siliceous dust” were the over all dominating material in PM, with 46% contribution to PM2.5 and 78% to PM10–2.5. Combustion particles and secondary organics (EC + OM) comprised 23% of PM2.5 and 6% of PM10–2.5. EC, as well as OC ambient levels were higher (59% and 56%) in PM10–2.5 than in PM2.5. Biomass burning contributed about 3% to PM2.5, and had a share of about 13% of “EC + OM” in PM2.5. The impact of bioaerosol (fungal spores) was minor and had a share of 1 and 2% of the OC in the PM2.5 and PM10–2.5 size fractions. In case of secondary inorganic aerosols, ammonium sulphate (NH4)2SO4 contributes 4.4% to PM2.5 and no detectable quantity were found in fraction PM10–2.5. The sea salt contribution is about 2% both to PM2.5 and PM10–2.5.