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Background Worldwide, ambient air pollution accounts for around 3.7 million deaths annually. Measuring the burden of disease is important not just for advocacy but also is a first step towards carrying out a full cost-utility analysis in order to prioritise technological interventions that are available to reduce air pollution (and subsequent morbidity and mortality) from industrial, power generating and vehicular sources. Methods We calculated the average national exposure to particulate matter particles less than 2.5 μm (PM2.5) in diameter by weighting readings from 52 (non-roadside) monitoring stations by the population of the catchment area around the station. The PM2.5 exposure level was then multiplied by the gender and cause specific (Acute Lower Respiratory Infections, Asthma, Circulatory Diseases, Coronary Heart Failure, Chronic Obstructive Pulmonary Disease, Diabetes, Ischemic Heart Disease, Lung Cancer, Low Birth Weight, Respiratory Diseases and Stroke) relative risks and the national age, cause and gender specific mortality (and hospital utilisation which included neuro-degenerative disorders) rates to arrive at the estimated mortality and hospital days attributable to ambient PM2.5 pollution in Israel in 2015. We utilised a WHO spread-sheet model, which was expanded to include relative risks (based on more recent meta-analyses) of sub-sets of other diagnoses in two additional models. Results Mortality estimates from the three models were 1609, 1908 and 2253 respectively in addition to 184,000, 348,000 and 542,000 days hospitalisation in general hospitals. Total costs from PM2.5 pollution (including premature burial costs) amounted to $544 million, $1030 million and $1749 million respectively (or 0.18 %, 0.35 % and 0.59 % of GNP). Conclusions Subject to the caveat that our estimates were based on a limited number of non-randomly sited stations exposure data. The mortality, morbidity and monetary burden of disease attributable to air pollution from particulate matter in Israel is of sufficient magnitude to warrant the consideration of and prioritisation of technological interventions that are available to reduce air pollution from industrial, power generating and vehicular sources. The accuracy of our burden estimates would be improved if more precise estimates of population exposure were to become available in the future. Electronic supplementary material The online version of this article (doi:10.1186/s13584-016-0110-7) contains supplementary material, which is available to authorized users.
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O R I G I N A L R E S E A R C H A R T I C L E Open Access
Mortality, hospital days and expenditures
attributable to ambient air pollution from
particulate matter in Israel
Gary M. Ginsberg
, Ehud Kaliner and Itamar Grotto
Background: Worldwide, ambient air pollution accounts for around 3.7 million deaths annually. Measuring the
burden of disease is important not just for advocacy but also is a first step towards carrying out a full cost-utility
analysis in order to prioritise technological interventions that are available to reduce air pollution (and subsequent
morbidity and mortality) from industrial, power generating and vehicular sources.
Methods: We calculated the average national exposure to particulate matter particles less than 2.5 μm (PM2.5) in
diameter by weighting readings from 52 (non-roadside) monitoring stations by the population of the catchment
area around the station. The PM2.5 exposure level was then multiplied by the gender and cause specific (Acute
Lower Respiratory Infections, Asthma, Circulatory Diseases, Coronary Heart Failure, Chronic Obstructive Pulmonary
Disease, Diabetes, Ischemic Heart Disease, Lung Cancer, Low Birth Weight, Respiratory Diseases and Stroke) relative
risks and the national age, cause and gender specific mortality (and hospital utilisation which included neuro-
degenerative disorders) rates to arrive at the estimated mortality and hospital days attributable to ambient PM2.5
pollution in Israel in 2015. We utilised a WHO spread-sheet model, which was expanded to include relative risks
(based on more recent meta-analyses) of sub-sets of other diagnoses in two additional models.
Results: Mortality estimates from the three models were 1609, 1908 and 2253 respectively in addition to 184,000,
348,000 and 542,000 days hospitalisation in general hospitals. Total costs from PM2.5 pollution (including premature burial
costs) amounted to $544 million, $1030 million and $1749 million respectively (or 0.18 %, 0.35 % and 0.59 % of GNP).
Conclusions: Subject to the caveat that our estimates were based on a limited number of non-randomly sited stations
exposure data. The mortality, morbidity and monetary burden of disease attributable to air pollution from particulate
matter in Israel is of sufficient magnitude to warrant the consideration of and prioritisation of technological
interventions that are available to reduce air pollution from industrial, power generating and vehicular sources.
The accuracy of our burden estimates would be improved if more precise estimates of population exposure were
to become available in the future.
Keywords: Attributable mortality, Hospitalisations, Air pollution, Particulate matter
* Correspondence:
Israel Ministry of Health, Public Health Services, Yirmiahu Street 39, Jerusalem
9446724, Israel
© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (, which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
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Ginsberg et al. Israel Journal of Health Policy Research (2016) 5:51
DOI 10.1186/s13584-016-0110-7
According to the WHO, air pollution accounted in 2012
for around 7,000,000 deaths worldwide [1], of which
3,700,000 deaths were attributable to ambient air pollution
(AAP) as opposed to household air pollution [2]. The
major contributor to AAP is ambient particulate matter
pollution (APMP), with ambient ozone pollution being
a minor contributor [2]. In 2005 and 2010, it was esti-
mated that there were around 565,000 and 500,000
deaths respectively in the WHO European region attrib-
utable to APMP, of which 2552 and 2452 deaths respect-
ively occurred in Israel [1].
The WHO mortality calculations were primarily made
by multiplying average pollution levels by cause specific
relative risks (RR) based on the literature [36]. An unpub-
lished study commissioned by the Israeli Ministry of En-
vironment protection [7], based on aggregation of spatial
emission rates from all pollutants, estimated the monetary
costs of air pollution from transport, industrial and electri-
city generation sources, but did not estimate mortality.
Measuring the burden of disease from air pollution is
important not just for advocacy but also is a first step
towards carrying out a full cost-utility analysis in order
to prioritise technological interventions that are avail-
able to reduce air pollution (and subsequent morbidity
and mortality) from industrial, electricity generating
and vehicular sources.
This paper aims to estimate mortality, serious mor-
bidity (proxied by hospitalization days) and associated
expenditures from APMP in Israel.
Population-weighted PM2.5 exposure
Annual average ambient PM2.5 and/or PM10 exposure
data was calculated based on published monthly data for
2015 from 52 non-roadside monitoring stations [8]. Read-
ings from stations that only recorded PM10 were con-
verted to PM2.5 by a monthly specific PM2.5/PM10 ratio
based on stations where both measurements were made
in the same region or on national data in the event
no regional data existed.
Mid-2015 population data by towns, cities and regions
(by urban and rural status) were multiplied by the rele-
vant local monitoring stations annual average PM2.5
level and divided by the national exposed population
figure of 8,608,500 (which included 236,000 temporary
migrants) in order to arrive at the national population
weighted average PM2.5 exposure level [9, 10].
Where more than one monitoring station existed in a
city, an average PM2.5 value was calculated and applied
to that citys population. Separately weighted urban and
rural regional average readings for each geographic region
were calculated and applied to other urban and rural pop-
ulations which were not covered by a monitoring station.
Relative risks
Age group (in five year increments) specific RR, based
on the WHO burden of disease calculations from AAP
[11], were obtained for ischemic heart disease (IHD) and
cerebrovascular disease (stroke) mortality from PM2.5
in adults aged over 25 years. Non-age specific RR were
obtained for chronic obstructive pulmonary disease
(COPD), lung cancer (LC) as well as for acute lower re-
spiratory infection (ALRI) in children under 5 years of
age. We utilised a test version of a spread-sheet for esti-
mating the burden of disease from ambient air pollu-
tion that we obtained from the WHO (based on the
methods described in
pdf?ua=1 and
doorair/databases/en/). Values reported in terms of PM10
were converted to PM2.5 equivalents by multiplying by
0.73 [12].
Sensitivity analyses (Table 1)
The WHO supplied RR values were only based on lit-
erature that was available up to mid-2013. We updated
these RR by including recent papers and meta-analyses
of incidence, utilization and mortality data and expanded
the categories in the test tool model to include type 2
Diabetes in Adults [13] and Asthma [14, 15] and Low
Table 1 Diagnostic composition of different models
(ages 25+ unless otherwise stated)
Ling Cancer C33-C34 X X X
Diabetes Type II E11 X X
Dementia F01F07 X
Parkinsons G20 X
Alzheimers G30 X
Circulatory I10I99 X
Cardiovascular I20I28, I30I52
IHD I20I25 X X
CHF I30I52 X
Stroke I60I61, I63, I64 X X
Respiratory J00J99 X
Asthma J45 X
Low Birth Weight P07.0P07.1 X
Based on literature up to and including 2015
Only for hospitalization days not for mortality
Under 1 year old only
All ages
Under five years old only
Ginsberg et al. Israel Journal of Health Policy Research (2016) 5:51 Page 2 of 7
Birth Weight [LBW] in the under-fives [16] in what we
call our MAXI (category) model.
A recent study of 9.8 million subjects in the USA [17] re-
ported that PM2.5 levels were positively related to elevated
hospitalization risks for Alzheimers disease, Parkinsons
disease and dementia. The results indicated that long-term
changes in PM2.5 accelerated neuro-degeneration, poten-
tially after the disease onset, hence we included the attribut-
able hospitalization days into our MAXI model. However,
we did not include estimates of attributable mortality, since
the study was unable to assess whether PM2.5 levels caused
the onset of neuro-degeneration, for which age is a pre-
dominant risk factor [18].
We applied age-specific relative risks for IHD and stroke
in proportion to the overall ratio of the RR calculated from
the meta-analyses to the overall RR from the WHO model.
We noticed that different meta-analyses of the long-
term effect (short-term effects were excluded) of pollut-
ants on a specific disease, did not always include identical
studies. Due to time constraints, in our calculation of
updated relative risks, we included every individual
study that had been included in meta-analyses, plus any
published data since the latest meta-analysis. However
we took care not to include multiple studies based on
the same temporal populations and preserving a hier-
archy of inclusion based primarily on mortality, then
hospitalisations, emergency room visits and incidence
risks (which we assumed will reflect proportionality of
pollution related risks).
However, we excluded studies based in the Far East
(China, South Korea, Japan etc.) as their risks (which
were usually higher) were generally based on higher
levels of air pollution than that of Israel, North America
and Europe [19].
In addition we included a WIDE category model, that
included the broad areas of all circulatory and all re-
spiratory diseases in addition to lung cancer, diabetes
and LBW.
Combined RR were calculated by applying weights in-
versely proportional to the square of the reported stand-
ard errors of the estimates of the diseases in the WIDE
and MAXI categories.
Population Attributable Fraction (PAF)
Age, gender and cause specific PAFs for APMP were
calculated according to the standard formula
Attributable mortality and hospital days
Age and cause specific mortality and days of hospital
utilisation by primary cause of death and hospitalisation
for 20092013 were obtained from the Ministry of
Healths national mortality and hospitalisation data bases.
These raw data were adjusted upwards by 6.8 % [9] to take
into account population growth until mid-2015. Finally
we calculated mortality and hospital days attributable to
PM2.5 by multiplying the age, gender and cause specific
mortality and hospitalization data by the relevant PAF.
Potential years of Life Lost (PYLL)
Extrapolations of age and gender specific life expectancies
to 2015 [10, 11] were multiplied by age-gender and cause
specific mortality data in order to calculate the cause spe-
cific PYLL attributable to PM2.5.
Disability adjusted life years (DALYs) lost
Age- and gender-specific disability weights, used by the
Ministry of Health, were applied to the life expectancies
in order to calculate each individuals additional Healthy
Adjusted Life Expectancy (HALE), using a 3 % per annum
discount rate. These HALEs were subsequently multiplied
by age-gender and cause specific mortality data in order to
calculate the cause specific DALYs lost due to mortality.
Attributable direct costs of ambient PM2.5 pollution
In 2015, Israel spent around $18.5 billion on health ser-
vices [9, 10]. Around 57 % of this was spent on capital
costs, medicines, equipment and ambulatory, emergency
room and out-patient visits [9, 10]. This figure was in
turn multiplied by the percentage of hospital days from
APMP for each of our models. The general hospitalisa-
tion costs (accounting for a further 19.6 %) were then
added, taking into account that the per diem hospital
costs were higher in departments [$916 vs $869] that
cared for persons with diagnoses affected by PM2.5 than
the average hospital cost [20].
We included premature burial costs (based on discount-
ing the $5263 average burial costs over the life years lost)
as the only monetary cost (in contrast to human costs
reflected in lost DALYs) attributable to mortality. In
addition, we calculated a statistical value of life loss
based on valuing each member of society [regardless of
age and gender] according to the national average gross
national product (GNP) per capita of $35,222 multi-
plied by their life expectancy, using a 3 % per annum
discount rate.
The hospital, health service and premature burial costs
were also expressed in terms of their percentages of GNP.
However since the statistical value of life computation is
based on virtualas opposed to real resource costs, this
was not expressed in terms of percentage of GNP.
The population weighted average PM2.5 exposure in
Israel in 2015 was 21.6 μg/m
. The calculated diagnostic
Ginsberg et al. Israel Journal of Health Policy Research (2016) 5:51 Page 3 of 7
specific RR due to 10 μg/m
changes in PM2.5 that we
used for the non-WHO models are listed along with
their diagnoses in Additional file 1: Appendix I. Risks
for ALRI (RR = 1.10, 95 % CI 1.061.12), Alzheimers
(3.00, 2.403.70), Asthma (1.02, 1.011.03), Dementia
(1.16, 1.101.22), Diabetes (1.05, 1.011,08), IHD (1.11,
1.081.15), Lung Cancer (1.11, 1.051.16), Parkinsons
(1.88, 1.442.40) and Respiratory Diagnoses (1.04, 1.001
1.08) were all significant. COPD (1.03, 0.9971.07) and
LBW (1.06, 0.9891.12) were marginally not-significant,
whilst there was a non-significant elevated risk for Strokes
[1.08, 0.931.24].
According to the WHO model, 1609 (95 % CI 863
2361) deaths (or 3.6 % of all fatalities) were attributable
to ambient PM2.5. Around half were due to IHD and a
quarter attributable to strokes (Table 2).
The Wide list (containing wide circulatory and respira-
tory categorisations) estimated 15 % more deaths (1908,
95 % CI 11212804 being 4.3 % of all deaths) than the
WHO model, Circulatory disorders accounted for 64 %
of attributable mortality, with lung cancer and respira-
tory disorders each accounting for 18 % and 14 % re-
spectively (Table 3).
The maxi list (containing many more, but narrower
disease categories, than the wide list) produced an esti-
mate, 40 % higher than the WHO model, of 2253 (95 %
CI 6322904) deaths, being 5.1 % of all deaths. IHD, CHF
lung cancer and stroke accounting for 41 %, 18 %, 16 %
and 14 % of all attributable deaths respectively (Table 4).
Table 5 shows that PM2.5 pollution accounted for
between 183,000591,000 days in general hospitals,
costing between $168 million$592 million, 3.511.4 % of
all general hospital costs. Total health costs from PM2.5
pollution were between $541 million - $1028 million
accounting for between 2.44.6 % of health expendi-
tures in Israel. Total costs from PM2.5 pollution (in-
cluding premature burial costs) amounted to between
$544 million$1749 million or 0.18 %0.59 % of GNP.
Using a statistical value of life based on GNP per capita
methodology would add between $584 million$797
million to the morbidity costs of PM2.5 pollution.
In contrast to deaths which are clearly attributable to a
given causality (such as automobile accidents, suicides,
drowning), deaths due to air pollution and to personal
behaviour, such as smoking, nutritional habits and phys-
ical exercise are harder to identify. Despite this difficulty,
ambient particulate matter pollution has been implicated
as a factor in many causes of death [8].
The range of mortality from our three estimates of
between 16092253 deaths from PM2.5 alone is be-
tween four and five times that of road accident fatalities
(although road fatalities have a higher PYLL due to the
younger age of deceased persons) and between 1016
times that of homicides in Israel [10]. Mortality attrib-
utable to PM2.5 is however lower than deaths from
smoking [21], obesity [22] and sedentariness [23].
Our estimated deaths from PM2.5 are lower than the
2452 estimated by the WHO European region in 2010
[1] partly due to our model taking into account the fact
that the southern desert region of the country has higher
particulate levels but a far lower population density.
Particulate matter data in Israel are strongly impacted
by synoptic phenomena such as the occurrence of dust
Table 2 Mortality attributable to ambient air pollution from
PM2.5 (Israel 2015) (WHO model)
Deaths 95 % Lcl 95 % Ucl Discounted
Lung cancer 232 55 380 3952 3056 2249
COPD 110 44 189 1178 866 695
IHD 850 586 1112 10,460 7958 6075
Stroke 417 175 680 4937 3678 2842
ALRI 1 0 1 42 36 15
TOTAL 1609 861 2361 20,569 15,595 11,877
Table 3 Mortality attributable to ambient air pollution by
pollutant (Israel 2015) (WIDE list)
PM2.5 Deaths 95 % Lcl 95 % Ucl Discounted
Diabetes 78 24 122 820 600 481
LBW 0 0 0 17 15 6
Lung cancer 349 199 478 5945 4598 3384
Circulatory 1217 890 1585 12,445 9181 7274
Respiratory 265 8 618 2776 2047 1601
TOTAL 1908 1121 2804 22,003 16,441 12,745
Table 4 Mortality attributable to ambient air pollution from
PM2.5 (Israel 2015) (MAXI listSingle Pollutant Models)
PM2.5 Deaths 95 % Lcl 95 % Ucl Discounted
Diabetes 78 24 122 820 600 481
LBW 0 0 0 17156
Lung cancer 349 199 478 5945 4598 3384
COPD 78 8 157 834 614 492
IHD 914 696 1142 11,118 8447 6457
CHF 417 180 618 4313 3194 2474
Stroke 278 362 703 3659 2759 2078
ALRI 116 68 172 1155 853 657
Asthma 22 15 30 305 227 166
TOTAL 2253 811 3424 28,167 21,307 16,195
Ginsberg et al. Israel Journal of Health Policy Research (2016) 5:51 Page 4 of 7
stormsfrom surrounding deserts. Our estimates were
limited to pollution data from only 2015, when there was
a below average incidence of such storms. Hence our
overall estimates of mortality, hospitalizations and costs
are more likely to be downwardly biased than if they were
to have been based on multi-year pollution data.
Our estimates were based on the 52 non-roadside
monitoring stations, which fall far short of the current
infeasible goal of having monitoring stations in every
neighbourhood or street. These stations are not distrib-
uted randomly in the urban space, but are located after
careful thought, often in places of special interest (e.g.
potential hot spots, town halls etc.). Thus, averaging PM
concentrations over monitoring stations (for either a city
or a region) does not necessarily give a very good esti-
mate of the true population exposure. In addition, there
might also be data quality issues that need to be assessed
and corrected by air pollution experts. Nevertheless, we
consider our estimates to be an acceptable pragmatic
compromise for the purpose of an initial estimation of
the mortality effects from particulates. We consider our
estimation method to be preferable to estimates based
on industrial and transport emission volumes, where wind
direction and natural pollutant sources such as sand act
as confounders.
We consider the methodology for exposure assessment
used in this paper to be a valid and generally acceptable
for the purpose of making a national estimate of mortal-
ity. However, future localized estimates could be based
on improved methodologies utilizing spatial models of
particulate matter based on integrating data from moni-
toring stations, meteorology, traffic and other inputs.
A major limitation of our estimates is that due to the
lack of such studies in Israel, we employed, as an accept-
able compromise, relative risk estimates from studies in
countries where the PM2.5 is at a different exposure
level. In the event of non-linearity between risk and ex-
posure this would cause biased estimates. However, these
biases were lessened by our exclusion of Asian based stud-
ies, which tended to have higher PM2.5 levels.
A further source of potential bias is that the sources and
hence composition of PM2.5 and subsequent composition-
specific relative risks [24, 25] in international studies are
different from that in Israel. While relying on meta analyses
of risks might reduce any difference with Israel, an overall
bias cannot be ruled out.
It should be borne in mind that our estimates only relate
to one pollutant, particulate matter. A companion article
will estimate the mortality attributable to two other air
pollutants (Ozone and Nitrogen Dioxide). Due large nega-
tive and smaller positive correlations with particulate
matter levels respectively, a simple addition of all three
individual pollutant models will overestimate the total
deaths attributable to ambient air pollution. Therefore
adjustments will be made to the estimated total deaths
by means of combining data from three studies [2628]
that have reported results of multi-pollution models
(i.e.: that adjusted for the other two pollutants).
The WHO estimates, have a great advantage in that they
allow for uniform comparisons with other countries, and
that their relative risk information for IHD and Stroke was
age-specific. However their disadvantage is that their RR
were based on information that was available three years
ago in 2013.
Our WIDE and MAXI lists incorporated data from
studies on Diabetes, which had a significant RR. How-
ever, it could be considered contentious that we included
categories whose RR were marginally significant (COPD,
LBW) or not significant (Strokes), although Strokes
were considered significant in the WHO model. The
Table 5 Deaths, hospital utilization and costs from PM2.5 (Israel 2015)
Deaths 44,354 1609 1908 2253
3.6 % 4.3 % 5.1 %
Hospital days 5,172,000 183,276 348,039 591,014
3.5 % 6.7 % 11.4 %
General Hospital Costs $4,495,153,288 $167,941,477 $318,918,656 $541,563,409
As % of Gen Hosp costs 3.7 % 7.1 % 12.0 %
All Health Costs $22,432,880,000 $541,213,353 $1,027,757,036 $1,745,258,843
As % of all health costs 2.4 % 4.6 % 7.8 %
Mortality Costs
Friction costs $69,686,591 $2,461,150 $2,680,943 $3,366,447
Total Costs $22,502,566,591 $543,674,503 $1,030,437,979 $1,748,625,290
% of GNP 7.6 % 0.18 % 0.35 % 0.59 %
Value of Statistical Life
(GNP per capita based)
$16,346,340,983 $583,629,920 $631,308,623 $796,589,039
Ginsberg et al. Israel Journal of Health Policy Research (2016) 5:51 Page 5 of 7
inclusion of LBW did not affect the WIDE estimates
magnitude, since LBW contributed close to zero attribut-
able deaths. However the inclusion of COPD and Strokes
(in addition to LBW) in the MAXI list added 356 [95 %
CI, 370, +860] deaths.
The mortality, morbidity (between 3.5 %11.4 % of
general hospital days) and monetary burden (between
$544$1748 million annually) of diseases attributable
to air pollution in Israel is of sufficient magnitude to war-
rant the consideration and prioritisation of technological
interventions that are available to reduce air pollution
from industrial and vehicular sources.
While some interventions will be on a national scale
(eg: limits on vehicle emissions), others might be aimed
at local hot spots of high industry or vehicular pollution
where a significantly large population is being exposed.
Thus further analysis of our data (at pollution station
level) will be required to identify and prioritise high risk
localities and search for possible supplementary inter-
ventions (to national level interventions).
The data in this study provides a basis of mortality,
DALY and health costs that can form the basis of any
future cost-utility analyses of interventions (with proven
efficacy) to reduce the burden of disease from man-
made sources of particulate matter pollution. Interven-
tions will have the potential not only to reduce mortality
(and morbidity) but also to generate reductions in attribut-
able health service costs that account for between 2.4 %
7.8 % of all health expenditures in Israel.
In the UK in 2005 [1, 29], road transport accounted
for around 40 % of premature deaths from APMP, other
transport (20 %), power generation (20 %) and other
able number of deaths from particulate matter in Tel-
Aviv, Israel were shown to be attributable to diesel fuels
[30]. Ways have been suggested to almost eradicate re-
duce these emissions and hence their related mortality
and morbidity [31] by increasing the use of catalytic
converters and moving over to hybrid, electrical and
LPG powered vehiclesespecially trucks and buses.
Large desert areas account for the fact that the Middle
East is the region with the highest percentage of PM2.5
pollutants from natural sources [32], being around 52 %
compared with 42 % Japan, 22 % Africa, 21 %, India,
17 % China, 10 % USA and 5 % Western Europe. So the
potential for decreasing the percentage of particulate
mass concentrations (used in this paper) through techno-
logical improvements is lower in the Middle East than in
other regions (both developed and developing).
The effect of surrounding deserts on air Pollutant
levels in Israel was described almost a decade ago [33].
A natural experimental study on the Day of Atonement
from 20002008, when nearly all industry and vehicular
travel ceases, based on four stations in three cities,
reported a reduction in particulate concentrations ran-
ging from 11.4 %21.7 % [34]. However, a similar study
over a longer period (19982012) estimated a 74 % con-
tribution by natural sources to PM2.5 pollution [35].
Assuming 74 % of particulate pollution comes from
natural sources in Israel, means that for every 10 % rela-
tive decrease in man-made PM2.5 attained through the
implementation of intervention strategies [36], between
4259 lives will be saved each year, (in addition to be-
tween $14 million and $21 million in resource costs).
The considerable mortality and morbidity burden attribut-
able to ambient particulate matter pollution, cries out for
the establishment of an inter-ministerial plan to identify
and implement those intervention strategies that are cost-
effective, in order to decrease the considerable burden of
mortality and morbidity, in both human and monetary
terms, from ambient air pollution in Israel.
Additional file
Additional file 1: Appendix I. Studies contained in meta-analyses of RR
due to 10 ug/m3 changes in PM2.5. (DOC 192 kb)
AAP: Ambient air pollution; ALRI: Acute Lower Respiratory tract Infection;
APMP: Ambient Particular Matter Pollution; COPD: Chronic Obstructive
Pulmonary Disease; DALY: Disability adjusted life year; GNP: Gross national
product; HALE: Healthy Adjusted Life Expectancy; IHD: Ischemic Heart
Disease; LBW: Low Birth Weight; LC: Lung cancer; PAF: Population
Attributable Fraction; PM10: Particulate Matter Particles less than 10
micrometers in diameter; PM2.5: Particulate Matter Particles less than 2.5
micrometers in diameter; PYLL: Potential years of Life Lost; RR: Relative risk;
UK: United Kingdom of Great Britain and Northern Ireland; WHO: World
Health Organization
To Dr. Annette Prüss-Ustün and Pierpaulo Mudu of the Department of Public
Health and Environmental and Social Determinants, WHO, Geneva for
allowing us to use a test version of their spread-sheet for estimating the
burden of disease from ambient air pollution. To Ziona Haklai and Nehama
Goldberger of the Health Ministrys Statistical Unit in supplying the raw
mortality and hospitalization data.
Not applicable.
Availability of data and materials
The datasets during and/or analysed during the current study available from
the corresponding author on reasonable request.
GMG designed the study, collected the data, carried out the data analysis,
wrote the initial and wrote read and approved the final manuscript. EK
contributed to the interpretation of the data, made critical revision and
wrote, read and approved the final manuscript. IG initiated the study and
wrote, read and approved the final manuscript.
Competing interests
All the authors are salaried staff of the Ministry of Health and there are no
competing interests to declare.
Ginsberg et al. Israel Journal of Health Policy Research (2016) 5:51 Page 6 of 7
Ethics approval and consent to participate
As the study is based on published literature and a built spreadsheet, no
human subjects were involvedhence there is no need for ethical approval
or consent to participate.
Received: 18 April 2016 Accepted: 10 October 2016
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... Recently, it was reported that the entire Israeli population is exposed to PM 2.5 concentrations that exceed local target values according to Israel's Clean Air Law and the WHO annual mean (10 μg/m 3 ), with an annual average of 17.8 μg/m 3 (Levy et al., 2020). Furthermore, in a study that modeled and estimated the link between PM 2.5 exposure in Israel and the risk for respiratory and cardiovascular morbidities, type 2 diabetes in adults and low birth weight, it was estimated that in 2015 PM 2.5 exposure was the cause of 1,908 premature deaths (Ginsberg et al., 2016). ...
Background Recent studies conducted in several OECD countries have shown that chronic exposure to elevated levels of air pollutants, (especially PM2.5, PM10 and NOx), might negatively impact COVID-19 morbidly and mortality rates. The aim of this study was to examine the association between chronic exposure to air pollution in Israeli cities and towns and their demographic and socioeconomic status, to COVID-19 morbidity, during the three local morbidity waves. Methods We examined the associations between: (a) annual average concentrations of NOx, CO, PM10, PM2.5 and SO2 in 2016–2019, and demographic and socioeconomic parameters, and (b) COVID-19 positive cases in 279 Israeli cities and towns, in the four state-wide morbidity peaks: 1st wave peak: March 31st, 2020; 2nd wave peaks: July 24th and September 27th, 2020, and 3rd wave peak: January 17th, 2021, which occurred after the beginning of the nationwide vaccination campaign. These associations were calculated using both Spearman correlations and multivariate linear regressions. Results We found statistically significant positive correlations between the concentrations of most pollutants in 2016–19 and COVID-19 morbidity rate at the first three timepoints but not the 4th (January 17th, 2021). Population density and city/town total population were also positively associated with the COVID-19 morbidity rates at these three timepoints, but not the 4th, in which socioeconomic parameters were more dominant (we found a statistically significant negative correlation between socioeconomic cluster and COVID-19 morbidity). In addition, all multivariate models including PM2.5 concentrations were statistically significant, and PM2.5 concentrations were positively associated with the COVID-19 morbidity rates in all models. Conclusions We found a nationwide association between population chronic exposure to five main air pollutants in Israeli cities and towns, and COVID-19 morbidity rates during two of the three morbidity waves experienced in Israel. The widespread morbidity that was related to socioeconomic factors during the 3rd wave, emphasizes the need for special attention to morbidity prevention in socioeconomically vulnerable populations and especially in large household communities. Nevertheless, this ecological study has several limitations, such as the inability to draw conclusions about causality or mechanisms of action. The growing body of evidence, regarding association between exacerbated COVID-19 morbidity and mortality rates and long-term chronic exposure to elevated concentrations of air pollutants should serve as a wake-up call to policy makers regarding the urgent need to reduce air pollution and its harmful effects.
... According to the World Health Organisation, in 2016, household and ambient air pollution were responsible for seven million deaths [1]. During the last decade, many researchers have investigated both indoor and outdoor air quality monitoring systems because of air quality being intrinsically linked to human health [2][3][4][5][6] and the occurrence of premature deaths [7][8][9][10]. Therefore, having widespread, unattended portable and connected devices and networks for air quality monitoring and pollutant detection would be a decisive step forward for decreasing the prevalence of lethal diseases such as ischemic heart disease, stroke, chronic obstructive pulmonary disease, or even lung cancer [11][12][13]. ...
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During the few last years, indoor and outdoor Air Quality Monitoring (AQM) has gained a lot of interest among the scientific community due to its direct relation with human health. The Internet of Things (IoT) and, especially, Wireless Sensor Networks (WSN) have given rise to the development of wireless AQM portable systems. This paper presents the development of a LoRa (short for long-range) based sensor network for AQM and gas leakage events detection. The combination of both a commercial gas sensor and a resistance measurement channel for graphene chemoresistive sensors allows both the calculation of an Air Quality Index based on the concentration of reducing species such as volatile organic compounds (VOCs) and CO, and it also makes possible the detection of NO2, which is an important air pollutant. The graphene sensor tested with the LoRa nodes developed allows the detection of NO2 pollution in just 5 min as well as enables monitoring sudden changes in the background level of this pollutant in the atmosphere. The capability of the system of detecting both reducing and oxidizing pollutant agents, alongside its low-cost, low-power, and real-time monitoring features, makes this a solution suitable to be used in wireless AQM and early warning systems.
... Health Organization, fine pm (particulates a diameter of 2.5 μm or less, PM2.5) emissions are also major contributor to premature mortality[42]. In the year 2015, 250 people per million inhabitants died from illness associated with PM2.5[43]. Transitioning from coal to NG in power plants reduces the PM emissions by 70%, but emissions from solar energy are zero. ...
... High levels of atmospheric dust in Israel are associated with a variety of impacts on the environment, including decreased visibility [1,2], large radiative changes [3], and multiple negative human health outcomes. Dust and particulate matter in Israel have been linked with increases in cardiovascular-related hospital admissions [4], chronic obstructive pulmonary disease [5], pneumonia [6], and respiratory distress [7], along with possible increases in asthma [8] and more [9]. In addition, dust events are associated with decreases in indoor air quality [10], and dust storms in the region can also serve as an effective means to transport microorganisms, with specific microbes dependent on dust origin [11][12][13]. ...
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The Negev Desert in Israel is susceptible to frequent atmospheric events of high dust loading which have been linked with negative human health outcomes, including cardiovascular and respiratory distress. Previous research suggests that the highest levels of dust over the region occur during an atmospheric pattern with a cyclone situated over the eastern Mediterranean. This Cyprus Low can bring unsettled weather and strong westerly winds over the Negev. However, while the overall pattern associated with dust events in the Negev Desert is generally well-understood, it remains unclear why days with seemingly similar weather patterns result in different levels of atmospheric dust. Thus, the goal of this study is to better differentiate the atmospheric patterns during dust events over the Negev. Using PM 10 data collected in Be'er Sheva, Israel, from 2000 to 2015 in concert with 72-h HYSPLIT back trajectories at three different height levels (surface, 200 m, 500 m), we examine the source region, trajectory groups using a K-Means clustering procedure, and overall synoptic pattern during dust events. Further, we use sea-level pressure data across the region to determine how cyclone strength and location impact dust events in Be'er Sheva. We find that the highest levels of atmospheric dust in the Negev are associated with the Cyprus Low pattern, and air traversing Libya seems to play an especially important role, likely due to the country's arid surface cover. Cyclone strength is also a critical factor, as lower sea-level pressure results in more severe dust events. A better understanding of the atmospheric features associated with dust events over the Negev Desert will hopefully aid in forecasting these occurrences across the region.
... In recent years, there has been a significant reduction in the concentrations of several air pollutants in Israel (Ministry of Environment Protection, Annual air quality reports (Hebrew) 2018a). Still it is estimated that air pollution in Israel poses a significant cause of death, with estimations of about 2000 deaths per year (Ginsberg et al. 2016) and associated costs over $7 billion a year (Directorate OECD Environment 2017). ...
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Exposure to air pollution is associated with a wide range of health effects, including increased respiratory symptoms, cancer, reproductive and birth defects, and premature death. Air quality measurements by standardized measuring equipment, although accurate, can only provide an estimate for part of the population, with decreasing accuracy further away from the monitoring sites. Estimating pollution levels over large geographical domains requires the use of air quality models which ideally incorporate air quality measurements. In order to estimate actual exposure of the population to air pollution (population-weighted concentrations of air pollutants), there is a need to combine data from air quality models with population density data. Here we present the results of exposure estimates for the entire population of Israel using a chemical transport model combined with measurements from the national monitoring network. We evaluated the individual exposure levels for the entire population to several air pollutants based on census tract units. Using this hybrid model, we found that the entire population of Israel is exposed to concentrations of PM10 and PM2.5 that exceed the target values but are below the environmental values according to the Israeli Clean Air Law. In addition, we found and that over 1.5 million residents are exposed to NOx at concentrations higher than the target values. This data may help decision makers develop targeted interventions to reduce the concentrations of specific pollutants, based on population-weighted exposure.
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Air quality impacts human health from multiple perspectives. Ambient air pollution (AAP) exposure poses a great contribution to the global burden of disease (BoD). The United Nations launched the Sustainable Development Goals (SDGs) to evaluate sustainability levels and improve human living environments. In particular, the two indicators 3.9.1 and 11.6.2, i.e. fine particulate matters (PM2.5 and PM10) and relative disease mortality are listed to illustrate the development goals for the air environment. At present, countries around the world have adopted measures to mitigate AAP, and a quantitative evaluation of the effectiveness is necessary. Thus, statistics for AAP and BoD across the global 183 countries were analyzed to help assess the gap between the status quo and SDGs in this study. We offer a new perspective on BoD estimation research - proportional data (AAP-caused disease burden / total environment-caused disease burden) in grouped global countries (according to their geographical and economic conditions) were adopted to substitute the absolute value in this study, which is more reasonable for comparative analysis. The overlap of economic and geographic distribution shows that the heaviest BoD is concentrated in high-income and Middle Eastern regions. Concerning the type of disease burden, acute lower respiratory infections (ALRI) and ischemic heart disease (IHD) are two major contributors to BoD, and the worldwide deaths and Disability Adjusted Life Years (DALYs) caused by them need to be taken seriously. Generally, this study provides novel evidence for the formulation of air pollution control and management measures to reduce the related disease burden in global regions. To reduce the future BoD, different strategies should be designed depending on the order of driving factors in regions. Even the triggers of BoD are quite different across the globe, the correlation analysis results inform that reducing emissions along with CO2 from social operations at the source is the most direct and effective path in areas with a high density of susceptible populations.
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Alzheimer's disease (AD), non-AD dementia, and Parkinson's disease (PD) are increasingly common in older adults, yet all risk factors for their onset are not fully understood. Consequently, environmental exposures, including air pollution, have been hypothesized to contribute to the etiology of neurodegeneration. Because persistently elevated rates of AD mortality in the southern Piedmont area of North Carolina (NC) have been documented, we studied mortality and hospital admissions for AD, non-AD dementia, and PD in residential populations aged 65+ with long-term exposures to elevated levels of ambient air particulate matter 2.5 (PM2.5) exceeding the World Health Organization (WHO) air quality standards (≥10μg/m3). Health data were obtained from the State Center for Health Statistics and the Healthcare Cost and Utilization Project. PM2.5 levels were obtained from the MODIS/MISR and SeaWiFS datafiles. Residents in the Study group of elevated air particulate matter (87 zip codes with PM2.5≥10μg/m3) were compared to the residents in the Control group with low levels of air particulate matter (81 zip codes with PM2.5≤7.61μg/m3), and were found to have higher age-adjusted rates of mortality and hospital admissions for AD, non-AD dementia, and PD, including a most pronounced increase in AD mortality (323/100,000 vs. 257/100,000, respectively). After adjustment for multiple co-factors, the risk of death (odds ratio, or OR) from AD in the Study group (OR = 1.35, 95%CI[1.24-1.48]) was significantly higher than ORs of non-AD dementia or PD (OR = 0.97, 95%CI[0.90-1.04] and OR = 1.13, 95%CI[0.92-1.31]). The OR of hospital admissions was significantly increased only for AD as a primary case of hospitalization (OR = 1.54, 95%CI[1.31-1.82]). Conclusion: NC residents aged 65+ with long-term exposures to ambient PM2.5 levels exceeding the WHO standard had significantly increased risks of death and hospital admissions for AD. The effects for non-AD dementia and PD were less pronounced.
Air pollution is the leading cause of the global burden of disease from the environment, entailing substantial economic consequences. International shipping is a significant source of NOx, SO2, CO and PM, which can cause known negative health impacts. Thus, this study aimed to estimate the health impacts and the associated external costs of ship-related air pollution in the Iberian Peninsula for 2015. Moreover, the impact of CAP2020 regulations on 2015 emissions was studied. Log-linear functions based on WHO-HRAPIE relative risks for PM2.5 and NO2 all-cause mortality and morbidity health end-points, and integrated exposure-response functions for PM2.5 cause-specific mortality, were used to calculate the excess burden of disease. The number of deaths and years of life lost (YLL) due to NO2 ship-related emissions was similar to those of PM2.5 ship-related emissions. Estimated all-cause premature deaths attributable to PM2.5 ship-related emissions represented an average increase of 7.7% for the Iberian Peninsula when compared to the scenario without shipping contribution. Costs of around 9 100 million € yr-1 (for value of statistical life approach - VSL) and 1 825 million € yr-1 (for value of life year approach - VOLY) were estimated for PM and NO2 all-cause burden of disease. For PM2.5 cause-specific mortality, a cost of around 3 475 million € yr-1 (for VSL approach) and 851 million € yr-1 (for VOLY approach) were estimated. Costs due to PM and NO2 all-cause burden represented around 0.72% and 0.15% of the Iberian Peninsula gross domestic product in 2015, respectively for VSL and VOLY approaches. For PM2.5 cause-specific mortality, costs represented around 0.28% and 0.06%, respectively, for VSL and VOLY approaches. If CAP2020 regulations had been applied in 2015, around 50% and 30% respectively of PM2.5 and NO2 ship-related mortality would been avoided. These results show that air pollution from ships has a considerable impact on health and associated costs affecting the Iberian Peninsula.
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Data governance, smart mobility, sustainability.
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For reducing health impacts from air pollution, it is important to know the sources contributing to human exposure. This study systematically reviewed and analysed available source apportionment studies on particulate matter (of diameter of 10 and 2.5 microns, PM10 and PM2.5) performed in cities to estimate typical shares of the sources of pollution by country and by region. A database with city source apportionment records, estimated with the use of receptor models, was also developed and available at the website of the World Health Organization. Systematic Scopus and Google searches were performed to retrieve city studies of source apportionment for particulate matter. Six source categories were defined. Country and regional averages of source apportionment were estimated based on city population weighting. A total of 419 source apportionment records from studies conducted in cities of 51 countries were used to calculate regional averages of sources of ambient particulate matter. Based on the available information, globally 25% of urban ambient air pollution from PM2.5 is contributed by traffic, 15% by industrial activities, 20% by domestic fuel burning, 22% from unspecified sources of human origin, and 18% from natural dust and salt. The available source apportionment records exhibit, however, important heterogeneities in assessed source categories and incompleteness in certain countries/regions. Traffic is one important contributor to ambient PM in cities. To reduce air pollution in cities and the substantial disease burden it causes, solutions to sustainably reduce ambient PM from traffic, industrial activities and biomass burning should urgently be sought. However, further efforts are required to improve data availability and evaluation, and possibly to combine with other types of information in view of increasing usefulness for policy making.
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Rationale: Tropospheric ozone (O3) is potentially associated with cardiovascular disease risk and premature death. Results from long-term epidemiological studies on O3 are scarce and inconclusive. Objectives: This paper examines the association between chronic ambient O3 exposure and all-cause and cause-specific mortality in a large cohort of U.S. adults. Methods: Cancer Prevention Study-II participants were enrolled in 1982. A total of 669,046 participants were analyzed among which 237,201 deaths were observed through 2004. We obtained estimates of O3 concentrations at the participant residence from a Hierarchical Bayesian Space Time Model. Estimates of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations were obtained from land-use regression. Cox proportional hazards regression models were used to examine mortality associations adjusted for individual- and ecological-level covariates. Measurements and main results: In single-pollutant models, we observed significant positive associations between O3, PM2.5, and NO2 with all-cause and cause-specific mortality. In two-pollutant models adjusting for PM2.5, significant positive associations remained between O3 and all-cause (HR per 10 ppb = 1.02, 95% CI 1.01-1.04), circulatory (HR = 1.03, 95% CI 1.01-1.05), and respiratory mortality (HR = 1.12, 95% CI 1.08-1.16) that were unchanged with further adjustment for NO2. There were also positive mortality associations observed with both PM2.5 (both near-source and regional) and NO2 in multi-pollutant models. Conclusions: Findings from this large-scale prospective study suggest that long-term ambient O3 contributes to risk of respiratory and circulatory mortality. Substantial health and environmental benefits may be achieved through further measures aimed at controlling O3 concentrations.
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Background. Few cohort studies on the associations between long-term exposure to ambient air pollution and mortality have been national in scale, have simultaneously examined associations with exposures to multiple pollutants, and have accounted for changes in exposure due to residential mobility during follow-up. Objectives. We present an extensive analysis of the associations between cause-specific mortality and ambient concentrations of fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) in a national cohort of ~2.5 million Canadians. Methods. We assigned estimates of annual concentrations of these pollutants to the residential postal codes of subjects for each year during 16 years of follow-up. Historical tax data allowed us to track subjects’ addresses annually. We estimated hazard ratios for several causes of death from single and multiple pollutant models, for an increment of the mean of each pollutant minus the 5th percentile, namely 5.0 μg/m3 for PM2.5, 9.5 ppb for O3, and 8.1 ppb for NO2. Results. In multi-pollutant models, PM2.5 (mean=8.9 µg/m3), O3 (mean= 39.6 ppb), and NO2 (mean= 11.6 ppb) were most strongly associated with different causes of death, namely lung cancer, diabetes, and chronic obstructive pulmonary disease, respectively. We report a cumulative risk estimate for non-accidental mortality of 1.075; 95% CI: 1.067-1.084 for a change in exposure from the mean minus the 5th percentile of each pollutant. Conclusions. In this large, national-level cohort, we found strong, positive associations between several common causes of death and exposure to PM2.5, O3, and NO2, even at relatively low concentrations.
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Background: Air pollution constitutes a significant stimulus of asthma exacerbations; however, the impacts of exposure to major air pollutants on asthma-related hospital admissions and emergency room visits (ERVs) have not been fully determined. Objective: We sought to quantify the associations between short-term exposure to air pollutants [ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter ≤10μm (PM10) and PM2.5] and the asthma-related emergency room visits (ERV) and hospitalizations. Methods: Systematic computerized searches without language limitation were performed. Pooled relative risks (RRs) and 95% confidence intervals (95%CIs) were estimated using the random-effect models. Sensitivity analyses and subgroup analyses were also performed. Results: After screening of 246 studies, 87 were included in our analyses. Air pollutants were associated with significantly increased risks of asthma ERVs and hospitalizations [O3: RR(95%CI), 1.009 (1.006, 1.011); I2 = 87.8%, population-attributable fraction (PAF) (95%CI): 0.8 (0.6, 1.1); CO: RR(95%CI), 1.045 (1.029, 1.061); I2 = 85.7%, PAF (95%CI): 4.3 (2.8, 5.7); NO2: RR(95%CI), 1.018 (1.014, 1.022); I2 = 87.6%, PAF (95%CI): 1.8 (1.4, 2.2); SO2: RR(95%CI), 1.011 (1.007, 1.015); I2 = 77.1%, PAF (95%CI): 1.1 (0.7, 1.5); PM10: RR(95%CI), 1.010 (1.008, 1.013); I2 = 69.1%, PAF (95%CI): 1.1 (0.8, 1.3); PM2.5: RR(95%CI), 1.023 (1.015, 1.031); I2 = 82.8%, PAF (95%CI): 2.3 (1.5, 3.1)]. Sensitivity analyses yielded compatible findings as compared with the overall analyses without publication bias. Stronger associations were found in hospitalized males, children and elderly patients in warm seasons with lag of 2 days or greater. Conclusion: Short-term exposures to air pollutants account for increased risks of asthma-related ERVs and hospitalizations that constitute a considerable healthcare utilization and socioeconomic burden.
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The health effects of suspended particulate matter (PM) may depend on its chemical composition. Associations between maternal exposure to chemical constituents of PM and newborn's size have been little examined. We aimed to investigate the associations of exposure to elemental constituents of PM with term low birth weight (LBW, weight<2,500 g among births after 37 weeks of gestation), mean birth weight and head circumference, relying on standardised fine-scale exposure assessment and with extensive control for potential confounders. We pooled data from eight European cohorts comprising 34,923 singleton births in 1994-2008. Annual average concentrations of elemental constituents of PM smaller than 2.5 and 10 µm (PM2.5 and PM10) at maternal home addresses during pregnancy were estimated using land-use regression models. Adjusted associations between each birth measurement and concentrations of eight elements (copper, iron, potassium, nickel, sulfur, silicon, vanadium and zinc) were calculated using random-effects regression on pooled data. A 200 ng/m(3) increase in sulfur in PM2.5 was associated with an increased risk of LBW (adjusted odds ratio, 1.36, 95% confidence interval: 1.17, 1.58). Increased nickel and zinc in PM2.5 concentrations were also associated with an increased risk of LBW. Head circumference was reduced at higher exposure to all elements except potassium. All associations with sulfur were most robust to adjustment for PM2.5 mass concentration. All results were similar for PM10. Sulfur, reflecting secondary combustion particles in this study, may adversely affect LBW and head circumference, independently of particle mass.
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Long-term exposure to fine particles (PM2.5) has been consistently linked to heart and lung disease. Recently there has been increased interest to examine the effects of air pollution on the nervous system, with evidence showing potentially harmful effects on neurodegeneration. Our objective was to assess the potential impact of long-term PM2.5 exposure on event time, defined as time to the first admission for dementia, Alzheimer's or Parkinson's diseases (AD and PD, respectively) in an elderly population across the Northeastern US. We estimated the effects of PM2.5 on first hospital admission for dementia, AD and PD, among all Medicare enrollees >64 years in 50 northeastern US cities (1999-2010). For each outcome, we first ran a Cox proportional hazards model in each city, adjusting for prior cardiopulmonary-related hospitalizations and year, and stratified by follow-up time, age, gender and race. We then pooled the city-specific estimates together by employing a random effects meta-regression. We followed approximately 10 million subjects and observed significant associations of long-term PM2.5 city-wide exposure on all three outcomes. Specifically, we estimated a HR of 1.08; 95% CI: 1.05, 1.11 for dementia, 1.15; 95% CI: 1.11, 1.19 for AD and 1.08; 95% CI: 1.04, 1.12 for PD admissions per 1 μg/m(3) of increase in annual PM2.5 concentrations. To our knowledge, this is the first study to examine the relationship between long-term exposure to PM2.5 and time to the first hospitalization for the most common neurodegenerative diseases. We found strong evidence of an association for all three outcomes. Our findings provide the basis for more studies, as the implications to public health can be crucial.