Quantitative systematic review of short term associations between ambient air pollution

706 Pages·2010·5.93 MB·English

Quantitative systematic review of short term associations
between ambient air pollution (particulate matter, ozone,
nitrogen dioxide, sulphur dioxide and carbon monoxide), and
mortality and morbidity.

Contract number: 0020017

Report to Department of Health revised following first review

June 2007

HR Anderson
RW Atkinson
SA Bremner
J Carrington
J Peacock

Division of Community Health Sciences
St George's, University of London
Cranmer Terrace
LONDON SW17 0RE

Address for correspondence: HR Anderson
[email protected]
Tel: [phone]
Fax: [phone]
Table of contents

Abstract.................................................................................................................................3
Chapter 1: Executive Summary...........................................................................................4
Background.....................................................................................................................................4
Methods...........................................................................................................................................5
Overview of time series results.......................................................................................................6
Overview of panel results................................................................................................................7
Conclusions.....................................................................................................................................7
Chapter 2: Introduction.........................................................................................................9
Chapter 3: Methods............................................................................................................13
Data collection for APED...............................................................................................................13
Step 1 - Systematic ascertainment of relevant papers.............................................................13
Step 2 - Extraction of data........................................................................................................14
Step 3 - Data entry and standardization...................................................................................14
Categorization of outcome, age and pollution...............................................................................14
Analysis.........................................................................................................................................15
Lag selection.............................................................................................................................15
City selection.............................................................................................................................16
Estimation of summary effects and heterogeneity....................................................................17
Multipollutant and seasonal models..........................................................................................17
Analysis of publication bias.......................................................................................................17
Chapter 4: Results – Particulate matter (PM)....................................................................19
Meta-analysis of single city estimates...........................................................................................19
Mortality.....................................................................................................................................19
Hospital admissions..................................................................................................................20
Multicity studies.............................................................................................................................21
Single pollutant models.............................................................................................................21
Multipollutant models................................................................................................................22
Seasonal models......................................................................................................................22
Panel studies.................................................................................................................................22
Chapter 5: Results – Nitrogen dioxide (NO ).....................................................................24
2
Meta-analysis of single city estimates...........................................................................................24
Mortality.....................................................................................................................................24
Hospital admissions..................................................................................................................25
Emergency room visits..............................................................................................................26
Multicity studies.............................................................................................................................26
Single pollutant models.............................................................................................................26
Multipollutant models................................................................................................................26
Seasonal models......................................................................................................................27
Panel studies.................................................................................................................................27
Chapter 6: Results – Ozone (O ).......................................................................................28
3
Meta-analysis of single city estimates...........................................................................................28
Mortality.....................................................................................................................................28
Hospital Admissions..................................................................................................................29
Multicity studies.............................................................................................................................30
Single pollutant models.............................................................................................................30
Multipollutant models................................................................................................................31
Seasonal models......................................................................................................................31
Panel studies.................................................................................................................................31
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Chapter 7: Results – Sulphur dioxide (SO ).......................................................................33
2
Meta-analysis of single city estimates...........................................................................................33
Mortality.....................................................................................................................................33
Hospital Admissions..................................................................................................................34
Emergency room visits..............................................................................................................35
Multicity studies.............................................................................................................................35
Single pollutant models.............................................................................................................35
Multipollutant models................................................................................................................35
Seasonal models......................................................................................................................36
Panel studies.................................................................................................................................36
Chapter 8: Results – Carbon monoxide (CO)....................................................................37
Meta-analysis of single city estimates…………………………………………………………………..37
Mortality.....................................................................................................................................37
Hospital admissions..................................................................................................................37
Multicity studies.............................................................................................................................37
Single pollutant models.............................................................................................................37
Multipollutant models................................................................................................................37
Panel studies.................................................................................................................................37
Chapter 9: Overall Summary and Discussion....................................................................38
Summary of results.......................................................................................................................38
Overview of time series results.................................................................................................38
Overview of panel results..........................................................................................................39
Particulate matter......................................................................................................................39
Nitrogen dioxide........................................................................................................................40
Ozone........................................................................................................................................40
Sulphur dioxide.........................................................................................................................41
Carbon monoxide......................................................................................................................42
Approach.......................................................................................................................................42
Future work and work in progress.................................................................................................46
Further meta-analyses of panel studies....................................................................................46
Comparison with other meta-analyses.....................................................................................46
Comparison with multicity results.............................................................................................46
Heterogeneity............................................................................................................................47
Sensitivity analyses……………………………………………………………………………………47
Multipollutant models……………………………………………………………………………….....48
What do the results tell us about the causality of the associations?.............................................48
Use of these results for health impact assessment......................................................................49
Acknowledgements.............................................................................................................50
References..........................................................................................................................51
Appendix list……………………………………………………………………………………….53
Tables and Figures..............................................................................................................54
APED Quantitative Review 2
Abstract

All peer-reviewed papers with quantitative results from time series and panel studies of
ambient air pollution published up to 2006 were obtained. Estimates of effects were
extracted and standardized for meta-analysis. Meta-analyses were done for all
pollutant/outcome/diagnosis/age groups for which there were 4 or more estimates. The
pollutants were particulate matter (PM) (PM , PM , PM , BS, SO 2- and TSP), nitrogen
10 2.5 2.5-10 4
dioxide (NO ), ozone (O ), sulphur dioxide (SO ) and carbon monoxide (CO). For time
2 3 2
series studies 176 meta-analyses were done, based on 2657 individual estimates. 96% of
estimates were in an adverse direction and 74% were both adverse and statistically
convincing. None of the estimates in a protective direction were statistically convincing.
There was considerable heterogeneity and publication bias. While the evidence was fairly
similar for the various pollutants, there were some variations in the level of evidence
between them and between various outcomes. For panel studies 33 meta-analyses were
done based on 720 individual estimates. 30% were in an adverse direction and 12% were
both adverse and statistically convincing. 70% were in a protective direction and 18%
were both protective and statistically convincing. Overall, we consider that our results
largely support the position that ambient air pollution is a hazard to health. However, the
inconsistencies and difficulties in interpreting the evidence must also be acknowledged.
We have not been able to implicate one pollutant more than another. In the case of PM,
there was nothing major to distinguish the 6 different metrics.
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Chapter 1: Executive Summary

BACKGROUND
There is a large amount of evidence about the short term associations between ambient
concentrations of air pollutants and health or health related outcomes. This is based on
regression analyses of time series of daily data on air pollution and health outcomes,
including mortality, hospital admissions, emergency room attendance, primary care
consultations, lung function, symptoms and use of medications for respiratory problems.
Time series studies can be divided into population time series studies which use registry
data such as mortality (usually referred to as “time series studies”) and individual-level time
series studies of panels of subjects observed regularly over a number of days (usually
referred to as “panel studies”). The statistical methods are complex, with particular
emphasis on controlling for time related confounding factors such as long term trends,
season, day of the week and weather factors such temperature. Exposure data are
usually obtained from fixed monitoring stations situated so as to measure background
concentrations of ambient air pollutants. The studies have considerable statistical power
to investigate small effects.

The influence of these studies has been substantial. They are largely responsible for
showing that air pollution is associated with health effects at concentrations well below
guideline levels and that there is no identifiable threshold. Although the relative risks
observed are typically small, the consistency with which positive associations has been
observed in different places and by different investigators is an important argument in
favour of a causal relationship. The exposure response relationships are often used for
quantifying health effects for policy purposes. For this reason, the size and precision of
estimates from time series studies is also important.

Reviewing the evidence of time series and panel studies has become increasingly difficult
because of the large number of studies, complexity of the analyses and lack of
standardization of presentation and/or methods. Also, in recent years it has been
recognized that reviewing evidence requires a high degree of rigour to ensure lack of bias
and transparency. Many past reviews were not comprehensive and some were merely
qualitative. For these reasons, the Department of Health set up the Air Pollution
Epidemiology Database (APED) with the task of assembling results from all peer reviewed
short term effect studies in a form that would facilitate systematic review including
APED Quantitative Review 4
quantitative meta-analysis. This was achieved and the database has already provided
important results for research and policy. The data base continues to evolve by periodic
updating and improvements in database management and analysis.

The present research was designed to build on this work by conducting a quantitative
meta-analysis of all pollutant/diagnostic/age groupings with four or more estimates.
Previous quantitative meta-analyses had generally addressed a limited number of
pollutants and outcomes, and many had not been systematic. Remarkably, none had
formally examined the data for publication bias, a phenomenon that is generally
widespread and would be expected in a rapidly expanding field where there is sensitivity of
the result to the statistical methods used and the choice of lag.

The unique aspects of this study are that it is comprehensive in scope and transparent in
its methods. We expect that the results will be important for influencing thinking about the
evidence for air pollution as a health hazard and for providing sound data for policy
analysis.
METHODS
All time series studies (population time series and panel), were ascertained by standard
bibliographic methods, with language translation if required. All studies with estimates
were included, subject to minimum quality criteria. No panel studies were excluded. Data
were extracted into an Access relational database. Estimates were standardized to the
same units and pollutant increment and expressed as a percentage change. Summary
estimates were considered to show convincing evidence of an association if the 95%
confidence limits did not include 0%. 5 pollutants were analysed: particulate matter (PM),
nitrogen dioxide (NO ), ozone (O ), sulphur dioxide (SO ) and carbon monoxide (CO).
2 3 2
There were 6 categories of PM, all having a 24 hr averaging time; PM PM , PM ,
10, 2.5 2.5-10
Black Smoke (BS), sulphate (SO 2-) and Total Suspended Particulates (TSP). For the
4
gases, the averaging times were: NO , 1 hr maximum and 24 hr; O , 1 hr maximum, 8 hr
2 3
(maximum or fixed hours) and 24 hr; SO , 24 hr; and CO, 1hr maximum, 8 hr and 24 hr. In
2
total, 15 pollution categories were analysed. The time series studies reported a range of
outcomes which were categorized into 13 groups, of which mortality and hospital
admissions were by far the most frequent. The various diagnoses, usually reported as ICD
codes, were grouped into 15 categories. The various age groups were grouped into 7
categories, of which all-ages, children, adults and elderly were the most frequent. The
very wide range of symptoms reported by panel studies was collapsed into 5 categories.
Panels were also divided into child and adult studies, and then by whether the panels
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comprised the general population or subjects with respiratory symptoms. For both time
series and panel studies one lag was chosen for meta-analysis. This was the lag
highlighted by the author and if this was not clear, we chose that with the highest statistical
significance, irrespective of the direction of the effect. Where there was more than one
estimate per city, we chose the one that was part of a multicity study if that was the case,
or else the most recent. If only an average of several days’ lag was reported, this was
used. For each pollutant/outcome/diagnosis/age combination with more than 4 estimates,
quantitative meta-analysis was done to obtain fixed and random effects summary
estimates, a test of heterogeneity, a parametric and non parametric test of publication bias
(strictly speaking a test of small study bias) and summary estimate adjusted for publication
bias. Precision was assessed using 95% confidence intervals. Some papers reported
summary estimates from multicity studies and these are presented separately. These
multicity studies, to a varying extent, also contribute single city estimates to the single city
meta-analyses. We also obtained and present multipollutant and seasonal results from
multicity studies where available.
OVERVIEW OF TIME SERIES RESULTS
A qualitative overview of the time series meta-analyses is shown in Table 1.1. This shows,
for each of the five pollutant groups, the number of summary estimates, the number of
individual estimates underlying them, the number of random effects estimates in a positive
or negative direction, the numbers of these with 95% confidence limits which exclude zero
and numbers with heterogeneity. The table also shows the numbers of summary
estimates with evidence of publication bias and numbers substantially affected by
adjustment for this. From the potentially very large number of possible combinations of
pollutant, outcome, diagnosis and age, 176 groupings with 4 or more estimates were
identified and these were subjected to meta-analysis. These meta-analyses were based
on a total of 2,657 individual estimates. Each city was included no more than once in any
individual meta-analysis. 96% of summary effect estimates were in an adverse (positive)
direction, and 74% were both positive and had 95% confidence limits that excluded zero,
indicating that a null effect was unlikely. None of the 8 estimates in a negative direction
had confidence limits that excluded zero, indicating that these estimates were consistent
with no effect of pollution on the outcome. Thus, not one of the 176 summary estimates
showed convincing evidence of an association in a protective direction. Heterogeneity was
detected in 64% of meta-analyses. 22% showed evidence of publication bias and
adjustment for this reduced 33% of estimates by more than 20%, an arbitrary level chosen
to indicate potentially important bias. While these reductions were often small in absolute
terms, relative reductions can nevertheless be of public health importance.
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There were 79 summary estimates for mortality and 97 for hospital admissions, reflecting
the larger range of age/diagnostic/age groups in the latter outcome. The number of
individual estimates was, however, higher for mortality (1963) than for morbidity (694),
possibly reflecting the lesser availability of hospital admissions data. Overall, the evidence
for consistent results in an adverse direction was high for both mortality (100%) and
morbidity (92%). Mortality summary estimates that were positive were more likely than
morbidity estimates to have confidence limits that did not include zero (85% vs 65%). The
proportions with evidence of heterogeneity were similar (66% and 62% respectively).
Mortality showed considerably more publication bias than morbidity (35% vs 10%) and a
higher proportion showed a reduction of more than 20% after trim and fill adjustment (39%
vs 28%).
OVERVIEW OF PANEL RESULTS
For the panel studies most associations were in a protective direction and most were likely
to be explained by chance. Of 33 meta-analyses comprising 720 individual estimates,
30% were in an adverse direction and only 12% were both in an adverse direction and had
confidence intervals which excluded zero. The majority (70%) had estimates which were
in a protective direction and 18% were both in a protective direction and had confidence
intervals which excluded zero. 52% showed evidence of heterogeneity but publication bias
was minimal. The clearest evidence of an adverse association was for ozone for which all
4 meta-analyses showed adverse effects that were unlikely to be explained by chance.
CONCLUSIONS
1. Taken as a whole, the large body of evidence from time series studies shows very
consistent positive associations between measures of ambient air pollution and a wide
range of mortality and morbidity outcomes. This is true both for meta-analyses of single
cities and for multicity studies.

2. There are, however, several areas where the evidence of time series studies is null or
less convincing. A notable example was the lack of association between ozone and
hospital admissions for cardiac disease.

3. The evidence from panel studies for adverse effects is convincing only for O .
3

4. There is evidence of substantial heterogeneity.

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5. There is considerable evidence of small study effects/publication bias. A preliminary
analysis of PM and all-cause mortality suggests that this bias is also present in multicity
10
studies.

6. Use of the summary estimates for health impact assessment should take account of the
statistical uncertainty inherent in the formal meta-analytic method. It may also be
appropriate to supplement this with an assessment of uncertainty arising from other factors
e.g. residual confounding and information bias. It should be noted that the effect of
pollution on daily health events is likely to be the cumulation of several prior days of
exposure so that estimates based on single day lags, as were most of those in the present
report, may have underestimated the effects of air pollution. Another possible source of
downward bias is exposure misclassification.

7. These results provide evidence for and against the causality of the short term
associations between air pollution and health. In favour is the almost universal finding of
positive findings in the time series studies. On the other hand other aspects of the
evidence are less persuasive. Firstly, there is the small size of effects compared with other
sources of daily variation, and the lack of statistically convincing associations for a
substantial minority of the summary estimates. Secondly, there is a remarkable lack of
specificity for pollutant or outcome. Thirdly, on the basis of our results, there is a lack of
coherence between the time series and panel evidence.

8. It is important to recognize that our study is based on a protocol-driven, systematic and
objective quantitative approach. It does not encompass the whole richness of information
contained in time-series and panel studies, much of which requires subjective assessment.
The aim was essentially descriptive. One of the next major steps is to use the database to
understand the causes of the observed heterogeneity in many of the meta-analyses.
APED Quantitative Review 8
Chapter 2: Introduction

By the 1980's, it was generally thought that the levels of air pollution observed in most
cities of the developed world were "safe". In the United Kingdom for example, ambient
concentrations were below the currently promulgated WHO Guidelines (WHO 1987).
Population studies had previously shown the adverse health effects of high levels of air
pollution during episodes and in highly polluted cities, but lower levels were of little
concern. It had been observed as early as the 1950's that daily deaths in London were
related to air pollution concentrations in non-episode conditions but the formidable
problems of dealing with serial correlation of data and of controlling for confounding
influences of factors such as season and temperature could not be adequately addressed
with statistical techniques then available.

By the 1980's, there had been important advances in the computing and statistical
techniques for time series analysis which could be used to study the short term temporal
associations between air pollution and health outcomes. These were applied to daily data
on air pollution and health related events (deaths, hospital admissions), which were also
becoming more readily available, and to purpose designed "panel" studies in which a
cohort of individuals was assessed day by day over a period of time to construct a daily
time series of health related outcomes (e.g. symptoms, medication use and lung function)
and air pollution exposure. The custom, which we shall also adopt, is to use the term “time
series studies” for studies of routine data at the population level, and the term “panel
studies” for studies at the individual level. Both however investigate short term temporal
associations using time series techniques.

The relative ease with which time series studies could be done led to a rapid increase in
such studies. Based on our literature searches up until the beginning of 2006, there had
been 524 and 186 papers reporting the results of time series and panel studies
respectively (Figure 2.1). Because each study could potentially report estimates for a
number of pollutants, outcomes, lags and statistical approaches, the number of estimates
was much greater. Figures 2.2 and 2.3 show the number of estimates for various
outcomes, by pollutant, for time series studies published up to the beginning of 2006.
These data were obtained from the Air Pollution Epidemiology Database (APED) which is
described later. There were 14,013 estimates for population time series studies and 7,170
APED Quantitative Review 9