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|Year : 2013
: 15 | Issue : 67 | Page
|The cost of hypertension-related ill-health attributable to environmental noise
Anne-Helen Harding1, Gillian A Frost1, Emma Tan1, Aki Tsuchiya2, Howard M Mason1
1 Health and Safety Laboratory, Harpur Hill, Buxton, Derbyshire, SK17 9JN, United Kingdom
2 School of Health and Related Research, Health Economics and Decision Science, University of Sheffield, 30 Regent Street, Sheffield S1 4DA, United Kingdom
Click here for correspondence address
|Date of Web Publication||12-Nov-2013|
Hypertension (HT) is associated with environmental noise exposure and is a risk factor for a range of health outcomes. The study aims were to identify key HT related health outcomes and to quantify and monetize the impact on health outcomes attributable to environmental noise-related HT. A reiterative literature review identified key HT related health outcomes and their quantitative links with HT. The health impact of increases in environmental noise above recommended daytime noise levels (55 dB[A]) were quantified in terms of quality adjusted life years and then monetized. A case study evaluated the cost of environmental noise, using published data on health risks and the number of people exposed to various bands of environmental noise levels in the United Kingdom (UK). Three health outcomes were selected based on the strength of evidence linking them with HT and their current impact on society: Acute myocardial infarction (AMI), stroke and dementia. In the UK population, an additional 542 cases of HT-related AMI, 788 cases of stroke and 1169 cases of dementia were expected per year due to daytime noise levels ≥55 dB(A). The cost of these additional cases was valued at around £1.09 billion, with dementia accounting for 44%. The methodology is dependent on the availability and quality of published data and the resulting valuations reflect these limitations. The estimated intangible cost provides an insight into the scale of the health impacts and conversely the benefits that the implementation of policies to manage environmental noise may confer.
Keywords: Acute myocardial infarction, dementia, environmental noise, hypertension, stroke
|How to cite this article:|
Harding AH, Frost GA, Tan E, Tsuchiya A, Mason HM. The cost of hypertension-related ill-health attributable to environmental noise. Noise Health 2013;15:437-45
| Introduction|| |
In 1996, the European Commission estimated that the health and well-being of 20% of European Union citizens may be affected by exposure to high levels of environmental noise.  The 2000/2001 United Kingdom (UK) National Noise Incidence Study estimated that 54% of the population lived in houses exposed to environmental noise exceeding recommended daytime noise levels (55 dB L Aeq,16h ) and that 67% lived in houses exposed to environmental noise exceeding recommended night time levels (45 dB L Aeq,8h ).  In 1999, the World Health Organization (WHO) noted that noise pollution was growing but that continued growth was unsustainable because of its impact on, among other things, health. 
Environmental noise is linked with a wide range of adverse physical and psychological health effects.  The focus of research into environmental and occupational noise has been on noise as a risk factor for cardiovascular disease. Higher blood pressure and an increased risk of hypertension (HT) are associated with exposure to high levels of occupational noise for between 5 and 30 years. However, environmental noise studies tend to report only weak associations between long-term exposure to noise and HT. Methodological difficulties in exposure assessment affect many of these environmental noise studies, potentially resulting in the attenuation of any observed associations. Occupational studies provide stronger evidence of association between noise and HT, possibly because noise exposure and confounding factors are more readily assessed in these studies. 
In 2006, Babisch published an extensive review of the epidemiological evidence on the relationship between transport noise, a major source of environmental noise and cardiovascular risk.  He concluded that there was sufficient evidence for a causal relationship between environmental noise, and ischemic heart disease (IHD) and that there was limited or insufficient evidence for a causal relationship between environmental noise and HT. The WHO night noise guidelines suggest that the evidence is limited for both myocardial infarction and for HT, but that a plausible biological pathway can be constructed from the evidence and that an observed effect threshold level can be determined.  The proposed mechanism indicates that environmental noise may lead to HT through stress indicators on direct and indirect pathways. In a meta-analysis of seven studies, Babisch estimated a common dose-response curve relating environmental noise with the risk of myocardial infarction.  Based on this dose-response curve and making many assumptions, Babisch estimated the number of noise-related cases of myocardial infarction in the German population. Berry and Flindell used the same dose-response relationship to compare the health impact costs, in terms of disability adjusted life years (DALYs),  of two scenarios for road traffic noise in the Greater London Authority.  In 2009, Babisch and Kamp undertook a systematic review of the relationship between aircraft noise and HT.  Based on five eligible studies, they reported a pooled odds ratio (OR) of HT of 1.13 (95% confidence interval [CI]: 1.00-1.28) for an increase in day-night noise of 10 dB(A). A meta-analysis of studies on the association between increased annoyance due to road traffic noise and arterial HT reported a pooled risk estimate of 1.16 (95% CI: 1.02-1.29).  The most recent investigation of the association between environmental noise and the risk of HT was carried out by van Kempen and Babisch.  Based on 24 eligible studies, they reported a small, but statistically significant pooled OR for the prevalence of HT (OR: 1.034, 95% CI: 1.011-1.56) associated with a 5 dB L Aeq,16h increase in daytime road traffic noise.
In Britain, the remit of the Interdepartmental Group on Costs and Benefits (noise subject group) (IGCB[N]) is to develop, maintain and disseminate best practice appraisal for changes in noise. The IGCB(N) identified a gap in the appraisal, set the broad framework and commissioned a program of research to address the information gap. This study is one component in this program. Its aims were to identify the key health outcomes related to HT, to quantify the links between environmental noise-related HT and these outcomes and then to monetize the health impact to calculate the intangible cost in a case study of the UK population.
| Methods|| |
Identifying the key HT related health outcomes
The objective of the literature review was to identify all health outcomes associated with HT or blood pressure, irrespective of the strength of evidence for the association. Preliminary discussions with information specialists highlighted difficulties in defining a single, unbounded search question while open search criteria across EMBASE and PMID citation databases using the terms "HT and health outcome (or synonyms)" or "blood pressure and health outcome (or synonyms)" resulted in more than 20,000 hits. Consequently a reiterative approach was adopted in which an "open" search question was used, but restricted to "reviews," the last 10 years, in English and within the fields of epidemiology and public health medicine. The first pass of literature was used to identify the full range of potential health outcomes associated with blood pressure, the possible nature of the relationship and further primary publications with data relevant to the project. The necessary evidence was then collected using a reiterative process. Specific searches were undertaken in order to find further publications dealing with biological mechanisms, susceptible groups, end-stage renal disease, eye-related and pregnancy outcomes.
Quantifying the links
van Kempen and Babisch's pooled estimate of the risk of HT associated with environmental noise was used for the first step in quantifying the link between environmental noise and HT.  This meta-OR was converted into a relative risk using the formula by Zhang and Yu.  Studies, which reported the HT associated risk, were identified for each of the key health outcomes on the basis of quality and relevance to the UK population. Where more than one study was identified for a particular outcome, a meta-analysis was undertaken to determine whether a pooled risk estimate would be appropriate. The marginal increase in mortality (additional risk) of each HT related health outcome associated with a 10 dB(A) increase in environmental noise was calculated using the following formula:
PHT × RR O × i N × (RR HT - 1) (1)
Where pHT is the prevalence of HT in the population; RR O is the relative risk of the health outcome; iN is the incidence of the health outcome in those without HT; and RR HT is the risk of HT associated with environmental noise.  The marginal increase was calculated by sex and by 10-year age groups. In these calculations, the selected health outcomes were treated as mutually independent.
Monetizing the links
In order to convert the health outcomes into monetary values, the impact on health due to HT is quantified using a measure of health that combines mortality and morbidity into a single numerical unit. One such measure used by the National Institute for Health and Clinical Excellence (NICE) is the quality adjusted life year (QALY).  For example, a person living in 60% health for 80 years is said to have 48 QALYs. The level of health is measured on a scale with one for full health and zero for being dead. Developing one of the identified health outcomes would reduce the number of QALYs due to living with the condition for a number of years (and therefore no longer being in "full health"), premature mortality, or a combination of the two. The person with the condition would therefore experience a "QALY loss" and it was this QALY loss that was used to measure health impact. The DALY used by Berry and Flindell  above is a similar measure, but instead of health weights, uses disability weights, with zero for no disability or full health and one for being dead.
Building on the DALY literature,  QALY loss associated with each of the identified HT-related health outcomes was estimated as:
QALYs lost = Quality-of-life lost (QLL) + life expectancy lost (2)
Where QLL = Years lived with disability × (1 − quality-of-life weight).
It was therefore necessary to obtain estimates for the number of years a person would live with the condition and the number of years lost due to premature mortality (if the condition could lead to death) from published literature. Also required was a quality-of-life weight which weights the number of years lived with the condition such that one represents full health and zero represents being dead. The WHO's Global Burden of Disease (GBD) study produced a list of disability weights for a large number of conditions, which they used to measure DALYs. , There are two things to note regarding the current study. First, this study used one minus the disability weight as the quality-of-life weight for the identified health outcomes, which were aggregated in terms of QALYs. The study does not report the health loss in terms of DALYs because it does not incorporate age weighting or temporal discounting, which are features of the DALY. Second, the GBD study treats HT as a risk factor for disease rather than a disease state itself and so there is no disability weight associated with HT itself.
The estimated QALY loss per case was then combined with the additional increase in risk to obtain QALYs lost per person (in a population that includes people without the health outcome). This would provide the additional QALYs lost in a population through time attributable to an additional risk in a particular year. In order to obtain the monetary intangible cost the QALY loss was multiplied by £60,000, which represents the value of a life recommended by the Department of Health and used across government. 
Note that the temporal relationship, between exposure to environmental noise and developing HT and associated health outcomes, is ill-defined and so temporal discounting was not used when estimating QALY loss and monetizing this loss.
Sensitivity and uncertainty analysis
The central estimates of the relative risks of HT (RR HT ) , IHD (RR IHD ), stroke (RR s ) and the OR of dementia (OR d ) obtained from published scientific literature were used to calculate the additional risks of the health outcomes. Although single summary outcomes for these additional risks may be presented, the interpretation of the results will depend on the level of uncertainty in the risk estimates. These uncertainties must be accounted for in order to capture the associated uncertainties in the additional increases in risk. In addition, there was uncertainty in the assumed increase in systolic blood pressure (SBP) (denoted by the parameter S) in non-hypertensives associated with a 10 dB(A) increase in noise.
The sensitivity analysis investigated the robustness of the additional increases in risk estimates of each of the health outcomes, by calculating the sensitivity ratio (SR), defined as the ratio of the change in the dependent variable per unit change in the independent variable. The parameters RR HT, RR IHD, RR s , OR d and S were treated as independent variables and were varied by 20% about their central estimates. The additional risks of each of the health outcomes were the dependent variables.
The aim of the case study was to evaluate the additional cases of the key health outcomes arising in 1 year from exposure to environmental noise above the baseline level (L Aeq,16h <55 dB[A]) in the UK and to evaluate the cost of these cases. In 2000-2001, the Building Research Establishment (BRE) undertook the UK National Noise Incidence Study, a nationally representative survey of home environmental noise levels.  In a cluster-randomized design, 1160 sites across the UK were sampled. Measurements were taken at a height of 1.2 m and a distance of 1 m from the façade over a 24-h period; reflections from the façade were included. Averaged over the UK, these noise levels would be similar to those measured at a height of 4 m, a distance of 2 m from the façade and excluding reflections from the façade. The survey reports the proportion of the UK population exposed to environmental noise in the categories L Aeq,16h <55 dB(46%), 55-59 dB(31%), 60-64 dB(14%) and ≥65 dB(9%). 
The methodology outlined above was implemented in the case study using the BRE noise exposure data, together with data on the age/sex distribution of the UK population published by the Office for National Statistics,  to estimate the QALY losses and the monetary cost of these losses for those resident in areas with environmental noise levels L Aeq,16h ≥55 dB(A). . For the case study, an assumed increase in SBP of approximately 20 mmHg was used to estimate the additional risk due to HT associated with environmental noise. This change in blood pressure was used since it represents the difference between average SBP (120 mmHg) and the threshold SBP (140 mmHg) used in the diagnosis of HT.  For each health outcome, noise band and age by sex group in the case study, the following steps were carried out: (i) The additional risk was calculated for the specified increase in noise level above the baseline level; (ii) this was multiplied by the number of people in that group, to give the expected number of additional cases per year; (iii) this was multiplied by the QALYs lost per case to give the expected QALY loss resulting from these additional cases; (iv) this was multiplied by £60,000 to give the associated cost.
| Results|| |
The first pass of the literature review produced approximately 2000 "reviews" from EMBASE or PMID, where "reviews" included mainly abstracts from descriptive and systematic reviews, commentaries and publications, and reports and book chapters from authoritative bodies. After examining these for relevance, 164 full text articles were obtained and in the second wave a further 350 full text publications were obtained. Together with the publications obtained from the more specific searches, nearly 600 relevant articles were appraised during the literature review. There was good evidence that increased blood pressure is associated with a higher risk of cardiovascular disease (IHD and stroke), dementia, end stage renal disease (ESRD) or chronic renal failure and fetal mortality and morbidity during pregnancy. The strength of the epidemiological evidence of the relationship between HT and each health outcome, the societal impact of the health outcome and the availability of data in the format required for the calculations, are summarized in [Table 1]. Based on the available evidence, IHD, stroke and dementia were selected as the key health outcomes associated with HT. Acute myocardial infarction (AMI) is a major contributor to IHD mortality and so AMI rather than IHD was selected for analysis.
|Table 1: Summary of the evidence relating hypertension and the main health outcomes|
Click here to view
The data required for the calculations were sourced from published scientific literature and government statistics. van Kempen and Babisch's pooled estimate of the risk of HT associated with environmental noise was taken as the first link in the quantification of risk.  The risk of IHD and stroke mortality associated with a 20 mmHg increase in SBP reported by the Prospective Studies Collaboration meta-analysis of 61 studies was used in the calculations quantifying the risk of AMI and stroke [Table 2].  A further pooling of the Prospective Studies Collaboration risk estimates with those reported by the Asia Pacific Cohort Studies Collaboration  was not undertaken due to heterogeneity between the studies. A pooled risk estimate of dementia associated with HT was obtained from a meta-analysis of the risks of Alzheimer's Disease reported for two population based follow-up studies: A Finnish study developed within the Karelia Project and FINMONICA study population samples  and the Honolulu-Asia Aging Study [Table 2].  The meta-OR used for the calculations represents the odds of developing Alzheimer's Disease in those with SBP of 140-159 mmHg compared with those with "normal" (<140 mmHg) SBP. The risk of HT associated with an increase in environmental noise above the baseline level (<55 dB LAeq,16h ) was combined with the risk associated with HT for each selected health outcome using the formula provided in the methods section (Eq. 1) to quantify the risk of each health outcome.
Quantifying and evaluating the risk
For AMI and stroke, the additional risk obtained from the literature related to mortality rather than incidence. Therefore, an additional step was required to convert the additional risk of mortality to the additional risk of incidence. Full details are reported elsewhere,  however in essence, this step involved back calculating using case-fatality rates and the proportion of deaths attributed to the health outcome of interest. The resulting additional increase in incidence for an unspecified environmental noise exposure of x dB(A) above a baseline of <55 dB(A) L Aeq,16h is provided in [Table 3]. The additional increase in risk of AMI and stroke arising from HT was assumed to be zero for those aged less than 40 years and for dementia was assumed to be zero for those aged less than 60 years. This assumption was made because of the low risk of these outcomes in younger individuals.
|Table 3: Additional increase in the annual number of cases and the number of QALYs lost per case of hypertension-related AMI, stroke and dementia due to environmental noise levels above baseline, by sex and age|
Click here to view
The GBD study, which produced the list of disability weights, had very clear case definitions and disease progressions.  These were followed as closely as possible in the current study and are described below, along with the main sources of data. Average life expectancy for men and women was obtained from the Office for National Statistics Interim Life Tables. 
In the GBD study, AMI was investigated as part of IHD and was defined as "Definite and possible episodes of AMI according to the MONICA study criteria".  AMI events were divided into those who die within 30 days, those who survive 30 days with complete recovery and those who survive 30 days but suffer congestive heart failure as a result of the AMI (defined as "Mild and greater (Killip scale k2-k4)."  The main sources of information used in estimating the QALY loss (Eq. 2) were the Oxford Record Linkage Study for AMI 30-day case-fatality rates,  and the Framingham Heart Study for heart failure rates among AMI survivors and survival time. ,,
The case definition for stroke (or cerebrovascular disease) was divided into first-ever strokes ("First-ever stroke according to WHO definition (includes subarachnoid hemorrhage but excludes transient ischemic attacks, subdural hematoma and hemorrhage or infarction due to infection or tumor)") and long-term stroke survivors ("Persons who survive more than 28 days after first-ever stroke") in the GBD study.  First-ever stroke events were therefore divided into those who die within 30 days, those who survive 30 days with complete recovery after 1 year and those who survive 30 days but suffer with a life-long disability. The main sources of information used in estimating the QALY loss were the Oxford Vascular Study for 30-day case-fatality rates  and the Oxfordshire Community Stroke Project for disability rates among stroke survivors and survival times. ,
The case definition used in the GBD study for dementia was "mild, moderate and severe Alzheimer disease, senile and other dementias".  There is currently no cure for dementia and its progression cannot be reversed; so it was assumed that a person living with dementia would suffer with the disabling effects of dementia for the remainder of their life after onset. The main source of information used in estimating the QALY loss for dementia was a multicenter population-based study in England and Wales, which provided survival times (duration of disability) for dementia. 
The resulting QALYs lost per case for each of the HT-related health outcomes are shown in [Table 3]. and more details about their derivation can be found elsewhere.  Dementia tended to have the highest QALY loss of the three health outcomes and at younger ages the QALY loss associated with stroke was greater than that of AMI.
[Figure 1] presents a tornado plot of SRs for a 20% increase and 20% decrease in the risk parameters associated with a 10 dB(A) increase, where the output was the additional increase in the associated health outcomes for ages 80 to 89 (for OR HT , the SR was the same across all three health outcomes; for S, the SRs were similar across all three health outcomes but only the ratio associated with IHD has been presented). The additional increase in each of the health outcomes was found to be most sensitive to the relative risk of HT associated with environmental noise, OR HT , with the additional increase in health outcomes increasing by one unit for a unit increase in OR HT . In contrast, variations in the risk of IHD, stroke and dementia associated with HT and the change in blood pressure associated with environmental noise hardly affected the additional increases in the associated health outcomes.
|Figure 1: Sensitivity ratios for the marginal increase in health outcomes associated with a 20% increase and 20% decrease in risk parameters|
Click here to view
According to the National Noise Incidence Study,  54% of the UK population lived in areas with noise levels L Aeq,16h ≥55 dB during 2000-2001. The additional number of cases arising in 1 year was calculated using probabilistic uncertainty analysis; uncertainties were modeled using Monte Carlo simulations where each parameter was assumed to be a variable quantity with an associated probability distribution. The median values of the additional number of cases, the lifetime QALYs lost and monetary valuation resulting from home environmental noise exposure L Aeq,16h ≥55 dB are shown in [Table 4], along with the 95% uncertainty intervals determined from the 2.5 th and 97.5 th percentiles of the empirical uncertainty distributions. An estimated additional 542 AMI cases, 788 stroke cases and 1169 dementia cases arising from exposure to noise levels above baseline are expected in 1 year, resulting in a total intangible cost of £1.09 billion. Although only 9% of the UK population was exposed to L Aeq,16h ≥65 dB noise levels, 31% (£342 million) of the total intangible costs occurred in this category. Of the three selected health outcomes, AMI accounted for the smallest intangible costs (£294 million) and dementia for the largest (£475 million).
|Table 4: QALYs lost and valuation for the additional cases of AMI, stroke and dementia arising in 1 year from environmental noise ≥55 LAeq, 16h (dB) in the UK population|
Click here to view
| Discussion|| |
Cardiovascular diseases and dementia were selected as the key health outcomes associated with HT for this analysis, based on the body of scientific evidence linking them with HT and their impact on society. Altogether the additional cases of the three selected outcomes arising in 1 year, which were attributable to exposure to home environmental noise in the UK, were valued at £1.09 billion. This valuation was based on intangible costs arising from loss of healthy life due to morbidity and mortality, which can be relatively small compared to the wider societal costs for these health outcomes. In 2008, approximately 99% of the total costs for dementia were attributable to the combined costs of health, social and informal care and less than 1% of costs were attributable to morbidity and mortality, while for stroke and IHD the combined care costs accounted for 75% and 52% of total costs respectively. 
The calculations assumed that the three selected health outcomes were independent and did not take co-morbidity into account. This may result in an overestimate of the QALY losses for the three health outcomes combined. On the other hand, health outcomes, such as ESRD and hypertensive retinopathy, are also associated with HT and will give rise to QALY losses attributable to environmental noise in the same way as the selected outcomes. Another group of individuals may be affected by a relationship between environmental noise and blood pressure: If environmental noise is also associated with a further increase in blood pressure in those with HT, additional cases of cardiovascular disease and dementia will occur in this group. Approximately 30% of the adult population in the UK is hypertensive,  but the valuation only considered the effect of environmental noise on normotensive individuals. Consequently, it is very likely that the overall QALY loss attributable to environmental noise related HT will in reality be greater than that reported here.
The estimates presented depend entirely on published data and as such reflect the limitations in the data available. The risk of noise related HT was the key risk estimate, since it was used in all calculations and was shown in the sensitivity analysis to be the component with the greatest influence on the output. There was considerable variability between the 24 studies included in the calculation of the pooled risk estimate of HT (OR HT ), with age and sex of the study population, the exposure assessment and the noise reference level particularly important sources of heterogeneity. 
The risk estimate linking environmental noise exposure to HT used as its outcome a binary measure, the presence or absence of HT identified by self-reported, clinical diagnosis, or a combination of self-report and clinical diagnosis. This use of manifest HT may be too simplistic since there is evidence that the risk of cardiovascular disease increases across the range of blood pressure, with no threshold down to at least 115 mmHg SBP. For the purpose of this analysis, a change in blood pressure of 20 mmHg was used to represent the change from normotensive to hypertensive. Studies, which have reported values of blood pressure indicate that SBP is up to 5 mmHg higher among those exposed to higher levels compared to those exposed to lower levels of aircraft noise.  Chang et al. observed a statistically non-significant 1.15 mmHg increase in SBP in men and a statistically significant 1.65 mmHg increase in SBP in women per 5 dB(A) increase in average 24-h aircraft noise.  However, the sensitivity analysis indicated that the change in blood pressure associated with noise was the component in the calculations that had the least impact on the output. This suggested that the relatively large change in blood pressure used in this study would have little effect on the results.
Time scales were an issue in this analysis and they could not be addressed with the information available. A lag of 10 or more years is reported between developing HT and AMI mortality  and a lag of 10-20 years is reported between high blood pressure and dementia. , Consequently, the calendar time period when exposure to environmental noise occurred, the duration of exposure and the time intervals between first exposure and HT and between HT and for example AMI were not taken into account in the calculations. The QALYs were calculated for the additional cases arising during 1 year and followed through to death and the monetary costs were not time discounted because no origin could be defined for the timescales. However, the extended time lags are important when considering the health impact and costs of any changes in the levels of environmental noise.
Evaluations of the health impact of environmental noise in the UK have been reported previously. The WHO used DALYs and a value of £46,000 for a DALY to measure the impact of environmental noise: Preliminary results indicated that the total disutility of environmental noise in the UK was valued at over £7 billion/year. The monetized impact on heart disease was estimated to be £1.83 billion/year  and of this, approximately 40% will be due to AMI.  Using the same methodology as the current study, but substituting the Babisch and Kamp 2009 estimated risk of HT  into Eq. 1 in the case study calculations, the total impact of environmental noise on AMI, stroke and dementia in the UK was valued at £2.53 billion. This is substantially higher than the estimate in the current study because the Babisch and Kamp 2009 risk of HT is higher and because Babisch and Kamp used L DEN (day-night noise) rather than L Aeq,16h (daytime noise) as the noise metric in the risk of HT estimate and the proportion of the UK population exposed to environmental noise above the recommended level is greater for L DEN (67%) than for L Aeq,16h (54%). 
This study demonstrated a methodology, using readily available published data to evaluate the impact of health outcomes associated with environmental noise related HT. The methodology has significant limitations, relating to the nature and quality of the published data, but it provides an important insight into the scale of the impacts that environmental noise has on health and the benefits that may result from policies to manage environmental noise in the UK.
| Acknowledgment|| |
The authors would like to acknowledge Nick Warren's advice on developing the methodology and the sensitivity analysis.
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Health and Safety Laboratory, Harpur Hill, Buxton, Derbyshire, SK17 9JN
Source of Support: The main project was funded by Defra, as part of the IGCB(N)’s research programme into the impact of environmental noise on health. The Health & Safety Laboratory funded the preparation of this manuscript and the development of the case study in this paper, Conflict of Interest: None
[Table 1], [Table 2], [Table 3], [Table 4]
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