SETURI: National estimates of DALY of environmental risks

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The purpose of this page is to serve as a forum for estimating DALYs due to exposure to environmental and other risks.

General

General procedure

The aim is to analyze current chemical and physical exposures in Finland and their health consequences. The procedures used a similar to a project done in the Netherlands (de Hollander 1999) and the Global burden of disease project of WHO (http://www.who.int/topics/global_burden_of_disease/en/). The work is expected to contribute to a comparative study between Finland, the Netherlands, and Norway (Jantunen: Study plan)

The work will start with selected exposures after which more exposures will be analyzed. The emphasis is on comparability, not comprehensiveness. The selected procedure requires good data on exposure and dose-response, which means that all exposures and all outcomes can not be included.

First, the current exposure distribution is estimated for all Finns (or only those exposed). Based on this exposure distribution and the uncertainties in its estimations, the best guess for the average exposure in Finland (or among those exposed) is estimated together with its uncertainty. The uncertainty in the average exposure is expressed by almost lowest possible (5th percentile) and the almost highest possible (95th percentile) value for the average exposure (i.e. as a distribution, more details below).

To be able to calculate attributable cases, in addition to current average exposure, one needs to determine, which is the lowest feasibly achievable average exposure in Finland. For several substances this is not zero, e.g. there is a natural background for particulate air pollution.

Second, exposure/dose-response functions and their uncertainties (5th and 95th percentiles, as above) are derived for all outcome with sufficient data. It is important that the exposure/dose-response function uses exactly the same exposure/dose marker that was used in the exposure estimation above (more details below).

Third, attributable number of cases is estimated by multiplying the exposure difference with exposure/dose-response and number of exposed using probabilistic methods (Monte-Carlo)

List of potential exposures that could be considered in the evaluation

Criteria 1) Public health effects 2) Concern 3) High exposures in specific groups, e.g. occupational exposures

• Alcohol, metanol
• Particulate air pollution by source
• Ozone
• CO and NO2 (probably included in the above)
• PAHs* Environmental tobacco smoke
• CO indoors
• Benzene* Formaldehyde, naphthalene, hexane, asetaldehyde
• 1,3-butadiene
• Lead
• Damp housing
• Noise* Foodborn epidemics
• Waterborn epidemics
• Chlorination by-products
• Arsenic
• Fluoride
• Dioxin, PCBs, phtalates
• Methyl mercury, mercury
• Radon
• UV radiation
• EMF
• Man-made radiation
• Chemicals in food (acrylamide, pesticides, food additives)
• Accidents (traffic, occupational, domestic/other)

Provisional list of selected exposures and responsible persons

• Indoor radon, STUK/Päivi Kurttio and ?
• Fine particles, KTL/Juha Pekkanen, Olli Leino?
• Formaldehyde, TTL, Eero Priha
• Alcohol, STAKES/Timo Ståhl

• Dioxins, KTL/Juha Pekkanen, Olli Leino?
• ?Damp housing, KTL/Aino Nevalainen, Ulla Haverinen
• Arsenic, KTL/Hannu Komulainen
• ?Methyl mercury, KTL/Juha Pekkanen, Olli Leino?

Methods

Exposure estimation

Below link to the exposure assessment done for the earlier exposure seminar of our group http://www.ttl.fi/Internet/Suomi/Aihesivut/Kemikaaliturvallisuus/Valittua+kemikaalitietoa/suomaltkemsateil.htm

Occupational exposure data is based on environmental measurements, modelling and other information on exposure factors (e.g. exposure times, skin contact, consumption data etc.). In workplaces exposure varies considerably depending on the sector of industry and even within a factory depending on work task. Also exposure level also changes often during a work day.

The following table outlines some occupationally important exposures on Finnish workplaces:

Dose-response assessment

Dose-response information can based on epidemiological studies or in toxicological tests. Epidemiological data is normally preferred to animal tests. However, in most cases dose-response data (e.g. IRIS database) is based animal tests and consequent calculations. In some cases epidemilogical data is suitable for quantitative estimates of risk. In majority of cases, the available epidemiological studies are inadequate and then cancer risks assessment is based on animal bioassays.

Probabilistic risk assessment

Probabilistic exposure/risk assessment methods can be used to analyze the exposure and risk more closely. The needed parameters of the used formula/algoritm are given as distributions (e.g. log-normal, normal, uniform, triangular) and the result of simulation are also distributions. Thus different recentiles of risk are obtained.

Exposures and dose-responses for selected exposures

Fine particles

Target population: All Finnish subjects aged 35 and above

Average, population weighted, PM2.5 concentration: So far we don’t have any available data on fine particles concentrations in Finland. The population average concentration can be estimated to be somewhere between 5 and 10 µg/m3 based on measurements done in Helsinki.

• Population average concentration (mean; min-max estimate mean): 7.0; 6.0-8.0
• Distribution of population PM exposure 5%; 50%; 95%;: 2; 6; 12;

All non-accidental mortality in Finland (year 2000): Mortality counts can be estimated from WHO-mortality database (http://www.who.int/healthinfo/morttables/en/index.html). The number of non-accidental deaths in Finnish subjects aged 35 and above in year 2000 was ?.

Concentration-response function for PM2.5 (RR/(10ug/m3)): Based on Pope et al. 2002 study, the relative risk estimate for 10 µg/m3 changes in PM2.5 concentration is 1.06 and 95% confidence interval 1.02 – 1.11.

• Relative risk for PM2.5 (mean; min; max): 1.06; 1.02; 1.11

Low exposure/threshold: Although current scientific knowledge has not revealed any threshold value for fine particles, for the analysis we use threshold value 5 µg/m3.

• Threshold value: 5 µg/m3

Exposure above threshold: This is the average fine particles exposure above the threshold limit. Estimated by subtracting the threshold from the average exposure.

• Population average concentration above threshold (mean; min; max): 2.0; 1;0; 3.0

Relative risk above threshold: Relative risk estimate for the given exposure. This is estimated from RR-values with formula exp(ln(RR)/10*exposure), that is, for mean estimate exp(ln(1.02)/10*2.0.

• Relative risk above threshold (mean; min; max): 1.01; 1.00; 1:03

Attributable risk above threshold: Percentage change in all-cause mortality due to exposure. Estimate from Relative Risk above threshold with formula -> (RR-1)/RR

• Attributable death above threshold (mean; min; max): 1.2%; 0.2%; 3.1%

Number of excess deaths in Finnish population: Mortality with the current information.

• Number of excess deaths in Finnish population (mean; min; max): 877; 150; 2333

The excel sheet with the calculations: http://heande.pyrkilo.fi/heande/images/5/5a/Tainio_Finland.xls

Formaldehyde

Formaldehyde has been classified as a human carcinogen by WHO/IARC (2004). Formaldehyde causes sinonasal cancer in rats (Kerns 1983) already at exposure levels (2-6 ppm) close those occurring at workplaces in the 1970s. In the epidemiological studies, there was sufficient evidence thatformaldehyde causes nasopharyngeal cancer and limited evidence that formaldehyde causes sinonasal cancer in humans.

Dose-response data

US EPA has established a unit risk for formaldehyde which is 1.3x10-5 per ug/m3. This unit risk (for sinonasal cancer) is based on animal inhalation tests and linearized multistage (LMS) model(upper bound extrapolation from 10% response level). Unit risk means lifetime excess risk at exposure level of 1 ug/m3. Unit risk can be applied for exposure levels up to 800 ug/m3.

The most important epidemiological study (Hauptman 2004) found SMR 2.1 (1.05-4.21)to nasopharyngeal cancer in workers exposed in formaldehyde/resin industry. For sinonasal cancers excess was less clear (SMR=1.19).