Talk:Benefit-risk assessment of fish consumption for Beneris

From Testiwiki
Jump to: navigation, search

How to read discussions

Statements: Decision options/scenarios

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: Decision options (decision variables) that should be included in the assessment to help decision and risk-benefit management include at least fish eating recommendations and restrictions allocated age-, fish species-, and country-specifically. Other potential policy options that should be considered can be viewed here: Benefit-risk assessment of fish and related policy options. --Anna Karjalainen 14:59, 30 October 2007 (EET)


I. List of variables (nodes) in the Bayesian Belief Network for the fish case study in the BENERIS project

Nutritional effectors:

  • fish consumption in age group [0,2yr),
  • fish consumption in age group [2,18yr),
  • fish consumption in age group [18,55yr),
  • fish consumption in age group [55+ yr),
  • concentration of PCDD/Fs in fish,
  • concentration of PCBs in fish,
  • concentration of omega-3 fatty acids in fish,
  • concentration of methyl mercury in fish,
  • concentration of selenium in fish,
  • concentration of iodine in fish,
  • exposure to PCDD/Fs from fish in age group [0,2yr),

Exposure to (=intake of) pollutant/nutrient from fish for age group i will be calculated as the product of fish consumption in age group i and concentration of pollutant/nutrient in fish. This will be further divided by the body weight to express the exposure per kg of body mass.

  • exposure to PCDD/Fs from fish in age group [2,18yr),
  • exposure to PCDD/Fs from fish in age group [18,55yr),
  • exposure to PCDD/Fs from fish in age group [55+ yr),
  • exposure to PCBs from fish in age group [0,2yr),
  • exposure to PCBs from fish in age group [2,18yr),
  • exposure to PCBs from fish in age group [18,55yr),
  • exposure to PCBs from fish in age group [55+ yr),
  • exposure to omega-3 fatty acids from fish in age group [0,2yr),
  • exposure to omega-3 fatty acids from fish in age group [2,18yr),
  • exposure to omega-3 fatty acids from fish in age group [18,55yr),
  • exposure to omega-3 fatty acids from fish in age group [55+ yr),
  • exposure to methyl mercury from fish in age group [0,2yr),
  • exposure to methyl mercury from fish in age group [2,18yr),
  • exposure to methyl mercury from fish in age group [18,55yr),
  • exposure to methyl mercury from fish in age group [55+ yr),
  • exposure to selenium from fish in age group [0,2yr),
  • exposure to selenium from fish in age group [2,18yr),
  • exposure to selenium from fish in age group [18,55yr),
  • exposure to selenium from fish in age group [55+ yr),
  • exposure to iodine from fish in age group [0,2yr),
  • exposure to iodine from fish in age group [2,18yr).


Personal effectors:

  • body weight in age group [0,2yr),
  • body weight in age group [2,18yr),
  • body weight in age group [18,55yr),
  • body weight in age group [55+ yr),
  • socioeconomic status (parental educational level-number of years of schooling received) in age group [0,2yr),
  • socioeconomic status (number of years of schooling received) in age group [2,18yr),
  • socioeconomic status (number of years of schooling received) in age group [18,55yr),
  • socioeconomic status (number of years of schooling received) in age group [55+ yr),
  • exposure to nicotine via active smoking in age group [2,18yr),
  • exposure to nicotine via active smoking in age group [18,55yr),
  • exposure to nicotine via active smoking in age group [55+ yr).

Indicators/ Health endpoints:

  • change in IQ in children between 0 and 2 years of age,
  • change in IQ in children between 2 and 18 years of age,
  • change in IQ in children (between 0 and 18 years of age),
  • risk of dental aberrations in children between 0 and 2 years of age,
  • risk of dental aberrations in children between 2 and 18 years of age,
  • risk of dental aberrations in children (between 0 and 18 years of age),
  • the (remaining) lifetime risk of cancer in adults between 18 and 55 years of age,
  • the (remaining) lifetime risk of cancer in adults older than 55 years of age,
  • the (remaining) lifetime risk of cancer in adults (older than 18 years of age),
  • the (remaining) lifetime risk of myocardial infarction in adults between 18 and 55 years of age,
  • the (remaining) lifetime risk of myocardial infarction in adults older than 55 years of age,
  • the (remaining) lifetime risk of myocardial infarction in adults (older than 18 years of age).

II. Data requirements for the BBN:

In order to quantify non-functional nodes of the Bayesian Belief Network for the fish case study the following data is needed:

  • distribution of the fish consumption in age group [0,2yr),
  • distribution of the fish consumption in age group [2,18yr),
  • distribution of the fish consumption in age group [18,55yr),
  • distribution of the fish consumption in age group [55+ yr),
  • distribution of the concentration of PCDD/Fs in fish,
  • distribution of the concentration of PCBs in fish,
  • distribution of the concentration of omega-3 fatty acids in fish,
  • distribution of the concentration of methyl mercury in fish,
  • distribution of the concentration of selenium in fish,
  • distribution of the concentration of iodine in fish,
  • distribution of the body weight in age group [0,2yr),
  • distribution of the body weight in age group [2,18yr),
  • distribution of the body weight in age group [18,55yr),
  • distribution of the body weight in age group [55+ yr),
  • distribution of socioeconomic status (parental educational level-number of years of schooling received) in age group [0,2yr),
  • distribution of socioeconomic status (number of years of schooling received) in age group [2,18yr),
  • distribution of socioeconomic status (number of years of schooling received) in age group [18,55yr),
  • distribution of socioeconomic status (number of years of schooling received) in age group [55+ yr),
  • distribution of the nicotine intake via active smoking in age group [2,18yr),
  • distribution of the nicotine intake via active smoking in age group [18,55yr),
  • distribution of the nicotine intake via active smoking in age group [55+ yr).


In order to quantify functional nodes of the Bayesian belief Network (health risks and benefits) the following information is needed:

  • information about percentage of people of the target population in age group [0,2yr),
  • information about percentage of people of the target population in age group [2,18yr),
  • information about percentage of people of the target population in age group [18,55yr),
  • information about percentage of people of the target population in age group [55+ yr),
  • information about percentage of people in age group [0,2yr) and in age group [2,18yr) in a subpopulation of the target population in age group [0,18yr),
  • information about percentage of people in age group [18,55yr) and in age group [55+ yr) in a subpopulation of the target population in age group [18+ yr),
  • information about the expected lifetime in the target population.


Additional data needed per each health effect considered in the case study:


IQ change age group [0,2yr):

  • information about background unit change in IQ in age group [0,2yr),
  • exposure-response of exposure to methyl mercury for IQ change for people in age group [0,2yr),
  • exposure-response of exposure to selenium for unit IQ change for people in age group [0,2yr),
  • exposure-response of exposure to ω-3 fatty acids for unit IQ change for people in age group [0,2yr),
  • exposure-response of exposure to iodine for unit IQ change for people in age group [0,2yr),
  • exposure-response of socioeconomic status for unit IQ change for people in age group [0,2yr),
  • exposure-response of exposure to methyl mercury and selenium for unit IQ change for people in age group [0,2yr).


IQ change age group [2,18yr):

  • information about background unit change in IQ in age group [2,18yr),
  • exposure-response of exposure to methyl mercury for IQ change for people in age group [2,18yr),
  • exposure-response of exposure to selenium for unit IQ change for people in age group [2,18yr),
  • exposure-response of exposure to ω-3 fatty acids for unit IQ change for people in age group [2,18yr),
  • exposure-response of exposure to iodine for unit IQ change for people in age group [2,18yr),
  • exposure-response of socioeconomic status for unit IQ change for people in age group [2,18yr),
  • exposure-response of exposure to nicotine via active smoking for unit IQ change for people in age group [2,18yr),
  • exposure-response of exposure to methyl mercury and selenium for unit IQ change for people in age group [2,18yr).


Developmental dental aberration risk age group [0,2yr):

  • information about background incidence of teeth defects among people in age group [0,2yr),
  • exposure-response of exposure to PCDD/Fs for teeth defects risk for people in age group [0,2yr),
  • exposure-response of exposure to PCBs for teeth defects risk for people in age group [0,2yr),
  • exposure-response of socioeconomic status for teeth defects risk for people in age group [0,2yr).


Developmental dental aberration risk age group [2,18yr):

  • information about background incidence of teeth defects among people in age group [2,18yr),
  • exposure-response of exposure to PCDD/Fs for teeth defects risk for people in age group [2,18yr),
  • exposure-response of exposure to PCBs for teeth defects risk for people in age group [2,18yr),
  • exposure-response of socioeconomic status for teeth defects risk for people in age group [2,18yr),
  • exposure-response of exposure to nicotine via active smoking for teeth defects risk for people in age group [2,18yr).


Cancer risk age group [18,55yr):

  • information about background incidence of cancer in age group [18,55yr),

Incidence of cancer and myocardial infarction is defined as a probability of having a disease over person’s lifetime.

  • exposure-response of exposure to PCDD/Fs for lifetime cancer risk for people in age group [18,55yr),
  • exposure-response of exposure to PCBs for lifetime cancer risk for people in age group [18,55yr),
  • exposure-response of socioeconomic status for lifetime cancer risk for people in age group [18,55yr),
  • exposure-response of exposure to nicotine via active smoking for lifetime cancer risk for people in age group [18,55yr).


Cancer risk age group [55+ yr):

  • information about background incidence of cancer in age group [55+ yr),
  • exposure-response of exposure to PCDD/Fs for lifetime cancer risk for people in age group [55+ yr),
  • exposure-response of exposure to PCBs for lifetime cancer risk for people in age group [55+ yr),
  • exposure-response of socioeconomic status for lifetime cancer risk for people in age group [55+ yr),
  • exposure-response of exposure to nicotine via active smoking for lifetime cancer risk for people in age group [55+ yr).


Myocardial infarction risk age group [18,55yr):

  • information about background incidence of myocardial infarction in age group [18,55yr),
  • exposure-response of exposure to methyl mercury for lifetime myocardial infarction risk for people in age group [18,55yr),
  • exposure-response of exposure to selenium for lifetime myocardial infarction risk for people in age group [18,55yr),
  • exposure-response of exposure to ω-3 fatty acids for lifetime myocardial infarction risk for people in age group [18,55yr),
  • exposure-response of socioeconomic status for lifetime myocardial infarction risk for people in age group [18,55yr),
  • exposure-response of exposure to nicotine via active smoking for lifetime myocardial infarction risk for people in age group (18,55yr),
  • exposure-response of exposure to methyl mercury and selenium for lifetime myocardial infarction risk for people in age group [18,55yr).

Myocardial infarction risk age group [55+ yr):

  • information about background incidence of myocardial infarction in age group [55+ yr),
  • exposure-response of exposure to methyl mercury for lifetime myocardial infarction risk for people in age group [55+ yr),
  • exposure-response of exposure to selenium for lifetime myocardial infarction risk for people in age group [55+ yr),
  • exposure-response of exposure to ω-3 fatty acids for lifetime myocardial infarction risk for people in age group [55+ yr),
  • exposure-response of socioeconomic status for lifetime myocardial infarction risk for people in age group [55+ yr),
  • exposure-response of exposure to nicotine via active smoking for lifetime myocardial infarction risk for people in age group [55+ yr),
  • exposure-response of exposure to methyl mercury and selenium for lifetime myocardial infarction risk for people in age group [55+ yr).

Discussions

How to read discussions

Statements: Age as a driving variable

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: In my opinion "age" is a driving variable in the fish case study. It is used to divide the target population into separate subgroups (basically children and adults or even more detailed sub-groups like 4 age groups as currently specified) and to estimate various health effects for these subgroups. Patrycja Jesionek

2: This is a reasonable strating point for the study. --Anna Karjalainen 12:48, 5 October 2007 (EEST)


How to read discussions

Statements: We still need resolution on the age category classifications used in the model

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: We propose the following categories: 1) 0-2 years to describe exposure during periods of prenatal, suckling and infancy; 2) 2-18 years for childhood and puberty period; 3) 18-55 years for adulthoo; and 4) over 55 years to describe both a probable period of prevalence of many diseases such as cancer and cardiovascular diseases included as endpoints in the model and old age. --O. Leino, JT Tuomisto, Anna Karjalainen 12:48, 5 October 2007 (EEST)


How to read discussions

Statements: Age-group-specific characteristics

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: Each age group has its own characteristics like exposure to fish constituents, body mass index and background incidences of health effects. For that reason "age" is connected in the diagram with "exposures", "body mass index" and "background incidences".Enter your comment between these two bars P. Jesionek

2P: Yes, reasonable. --Anna Karjalainen 12:48, 5 October 2007 (EEST)


How to read discussions

Statements:

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

1P: Body mass index for a given age group (if applicable) P. Jesionek

2P: To my understanding, these should be used as means in the final interpretation of the health effecs, so we don't aim to describe any "exposure-responses of BMI on e.g. IQ." --Anna Karjalainen 12:48, 5 October 2007 (EEST)


How to read discussions

Statements: Background incidence of that health effect in a given age group

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: Background incidence of that health effect in a given age group needed. P. Jesionek(EEST)

2P: Yes, if available (should be mostly available at least in Finland in statistical databases) --Anna Karjalainen 13:23, 5 October 2007 (EEST)


How to read discussions

Statements: Exposure-responses of fish constituents for that health effect and given age group

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: Is beeing cathered currently at least by Henna Karvonen (FoodFiles), Leino (KTL), Anna Karjalainen (KTL) --Anna Karjalainen 13:23, 5 October 2007 (EEST)


How to read discussions

Statements: SES interaction with the chosen endpoints

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: In the preliminary BBN for the fish case study socioeconomic status has an influence on cancer and cardiovascular effects while smoking status affects cancer, cvd and developmental defects. Do we keep this set-up in the new BBN or do we assume that both statuses affect all health effects? P. Jesionek

2P: Both statuses - SES and smoking affect all health effects --O. Leino, JT Tuomisto, Anna Karjalainen 13:23, 5 October 2007 (EEST)


How to read discussions

Statements: Defining health effects

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: How do we define health effects like developmental teeth defects and IQ change? Are these lifetime risks or childhood risks? P. Jesionek (EEST)

2P: Both are childhood risks. Developmental defects can be defined as dental aberration dose-responses (exposure concentration correlated incidence of dental aberrations in humans). IQ change can be defined as unit or percentual change. --Anna Karjalainen 13:25, 5 October 2007 (EEST)


How to read discussions

Statements: Background IQ change is zero?Needs editing

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: Do we still assume that the background IQ change is zero? Or maybe there are some data on this and we will us it? P. Jesionek

2P: At least for no, yes. --O. Leino, J.T. Tuomisto, Anna Karjalainen 13:23, 5 October 2007


How to read discussions

Statements: Smoking status is age-specific

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: In my opinion each age group should have its own smoking status because of different percentages of smokers and non-smokers in these groups. --Patrycja Jesionek 15:46, 5 October 2007 (EEST)

2P: Do I recall right that we agreed on to take into account only active smoking? I can surely see SES as a dependent variable of age (age-groups). --Anna Karjalainen 18:51, 8 October 2007 (EEST)

3P: Yes, we agreed on active smoking. Thus, the differentiation between active smokers and non-smokers certainly applies to age groups 18-55yr and 55yr +. However, there might be also some percentage of people smoking in the age group 2-18yr. Do we take this into account or do we assume that there are only non-smokers in this age group? Obviously, there are no actively smoking children in age group 0-2yr. But, are we going to include information about actively smoking pregnant women and nursing mothers and examine impact of that smoking on health effects in the two youngest age groups (IQ loss and dental defects)? --Patrycja Jesionek 11:17, 9 October 2007 (EEST)

4: I would say yes for both, but ONLY if it is reasonably feasible to take into account smokers in age-group 2-18yr and passive smoking in age group 0-2yr. --Anna Karjalainen 13:33, 11 October 2007 (EEST)


How to read discussions

Statements: SES - population vs age-group specific

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: Do age groups differ with respect to socioeconomic status? SES could be different among age groups 18-55yr and 55yr+. What is the SES for age groups 0-2yr and 2-18yr? --Patrycja Jesionek 16:16, 5 October 2007 (EEST)

2P: A reasonable assumption might be that the two youngest age groups's SES would be according to the parents SES, but I'm not really sure if this feasible. Anyhow, if we aim to country-specific populations, I suppose SES cannot be population specific. --Anna Karjalainen 18:51, 8 October 2007 (EEST)


How to read discussions

Statements: Socioeconomic and smoking status as continuous variables

Resolution: Resolution not yet found.

(A stable resolution, when found, should be updated to the main page.)

Argumentation:

--1P: During the workshop in Berlin it has been decided that socioeconomic status and smoking status should be discrete variables having respectively three (low/medium/high) and two (smoking/not-smoking) states. Moreover, as indicated in the discussion on this website, distributions of these variables are age-group and country specific. However, if socioeconomic status and smoking status are discrete variables then the modeling of dose-response functions become more complex and imposes higher requirements on data which in some cases may not be available. For example, suppose that we want to estimate the (remaining) lifetime cancer risk of people in the third age group (18-55yr) in a selected population. In order to determine the dose-response function in this case one needs to specify, among others, the background (or average) level of the (remaining) lifetime risk of cancer in the considered age group. If smoking and socioeconomic statuses impact cancer risk via background risk and are assumed to be discrete variables (with states as above) then the background risk is a function of these statuses and takes six different values. These values have to be extracted from data. If there is not enough data on background risk levels in different socioeconomic and smoking groups within a given age group we propose to replace discrete variables by continuous ones (they could be defined as daily intake of nicotine smoke and number of years of schooling received). This replacement implies that smoking and socioeconomic statuses won’t interact through background risk but they will be included in the dose-response function as additional variables, whose slopes in relation to the health effect studied have to be determined from data. This replacement will also allow capturing and quantifying effects of much larger group of interactions including interactions between intakes of fish constituents and smoking (and/or socioeconomic) status and interaction among smoking and socioeconomic statuses. --Patrycja Gradowska 17:13, 26 October 2007 (EEST)

--2: The title of this discussion is ambiguous. Does it mean probability of exposure, or health risks associated with exposure. If the latter, then the age classification needs to take into account the timing of the exposure that results in the health effect. For many of the contaminants this means in utero exposure of the fetus, but the critical timing of exposure to the mother is determined by the toxicokinetics of the contaminant under consideration. For accumulative contaminants it is not just during pregnancy but in the months (e.g. methylmercury) or years (e.g. dioxins) leading up to pregancy -Diane Benford 11:20, 8 November 2007 (EET)D↷