Domestic fish consumption of the pregnant women in Finland

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Question

What is the fish consumption of the pregnant women in Finland? Exposure due to Finnish fish consumption only. Imported fish are not considered. D↷ D↷

Answer

Data 1

Fish consumption among fish users according to Tero Hirvonen, 2007 (g/d).
Fish species Consumption
Baltic herring (Clupea harengus membras) 3.539
Herring (Clupea harengus) 0.0988
Vendace (Coregonus albula) 0.9498
Whitefish (Coregonus lavaretus) 5.589
Pike (Esox lucius) 1.526
Rainbow trout (Onchorhynchus mykiss) 8.691
Shrimp (Pandalus sp.) 2.31
Perch (Perca fluviatilis) 0.5699
Saithe (Pollachius virens) 7.822
Atlantic salmon (Salmo salar) 1.636
Pike-perch (Sander lucioperca) 0
Tuna (Thunnus thynnus) 6.192


Data 2

Fish consumption according to Leino et al., 2007 (g/d).
Fish species High consumption Median consumption Low consumption
Farmed salmon (sea+inland) 13.92 3.61 0.32
Wild salmon 0.82 0.21 0.02
Herring(sea) 0.34 0.04 0.04
White fish(sea) 5.3 1.24 1.24
Sprat(sea) 0 0 0
Perch(sea) 0.6 0.02 0.01
Flounder(sea) 0 0 0
Pike-perch(sea) 0 0 0
Bream(sea) 0 0 0
Pike(sea) 1.38 0.02 0.01
Vendace(sea) 0.14 0.01 0
Burbot(sea) 0 0 0
Wild salmon(inland) 1.65 0.43 0.04
White fish(inland) 8.41 1.96 1.96
Perch(inland) 1.68 0.07 0.03
Pike-perch(inland) 0 0 0
Bream(inland) 0 0 0
Pike(inland) 6.04 0.07 0.04
Vendace(inland) 3.46 0.18 0.04
Burbot(inland) 0 0 0


Data 3

Fish consumption (g/d).
Fish Species Mean consumption
BS Herring 2.06
Vendace(inland) 0.51
Vendace(sea) 0.02
Whitefish(inland) 0.84
Whitefish(sea) 0.54
Pike(inland) 0.8
Pike(sea) 0.19
Perch(inland) 0.27
Perch(sea) 0.09
Atlantic Salmon 1.11
Pike-perch(inland) 0
Pike-Perch(sea) 0

Rationale

Data 1

Fish consumption by pregnant women [1] for twelve various fish species commonly consumed in Finland as normal distributions (mean, SD).

Data 2

Domestic fish consumption of the pregnant women include fish consumption data [2] for twelve different species and demonstrate five fractiles (0.05, 0.25, 0.5, 0.75 and 0.95). There are several species with zero consumption. These values are replaced with a very low value 1u=10-6 to avoid errors prompts in the further calculations of the model. In addition we use the estimated fish consumption of the general population [3], as a reference. D↷

Data 3

Consumption of sea and freshwater fish species by pregnant women was extracted from [1] where the summary statistics of intakes of twelve fish species by users only are given (mean, sd and percentiles: 5th,25th, 50th, 75th, 95th). The estimation process was basically broken down into three steps. In the first step fish intake distributions for fish users were determined based on data in [1]. Here, for a given species the starting/initial cumulative distribution function (CDF) of intake was first constructed by linear interpolation between known percentiles. In general, this distribution will not reproduce the mean and SD as provided by the data. Therefore, the constrained optimization was further used to find the CDF that satisfies the percentiles given and whose mean and variance are as close as possible to the mean and variance from the data. In the second step the intake distributions for all pregnant women were determined. This was possible thanks to information about the percentage of pregnant women consuming particular fish species. Finally, species specific data on the sea and inland intake proportions (assumed to be the same as proportion of sea and inland fishery catch and extracted from [4]) was used to estimate the intake of sea and freshwater fish species by all pregnant women.

Unit

g/d (in Data 1 in the subpopulation of fish users)

Formula

Data 1

<anacode>3.539 4.046 0.0988 0.1122 0.9498 1.512 5.589 5.162 1.526 3.585 8.691 9.747 2.31 1.904 0.5699 1.161 7.822 6.761 1.636 1.713 0.000e+000 0.000e+000 6.192 7.883</anacode>

Data 2

Analytica_id:

<anacode>Table(Quantile,Fish)( 3.538520795,0.0987977390000001,0.949758417,5.588543108,1.526348165,8.690571699, 2.309576484,0.569864064,7.822047198,1.6355467,0,6.192115439, 4.046127233,0.112185126,1.512467425,5.161569621, 3.585166761,9.746680784,1.904184514,1.161265955,6.76128292,1.712611279,0,7.882813666, 0.486401325,0.039995998, 0.044445555,3.199680074,0.044445555,0.543945572,1.319868031,0.044445555,2.924507455,0.213311992,0,2.474752424, 0.606605988,0.039995998,0.044445555,3.199680074,0.044445555,2.055794298,1.319868031,0.044445555,2.924507455, 0.426623983,0,2.474752424, 1.945751342,0.039995998,0.190503825,3.199680074,0.0888911100000001,6.076351881,1.319868031, 0.0888911100000001,5.849014909,1.133886573,0,4.949504848, 4.944405412,0.099995997,1.155451108,6.399360148,1.850337694, 11.27679141,2.639736061,1.138019529,10.66421104,2.267773146,0,7.425000072, 10.52461027,0.342851994,3.601659561,13.7145601, 7.420697623,23.43747716,5.657256199,2.276039057,18.40303739,5.073409465,0,21.21396707 )</anacode>

See also

References

  1. 1.0 1.1 1.2 Tero Hirvonen. 2007. Beneris_Food consumption pregnant women_FINLAND_300507_th.xls
  2. Methyl mercury: BENERIS WP2 Database
  3. Methyl mercury:Leino et al. 2007 submitted
  4. RKTL,2006. Finnish Fisheries Statistics.

Related files

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