Dynamic simulation periods are specified in Time's definition. This is usually a list of numbers or labels, typically in some unit of time (days, weeks, months, etc.). Use the ÒDynamic()Ó function in your variables to perform dynamic simulation. 1000 0 0 1 4 13 0 1 2 0 0 0 28.6.2004 Jouni Tuomisto This is the version 4 of the model calculating risks and benefits of farmed salmon. (c) Copyright KTL (National Public Health Institute, Finland). <ref>[http://ytoswww/yhteiset/Huippuyksikko/Tutkimus/Viljelylohi/Materiaali/Viljelylohi.rmd Reference Manager database</ref> <ref>[http://ytoswww/yhteiset/Huippuyksikko/Tutkimus/Viljelylohi/ Directory for data and models</ref> Jouni Tuomisto 9. tamta 2004 20:14 jtue 8. syyta 2008 17:08 48,24 1,19,28,905,585,17 2,102,90,553,461 Trebuchet MS, 13 0,Model Risks_from_farmed_an,2,2,0,1,E:\Tee\Farmed_salmon-3c.ANA 97,1,1,0,2,1,2794,4312,0 2,25,65,696,600 avoided cases/a Pollutant health risk is calculated assuming additivity between the pollutants. However, dioxin risks are not considered because they were not considered in Hites. After unit conversion, numbers are calculated for Western Europe as cases per year. Note that negative numbers mean increased risk unlike in previous versions of the model. var a:= -H1906*H1905/1000*H1910; var b:= (if pollutant1='Dioxin' then 0 else a); var c:= sum(b,pollutant1); c 256,336,1 48,24 1,1,1,1,1,1,0,,1, 2,291,123,476,224 2,357,128,628,450,0,MEAN Graphtool:0 Distresol:10 Diststeps:1 Cdfresol:5 Cdfsteps:1 Symbolsize:6 Baroverlap:0 Linestyle:1 Frame:1 Grid:1 Ticks:1 Mesh:1 Scales:1 Rotation:45 Tilt:0 Depth:70 Frameauto:1 Showkey:1 Xminimum:0 Xmaximum:1 Yminimum:0 Ymaximum:1 Zminimum:0 Zmaximum:1 Xintervals:0 Yintervals:0 Includexzero:0 Includeyzero:0 Includezzero:0 Statsselect:[1,1,1,1,1,0,0,0] Probindex:[0.05,0.25,0.5,0.75,0.95] [H1899,H1898] [1,0,0,0] avoided cases/a Numbers are calculated for Western Europe as avoided deaths per year. Note that positive numbers mean increased benefit unlike in previous versions of the model. -H1909*min([H1908,benefit_limit])*H1911 384,336,1 48,24 1,1,1,1,1,1,0,,1, 2,80,222,476,224 2,95,7,589,375,0,MEAN [H1898,Salmon1] [1,0,0,0] [Reg_poll,1,Year3,1,Salmon1,1,Recommendation1,1] avoided cases/a Net health effect of pollutant cancer and omega-3 cardiac benefit. H1912+H1900 320,408,1 48,24 1,1,1,1,1,1,0,,1, 2,102,90,476,420 2,537,56,726,259,0,MIDM [H1898,Salmon1,1,2] [0,0,0,0] [Salmon,1,Reg_poll,1,Recommendation,1,Sys_localindex('PROBABILITY'),1] ktluser 11. tamta 2004 9:20 48,24 56,208,1 48,24 1,40,0,610,544,17 100,1,1,0,2,9,4744,6798,7 Epa_model 288,40,1 56,32 However, defending his study in an interview with IntraFish yesterday afternoon, David Carpenter of the State University of New York at Albany said that the differences between wild and farmed salmon PCBs levels are not insignificant. ÒI donÕt agree with [Gallo] and I donÕt think others would agree with him either.Ó Carpenter said that the EPA risk assessment model that he and his colleagues used to determine that salmon posed a health risk is a well-respected and sound one. ÒIt is not just something that we made up. It is a time-tested measureÉitÕs a yard stick that we have.Ó <ref>http://www.intrafish.com/articlea.php?articleID=41070&s=1</ref> Epa_model 288,128,1 52,36 2,102,90,630,401 A set of four volumes that provides guidance for assessing health risks associated with the consumption of chemically contaminated non-commercial fish and wildlife. EPA developed the series of documents to help state, local, regional, and tribal environmental health officials who are responsible for developing and managing fish consumption advisories. <ref>http://www.epa.gov/waterscience/fish/guidance.html</ref> Developed_for_spceci 528,192,1 56,28 Developed_for_spceci 360,432,1 68,56 Applies_only_to_non_+Developed_for_spceci 528,296,1 64,56 200,296,1 48,38 [Constant Developed_for_spceci] Point_of_view_is_tha+This_is_not_a_public 528,432,1 64,56 2,102,90,476,373 Epa_model 528,80,1 72,64 Epa_model 360,296,1 84,56 [Constant Precautionary_princi] Epa_model+Fda_model 64,288,1 52,52 5 64,448,1 48,24 2,136,146,416,303,0,MIDM [] <ref>U.S.EPA. Guidance for Assessing Chemical Contaminant Data for Use in Fish Advisory. Volume 2: Risk Assessment and Fish Consumption Limits, 3rd Edition. 2000. Table 3-1. [http://www.epa.gov/waterscience/fish/guidance.html Open access Internet file] [http://ytoswww/yhteiset/Huippuyksikko/Kirjallisuus/Fish_and_health/EPAFishAdvisory/ Intranet file]</ref> jtue 28. Junta 2004 18:03 48,24 64,80,1 48,29 1,40,0,517,300,17 2^(Floor(logten(Epa_model)/logten(2))) 56,176,1 48,24 2,48,219,743,303,1,MIDM [Location1,Undefined] meals/month CRmm variable in the U.S.EPA advisory model. <ref>U.S.EPA. Guidance for Assessing Chemical Contaminant Data for Use in Fish Advisory. Volume 2: Risk Assessment and Fish Consumption Limits, 3rd Edition. 2000. Table 3-1. [http://www.epa.gov/waterscience/fish/guidance.html Open access Internet file] [http://ytoswww/yhteiset/Huippuyksikko/Kirjallisuus/Fish_and_health/EPAFishAdvisory/ Intranet file]</ref> index Effect:=['Cancer','Non-cancer']; var MS:= 0.227; var Tap:= 365.25/12; var CSF:=Potency[potency='Ca (CSF)']; var RfD:= Potency[Potency='Non-Ca (RfD)']; var CRlimCa:= ARL*BW/sum(CSF*in1*(Poll_salmon_hites/1000),Pollutant1); var a:= In1*RfD/(Poll_salmon_hites/1000); var b:= if isnan(a) then 1 else a; var c:= if b>0 then b else 1; var CRlimNonCa:= min(c,Pollutant1)*BW; var CRlim:= array(Effect,[CRlimCa,CRlimNonCa]); var CRmm:= CRlim*Tap/MS; CRmm 56,104,1 48,29 2,43,74,632,412 2,120,130,416,303,0,MIDM [] 1 56,32,1 48,24 Poll_salmon_hites Table(Pollutant1)( 1,1,0,1) 216,160,1 48,24 2,469,131,476,224 2,242,231,416,303,0,MIDM 1 216,104,1 48,24 Potency probability Acceptable risk level <ref>U.S.EPA. Guidance for Assessing Chemical Contaminant Data for Use in Fish Advisory. Volume 2: Risk Assessment and Fish Consumption Limits, 3rd Edition. 2000. Table 3-1. [http://www.epa.gov/waterscience/fish/guidance.html Open access Internet file] [http://ytoswww/yhteiset/Huippuyksikko/Kirjallisuus/Fish_and_health/EPAFishAdvisory/ Intranet file]</ref> 10u 216,32,1 48,24 2,471,122,476,382 ktluser 11. tamta 2004 9:20 48,24 760,96,1 48,24 1,0,0,1,1,1,0,,0, 1,193,72,636,526,17 ['Dieldrin','Toxaphene','Dioxin','PCB'] 504,64,1 48,12 ['Dieldrin','Toxaphene','Dioxin','PCB'] kg 70 504,392,1 48,24 1,1,1,1,1,1,0,0,0,0 ['Scotland','Faroe Islands','Frankfurt','Edinburgh','Norway','Paris','London','Oslo','East Canada','Boston','Maine','San Francisco','West Canada','Toronto','Los Angeles','Vancouver','Washington DC','Seattle','Chicago','New York','Washington St','Chile','SE AK Chinook','Denver','BC Chinook','BC Sockeye','Oregon Chinook','SE AK Sockeye','New Orleans','BC Coho','Kodiak AK Sockeye','SE AK Coho','Kodiak AK Coho','BC Pink','Kodiak AK Pink','SE AK Pink','SE AK Chum','BC Chum','Kodiak AK Chum'] 504,32,1 48,12 ['Scotland','Faroe Islands','Frankfurt','Edinburgh','Norway','Paris','London','Oslo','East Canada','Boston','Maine','San Francisco','West Canada','Toronto','Los Angeles','Vancouver','Washington DC','Seattle','Chicago','New York','Washington St','Chile','SE AK Chinook','Denver','BC Chinook','BC Sockeye','Oregon Chinook','SE AK Sockeye','New Orleans','BC Coho','Kodiak AK Sockeye','SE AK Coho','Kodiak AK Coho','BC Pink','Kodiak AK Pink','SE AK Pink','SE AK Chum','BC Chum','Kodiak AK Chum'] ['Farmed salmon','Wild salmon','Market salmon'] 504,96,1 48,13 ['Farmed salmon','Wild salmon','Market salmon'] 20.1.2004 Jouni Tuomisto En ole ehtinyt aiemmin lokia kirjoittaa, joten nyt yleiskuvaus mallista. Viljelylohi on tehty arvioimaan, onko Hites et al (Science 9.1.2004) riskinarviointi hyvin tehty. Ensikommenttina KTL:ssŠ oli se, ettŠ kalan terveyshyšdyt on unohdettu. NiinpŠ rakensimme mallin, joka 1) kŠyttŠŠ samaa EPAn riskimallia saasteiden terveyshaittojen laskemiseen kuin Hites (PCB:n, dieldriinin ja toksafeenin (mutta ei dioksiinien) aiheuttama yhdistetty syšŠriski olettaen additiivisuuden ja linearised multistage-mallin eli suoraan kŠyttŠmŠllŠ EPAn CSF-arvoja) ja 2) laskee myšs omega-3-rasvahappojen tuoman hyšdyn sydŠnkuolemariskiin. Vertailu tehtiin 1) olettamalla lohensyšntiŠ 0.25 - 32 amerikkalaista annosta kuukaudessa ja laskemalla syšpŠriski ja/tai sydŠnhyšty sekŠ 2) olettamalla jokin lohensyšnti (esim. 20 g/d) ja lisŠksi jotain oletuksia muista omega-3-lŠhteistŠ sekŠ niiden muutoksista jos lohensyšnti muuttuisi. Vaikutuksen lisŠksi tehtiin argumenttianalyysi (oma moduli) jossa katsottiin importance analysis eli rank-korrelaatio lŠhtšmuuttujien ja lopputuleman vŠlille. TŠssŠ oli mukana erilaisia pŠŠtšksiŠ, mm. pitŠisikš katsoa saasteiden syšpŠhaittaa vai nettovaikutusta?, PitŠisikš katsoa terveysvastetta lainkaan vai pelkkŠŠ altistusta? ja MillŠ viljelty lohi pitŠisi korvata? PŠŠtškset otettiin mukaan analyysiin siten, ettŠ kullekin pŠŠtšsvaihtoehdolle oletettiin sama todennŠkšisyys, ja ne otettiin mukaan satunnaismuuttujina (ikŠŠn kuin me yrittŠisimme arvioida, mikŠ on ŠŠnestyksen tulos kun tŠstŠ ŠŠnestetŠŠn). TŠhŠn liittyen jŠin pohtimaan sitŠ, pitŠisikš meidŠn olettaa pienempi todennŠkšisyys huonoille vaihtoehdoille (kuten epŠtodennŠkšisille presidenttiehdokkaille annetaan vŠhemmŠn aikaa televisiossa) mutta en pŠŠtynyt tŠssŠ mihinkŠŠn lopputulokseen, ja niin tasajako jŠi malliin. LisŠksi on tehty VOI-analyysi (oma moduli). TŠssŠ yritin rakentaa VOI-funktiota, joka olisi suoraan laskenut mielenkiinnon kohteena olevan tuloksen (helpottaisi mallinrakennusta jatkossa ja tekisi erilaisten VOIn laskemisen kŠtevŠksi), mutta ongelmaksi muodostui se, ettŠ mean-funktio toimi oikein vain, kun se laskettiin variablesta. Jos yritti laskea sen tilapŠisestŠ, solmun sisŠllŠ olevasta muuttujasta, tuloksena oli yleensŠ mid. NiinpŠ tyydyttiin laskemaan homma kŠsipelillŠ kuten Particle VOI -mallissa. Conclusions from Hites 2004 sisŠltŠŠ sitaatteja ja argumentteja keskustelusta, joka on Hitesin myštŠ kŠynnistynyt. What should be the scope of the assessment oli aikeissa olla moduli, josta eri pŠŠtšsvaihtoehdot olisivat sinne kirjatun argumentoinnin seurauksena nousseet, mutta sitŠ ei ollut aikaa tyšstŠŠ kovin pitkŠlle. Confounder analysis -moduli sisŠltŠŠ pohdintaa siitŠ, millaiset tekijŠt voivat vaikuttaa Hitesin lopputulokseen ja kvalitatiivista argumentointia niiden mahdollisista vaikutuksista tulosten tulkintaan. Help on yksinkertaisesti kopio Help v4 mallista. 20.1. alkoi ongelmaksi tulla se, ettŠ malli ršnsysi liikaa, ja oli hankalaa saada indeksit tŠsmŠŠmŠŠn lŠhtšarvojen ja lopputuloksen kesken. NiinpŠ pŠŠtin tehdŠ uuden version 3, josta kaikki ršnsyt on poistettu ja jonka tarkoituksena on toimia mallina Science-artikkelia varten. Kaikki laajemmat tarkastelut siis sŠŠstetŠŠn mallin seuraaviin versioihin. NiinpŠ versio 2:een jŠtetŠŠn kaikki ršnsyt, josta niitŠ sitten voi tarpeen mukaan kopioida takaisin kŠytšssŠ olevaan malliversioon. NŠin ehkŠ pysyy selvŠnŠ se, mitŠ Science-vastineessa on ja mitŠ ei ole. Fishing and farming, Arguments on fish pollutants, Total pollutant exposure, What should be the scope of risk assessment?, Conclusions from Hites 2004, ja Confounder analysis ovat semmoiset modulit jotka nyt poistetaan versiosta 3. Samoin poistetaan pŠŠmodulista solmut Risk or net health effect?, Acceptable risk ja Health effects or exposures? sekŠ nŠiden input nodet. 0 504,128,1 48,12 2,463,67,476,399 65535,54067,19661 20.1.2003 Jouni Tuomisto Versiosta 3 siis on tehty riisuttu versio Science-juttua varten. Lue tarkemmin Loki v 2:sta. Nyt versiosta 3 poistetaan aiemmin kuvatun lisŠksi Other parts -modulista indeksejŠ, joita ei kŠytetŠ missŠŠn. NŠmŠ ovat Viljelyalue, Kalastusalue, Ostokaupunki, Lohilaji ja Saaste. Argument analysis -modulista poistetaan solmut We should not consider concentrations..., Acceptable exposure, Va2, Health or exposure?, What is salmon replacement?, Va5, Va3, Va3 inputs, Va3 importance eli kaikki solmut. TŠrkeyssolmu luodaan uudelleen, mutta nyt se voidaan tehdŠ suoraan Outcome-solmulle ilman indeksimuunnoksia. NiinpŠ koko Argument analysis -moduli poistetaan ja asia siirretŠŠn VOIs-moduliin, joka nimetŠŠn uudelleen VOI and importance analysis. Food intake -modulista poistetaan Salmon consumption, Salmon replacement, Food change, Salmon amount, Oil increase, Food intake, Wild salmon compensation, Va1, Food_rec, Source1. Eli kaikki solmut keskittyvŠt nyt vain loheen, eikŠ muita omega-3-lŠhteitŠ huomioida. Ne tulevat mukaan malliin raja-arvossa, joka kuvaa hyšdyllisen lisŠsaannin rajaa ja siis sisŠltŠŠ absoluuttisen fysiologisen rajan, josta on vŠhennetty muusta ravinnosta tuleva mŠŠrŠ. TŠmŠ solmu tehdŠŠn Annosvastemoduliin. VOIs-modulista poistetaan Va16, Va12, VOI, VOI1 ja VOI-laskenta tehdŠŠn suoraan Outcome-solmusta. 21.1.2004 Jouni Tuomisto Malli muuttui eilen siten, ettŠ nyt lasketaan VOI kahdelle eri kysymykselle: pitŠisikš suositella viljellyn lohen enimmŠissaanniksi 1 annos/kk ja pitŠisikš rajoittaa enemmŠn kalanrehun saastepitoisuuksia. NŠmŠ kaksi nostetaan esiin, koska edellinen on suora vastine Hitesin ym. argumenttiin, ja jŠlkimmŠinen on korostamassa sitŠ, ettŠ asetettu kysymys mŠŠrŠŠ sen, mikŠ tieto on tŠrkeŠŠ ja mikŠ ei. Other parts -modulista poistetaan solmut Acceptable exposure increase ja Amount or replacement, ja ARL siirretŠŠn Fish advirories -moduliin sekŠ Potency Exposure-response function for pollutant risk -moduliin. NŠistŠ moduleista poistetaan vastaavat aliakset. Unit- ja Description-kentŠt pŠivitetŠŠn koko mallissa, ja viitteitŠ listŠtŠŠn sikŠli kuin ne ovat helposti kŠsillŠ. Kuitenkin viitteet on vielŠ pistettŠvŠ kuntoon, nyt muotoilut eivŠt ole kunnossa. 0 504,152,1 48,12 2,212,144,476,344 65535,54067,19661 g/d H1900/H1909/H1910 504,224,1 48,24 [H1898,Salmon1] var a:= sum(H1900,Salmon1); Probability(a[H1898='BAU']+0.0001>a[H1898='Restrict farmed salmon use']) 504,336,1 48,24 2,115,372,476,291 var a:= sum(H1901,Salmon1); Probability(a[H1898='BAU']>a[H1898='Change farmed to wild salmon']) 504,280,1 48,24 index a:= ['Net effect of salmon recommendation','Net effect of feed regulation','Cancer effect of recommendation']; var b:= array(a,[H1901,0,H1900]); var c:= b[H1898='Restrict farmed salmon use']-b[H1898='BAU']; var d:= (if regulate_pollutants_=1 then c[H1899='More actions'] else c[H1899='BAU']); var e:= H1901[H1899='More actions'] - H1901[H1899='BAU']; var f:= (if recommend= 1 then e[H1898='Restrict farmed salmon use'] else e[H1898='BAU']); var g:= (if a= 'Net effect of feed regulation' then f else d); var h:= sum(g,Salmon1); h 232,264,1 48,24 2,452,264,476,469 2,767,202,367,474,0,MEAN probability A chance node that collapses the decision about whether the proper endpoint metric is pollutant risk or net health effect. Bernoulli( .5 ) 336,56,1 48,29 1,1,1,1,1,1,0,0,0,0 2,585,196,416,303,0,MIDM 2,168,178,416,303,0,SAMP cases/a Net health effect indexed by only consumption recommendation. if Regulate_pollutants_=1 then outcome3[H1899='More actions'] else outcome3[H1899='BAU'] 168,152,1 48,32 2,102,90,476,293 2,499,269,416,303,0,MIDM 2,415,126,518,378,0,MEAN [Salmon1,H1898] probability A chance node that collapses the decision about regulating fish feed. bernoulli(0.5) 56,152,1 48,24 cases/a Net health effect indexed by only fish feed regulation. if recommend = 1 then outcome3[H1898='Restrict farmed salmon use'] else outcome3[H1898='BAU'] 280,152,1 48,32 2,408,141,646,274 2,499,269,416,303,0,MIDM 2,77,202,518,378,0,MEAN [Salmon1,H1898] probability A chance node that collapses the decision about consumption recommendations for farmed salmon. bernoulli(0.5) 384,152,1 48,24 1,1,1,1,1,1,0,0,0,0 2,298,233,476,224 2,80,145,416,303,0,SAMP cases/a Net health effect indexed by the two decisions of concern: a) whether to recommend salmon consumption restrictions and b) whether to apply stricter regulations for fish feed. The definition contained also this row: if a>ARL then 1 else 0 But it was removed when we cut the acceptable concentration concept out of the model. var a:= (if Poll_or_net = 1 then H1900 else H1901); sum(a,Salmon1) 224,56,1 48,46 2,102,90,476,277 2,499,269,416,303,0,MIDM 2,723,592,518,176,0,MEAN [H1899,H1898] [1,0,0,0] 28.6.2004 Jouni Tuomisto This version is an update of the model that was used for calculating the results for Tuomisto paper submitted to Science on January 28, 2004. Only argumentation and comments have been clarified and added. No substantive changes have been made to definitions. The descriptions of the variables described in the Table 1 in 'Supportive online material' have not been changed. Therefore, this version produces the results that were presented in the manuscript. The main conclusions of this study were added as arguments on the top level of the model. The argumentation about the pollutant model selection was clarified (see module Fish advisories). 11.1.2005 Jouni Tuomisto The model was given a unified resource name (URN) and metadata. The only addition since 28.6.2004 is the node Urn and this note. 0 504,184,1 48,12 2,306,93,476,540 [Alias Log_v4] 65535,54067,19661 index benefit_risk: ['Benefits','Risks']; var a:= array(benefit_risk,[H1912,H1900]); a[Salmon1='Farmed salmon'H1899='BAU'] 72,264,1 48,42 2,20,7,551,791,1,MEAN [Sys_localindex('BENEFIT_RISK'),H1898,Undefined,Undefined,1] [0,0,0,0] [Recommendation,1,Sys_localindex('BR'),1,Sys_localindex('STEP'),1] 72,352,1 48,32 var a:= slice(Result_reporting,Result_reporting.decision,4); '"'&3000+run&'";"'&1&'";"'&a&'";"'&run&'"' 400,288,1 48,24 2,102,90,490,397 2,568,87,416,303,0,MIDM 2,I,4,2,0,0,4,0,$,0,"ABBREV",0 1..4000 56,32,1 48,24 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Calculate rows for the SQL result database. It assumes 1000 iterations. var a:= ['Business as usual','Recommend restrictions to salmon consumption','Stricter limits for fish feed pollutants','Restrictions to salmon consumption AND stricter fish feed limits']; var b:= floor((in2-1)/1000); '"'&in2&'";"1";"'&slice(a,a,b+1)&'"' 400,344,1 48,24 (param1) var a:= slice(Net_health_effects_i,net_health_effects_i.decision,4); '"'&3000+run&'";"'&1&'";"'&a&'";"'&run&'"' 56,88,1 48,24 2,102,90,476,224 param1 This node is used to report results from this model. Just replace the variable name on the first row with the variable you want to report and calculate. This node calculates the result only for farmed salmon, and it looks all four possible deicisions along one dimension (not 2*2 table). var a:= sample(H1909); a:= a[Salmon1='Farmed salmon']; index decision:= ['Business as usual','Recommend restrictions','Stricter rules for feed','Both']; a:= array(decision,[ slice(slice(a,H1898,1),H1899,1), slice(slice(a,H1898,2),H1899,1), slice(slice(a,H1898,1),H1899,2), slice(slice(a,H1898,2),H1899,2)]); index statistics:= ['Mean','SD','0.01','0.025','0.05','0.25','0.5 (Median)','0.75','0.95','0.975','0.99']; array(statistics,[mean(a), sdeviation(a), getfract(a,0.01), getfract(a,0.025), getfract(a,0.05), getfract(a,0.25), getfract(a,0.5), getfract(a,0.75), getfract(a,0.95), getfract(a,0.975), getfract(a,0.99)]) 232,328,1 48,24 2,102,90,476,485 2,362,39,568,303,0,MIDM [Sys_localindex('DECISION'),Sys_localindex('STATISTICS'),Undefined,Undefined,Undefined,1] 2,D,4,2,0,0,4,0,$,0,"ABBREV",0 [Pollutant1,1,Sys_localindex('STATISTICS'),1,Sys_localindex('DECISION'),1] µg/kg/d Pollutant exposure per body weight per day. H1903*H1904/1000/BW 256,272,1 48,24 1,1,1,1,1,1,0,,1, 2,287,149,476,224 2,72,47,653,399,0,MIDM [Salmon1,Pollutant1] [1,0,0,0] ktluser 11. Janta 2004 12:08 48,24 168,144,1 48,24 1,472,152,516,377,17 2,40,50,576,600 Rideout said that major feed companies have been able reduce toxin levels in their fish meal over the past several years by using substitute ingredients and less contaminated fish. ÒIt has been an issue that the industry is responding to. Feed companies have been working overtime to use high quality meals that are very low in contaminants and have twice the amount of omega-3sÉThe line is trending downward. We donÕt like having this in our product.Ó <ref>http://www.intrafish.com/articlea.php?articleID=41061&s=1</ref> Feed_backgr 328,48,1 64,36 2,102,90,720,332 var a:= (if H1899='More actions' then impr_in_feed else 0); Feed_backgr*(1-a) 192,128,1 48,29 1,1,1,1,1,1,0,,1, 2,291,326,636,303,0,SAMP [Undefined,H1899,Undefined,Undefined,Undefined,1] [1,0,0,0] H1902 192,240,1 60,44 Impr_in_feed+H1898+H1899 64,248,1 48,55 [Alias Should_we_change_fi1] - Pollutant concentrations in fish feed can be further reduced from current levels. The estimate of 0-100 % with a gradual decrease in probability density is based on author judgement. It reflects rather a theoretical range of improvement than a realistic estimate. Triangular( 0, 0, 1 ) 64,128,1 48,38 2,102,90,476,409 2,515,277,416,303,0,MIDM 2,216,226,416,303,1,CDFP 52425,39321,65535 - This is a dummy variable only, because the actual concentrations in fish feed are not needed in the current model. 1 192,48,1 48,24 52425,39321,65535 Two options are assumed for fish feed regulations: 1) business as usual (BAU) with current legislation, and 2) More restrictive regulations for fish feed, resulting in reduction of pollutant levels in feed and consequently in salmon. (This is irrespective of any trends unrelated to the decision). ['BAU','More actions'] 280,144,1 48,32 1,1,1,1,1,1,0,,1, ['BAU','More actions'] jtue 12. Janta 2004 8:51 48,24 504,336,1 48,42 1,76,122,586,421,17 probability/(g/d) Exposure-response function where also the uncertainty about the population that benefits from omega-3 is taken into account. var a:= Erf_hcrude*(if All_or_chd=1 then 1 else F_chd_pati); array(cause_of_death3,[a]) 200,248,1 52,44 1,1,1,1,1,1,0,,1, 2,291,175,476,224 2,136,146,489,288,0,MEAN Graphtool:0 Distresol:10 Diststeps:1 Cdfresol:5 Cdfsteps:1 Symbolsize:6 Baroverlap:0 Linestyle:1 Frame:1 Grid:1 Ticks:1 Mesh:1 Scales:1 Rotation:45 Tilt:0 Depth:70 Frameauto:1 Showkey:1 Xminimum:0 Xmaximum:1 Yminimum:0 Ymaximum:1 Zminimum:0 Zmaximum:1 Xintervals:0 Yintervals:0 Includexzero:0 Includeyzero:0 Includezzero:0 Statsselect:[1,1,1,1,1,0,0,0] Probindex:[0,0.01,0.05,0.25,0.5,0.75,0.95,0.99,1] [0,0,0,0] Erf_hcrude 336,152,1 52,56 All_or_chd 64,56,1 48,46 probability A large part of omega-3 benefit literature is based on studies on cardiac patients. This node reflects the uncertainty whether there is cardiac health benefit for everyone or only coronary heart disease (CHD) patients. The estimate is not based on data but the aim is to maximise uncertainty. Bernoulli( 0.5 ) 64,160,1 48,38 2,102,90,476,333 52425,39321,65535 fraction Fraction of coronary heart disease patients among the deaths. Current estimate is based on the fraction of cardiac deaths from total deaths in EEA countries, although there are cardiac deaths among non-CHD patients, and there are CHD patients with other causes of death. <ref>[http://www.who.int WHO data]</ref> 1.5717M/3.8664M 64,248,1 48,38 2,102,90,476,434 probability/(g/d) Dose-response function comes from secondary prevention trials reviewed by Din 2004 Table 1. The relative risk reductions are divided by the omega3 exposure in each study. A continuous distribution is used, and each study result is used as a quintile point for the distribution. Another review is Marckmann and Gronbaek 1999 that concluded that 0.6-0.9 g/d of omega-3 results in 40-60 % decrease in coronary heart disease mortality. The low estimate from this result was used (40% per 0.9 g/d). <ref>Din JN, Newby DE, Flapan AD. Science, medicine, and the future - Omega 3 fatty acids and cardiovascular disease - fishing for a natural treatment. British Medical Journal 2004; 328(7430):30-35. [http://ytoswww/yhteiset/Huippuyksikko/Kirjallisuus/Fish_and_health/Din_Omega3andCVD_BMJ2004.pdf Intranet file]</ref> <ref>Marckmann P, Gronbaek M. Fish consumption and coronary heart disease mortality. A systematic review of prospective cohort studies. European Journal of Clinical Nutrition 1999; 53(8):585-590.</ref> -Fractiles( [0/3.5,.325/1.5,.482/1.8,.297/0.85, 0.4/0.9 ]) 200,152,1 52,32 2,102,90,512,527 2,72,82,416,303,1,PDFP 52425,39321,65535 g/d Describes the amount of fish that is still beneficial when added to diet. After this limit, no extra benefit is assumed from omega-3 fatty acids. The value reflects both the physiological need of omega-3 and the current intake of omega-3 from other sources than salmon. Both parts of the estimate are complicated, and the latter varies from country to country. This might have implications to the decision if we could give country-wise recommendations of feed regulations. The estimate is based on author judgement. A rough idea about the magnitude comes from Din 2004, where the trials had 0.85 - 1.8 g/d of omega-3 with benefit but 3.5 g/d showed no benefit in a small trial where the population used reasonable amount of fish anyway. If the physiological limit is lower, the slope of the exposure-response function should be steeper. Another data comes from Albert 1998: the benefit may be limited to omega-3 doses <4.9 g/mo = 0.16 g/d. Markmann and Gronbaek concluded that 0.6-0.9 g/d is beneficial. <ref>Din JN, Newby DE, Flapan AD. Science, medicine, and the future - Omega 3 fatty acids and cardiovascular disease - fishing for a natural treatment. British Medical Journal 2004; 328(7430):30-35. [http://ytoswww/yhteiset/Huippuyksikko/Kirjallisuus/Fish_and_health/Din_Omega3andCVD_BMJ2004.pdf Intranet file]</ref> <ref>Albert CM, Hennekens CH, O'Donnell CJ, Ajani UA, Carey VJ, Willett WC et al. Fish consumption and risk of sudden cardiac death. Jama-Journal of the American Medical Association 1998; 279(1):23-28.</ref> <ref>Marckmann P, Gronbaek M. Fish consumption and coronary heart disease mortality. A systematic review of prospective cohort studies. European Journal of Clinical Nutrition 1999; 53(8):585-590.</ref> Triangular( .2, .5, 1 ) 496,64,1 48,38 2,135,16,476,598 52425,39321,65535 ['Cardiovascular'] 200,304,1 56,12 Pieta 16. tamta 2004 1:32 48,24 136,336,1 48,51 1,141,229,418,300,17 (mg/kg/d)^Æ1 Potency of pollutants. Cancer slope factors (CSF) are used for cancer and Reference Dose (RfD) values are used for non-cancer endpoints. The data comes from the U.S.EPA. <ref>U.S.EPA. Guidance for Assessing Chemical Contaminant Data for Use in Fish Advisory. Volume 2: Risk Assessment and Fish Consumption Limits, 3rd Edition. 2000. Table 3-1. [http://www.epa.gov/waterscience/fish/guidance.html Open access Internet file]</ref> <ref>[http://ytoswww/yhteiset/Huippuyksikko/Kirjallisuus/Fish_and_health/EPAFishAdvisory/ Intranet file]</ref> Table(Pollutant1,Self)( 16,50u, 1.1,250u, 156K,0, 2,20u ) ['Ca (CSF)','Non-Ca (RfD)'] 64,40,1 48,24 2,249,11,476,457 2,480,276,416,303,0,MIDM 2,103,144,416,303,0,MIDM [Alias Potency1] 65535,52427,65534 [Self,Pollutant1] [Self,Pollutant1] [1,0,0,0] (mg/kg/d)-1 The response assessment is restricted to cancer endpoints, because it is the more sensitive endpoint. potency[Potency='Ca (CSF)'] 64,128,1 48,38 1,1,1,1,1,1,0,,1, 2,102,90,476,399 2,499,251,655,303,0,MIDM [0,0,0,0] H1906 232,128,1 72,72 2,436,19,476,224 jtue 16. Janta 2004 12:54 48,24 320,208,1 48,24 1,81,109,605,297,17 ÒWeÕre telling people that if they want to reduce their risk of cancer, they should not eat more than one meal of farmed salmon a month,Ó Carpenter said. He added that the cancer risk from the toxins effectively cancels out the benefits of omega-3 fatty acids found in farmed salmon, which have not been proven to prevent or reduce the risk of cancer. ÒThere are other places to get omega-3s - wild salmon, other fish, canola oil, flaxseed oil,Ó Carpenter said. <ref>[http://www.intrafish.com/articlea.php?articleID=41061&s=1 Intrafish.com press release 9 Jan 2004]</ref> F 120,56,1 60,44 2,102,90,609,347 g/d Data comes from EPIC study looking at fish consumption in 10 European countries by gender. We take the minimum, the unweighed average and the maximum of these values in the distribution to represent uncertainty in population average fatty fish intake. All fatty fish is assumed to be salmon. <ref>Welch AA, Lund E, Amiano P, Dorronsoro M. Variability in fish consumption in 10 European countries. In: Riboli E, Lambert R, editors. Nutrition and lifestyle: opportunities for cancer prevention. Lyon: International Agency for Research on Cancer, 2002: 221-222. [http://ytoswww/yhteiset/Huippuyksikko/Kirjallisuus/Fish_and_health/RiboliNutritionLifestyle_IARC156_2002.pdf PDF of article] [http://ytoswww/yhteiset/Huippuyksikko/Tutkimus/Viljelylohi/Materiaali/ConsumptionOfFish.xls Data in Excel]</ref> Triangular( 7.5, 15.3, 31 ) 352,48,1 48,38 2,376,70,476,496 2,0,0,793,492,0,MEAN [Chance Welch_et_al_2002] [1,0,0,0] fraction Fraction of farmed salmon of total salmon consumption in Western Europe. The current estimate is based on author judgement after discussions with people from the Finnish Game and Fisheries Research Institute. Uniform( .8, 1 ) 248,48,1 52,44 2,102,90,476,367 g/d Intake of farmed and wild salmon after the two decisions (regulate fish feed pollutants / recommend restrictions for farmed salmon use) has been made. Although market salmon exists in the index, it is not used in this version of the model. Wild salmon use after restricting farmed salmon use has a triangular probability distribution. Min assumes the same relative decrease as in farmed salmon; mode assumes no change; max assumes that wild salmon intake increases so much that it totally compensates the decrease in farmed salmon use. Estimates are based on author judgement. The wild salmon production capacity is probably much than the max used for the variable. This overestimation causes bias towards smaller costs due to salmon use restrictions. Table(Salmon1,H1899,H1898)( F,(A*F), (F+Pollutant_scare),((A*F)+Pollutant_scare), W,Triangular((A*W),W,(W+((1-A)*F))), W,Triangular((A*W),W,(W+((1-A)*F))), 0,0, 0,0 ) 248,216,1 48,24 1,1,1,1,1,1,0,,1, 2,516,77,476,224 2,58,276,500,232,0,MIDM 2,248,258,443,303,1,PDFP [H1898,Salmon1] [Undefined,H1898,Undefined,Undefined,1] [Index Salmon1] [1,0,0,0] g/d Average farmed salmon consumption in Western Europe in the base case. Fraction_farmed*crude_salmon 248,144,1 48,29 2,469,178,476,300 g/d Average wild salmon consumption in Western Europe in the base case. (1-Fraction_farmed)*crude_salmon 352,144,1 48,24 fraction Farmed salmon use per baseline after a recommendation to restrict farmed salmon use. A uniform distribution between 1 American meal/month (227 g) and no change to baseline. If baseline is lower than the recommendation, no change occurs. var a:= 1*227/(365.25/12); var b:= min([a/f,1]); uniform(b,1) 128,144,1 56,36 2,264,94,476,252 2,552,65,424,320,0,MIDM g/d Change in farmed salmon use when fish feed is more strictly regulated. Consumer may consume more salmon, when pollutant problems are handled. However, there is a possibility of bad reputation ('There is a big problem, because authorities have to intervene'). The range overlaps zero to reflect this uncertainty. The expectation is slightly positive. The estimate is based on author judgement. Triangular( -1, 0.5, 1 ) 128,216,1 52,32 2,151,377,416,303,1,PDFP <ref>Welch AA, Lund E, Amiano P, Dorronsoro M. Variability in fish consumption in 10 European countries. In: Riboli E, Lambert R, editors. Nutrition and lifestyle: opportunities for cancer prevention. Lyon: International Agency for Research on Cancer, 2002: 221-222. [http://ytoswww/yhteiset/Huippuyksikko/Kirjallisuus/Fish_and_health/RiboliNutritionLifestyle_IARC156_2002.pdf PDF of article] [http://ytoswww/yhteiset/Huippuyksikko/Tutkimus/Viljelylohi/Materiaali/ConsumptionOfFish.xls Data in Excel]</ref> 0 472,48,1 48,24 2,102,90,476,379 2,40,50,416,303,0,MIDM 65535,52427,65534 [Chance Crude_salmon] A decision about whether a general recommendation should be given to restrict the consumption of European farmed salmon to one meal (227 g) per month or not (business as usual, BAU). ['BAU','Restrict farmed salmon use'] 424,144,1 76,32 1,1,1,1,1,1,0,,1, 2,102,90,476,354 ['BAU','Restrict farmed salmon use'] g/g Omega-3 fatty acid content in salmon. Estimate is from Din 2004 Table 2. In a previous version, there were other fish types as well: min is the lowest value, max is the highest value and mode is the average of the two. <ref>Din JN, Newby DE, Flapan AD. Science, medicine, and the future - Omega 3 fatty acids and cardiovascular disease - fishing for a natural treatment. British Medical Journal 2004; 328(7430):30-35. [http://ytoswww/yhteiset/Huippuyksikko/Kirjallisuus/Fish_and_health/Din_Omega3andCVD_BMJ2004.pdf Intranet file]</ref> array(Year3,[Uniform(0.0128,0.0215)]) 464,216,1 48,32 1,1,1,1,1,1,0,0,1,0 2,102,90,476,445 2,106,70,416,303,0,MIDM 2,472,482,416,303,0,MIDM 52425,39321,65535 [1,0,0,0] g/d Omega-3 fatty acid intake from salmon. H1904*H1907 384,272,1 48,24 1,1,1,1,1,1,0,,1, 2,102,90,476,224 2,57,94,723,303,0,MIDM [H1898,Salmon1] [1,0,0,0] [H1899,1,Year3,1,Salmon1,1,H1898,1] jtok 16. tamta 2004 22:14 48,24 168,208,1 48,24 1,439,232,556,308,17 µg/kg Pollutant concentration data from Hites et al, Fig 2. <ref>Hites RA, Foran JA, Carpenter DO, Hamilton MC, Knuth BA, Schwager SJ. Global assessment of organic contaminants in farmed salmon. Science 2004; 303(5655):226-229. [http://ytoswww/yhteiset/Huippuyksikko/Kirjallisuus/Fish_and_health/HitesRA%26al_Science2004.pdf Intranet file]</ref> Table(Location1,Pollutant1)( 5.607,160.008,2.94m,50.904, 5.607,190.0095,2.5725m,48.177, 6.8085,136.6735,2.52m,47.268, 3.738,126.673,2.31m,49.995, 4.539,113.339,2.31m,41.814, 4.9395,150.0075,1.995m,37.269, 3.6045,93.338,2.52m,46.359, 4.4055,153.341,2.1m,34.542, 3.204,66.67,1.7325m,39.087, 2.5365,43.3355,1.89m,34.1784, 3.3375,70.0035,1.4175m,29.997, 2.8035,43.3355,1.449m,34.542, 2.5365,36.6685,1.5225m,34.542, 2.403,36.6685,1.3545m,32.724, 2.0025,30.0015,1.554m,26.361, 1.7355,32.0016,1.1025m,21.816, 2.0025,58.6696,840u,12.726, 1.2015,23.3345,1.344m,22.725, 1.2015,23.3345,945u,18.18, 1.2015,26.668,787.5u,15.453, 0.9345,14.6674,1.344m,21.816, 1.068,18.6676,892.5u,21.816, 1.2015,53.336,1.575m,7.272, 0.801,18.6676,1.155m,14.544, 0.534,20.6677,430.5u,15.453, 0.6675,23.3345,315u,7.272, 0.534,26.668,283.5u,8.181, 0.4806,20.001,315u,6.363, 0.4806,13.334,735u,9.09, 0.4005,16.6675,178.5u,4.545, 0.267,13.334,210u,3.636, 0.4005,14.0007,105u,3.636, 0.4005,15.3341,105u,3.636, 0.4005,12.0006,126u,3.636, 0.4005,10.0005,105u,2.727, 0.4005,10.0005,105u,1.818, 0.267,6.667,105u,1.818, 0.267,6.667,105u,1.818, 0.267,6.667,105u,1.818 ) 56,48,1 48,29 2,354,132,476,475 2,17,12,416,638,0,MIDM [Alias Pollutants_in_salmo2] 65535,52427,65534 [Pollutant1,Location1] [Pollutant1,Location1] , , , [1,0,0,0] µg/kg Pollutant concentrations in salmon Poll_i_types*H1902 312,112,1 48,24 1,1,1,1,1,1,0,,1, [Salmon1,Pollutant1] [1,0,0,0] [Reg_poll,2,Pollutant1,1,Salmon1,1] Data from Hites classified based on salmon type (farmed, wild, market) Table(Location1,Self)( 'Farmed salmon','Europe', 'Farmed salmon','Europe', 'Market salmon','Europe', 'Market salmon','Europe', 'Farmed salmon','Europe', 'Market salmon','Europe', 'Market salmon','Europe', 'Market salmon','Europe', 'Farmed salmon','North America', 'Market salmon','North America', 'Farmed salmon','North America', 'Market salmon','North America', 'Farmed salmon','North America', 'Market salmon','North America', 'Market salmon','North America', 'Market salmon','North America', 'Market salmon','North America', 'Market salmon','North America', 'Market salmon','North America', 'Market salmon','North America', 'Farmed salmon','North America', 'Farmed salmon','South America', 'Wild salmon','North America', 'Market salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America', 'Wild salmon','North America' ) ['Type','Region'] 56,112,1 48,24 2,102,90,476,395 2,72,82,416,614,0,MIDM 52425,39321,65535 [Self,Location1] [Self,Location1] µg/kg Dieldrin, toxaphene, PCB, and dioxin concentrations in farmed, wild, and market salmon. Triangular probability distribution is used for each pollutant and salmon type. Estimates are based on data from Hites 2004. Parameters min, mode, and max are the minimum, average, and maximum of Hites' data, respectively. var typ:= salmon_type[salmon_type='Type']; var a:= (if Salmon1=typ then poll_salmon_hites else 0); var b:= (if Salmon1=typ then 1 else 0); var c:= max(a,location1); var d:= sum(a,location1)/sum(b,location1); var e:= (if Salmon1=typ then poll_salmon_hites else 1M); var f:= min(e,location1); triangular(f,d,c) 192,113,1 48,38 2,36,56,476,309 2,489,195,416,303,1,PDFP jtue 28. Junta 2004 18:03 48,24 488,40,1 48,24 1,0,1,1,1,1,0,,0, 1,40,0,517,300,17 µg/kg Triangular probability distribution for concentrations indexed by salmon type AND THE THREE REGIONS based on data from Hites 2004. Min is the minimum of Hites, Max is the maximum of Hites, and Mode is the average of Hites. Currently not used, but probably we should look at European values, because the consumption and population data comes from Europe. var typ:= salmon_type[salmon_type='Type']; var reg:= salmon_type[salmon_type='Region']; var a:= (if typ=Salmon1 and reg=Region then poll_salmon_hites else 0); var b:= sum((if typ=Salmon1 and reg=Region then 1 else 0),location1); var c:= max(a,location1); var d:= if b>0 then sum(a,location1)/b else 0; var e:= (if Salmon1=salmon_type then poll_salmon_hites else 1M); var f:= min(e,location1); d 56,32,1 48,29 2,102,90,476,402 2,72,82,451,390,0,MIDM [Salmon1,Pollutant1] The three regions considered in Hites et al 2004. ['Europe','North America','South America'] 56,72,1 48,12 µg/kg Triangular probability distribution for concentrations indexed by salmon type based on data from Hites et al, 2004. Min is the minimum, Mode is the average, and Max is the maximum calculated for each salmon type (farmed, wild, and market) separately. var typ:= salmon_type[salmon_type='Type']; var a:= (if Salmon1=typ then poll_salmon_hites else 0); var b:= (if Salmon1=typ then 1 else 0); var c:= max(a,location1); var d:= sum(a,location1)/sum(b,location1); var e:= (if Salmon1=typ then poll_salmon_hites else 1M); var f:= min(e,location1); index x:=['Min','Mode','Max']; array(x,[f,d,c]) 56,136,1 48,38 2,102,90,476,365 2,561,214,416,303,0,MIDM 1,D,4,2,0,0 cases/a Total mortality in European Economic Area countries (386.63 million inhabitants) <ref>[http://www.who.int WHO data]</ref> array(Year3,[3.8664M]) 136,424,1 48,32 1,1,1,1,1,1,0,,1, 2,102,90,476,330 65535,52427,65534 [1,1,0,1] cases/a Coronary heart disease mortality in European Economic Area countries (386.63 million inhabitants). The estimate consists of acute myocardial infarction and other ischaemic heart diseases (ICD 10: 270, 279). <ref>[http://www.who.int WHO data]</ref> array(Year3,[615.3k]) 504,416,1 48,32 1,1,1,1,1,1,0,,1, 2,102,90,476,224 65535,52427,65534 [1,1,0,1] 1 568,145,1 48,61 Should_we_change_fis 1 760,144,1 52,12 65535,54067,19661 Loki_v4 H1901+H1900 256,488,1 60,51 65535,65532,19661 H1898+V3 424,51,1 64,51 65535,65532,19661 H1899+V1 280,48,1 72,42 65535,65532,19661 DC-attribute with refinement Scheme (if any) Value Title Risk benefit analysis of eating farmed salmon Creator.personalName Tuomisto, Jouni T Creator.personalName Tuomisto, Jouko Creator.personalName Tainio, Marko Creator.personalName Niittynen, Marjo Creator.personalName Verkasalo, Pia Creator.personalName Vartiainen, Terttu Creator.personalName Kiviranta, Hannu Creator.personalName Pekkanen, Juha Subject risk benefit analysis Subject persistent organic pollutants Subject omega-3 fatty acids Subject MeSH polychlorinated biphenyls Subject MeSH salmon Subject MeSH risk assessment Subject MeSH fatty acids, omega-3 Subject UDC 614 Public health and hygiene. Description.abstract In their Report ÒGlobal assessment of organic contaminants in farmed salmon,Ó R. A. Hites and co-workers analyzed wild and farmed salmon samples from North and South America and Europe for organic pollutants (9 Jan. 2004, p. 226). The authors conclude that, because of chemical contaminants, farmed salmon should not be eaten more often than 0.25 to 1 times per month. However, the model used does not take into account any beneficial effects of eating fish. We analyzed both risks and benefits. We also performed a value-of-information analysis to see which uncertainties were relevant for decision-making. This is the version 4 of the model calculating risks and benefits of farmed salmon. (c) Copyright Kansanterveyslaitos (KTL; National Public Health Institute, Finland). Publisher Kansanterveyslaitos Date.issued W3C-DTF 2004-07-23 Type DCMIType Software Format IMT text/xml Format.medium computerFile Format 115 kB Identifier http://www.ktl.fi/risk Identifier URN URN:NBN:fi-fe20042774 Language ISO639-2 en Relation.hasPart URL http://www.sciencemag.org/cgi/content/full/305/5683/476 Rights Copyright Kansanterveyslaitos, 2004 0 744,176,1 80,12 2,102,90,523,439 65535,54067,19661 [2000] 504,456,1 48,12 The node Variables_to_be_saved in the module RDB-connection.ANA from Heande should contain the following: Var_name Probabilistic? 'H1898' 0 'H1899' 0 'H1900' 1 'H1901' 1 'H1902' 1 'H1903' 1 'H1904' 1 'H1905' 1 'H1906' 0 'H1907' 1 'H1908' 1 'H1909' 1 'H1910' 0 'H1911' 0 'H1912' 1 760,32,1 48,24 65535,54067,19661