Disease risk

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Question

What are incidence or prevalence rates of different diseases in Finland?

Answer

+ Show code- Hide code library(OpasnetUtils) # A package with Opasnet functionalities library(xtable) # A package with table formats library(ggplot2) # A package with fancy graph formats objects.latest("Op_en5917", "initiate") # Get the latest ovariables from code calculations on page Op_en5917. diseaseRisk <- EvalOutput(diseaseRisk) oprint(summary(diseaseRisk)) ggplot(diseaseRisk@output, # Show a bar chart aes(x = Disease, y = diseaseRiskResult, fill = Response.metric)) + geom_bar(position="dodge") + theme_grey(base_size = 24) + theme(axis.text.x = element_text(angle = 90, hjust = 1)) + scale_y_log10() # limits = c(1, 1000000))

----#: . Code seems to work, but gives out the yellow errorbox. --Heta 13:02, 27 August 2013 (EEST) (type: truth; paradigms: science: comment)

Rationale

Data

Goherr data from IHME

This is temporary data used because IHME database is down. Otherwise this is OK data but the age groups are wrong.

Show details

Goherr IHME(DALY) Obs Location Year Age Sex Cause Measure Value Lower Upper 1 Finland 2017 70+ years Male Ischemic heart disease DALYs 56315.2751679953 52039.4175530624 61341.2067999029 2 Finland 2017 70+ years Male Breast cancer DALYs 79.5125008547994 65.7423816474743 95.9723869500564 3 Finland 2017 70+ years Male Male infertility DALYs 0 0 0 4 Finland 2017 70+ years Male Major depressive disorder DALYs 1428.95241428931 973.154944650354 1965.01460302962 5 Finland 2017 70+ years Female Ischemic heart disease DALYs 44695.727780164 40951.1264856603 49402.0724715572 6 Finland 2017 70+ years Female Breast cancer DALYs 7307.95842859461 6495.79803708212 8289.58210032476 7 Finland 2017 70+ years Female Male infertility DALYs 0 0 0 8 Finland 2017 70+ years Female Major depressive disorder DALYs 3170.15462206651 2212.34454065649 4271.11690891755 9 Sweden 2017 70+ years Male Ischemic heart disease DALYs 84813.2727063192 78488.7802601174 94342.3940640882 10 Sweden 2017 70+ years Male Breast cancer DALYs 166.425451145263 143.842420064141 190.323295569784 11 Sweden 2017 70+ years Male Male infertility DALYs 0 0 0 12 Sweden 2017 70+ years Male Major depressive disorder DALYs 2776.96336665194 1883.43402071075 3844.83811585326 13 Sweden 2017 70+ years Female Ischemic heart disease DALYs 66243.3017632682 60735.3522390338 73795.2100259806 14 Sweden 2017 70+ years Female Breast cancer DALYs 14735.1837886885 13321.1902732261 16308.9362684012 15 Sweden 2017 70+ years Female Male infertility DALYs 0 0 0 16 Sweden 2017 70+ years Female Major depressive disorder DALYs 6473.84464110293 4372.26104767627 8821.87748679089 17 Denmark 2017 70+ years Male Ischemic heart disease DALYs 32582.127899933 29783.6905112799 35839.0086187017 18 Denmark 2017 70+ years Male Breast cancer DALYs 130.596378204639 107.924780754222 155.920222130995 19 Denmark 2017 70+ years Male Male infertility DALYs 0 0 0 20 Denmark 2017 70+ years Male Major depressive disorder DALYs 1066.05892620269 725.577404075283 1482.81231447922 21 Denmark 2017 70+ years Female Ischemic heart disease DALYs 24090.9132487552 21989.677152409 26565.4514079687 22 Denmark 2017 70+ years Female Breast cancer DALYs 10242.0078233568 9119.80489372234 11427.018587514 23 Denmark 2017 70+ years Female Male infertility DALYs 0 0 0 24 Denmark 2017 70+ years Female Major depressive disorder DALYs 2171.19978394934 1437.372134315 2990.45116223703 25 Estonia 2017 70+ years Male Ischemic heart disease DALYs 14468.2575037341 12278.6173595973 19065.7939752037 26 Estonia 2017 70+ years Male Breast cancer DALYs 13.9915147948632 11.2727498977976 17.2268209225218 27 Estonia 2017 70+ years Male Male infertility DALYs 0 0 0 28 Estonia 2017 70+ years Male Major depressive disorder DALYs 404.820723283056 268.484534476474 552.48618357069 29 Estonia 2017 70+ years Female Ischemic heart disease DALYs 21287.8843781331 17417.4579274491 29647.6233887735 30 Estonia 2017 70+ years Female Breast cancer DALYs 1499.20925222737 1244.75926523047 1811.1359220894 31 Estonia 2017 70+ years Female Male infertility DALYs 0 0 0 32 Estonia 2017 70+ years Female Major depressive disorder DALYs 1695.08052475147 1152.34126068759 2367.50790585401 33 Finland 2017 50-69 years Male Ischemic heart disease DALYs 42276.5956099849 38357.8144003007 47482.370958431 34 Finland 2017 50-69 years Male Breast cancer DALYs 85.4020580685615 70.0618057377157 103.914438376935 35 Finland 2017 50-69 years Male Male infertility DALYs 0 0 0 36 Finland 2017 50-69 years Male Major depressive disorder DALYs 3190.66750516571 2174.54597309043 4407.09165796333 37 Finland 2017 50-69 years Female Ischemic heart disease DALYs 9151.64268177568 8120.35615665832 10335.0574654037 38 Finland 2017 50-69 years Female Breast cancer DALYs 10949.5708224826 9639.19910363983 12400.1943791976 39 Finland 2017 50-69 years Female Male infertility DALYs 0 0 0 40 Finland 2017 50-69 years Female Major depressive disorder DALYs 5952.28149167875 4014.75910813902 8082.75060035307 41 Sweden 2017 50-69 years Male Ischemic heart disease DALYs 46381.2915355143 42895.3155913912 50149.0969921018 42 Sweden 2017 50-69 years Male Breast cancer DALYs 138.429419109987 120.573610857783 159.716966293469 43 Sweden 2017 50-69 years Male Male infertility DALYs 0 0 0 44 Sweden 2017 50-69 years Male Major depressive disorder DALYs 5564.10649957795 3774.79128645748 7704.14153993077 45 Sweden 2017 50-69 years Female Ischemic heart disease DALYs 14670.3608398164 13160.9153559661 16176.2758647884 46 Sweden 2017 50-69 years Female Breast cancer DALYs 18248.4394354961 16517.9364702388 20302.9834072412 47 Sweden 2017 50-69 years Female Male infertility DALYs 0 0 0 48 Sweden 2017 50-69 years Female Major depressive disorder DALYs 11589.8948100489 7876.40918409439 16145.1421058479 49 Denmark 2017 50-69 years Male Ischemic heart disease DALYs 22096.2514806926 20074.9812036842 24509.6274297806 50 Denmark 2017 50-69 years Male Breast cancer DALYs 129.843042512704 107.405626102942 154.990062169289 51 Denmark 2017 50-69 years Male Male infertility DALYs 0 0 0 52 Denmark 2017 50-69 years Male Major depressive disorder DALYs 2327.91236686164 1566.40514944963 3250.65401544039 53 Denmark 2017 50-69 years Female Ischemic heart disease DALYs 6676.18685202032 5870.69427978746 7557.0354822643 54 Denmark 2017 50-69 years Female Breast cancer DALYs 13616.0427914127 12052.8323377586 15358.4253745665 55 Denmark 2017 50-69 years Female Male infertility DALYs 0 0 0 56 Denmark 2017 50-69 years Female Major depressive disorder DALYs 4276.06113976365 2829.34783268566 5929.14221511685 57 Estonia 2017 50-69 years Male Ischemic heart disease DALYs 13411.385994707 11065.1657683079 17133.7498839334 58 Estonia 2017 50-69 years Male Breast cancer DALYs 21.0241213496356 16.7119870749367 27.3554075919703 59 Estonia 2017 50-69 years Male Male infertility DALYs 0 0 0 60 Estonia 2017 50-69 years Male Major depressive disorder DALYs 816.865242466261 548.38222836745 1145.38871022423 61 Estonia 2017 50-69 years Female Ischemic heart disease DALYs 4144.34200290187 3303.84643620184 5523.53032628345 62 Estonia 2017 50-69 years Female Breast cancer DALYs 2632.91853815089 2156.36536339054 3187.12586050396 63 Estonia 2017 50-69 years Female Male infertility DALYs 0 0 0 64 Estonia 2017 50-69 years Female Major depressive disorder DALYs 1887.28792016728 1243.4179405901 2663.46643599906 65 Finland 2017 15-49 years Male Ischemic heart disease DALYs 4371.12829182068 3772.34266754555 5126.73061869348 66 Finland 2017 15-49 years Male Breast cancer DALYs 16.2470612343585 13.4431459123292 19.6547217693856 67 Finland 2017 15-49 years Male Male infertility DALYs 51.9975394298735 20.8958481322993 111.399655173724 68 Finland 2017 15-49 years Male Major depressive disorder DALYs 7168.79085587972 4935.18840053274 9817.88686578686 69 Finland 2017 15-49 years Female Ischemic heart disease DALYs 777.521660579127 654.222779373356 919.047276971295 70 Finland 2017 15-49 years Female Breast cancer DALYs 2952.82488092842 2548.53759197005 3432.89762799478 71 Finland 2017 15-49 years Female Male infertility DALYs 0 0 0 72 Finland 2017 15-49 years Female Major depressive disorder DALYs 11845.1840388046 8059.512552842 16108.4069979906 73 Sweden 2017 15-49 years Male Ischemic heart disease DALYs 6390.23902385725 5721.11008810619 7074.19961681548 74 Sweden 2017 15-49 years Male Breast cancer DALYs 32.9566477433603 28.487636295462 38.333137930806 75 Sweden 2017 15-49 years Male Male infertility DALYs 175.251628532079 73.2111086306143 367.325147605812 76 Sweden 2017 15-49 years Male Major depressive disorder DALYs 12259.5665246884 8227.22079584067 16771.6562226033 77 Sweden 2017 15-49 years Female Ischemic heart disease DALYs 1761.31810163589 1523.88800521899 2044.99756581175 78 Sweden 2017 15-49 years Female Breast cancer DALYs 6562.93942398197 5845.48662842491 7393.76129490786 79 Sweden 2017 15-49 years Female Male infertility DALYs 0 0 0 80 Sweden 2017 15-49 years Female Major depressive disorder DALYs 23149.4555815204 15588.7292304234 31917.3334632912 81 Denmark 2017 15-49 years Male Ischemic heart disease DALYs 3087.54782440886 2681.75182824144 3576.05936601009 82 Denmark 2017 15-49 years Male Breast cancer DALYs 21.7271192198948 17.6438171995736 26.5335073839654 83 Denmark 2017 15-49 years Male Male infertility DALYs 50.7909213036205 21.091263300572 107.50418333984 84 Denmark 2017 15-49 years Male Major depressive disorder DALYs 4576.80448307599 3091.74660704673 6359.88141230732 85 Denmark 2017 15-49 years Female Ischemic heart disease DALYs 708.929505164451 591.710074747954 835.40183408209 86 Denmark 2017 15-49 years Female Breast cancer DALYs 3755.79556167266 3219.92222825708 4341.32283992948 87 Denmark 2017 15-49 years Female Male infertility DALYs 0 0 0 88 Denmark 2017 15-49 years Female Major depressive disorder DALYs 6783.13672181049 4666.10282936231 9336.80141971734 89 Estonia 2017 15-49 years Male Ischemic heart disease DALYs 2025.57897224232 1573.16945245311 2574.3004955086 90 Estonia 2017 15-49 years Male Breast cancer DALYs 6.12351207334238 4.68005012454053 8.02649693591355 91 Estonia 2017 15-49 years Male Male infertility DALYs 35.1621911688859 14.6774923254009 72.2171832280172 92 Estonia 2017 15-49 years Male Major depressive disorder DALYs 1202.31831942663 803.765818126241 1656.53575033105 93 Estonia 2017 15-49 years Female Ischemic heart disease DALYs 346.673111522234 277.239180576975 432.02444008093 94 Estonia 2017 15-49 years Female Breast cancer DALYs 864.30923397303 682.985709118727 1092.44325680511 95 Estonia 2017 15-49 years Female Male infertility DALYs 0 0 0 96 Estonia 2017 15-49 years Female Major depressive disorder DALYs 1627.31555869184 1099.29556724111 2271.75540111025 97 Finland 2017 15-49 years Male All causes DALYs 207520.417986606 173800.459870437 246485.886492573 98 Finland 2017 15-49 years Female All causes DALYs 179570.112766941 141696.388607952 223561.073482014 99 Sweden 2017 15-49 years Male All causes DALYs 328999.874009797 269009.02778272 397534.051032743 100 Sweden 2017 15-49 years Female All causes DALYs 337360.262638401 265987.028656637 419970.815044994 101 Denmark 2017 15-49 years Male All causes DALYs 193274.681794909 158246.181525335 234051.24509321 102 Denmark 2017 15-49 years Female All causes DALYs 190594.731341407 150901.921196675 237443.167655282 103 Estonia 2017 15-49 years Male All causes DALYs 69026.686965026 58786.9765970678 80337.4437174382 104 Estonia 2017 15-49 years Female All causes DALYs 45203.5533162381 35815.5251350863 55283.804477302 105 Finland 2017 50-69 years Male All causes DALYs 319553.746559688 283600.533071296 363007.156188649 106 Finland 2017 50-69 years Female All causes DALYs 227095.430231189 191948.034855314 266925.024609513 107 Sweden 2017 50-69 years Male All causes DALYs 411896.345413221 358095.981854878 470932.059240055 108 Sweden 2017 50-69 years Female All causes DALYs 358307.07644009 303651.782623776 422462.343652292 109 Denmark 2017 50-69 years Male All causes DALYs 306525.500595414 269724.366774415 347072.617315533 110 Denmark 2017 50-69 years Female All causes DALYs 249614.253675992 215496.006811696 288848.658620397 111 Estonia 2017 50-69 years Male All causes DALYs 95590.2213561366 83973.1314955263 108501.32425046 112 Estonia 2017 50-69 years Female All causes DALYs 65574.802626921 54971.5536727616 76859.8924171885 113 Finland 2017 70+ years Male All causes DALYs 296163.511449765 271043.235542343 325942.434372211 114 Finland 2017 70+ years Female All causes DALYs 323901.430063555 289291.161232524 360525.097921403 115 Sweden 2017 70+ years Male All causes DALYs 521754.839865746 475866.923082829 573068.492503427 116 Sweden 2017 70+ years Female All causes DALYs 553113.744537967 498776.385385165 612584.75317485 117 Denmark 2017 70+ years Male All causes DALYs 301411.076878031 275069.907426085 329950.516220028 118 Denmark 2017 70+ years Female All causes DALYs 311645.293827931 282687.607561216 344758.408912781 119 Estonia 2017 70+ years Male All causes DALYs 61683.0064170076 55169.0392665845 68662.0565953199 120 Estonia 2017 70+ years Female All causes DALYs 98562.5248095964 86395.6371440109 111761.042667796 121 Finland 2017 70+ years Male Ischemic heart disease YLLs 53423.9737096138 49220.248497233 58589.2770589416 122 Finland 2017 70+ years Male Breast cancer YLLs 69.0581851085494 57.1271065440948 83.268764723987 123 Finland 2017 70+ years Male Male infertility YLLs 0 0 0 124 Finland 2017 70+ years Male Major depressive disorder YLLs 0 0 0 125 Finland 2017 70+ years Female Ischemic heart disease YLLs 42205.2336255192 38518.5123268345 46737.7280077635 126 Finland 2017 70+ years Female Breast cancer YLLs 6179.25921126402 5477.90310062408 6946.75749694254 127 Finland 2017 70+ years Female Male infertility YLLs 0 0 0 128 Finland 2017 70+ years Female Major depressive disorder YLLs 0 0 0 129 Sweden 2017 70+ years Male Ischemic heart disease YLLs 79149.1322439883 72787.710870278 88683.4828117565 130 Sweden 2017 70+ years Male Breast cancer YLLs 144.188862195848 127.022587414152 163.526372791302 131 Sweden 2017 70+ years Male Male infertility YLLs 0 0 0 132 Sweden 2017 70+ years Male Major depressive disorder YLLs 0 0 0 133 Sweden 2017 70+ years Female Ischemic heart disease YLLs 61434.6515681342 56224.6698333815 68660.9509116311 134 Sweden 2017 70+ years Female Breast cancer YLLs 12513.7902204788 11436.1539789445 13762.7795043163 135 Sweden 2017 70+ years Female Male infertility YLLs 0 0 0 136 Sweden 2017 70+ years Female Major depressive disorder YLLs 0 0 0 137 Denmark 2017 70+ years Male Ischemic heart disease YLLs 30693.0242745391 28085.5519240899 33872.6614361834 138 Denmark 2017 70+ years Male Breast cancer YLLs 115.043244719455 94.8704639760747 138.091604214542 139 Denmark 2017 70+ years Male Male infertility YLLs 0 0 0 140 Denmark 2017 70+ years Male Major depressive disorder YLLs 0 0 0 141 Denmark 2017 70+ years Female Ischemic heart disease YLLs 22732.5631468349 20644.0440003978 25117.4413037947 142 Denmark 2017 70+ years Female Breast cancer YLLs 9139.77120985814 8151.21509685202 10241.9215210158 143 Denmark 2017 70+ years Female Male infertility YLLs 0 0 0 144 Denmark 2017 70+ years Female Major depressive disorder YLLs 0 0 0 145 Estonia 2017 70+ years Male Ischemic heart disease YLLs 14017.1430501037 11814.6566885858 18614.8893083866 146 Estonia 2017 70+ years Male Breast cancer YLLs 12.4487128642332 10.0750222691639 15.2810456269085 147 Estonia 2017 70+ years Male Male infertility YLLs 0 0 0 148 Estonia 2017 70+ years Male Major depressive disorder YLLs 0 0 0 149 Estonia 2017 70+ years Female Ischemic heart disease YLLs 20413.9308627921 16571.7484433009 28679.603382899 150 Estonia 2017 70+ years Female Breast cancer YLLs 1343.5103753416 1109.03083645215 1613.85825646017 151 Estonia 2017 70+ years Female Male infertility YLLs 0 0 0 152 Estonia 2017 70+ years Female Major depressive disorder YLLs 0 0 0 153 Finland 2017 50-69 years Male Ischemic heart disease YLLs 40512.1136768105 36665.8377166374 45765.5408813692 154 Finland 2017 50-69 years Male Breast cancer YLLs 77.6777813752824 64.0547572389397 94.165620829062 155 Finland 2017 50-69 years Male Male infertility YLLs 0 0 0 156 Finland 2017 50-69 years Male Major depressive disorder YLLs 0 0 0 157 Finland 2017 50-69 years Female Ischemic heart disease YLLs 8126.45706819738 7122.14780469614 9298.5176977947 158 Finland 2017 50-69 years Female Breast cancer YLLs 9347.41210641182 8308.39410044636 10463.5388045313 159 Finland 2017 50-69 years Female Male infertility YLLs 0 0 0 160 Finland 2017 50-69 years Female Major depressive disorder YLLs 0 0 0 161 Sweden 2017 50-69 years Male Ischemic heart disease YLLs 43032.5702869828 39767.045072238 46705.7982325306 162 Sweden 2017 50-69 years Male Breast cancer YLLs 125.812409143351 109.343392624597 143.984300598834 163 Sweden 2017 50-69 years Male Male infertility YLLs 0 0 0 164 Sweden 2017 50-69 years Male Major depressive disorder YLLs 0 0 0 165 Sweden 2017 50-69 years Female Ischemic heart disease YLLs 12385.5387610602 11200.3130809116 13689.0182917353 166 Sweden 2017 50-69 years Female Breast cancer YLLs 15654.400233543 14329.00962527 17120.6735776803 167 Sweden 2017 50-69 years Female Male infertility YLLs 0 0 0 168 Sweden 2017 50-69 years Female Major depressive disorder YLLs 0 0 0 169 Denmark 2017 50-69 years Male Ischemic heart disease YLLs 20772.6305597539 18790.0572883847 23091.9835070747 170 Denmark 2017 50-69 years Male Breast cancer YLLs 119.338982710696 98.6534316353537 143.24048598274 171 Denmark 2017 50-69 years Male Male infertility YLLs 0 0 0 172 Denmark 2017 50-69 years Male Major depressive disorder YLLs 0 0 0 173 Denmark 2017 50-69 years Female Ischemic heart disease YLLs 5964.01614527167 5209.40047068911 6783.42499837288 174 Denmark 2017 50-69 years Female Breast cancer YLLs 11985.0899510605 10719.0965330947 13408.6201703274 175 Denmark 2017 50-69 years Female Male infertility YLLs 0 0 0 176 Denmark 2017 50-69 years Female Major depressive disorder YLLs 0 0 0 177 Estonia 2017 50-69 years Male Ischemic heart disease YLLs 12950.3717535656 10588.580887835 16714.4814595266 178 Estonia 2017 50-69 years Male Breast cancer YLLs 19.5588721568226 15.727181118878 25.4248107960115 179 Estonia 2017 50-69 years Male Male infertility YLLs 0 0 0 180 Estonia 2017 50-69 years Male Major depressive disorder YLLs 0 0 0 181 Estonia 2017 50-69 years Female Ischemic heart disease YLLs 3715.02517979456 2916.61995660954 5085.25823316303 182 Estonia 2017 50-69 years Female Breast cancer YLLs 2418.29200520782 1979.2774927077 2922.2474574791 183 Estonia 2017 50-69 years Female Male infertility YLLs 0 0 0 184 Estonia 2017 50-69 years Female Major depressive disorder YLLs 0 0 0 185 Finland 2017 15-49 years Male Ischemic heart disease YLLs 4115.5089855896 3527.02363952965 4859.72115406533 186 Finland 2017 15-49 years Male Breast cancer YLLs 14.6819162934941 12.1490176503009 17.8074005254612 187 Finland 2017 15-49 years Male Male infertility YLLs 0 0 0 188 Finland 2017 15-49 years Male Major depressive disorder YLLs 0 0 0 189 Finland 2017 15-49 years Female Ischemic heart disease YLLs 611.213488043458 501.060553890847 732.335195151345 190 Finland 2017 15-49 years Female Breast cancer YLLs 2528.31473943798 2194.55063396996 2917.17964233557 191 Finland 2017 15-49 years Female Male infertility YLLs 0 0 0 192 Finland 2017 15-49 years Female Major depressive disorder YLLs 0 0 0 193 Sweden 2017 15-49 years Male Ischemic heart disease YLLs 5753.05829336073 5138.33634578402 6385.09869384805 194 Sweden 2017 15-49 years Male Breast cancer YLLs 29.7622706631965 25.7254919907877 34.5137030631883 195 Sweden 2017 15-49 years Male Male infertility YLLs 0 0 0 196 Sweden 2017 15-49 years Male Major depressive disorder YLLs 0 0 0 197 Sweden 2017 15-49 years Female Ischemic heart disease YLLs 1239.87103651792 1061.80988927242 1425.75108174146 198 Sweden 2017 15-49 years Female Breast cancer YLLs 5648.28019444172 5089.99819028464 6252.33161360524 199 Sweden 2017 15-49 years Female Male infertility YLLs 0 0 0 200 Sweden 2017 15-49 years Female Major depressive disorder YLLs 0 0 0 201 Denmark 2017 15-49 years Male Ischemic heart disease YLLs 2862.33774415073 2463.0086530783 3332.90521793081 202 Denmark 2017 15-49 years Male Breast cancer YLLs 19.8040418888207 16.1099575771611 24.0701053239353 203 Denmark 2017 15-49 years Male Male infertility YLLs 0 0 0 204 Denmark 2017 15-49 years Male Major depressive disorder YLLs 0 0 0 205 Denmark 2017 15-49 years Female Ischemic heart disease YLLs 562.751060898628 458.978011797249 676.026246281035 206 Denmark 2017 15-49 years Female Breast cancer YLLs 3268.08467880475 2832.08365122509 3746.41135671019 207 Denmark 2017 15-49 years Female Male infertility YLLs 0 0 0 208 Denmark 2017 15-49 years Female Major depressive disorder YLLs 0 0 0 209 Estonia 2017 15-49 years Male Ischemic heart disease YLLs 1886.18675806478 1443.35888151459 2439.26765967279 210 Estonia 2017 15-49 years Male Breast cancer YLLs 5.65812062235349 4.35123057473262 7.4404398722888 211 Estonia 2017 15-49 years Male Male infertility YLLs 0 0 0 212 Estonia 2017 15-49 years Male Major depressive disorder YLLs 0 0 0 213 Estonia 2017 15-49 years Female Ischemic heart disease YLLs 264.023038093566 205.317608396129 343.351812719974 214 Estonia 2017 15-49 years Female Breast cancer YLLs 782.245232341884 616.994001896713 983.483055076456 215 Estonia 2017 15-49 years Female Male infertility YLLs 0 0 0 216 Estonia 2017 15-49 years Female Major depressive disorder YLLs 0 0 0 217 Finland 2017 70+ years Male All causes YLLs 207619.282105221 195519.782651395 222094.048510959 218 Finland 2017 70+ years Female All causes YLLs 199945.161696186 185665.685158436 215862.88028251 219 Sweden 2017 70+ years Male All causes YLLs 356701.951516626 336900.065233428 377573.346981157 220 Sweden 2017 70+ years Female All causes YLLs 346541.219617854 326411.482571605 367573.491859039 221 Denmark 2017 70+ years Male All causes YLLs 215764.703451762 202712.479533361 230110.120573845 222 Denmark 2017 70+ years Female All causes YLLs 202367.605286298 188273.550984774 219085.104178745 223 Estonia 2017 70+ years Male All causes YLLs 45841.014736776 40574.6393829272 51596.3534814006 224 Estonia 2017 70+ years Female All causes YLLs 63684.7461266195 54966.8242812993 73061.1617915455 225 Finland 2017 50-69 years Male All causes YLLs 193034.280262088 179777.792744554 209118.144354478 226 Finland 2017 50-69 years Female All causes YLLs 92945.1716921069 85202.010403063 101527.525987606 227 Sweden 2017 50-69 years Male All causes YLLs 215853.408066294 201885.016746988 230792.909829138 228 Sweden 2017 50-69 years Female All causes YLLs 144636.944285896 134866.235535506 154705.90249215 229 Denmark 2017 50-69 years Male All causes YLLs 181545.599097919 168583.135254896 195848.367800156 230 Denmark 2017 50-69 years Female All causes YLLs 118359.089605629 109037.985473212 129448.674453616 231 Estonia 2017 50-69 years Male All causes YLLs 66527.5996317978 57434.1144399354 76865.4222292359 232 Estonia 2017 50-69 years Female All causes YLLs 30930.6890788127 26077.5595477852 36231.7346327398 233 Finland 2017 15-49 years Male All causes YLLs 75301.7336062441 69738.2429828148 81963.3634109578 234 Finland 2017 15-49 years Female All causes YLLs 29677.9604303097 26959.7301623466 32712.6842218087 235 Sweden 2017 15-49 years Male All causes YLLs 99365.0775972225 92694.8406969773 106621.184032438 236 Sweden 2017 15-49 years Female All causes YLLs 49719.0224879848 46171.2674762738 53519.6861984218 237 Denmark 2017 15-49 years Male All causes YLLs 58552.5186282872 54081.8921152601 63524.8211183674 238 Denmark 2017 15-49 years Female All causes YLLs 32914.4340634689 30124.3144517068 36345.2329934996 239 Estonia 2017 15-49 years Male All causes YLLs 35438.8237026662 30292.1213397718 41464.9156919116 240 Estonia 2017 15-49 years Female All causes YLLs 11105.9893706944 9213.5688564786 13269.7250786093

Other data

• Burden of disease as DALY in Finland ⇤--#: . Inactivate and merge? --Jouni (talk) 16:03, 13 April 2017 (UTC) (type: truth; paradigms: science: attack)

Data from op_fi:Seturi/tautiriski

Population column defines the relevant population subgroup other than age and sex subgroups, which are defined in their respective columns. The numbers of cases are divided by the size of the population (total population even in cases where the cases are from a subgroup only. The population size is estimated at 5375276 in 2010, and this is used as denominator in the incidence calculation.

Disease risk: Difference between revisions(# /100000py, DALY)

Obs	Response	Population	Age	Sex	Unit	Incidence	Actual cases	Description
1	Lung cancer morbidity	Whole population			cases /100000py	42.342	2276	Year 2010 cancer register
2	Cardiopulmonary mortality	Whole population			cases /100000py	443.512	23840
3	Total mortality	Whole population			cases /100000py	940.752	50568	2011 data, Tilastokeskus
4	Bladder cancer morbidity	Whole population			cases /100000py	16.706	898	Year 2010 cancer register
5	Myocardial infarction morbidity	Whole population			cases /100000py	463.195	24898
6	Ischaemic heart disease mortality	Whole population			cases /100000py	221.142	11887
7	Coronary heart disease mortality	Whole population			cases /100000py	221.142	11887	This is a duplicate of the previous row to match more ERFs
8	CHD arrythmia mortality	Whole population			cases /100000py	221.142	11887	This is a duplicate of the previous row to match more ERFs
9	Asthma morbidity	Whole population			cases /100000py	270.888	14561
10	Asthma morbidity	Whole population	>21		cases /100000py	176.103	9466
11	Asthma morbidity	Whole population	<14		cases /100000py	81.224	4366
12	Pulmonary infection morbidity	Whole population	<2		DALY	35
13	Otitis media	Whole population	<3		DALY	48
14	Lower respiratory symptoms morbidity	Whole population			cases /100000py	8985.585	483000
15	Upper respiratory symptoms morbidity	Whole population			cases /100000py	17279.969	928846
16	Ischaemic heart disease/myocardial infarction morbidity	Whole population	35-64	Male	cases /100000py	86.6	4655	35-64v miesten 1. infarktin insidenssi 354/100000 1991-4. Aromaa ym Suomalaisten terveys s155
17	CHD	Whole population	35-64	Male	cases /100000py	86.6	4655	35-64v miesten 1. infarktin insidenssi 354/100000 1991-4. Aromaa ym Suomalaisten terveys s155. This is a duplicate of the previous row to match more ERFs
18	Nasal cancer morbidity	Whole population	20-64		cases /100000py	0.651	35	Age boundaries are assumed without original data
19	COPD mortality	Whole population	15-64		cases /100000py	20.966	1127
20	Asthma morbidity2	Whole population	15-64	Male	cases /100000py	58.044	3120
21	Asthma morbidity2	Whole population	15-64	Female	cases /100000py	78.954	4244
22	Cancer morbidity	Whole population			cases /100000py	202.408	10880
23	Cancer lifetime probability	Whole population			probability	1		This is used with absolute risk functions such as CSF to get rid of the parameter relative to background
24	All skin cancers and basalioma morbidity	Whole population			cases /100000py	163.285	8777
25	Skin cancer morbidity	Whole population			cases /100000py	37.3	2005
26	Melanoma morbidity	Whole population			cases /100000py	16.855	906
27	Carcinoma spinocellulare morbidity	Whole population			cases /100000py	20.445	1099
28	Basalioma morbidity	Whole population			cases /100000py	125.984	6772
29	Leukemia morbidity	Whole population			cases /100000py	10.027	539	Year 2010, cancer register

DALY/a thousands WHO 2002 EU-27 OECD, 22 Population, millions Trachea, bronchus & lung cancers Cardio-vascular diseases Trachea, bronchus & lung cancers Cardio-vascular diseases

DALY in Europe WHO 2002(-)

Obs	Country	EU-27	OECD22	Population	Trachea bronchus & lung cancers DALY/a thousands	Cardio-vascular diseases DALY/a thousands	Trachea bronchus & lung cancers DALY/a/100 000	Cardio-vascular diseases DALY/a/100 000	(sub)urban 2009-11 PM2.5 mean μg/m3	Description
1	Austria	1	1	8.4	27	189	321	2244	18.9
2	Belgium	1	1	11.0	55	209	499	1898	17.6
3	Bulgaria	1	0	7.3	32	526	435	7157	31.4
4	Cyprus	1	0	0.9	1	21	117	2467	21.3
5	Czech Republic	1	1	10.5	52	352	495	3352	23.0
6	Denmark	1	1	5.6	26	114	461	2021	14.0
7	Estonia	1	0	1.3	5	65	373	4852	19.5
8	Finland	1	1	5.4	14	122	260	2266	7.3
9	France	1	1	65.2	243	857	373	1315	17.9
10	Germany	1	1	81.8	354	2070	433	2530	16.8
11	Greece	1	1	10.8	49	341	453	3153	19.4
12	Hungary	1	1	10.0	76	410	762	4113	22.6
13	Ireland	1	1	4.5	12	77	265	1703	10.8
14	Italy	1	1	60.7	238	1222	392	2013	21.5
15	Latvia	1	0	2.1	10	130	486	6318	15.1
16	Lithuania	1	0	3.0	13	138	429	4555	12.7
17	Luxembourg	1	1	0.5	2	9	381	1715	15.9
18	Malta	1	0	0.4	1	8	240	1920	13.6
19	Netherlands	1	1	16.7	73	307	437	1839	17.0
20	Norway	0	1	5.0	15	87	303	1756
21	Poland	1	1	38.5	215	1226	558	3181	28.2
22	Portugal	1	1	10.6	29	263	275	2491	8.6
23	Romania	1	0	21.4	92	1094	430	5118	18.1
24	Slovakia	1	1	5.4	19	175	352	3242	25.0
25	Slovenia	1	0	2.1	9	51	439	2485	21.5
26	Spain	1	1	46.2	155	670	336	1450	12.5
27	Sweden	1	1	9.4	23	187	244	1981	8.0
28	Switzerland	0	1	7.9	25	116	316	1465
29	Turkey	0	1	74.8	115	2082	154	2785
30	United Kingdom	1	1	62.8	230	1297	366	2065	13.3
31	All of the above			590.2	2210	14415	374	2442	17.7
32	EU27 Total			502.6	2055	12130	409	2413	17.7
33	OECD Europe total			553.1	2052	12447	371	2250	17.7

Calculations

+ Show code- Hide code # This is code Op_en5917/initiate on page [[Burden of disease]] library(OpasnetUtils) d <- opbase.data("Op_en5917") d$Obs <- NULL colnames(d) <- gsub(" ", "_", colnames(d)) d$Result[d$Unit == "cases /100000py"] <- d$Result[d$Unit == "cases /100000py"] / 100000 # Units to cases/py levels(d$Unit)[levels(d$Unit) == "cases /100000py"] <- "cases /py" disincidence <- Ovariable("disincidence", data = d, save = TRUE) cat("Ovariable disincidence saved. page_indent = Op_en5917, code_name = initiate\n")

InpBoD is an ovariable to calculate total burden of disease for selected endpoints based on IHME data.

+ Show code- Hide code # This is code Op_en5917/InpBoD on page [[Burden of disease]] library(OpasnetUtils) #dat <- opasnet.csv( # "/d/d3/IHME-GBD_2017_goherr_diseases_dk_ee_fi_se.zip", wiki="opasnet_en", # unzip="IHME-GBD_2017_DATA-c3ad9a2c-1.csv", # dec=".", sep=",", header=TRUE, quote="\"" #) dat <- opbase.data("Op_en5917", subset="Goherr IHME") #colnames(dat) <- c("Measure","Location","Sex","Age","Cause","Metric","Year","Value","Upper","Lower") #dat <- dat[dat$Metric=="Number" & dat$Year=="2017" , ] dat$Location <- factor( dat$Location, levels=c("Denmark", "Estonia", "Finland", "Sweden"), labels=c("DK", "EE", "FI", "SE") ) levels(dat$Measure)[levels(dat$Measure)== "DALYs (Disability-Adjusted Life Years)"] <- "DALYs" levels(dat$Measure)[levels(dat$Measure)== "YLLs (Years of Life Lost)"] <- "YLLs" dat <- dat[dat$Measure=="DALYs" | dat$Cause %in% c("All causes", "Ischemic heart disease") , ] # YLL for this dat <- dat[!(dat$Measure=="DALYs" & dat$Cause %in% c("All causes", "Ischemic heart disease")) , ] if(FALSE) { BoDbg <- Ovariable( "BoDbg", data = dat[dat$Measure %in% c("DALYs","YLLs") , c("Country","Group","Response","Measure","Result")] ) BoDbg <- EvalOutput(BoDbg) BoDbg$Measure <- NULL summary(BoDbg) numbg <- Ovariable( "numbg", data = dat[dat$Measure %in% c("Deaths","Incidence") , c("Country","Group","Response","Measure","Result")] ) summary(BoDbg/numbg) summary(EvalOutput(numbg)) #dat <- dat[!dat$Age %in% c("All Ages","<1 year","1 to 4","5 to 9","10 to 14") , ] levels(dat$Age)[levels(dat$Age) %in% c("15 to 19","20 to 24","25 to 29","30 to 34", "35 to 39","40 to 44")] <- "18-45" levels(dat$Age)[levels(dat$Age) %in% c("45 to 49","50 to 54","55 to 59","60 to 64", "65 to 69","70 to 74","75 to 79","80 plus")] <- ">45" } # Endif levels(dat$Age)[levels(dat$Age) %in% c("15-49 years")] <- "18-45" levels(dat$Age)[levels(dat$Age) %in% c("50-69 years","70+ years")] <- ">45" levels(dat$Cause)[levels(dat$Cause)== "All causes"] <- "All-cause mortality" #levels(dat$Cause)[levels(dat$Cause)== "Breast cancer"] levels(dat$Cause)[levels(dat$Cause)== "Caries of permanent teeth"] <- "Yes or no dental defect" #levels(dat$Cause)[levels(dat$Cause)== "Depressive disorders"] #levels(dat$Cause)[levels(dat$Cause)== "Dysthymia"] levels(dat$Cause)[levels(dat$Cause)== "Idiopathic developmental intellectual disability"] <- "Loss in child's IQ points" #levels(dat$Cause)[levels(dat$Cause)== "Intracerebral hemorrhage"] levels(dat$Cause)[levels(dat$Cause)== "Ischemic heart disease"] <- "CHD2 mortality" levels(dat$Cause)[levels(dat$Cause)== "Ischemic stroke"] <- "Stroke mortality" #levels(dat$Cause)[levels(dat$Cause)== "Liver cancer"] levels(dat$Cause)[levels(dat$Cause)== "Major depressive disorder"] <- "Depression" levels(dat$Cause)[levels(dat$Cause)== "Male infertility"] <- "Sperm concentration" levels(dat$Cause)[levels(dat$Cause)== "Neoplasms"] <- "Cancer morbidity" #levels(dat$Cause)[levels(dat$Cause)== "Stroke"] #levels(dat$Cause)[levels(dat$Cause)== "Subarachnoid hemorrhage"] colnames(dat)[colnames(dat)=="Cause"] <- "Response" colnames(dat)[colnames(dat)=="Location"] <- "Country" dat$Value <- ifelse(dat$Value=="0","0.001",as.character(dat$Value)) dat$Result <- ifelse(dat$Result=="0","0.002",as.character(dat$Result)) dat$Result <- gsub(",","",paste0(dat$Value, "1 (", dat$Lower, " - ", dat$Result, "2)")) levels(dat$Sex) <- gsub("s","",levels(dat$Sex)) dat$Group <- paste(dat$Sex, dat$Age) InpBoD<- Ovariable( "InpBoD", data = dat[c("Country","Group","Response","Result")], # "Measure" unit = "DALY /a per subpopulation" ) objects.store(InpBoD) cat("Ovariable InpBoD stored.\n") InpBoD <- EvalOutput(InpBoD) oprint(summary(oapply(InpBoD, NULL,sum,"Group")))

See also

• OECD health data [1]