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.

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(# /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
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")))

Keywords

References

Disease risk

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Question

Answer

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Goherr data from IHME

Other data

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