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)

Rationale

Data

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	Trait	Population	Age	Sex	Response metric	Unit	Incidence	Actual cases	Description
1	Lung cancer	Whole population			Morbidity	cases /100000py	42.34201	2276	Year 2010 cancer register
2	Cardiopulmonary	Whole population			Mortality	cases /100000py	443.51211	23840
3	Total mortality	Whole population			Mortality	cases /100000py	940.75169	50568	2011 data, Tilastokeskus
4	Bladder cancer	Whole population			Morbidity	cases /100000py	16.70612	898	Year 2010 cancer register
5	Myocardial infarction	Whole population			Morbidity	cases /100000py	463.19482	24898
6	Ischaemic heart disease	Whole population			Mortality	cases /100000py	221.14213	11887
7	CHD	Whole population			Mortality	cases /100000py	221.14213	11887	This is a duplicate of the previous row to match more ERFs
8	Asthma	Whole population			Morbidity	cases /100000py	270.88842	14561
9	Asthma	Whole population	>21		Morbidity	cases /100000py	176.10259	9466
10	Asthma	Whole population	<14		Morbidity	cases /100000py	81.22374	4366
11	Pulmonary infections	Whole population	<2		Morbidity	DALY	35
12	Otitis media	Whole population	<3		Morbidity	DALY	48
13	Lower respiratory symptoms	Whole population			Morbidity	cases /100000py	8985.58511	483000
14	Upper respiratory symptoms	Whole population			Morbidity	cases /100000py	17279.96851	928846
15	Ischaemic heart disease/myocardial infarction	Whole population	35-64	M	Morbidity	cases /100000py	86.6002	4655	35-64v miesten 1. infarktin insidenssi 354/100000 1991-4. Aromaa ym Suomalaisten terveys s155
16	CHD	Whole population	35-64	M	Morbidity	cases /100000py	86.6002	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
17	Nasal cancer	Whole population	20-64		Morbidity	cases /100000py	0.65113	35	Age boundaries are assumed without original data
18	COPD	Whole population	15-64		Mortality	cases /100000py	20.96637	1127
19	Asthma	Whole population	15-64	M	Morbidity	cases /100000py	58.04353	3120
20	Asthma	Whole population	15-64	F	Morbidity	cases /100000py	78.95409	4244
21	Cancer	Whole population			Morbidity	cases /100000py	202.40821	10880
22	All skin cancers and basalioma	Whole population			Morbidity	cases /100000py	163.28464	8777
23	Skin cancer	Whole population			Morbidity	cases /100000py	37.30041	2005
24	Melanoma	Whole population			Morbidity	cases /100000py	16.85495	906
25	Carcinoma spinocellulare	Whole population			Morbidity	cases /100000py	20.44546	1099
26	Basalioma	Whole population			Morbidity	cases /100000py	125.98423	6772
27	Leukemia	Whole population			Morbidity	cases /100000py	10.02739	539	Year 2010, cancer register

Calculations

+ Show code- Hide code library(OpasnetUtils) d <- opbase.data("Op_en5917") d$Obs <- NULL colnames(d) <- gsub(" ", "_", colnames(d)) disincidence <- Ovariable("disincidence", data = d, save = TRUE) cat("Ovariable disincidence saved. page_indent = Op_en5917, code_name = initiate\n")

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