Asthma prevalence due to building dampness in Europe: Difference between revisions

Latest revision as of 12:23, 11 April 2011

This page is a knowledge crystal of subtype variable. The page identifier is Op_en4723
Moderator:Teemu R (see all)

Upload data {{#opasnet_base_link:Op_en4723}}

Scope

Europe in 2010, 2020, 2030, 2050.

Definition

This variable is calculated entirely from upstream variables listed under #Dependencies. Mathematical method described under #Formula.

Data

Dependencies

Unit

#

Formula

Formula calculates number of asthma cases which can be attributed to dampness in Europe in years 2010-2050 by using the following:

Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle extra cases = (prevalencetotal - prevalencenondamp) * population}
Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle prevalencetotal = prevalencenondamp * (%damp * OR + 1 - %damp)}
Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle prevalence_0 = %damp * OR * prevalencenondamp + (1 - %damp) * prevalencenondamp}

Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle prevalencenondamp = \frac{prevalence_0}{%damp * OR + 1 - %damp}}

Prevalences for nondamp and damp homes are assumed constant, for a given iteration in a given country.

dampness <- op_baseGetData("opasnet_base", "Erac2988")
pop <- op_baseGetData("opasnet_base", "Op_en4691", include = 1367, exclude = c(1435, 1436))
countries <- c("Austria", "Belgium", "Bulgaria", "Switzerland", "Cyprus", "Czech Republic", "Germany", "Denmark", "Estonia", "Spain", 
	"Finland", "France", "Greece", "Hungary", "Ireland", "Iceland", "Italy", "Lithuania", "Luxembourg", "Latvia", "Malta", "Netherlands", 
	"Norway", "Poland", "Portugal", "Romania", "Sweden", "Slowenia", "Slovakia", "United Kingdom")
levels(pop[,"CountryID"]) <- countries #IDs converted to actual names, for compatibility with other data
colnames(pop)[c(4,7)] <- c("Country","Population")
asthma <- op_baseGetData("opasnet_base", "Op_en4789")
erf <- op_baseGetData("opasnet_base", "Op_en4716")
poparray <- DataframeToArray(pop, "Population")
dampxpop <- IntArray(dampness, poparray, "Population")
asthmaarray <- DataframeToArray(asthma)
dampxpopxasthma <- IntArray(dampxpop, asthmaarray, "InitialPrevalence")
erfarray <- DataframeToArray(erf)
dampxpopxasthmaxerf <- IntArray(dampxpopxasthma, erfarray, "ERF")
p_nd <- data.frame(dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010", c("obs","Country","Age","Sex")], 
	p_nd=dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010", "InitialPrevalence"] * 100 /(dampxpopxasthmaxerf[
	dampxpopxasthmaxerf[,"Year"]=="2010", "Result"] * dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010", 
	"ERF"] + 100 - dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010", "Result"]))
p_ndarray <- DataframeToArray(p_nd, "p_nd")
dampxpopxasthmaxerfxp_nd <- IntArray(dampxpopxasthmaxerf, p_ndarray, "p_nd")
final <- data.frame(dampxpopxasthmaxerfxp_nd[,c("obs","Country","policy","Year","Age","Sex")], 
Result=dampxpopxasthmaxerfxp_nd[,"Population"] * dampxpopxasthmaxerfxp_nd[,"p_nd"] * 
dampxpopxasthmaxerfxp_nd[,"Result"] * (dampxpopxasthmaxerfxp_nd[,"ERF"] - 1) / 10000)
###Fancy alternative below, might be better, requires more testing
#final <- model.frame(I(Result*Population*p_nd*(ERF-1)/10000)~ obs + Country + policy + Age + Sex + Outcome, 
#data = dampxpopxasthmaxerfxp_nd)

Result

**Asthma cases (prevalence) in Europe due to residential building dampness (mean and 95% confidence interval).**
	Year
Policy	2010	2020	2030	2050
BAU	1715846 (794208-2918407)	2069089 (929518-3645690)	2300513 (1007103-4193891)	2417413 (1016202-4559645)
All	NA	2071501 (940391-3650210)	2634778 (1139578-4745158)	3009693 (1251020-5519308)
Biomass	NA	NA	NA	2998888 (1249803-5529395)
Insulation	NA	NA	NA	3002498 (1239186-5524389)
Renovation	NA	NA	NA	3416010 (1443227-6233562)

**Asthma cases (prevalence) attributable to residential building dampness in Europe in 2010.**
Country of observation	Mean	SD
Austria	23661	22103
Belgium	46341	30025.2
Cyprus	2988	1251
Czech Republic	65025	39220
Denmark	9051	7432
Estonia	7828	3876
Finland	10929	18613
France	302344	201280
Germany	375145	265165
Greece	20343	10627
Italy	276619	142459
Latvia	11875	5228
Poland	267934	105393
Portugal	47961	25133
Spain	227574	126839
Sweden	20225	27113
Total	1715846

Keywords

Asthma, indoor air, dampness, Europe

References

Related files

@@ Line 1: / Line 1: @@
-{{variable|moderator=Teemu R|stub=Yes}}
+[[Category:Indoor air]]
+[[Category:Mega case study]]
+[[Category:Health impact]]
+{{variable|moderator=Teemu R}}
 == Scope ==
@@ Line 6: / Line 9: @@
 == Definition ==
+This variable is calculated entirely from upstream variables listed under [[#Dependencies]]. Mathematical method described under [[#Formula]].
 === Data ===
- Description of the data used for obtaining the value of the variable
- (e.g. measurement data; mathematical method and its parameters). <br>
- Please include references (preferably using the ''<nowiki><ref> </ref></nowiki>'' tags)
- and links to original data, as appropriate.
 === Dependencies ===
@@ Line 18: / Line 18: @@
 *[[:heande:Moisture damage]]
 *[[Population of Europe by Country|Population of Europe]]
-*Asthma incidence from the [http://data.euro.who.int/hmdb/index.php WHO: European hospital morbidity database (HMDB)]
+*[[Asthma prevalence]]
 *[[ERF of indoor dampness on respiratory health effects]]
 === Unit ===
- Unit in which the result is expressed.
+<nowiki>#</nowiki>
 === Formula ===
-*Asthma prevalence is estimated by summing in-patients and day-cases from the hospital morbidity database.
+Formula calculates number of asthma cases which can be attributed to dampness in Europe in years 2010-2050 by using the following:
-*Wheeze ERF used, as it approximately corresponds to the type of cases likely to be registered by the database.
+#<math>extra cases = (prevalencetotal - prevalencenondamp) * population</math>
+#<math>prevalencetotal = prevalencenondamp * (%damp * OR + 1 - %damp)</math>
+#<math>prevalence_0 = %damp * OR * prevalencenondamp + (1 - %damp) * prevalencenondamp</math>
+::<math>prevalencenondamp = \frac{prevalence_0}{%damp * OR + 1 - %damp}</math>
+*Prevalences for nondamp and damp homes are assumed constant, for a given iteration in a given country.
   <nowiki>
-dampness <- op_baseGetData("opasnet_base", "Erac2988") #Current version is bugged
+dampness <- op_baseGetData("opasnet_base", "Erac2988")
 pop <- op_baseGetData("opasnet_base", "Op_en4691", include = 1367, exclude = c(1435, 1436))
 countries <- c("Austria", "Belgium", "Bulgaria", "Switzerland", "Cyprus", "Czech Republic", "Germany", "Denmark", "Estonia", "Spain",
 	"Finland", "France", "Greece", "Hungary", "Ireland", "Iceland", "Italy", "Lithuania", "Luxembourg", "Latvia", "Malta", "Netherlands",
 	"Norway", "Poland", "Portugal", "Romania", "Sweden", "Slowenia", "Slovakia", "United Kingdom")
-levels(pop[,"CountryID"]) <- countries
+levels(pop[,"CountryID"]) <- countries #IDs converted to actual names, for compatibility with other data
-colnames(pop)[4] <- "Country"
+colnames(pop)[c(4,7)] <- c("Country","Population")
-colnames(pop)[8] <- "Population"
+asthma <- op_baseGetData("opasnet_base", "Op_en4789")
-asthma <- read.csv("C:/Documents and Settings/tris/My Documents/Asthma cases hmdb.csv", sep = ";") #File constructed from hmdb data
+erf <- op_baseGetData("opasnet_base", "Op_en4716")
-asthma <- data.frame(Country=asthma[1:26,1], Casesper1000=(asthma[1:26,2]+asthma[1:26,3]))
-erf <- 1.50
 poparray <- DataframeToArray(pop, "Population")
 dampxpop <- IntArray(dampness, poparray, "Population")
-asthmaarray <- DataframeToArray(asthma, "Casesper1000")
+asthmaarray <- DataframeToArray(asthma)
-dampxpopxasthma <- IntArray(dampxpop, asthmaarray, "Casesper1000")
+dampxpopxasthma <- IntArray(dampxpop, asthmaarray, "InitialPrevalence")
-final <- data.frame(dampxpopxasthma[,c(2,3,4,6,7,8)], Result=(dampxpopxasthma[,"Result"] * dampxpopxasthma[,"Population"] * (erf - 1) *
+erfarray <- DataframeToArray(erf)
-dampxpopxasthma[,"Casesper1000"] / 1000))
+dampxpopxasthmaxerf <- IntArray(dampxpopxasthma, erfarray, "ERF")
-</nowiki>
+p_nd <- data.frame(dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010", c("obs","Country","Age","Sex")],
+	p_nd=dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010", "InitialPrevalence"] * 100 /(dampxpopxasthmaxerf[
+	dampxpopxasthmaxerf[,"Year"]=="2010", "Result"] * dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010",
+	"ERF"] + 100 - dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010", "Result"]))
+p_ndarray <- DataframeToArray(p_nd, "p_nd")
+dampxpopxasthmaxerfxp_nd <- IntArray(dampxpopxasthmaxerf, p_ndarray, "p_nd")
+final <- data.frame(dampxpopxasthmaxerfxp_nd[,c("obs","Country","policy","Year","Age","Sex")],
+Result=dampxpopxasthmaxerfxp_nd[,"Population"] * dampxpopxasthmaxerfxp_nd[,"p_nd"] *
+dampxpopxasthmaxerfxp_nd[,"Result"] * (dampxpopxasthmaxerfxp_nd[,"ERF"] - 1) / 10000)
+###Fancy alternative below, might be better, requires more testing
+#final <- model.frame(I(Result*Population*p_nd*(ERF-1)/10000)~ obs + Country + policy + Age + Sex + Outcome,
+#data = dampxpopxasthmaxerfxp_nd)</nowiki>
 == Result ==
 {{resultlink}}
+{|{{prettytable}}
+|+'''Asthma cases (prevalence) in Europe due to residential building dampness (mean and 95% confidence interval).'''
+! !!colspan="4"|Year
+|----
+!Policy!!2010!!2020!!2030!!2050
+|----
+|BAU || 1715846 (794208-2918407) || 2069089 (929518-3645690) || 2300513 (1007103-4193891) || 2417413 (1016202-4559645)
+|----
+|All || NA || 2071501 (940391-3650210) || 2634778 (1139578-4745158) || 3009693 (1251020-5519308)
+|----
+|Biomass || NA || NA || NA || 2998888 (1249803-5529395)
+|----
+|Insulation || NA || NA || NA || 3002498 (1239186-5524389)
+|----
+|Renovation || NA || NA || NA || 3416010 (1443227-6233562)
+|----
+|}
+{| {{prettytable}}
+|+ '''Asthma cases (prevalence) attributable to residential building dampness in Europe in 2010.
+! Country of observation!! Mean!! SD
+|----
+|| Austria || 23661 || 22103
+|----
+|| Belgium || 46341 || 30025.2
+|----
+|| Cyprus || 2988 || 1251
+|----
+|| Czech Republic || 65025 || 39220
+|----
+|| Denmark|| 9051 || 7432
+|----
+|| Estonia|| 7828 || 3876
+|----
+|| Finland|| 10929 || 18613
+|----
+|| France|| 302344 || 201280
+|----
+|| Germany|| 375145 || 265165
+|----
+|| Greece|| 20343 || 10627
+|----
+|| Italy|| 276619 || 142459
+|----
+|| Latvia|| 11875 || 5228
+|----
+|| Poland|| 267934 || 105393
+|----
+|| Portugal|| 47961 || 25133
+|----
+|| Spain|| 227574 || 126839
+|----
+|| Sweden|| 20225 || 27113
+|----
+! Total!! 1715846 ||
+|----
+|}
 ==See also==