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

Revision as of 13:46, 26 January 2011

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

<math>extra cases = (prevalence_total - prevalence_nondamp) population</math>
<math>prevalence_total = prevalence_nondamp(%damp * OR + 1 - %damp)</math>
<math>prevalence_0 = %damp * OR * prevalence_nondamp + (1 - %damp) * prevalence_nondamp</math>

<math>prevalence_nondamp = \frac{prevalence_0}{%damp * OR + 1 - %damp}</math>

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

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)

Result

**Asthma prevalence (#) in Europe due to indoor radon in residences (mean and 95% confidence interval).**
	Year
Policy	2010	2020	2030	2050
BAU	1719942 (1112299-2501866)	2074298 (1283407-3166039)	2307249 (1367574-3736504)	2415120 (1371764-3983910)
All	NA	2077607 (1287267-3174488)	2642618 (1569616-4149730)	3004924 (1758236-4783584)
Biomass	NA	NA	NA	2994210 (1712744-4763987)
Insulation	NA	NA	NA	2997521 (1717737-4737750)
Renovation	NA	NA	NA	3412703 (1987737-5394455)

**Asthma cases (prevalence) attributable to residential building dampness in Europe in 2010.**
Country of observation	Mean	SD
Austria	23958	19818
Belgium	46983	24769
Cyprus	3010	706
Czech Republic	65640	31215
Denmark	9088	6502
Estonia	8188	2735
Finland	10881	17198
France	303354	161230
Germany	379346	221077
Greece	20517	7842
Italy	279127	99106
Latvia	11991	3158
Poland	270064	49342
Portugal	48477	18082
Spain	226670	93709
Sweden	20039	24323
Total	1727332

Keywords

Asthma, indoor air, dampness, Europe

References

Related files

@@ Line 7: / Line 7: @@
 == Definition ==
-Initial Prevalence data from GINA<ref name=GINA>[http://www.ginasthma.com/download.asp?intId=29 Global Initiative for Asthma report: Global Burden of Asthma]</ref>.
+This variable is calculated entirely from upstream variables listed under [[#Dependencies]]. Mathematical method described under [[#Formula]].
-Formula calculates number of asthma cases which can be attributed to dampness in Europe in years 2010-2050 by using the following:
-#<nowiki><math>extra cases = (prevalence_total - prevalence_nondamp) population</math></nowiki>
-#<nowiki><math>prevalence_total = prevalence_nondamp(%damp * OR + 1 - %damp)</math></nowiki>
-#<nowiki><math>prevalence_0 = %damp * OR * prevalence_nondamp + (1 - %damp) * prevalence_nondamp</math></nowiki>
-::<nowiki><math>prevalence_nondamp = \frac{prevalence_0}{%damp * OR + 1 - %damp}</math></nowiki>
-*Prevalences for nondamp and damp homes are assumed constant, for a given iteration.
-Population data[http://en.opasnet.org/w/Population_of_Europe] included population growth scenarios so they too are included.
-Distribution represents uncertainty (mainly of fraction of affected homes).
 === Data ===
@@ Line 27: / Line 15: @@
 *[[:heande:Moisture damage]]
 *[[Population of Europe by Country|Population of Europe]]
-*Prevelance of Clinical Asthma<ref name=GINA></ref>
+*[[Asthma prevalence]]
 *[[ERF of indoor dampness on respiratory health effects]]
@@ Line 36: / Line 24: @@
 === Formula ===
-*ERF approximated as that for current asthma (OR = 1.56).
+Formula calculates number of asthma cases which can be attributed to dampness in Europe in years 2010-2050 by using the following:
+#<nowiki><math>extra cases = (prevalence_total - prevalence_nondamp) population</math></nowiki>
+#<nowiki><math>prevalence_total = prevalence_nondamp(%damp * OR + 1 - %damp)</math></nowiki>
+#<nowiki><math>prevalence_0 = %damp * OR * prevalence_nondamp + (1 - %damp) * prevalence_nondamp</math></nowiki>
+::<nowiki><math>prevalence_nondamp = \frac{prevalence_0}{%damp * OR + 1 - %damp}</math></nowiki>
+*Prevalences for nondamp and damp homes are assumed constant, for a given iteration.
   <nowiki>
@@ Line 44: / Line 38: @@
 	"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 prevalence.csv", sep = ";")
+erf <- op_baseGetData("opasnet_base", "Op_en4716")
-asthma <- data.frame(Country=c('Scotland','Jersey','Guernsey','Wales','Isle of Man','England','New Zealand','Australia','Republic of Ireland',
-'Canada','Peru','Trinidad & Tobago','Costa Rica','Brazil','United States of America','Fiji','Paraguay','Uruguay','Israel','Barbados','Panama',
-'Kuwait','Ukraine','Ecuador','South Africa','Czech Republic','Finland','Malta','Ivory Coast','Colombia','Turkey','Lebanon','Kenya','Germany',
-'France','Norway','Japan','Sweden','Thailand','Hong Kong','Philippines','United Arab Emirates','Belgium','Austria','Spain','Saudi Arabia',
-'Argentina','Iran','Estonia','Nigeria','Chile','Singapore','Malaysia','Portugal','Uzbekistan','FYR Macedonia','Italy','Oman','Pakistan',
-'Tunisia','Cape Verde','Latvia','Poland','Algeria','South Korea','Bangladesh','Morocco','Occupied Territory of Palestine','Mexico','Ethiopia',
-'Denmark','India','Taiwan','Cyprus','Switzerland','Russia','China','Greece','Georgia','Nepal','Romania','Albania','Indonesia','Macau'),
-InitialPrevalence=c(18.4,17.6,17.5,16.8,16.7,15.3,15.1,14.7,14.6,14.1,13,12.6,11.9,11.4,10.9,10.5,9.7,9.5,9,8.9,8.8,8.5,8.3,8.2,8.1,8,8,8,7.8,7.4,
-.4,7.2,7,6.9,6.8,6.8,6.7,6.5,6.5,6.2,6.2,6.2,6,5.8,5.7,5.6,5.5,5.5,5.4,5.4,5.1,4.9,4.8,4.8,4.6,4.5,4.5,4.5,4.3,4.3,4.2,4.2,4.1,3.9,3.9,3.8,
-.8,3.6,3.3,3.1,3,3,2.6,2.4,2.3,2.2,2.1,1.9,1.8,1.5,1.5,1.3,1.1,0.7))
-#asthma <- data.frame(Country=asthma[1:26,1], Casesper1000=(asthma[1:26,2]+asthma[1:26,3]))
 poparray <- DataframeToArray(pop, "Population")
 dampxpop <- IntArray(dampness, poparray, "Population")
-asthmaarray <- DataframeToArray(asthma, "InitialPrevalence")
+asthmaarray <- DataframeToArray(asthma)
 dampxpopxasthma <- IntArray(dampxpop, asthmaarray, "InitialPrevalence")
-erf <- rnorm(nrow(dampxpopxasthma[dampxpopxasthma[,"Year"]=="2010",]), 1.56, (1.86-1.30)/3.92)
+erfarray <- DataframeToArray(erf)
-p_nd <- data.frame(dampxpopxasthma[dampxpopxasthma[,"Year"]=="2010", c("obs","Country","Age","Rate","Sex")],
+dampxpopxasthmaxerf <- IntArray(dampxpopxasthma, erfarray, "ERF")
-p_nd=dampxpopxasthma[dampxpopxasthma[,"Year"]=="2010",
+p_nd <- data.frame(dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010", c("obs","Country","Age","Sex")],
-"InitialPrevalence"] * 100 /(dampxpopxasthma[dampxpopxasthma[,"Year"]=="2010", "Result"] * erf + 100 - dampxpopxasthma[dampxpopxasthma[,"Year"]==
+	p_nd=dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010", "InitialPrevalence"] * 100 /(dampxpopxasthmaxerf[
-"2010", "Result"]))
+	dampxpopxasthmaxerf[,"Year"]=="2010", "Result"] * dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010",
+	"ERF"] + 100 - dampxpopxasthmaxerf[dampxpopxasthmaxerf[,"Year"]=="2010", "Result"]))
 p_ndarray <- DataframeToArray(p_nd, "p_nd")
-dampxpopxasthmaxp_nd <- IntArray(dampxpopxasthma, p_ndarray, "p_nd")
+dampxpopxasthmaxerfxp_nd <- IntArray(dampxpopxasthmaxerf, p_ndarray, "p_nd")
-erfdf <- p_nd
+final <- data.frame(dampxpopxasthmaxerfxp_nd[,c("obs","Country","policy","Year","Age","Sex")],
-colnames(erfdf)[ncol(erfdf)] <- "erf"
+Result=dampxpopxasthmaxerfxp_nd[,"Population"] * dampxpopxasthmaxerfxp_nd[,"p_nd"] *
-erfdf[,"erf"] <- erf
+dampxpopxasthmaxerfxp_nd[,"Result"] * (dampxpopxasthmaxerfxp_nd[,"ERF"] - 1) / 10000)</nowiki>
-erfarray <- DataframeToArray(erfdf, "erf")
-dampxpopxasthmaxp_ndxerf <- IntArray(dampxpopxasthmaxp_nd, erfarray, "erf")
-final <- data.frame(dampxpopxasthmaxp_ndxerf[,c("obs","Country","policy","Year","Age","Rate","Sex")],
-Result=dampxpopxasthmaxp_ndxerf[,"Population"] * dampxpopxasthmaxp_ndxerf[,"p_nd"] *
-dampxpopxasthmaxp_ndxerf[,"Result"] * (dampxpopxasthmaxp_ndxerf[,"erf"] - 1) / 10000)</nowiki>
 == Result ==