Difference between revisions of "Asthma prevalence due to building dampness in Europe"

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(Better data and revised formula)
(→‎Formula)
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=== Formula ===
 
=== Formula ===
  
−
#<nowiki><math>extra cases = \left ( \frac{OR - 1}{\frac{1}{%damp}-1} \right ) d</math></nowiki>
+
#<nowiki><math>extra cases = \left ( \frac{OR - 1}{\frac{100}{%damp}-1} \right ) d</math></nowiki>
−
#<nowiki><math>d = \frac{cases}{\frac{OR}{\frac{1}{%damp}-1}+1}</math></nowiki>
+
#<nowiki><math>d = \frac{cases}{\frac{OR}{\frac{100}{%damp}-1}+1}</math></nowiki>
  
 
*ERF approximated as that for current asthma (1.56).  
 
*ERF approximated as that for current asthma (1.56).  
Line 41: Line 41:
 
colnames(pop)[4] <- "Country"
 
colnames(pop)[4] <- "Country"
 
colnames(pop)[8] <- "Population"
 
colnames(pop)[8] <- "Population"
−
asthma <- read.csv("C:/Documents and Settings/tris/My Documents/Asthma prevalence.csv", sep = ";")
+
#asthma <- read.csv("C:/Documents and Settings/tris/My Documents/Asthma prevalence.csv", sep = ";")
 +
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'),
 +
Prevalence=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,
 +
7.4,7.2,7,6.9,6.8,6.8,6.7,6.5,6.5,6.2,6.2,6.2,6,5.8,5.7,5.6,5.5,5.5,5.4,5.4,5.1,4.9,4.8,4.8,4.6,4.5,4.5,4.5,4.3,4.3,4.2,4.2,4.1,3.9,3.9,3.8,
 +
3.8,3.6,3.3,3.1,3,3,2.6,2.4,2.3,2.2,2.1,1.9,1.8,1.5,1.5,1.3,1.1,0.7))
 
#asthma <- data.frame(Country=asthma[1:26,1], Casesper1000=(asthma[1:26,2]+asthma[1:26,3]))
 
#asthma <- data.frame(Country=asthma[1:26,1], Casesper1000=(asthma[1:26,2]+asthma[1:26,3]))
 
erf <- 1.56
 
erf <- 1.56
Line 48: Line 58:
 
asthmaarray <- DataframeToArray(asthma, "Prevalence")
 
asthmaarray <- DataframeToArray(asthma, "Prevalence")
 
dampxpopxasthma <- IntArray(dampxpop, asthmaarray, "Prevalence")
 
dampxpopxasthma <- IntArray(dampxpop, asthmaarray, "Prevalence")
−
final <- data.frame(dampxpopxasthma[,c(2,3,4,6,7,8)], Result=(dampxpopxasthma[,"Prevalence"] / 100 * dampxpopxasthma[,"Population"] / (erf / (100 /  
+
final <- data.frame(dampxpopxasthma[,c(2,3,4,6,7,8)], Result=(dampxpopxasthma[,"Prevalence"] / 100 * dampxpopxasthma[,"Population"] / (erf /  
−
dampxpopxasthma[,"Result"] - 1) + 1) * (erf - 1) / (100 / dampxpopxasthma[,"Result"] - 1)))</nowiki>
+
(100 / dampxpopxasthma[,"Result"] - 1) + 1) * (erf - 1) / (100 / dampxpopxasthma[,"Result"] - 1)))</nowiki>
  
 
== Result ==
 
== Result ==

Revision as of 07:37, 14 December 2010


Scope

Europe in 2010, 2020, 2030, 2050.

Definition

Data

Description of the data used for obtaining the value of the variable
(e.g. measurement data; mathematical method and its parameters). 

Please include references (preferably using the <ref> </ref> tags)
and links to original data, as appropriate.

Dependencies

Unit

#

Formula

  1. <math>extra cases = \left ( \frac{OR - 1}{\frac{100}{%damp}-1} \right ) d</math>
  2. <math>d = \frac{cases}{\frac{OR}{\frac{100}{%damp}-1}+1}</math>
  • ERF approximated as that for current asthma (1.56). 
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
colnames(pop)[4] <- "Country"
colnames(pop)[8] <- "Population"
#asthma <- read.csv("C:/Documents and Settings/tris/My Documents/Asthma prevalence.csv", sep = ";")
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'), 
Prevalence=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, 
7.4,7.2,7,6.9,6.8,6.8,6.7,6.5,6.5,6.2,6.2,6.2,6,5.8,5.7,5.6,5.5,5.5,5.4,5.4,5.1,4.9,4.8,4.8,4.6,4.5,4.5,4.5,4.3,4.3,4.2,4.2,4.1,3.9,3.9,3.8, 
3.8,3.6,3.3,3.1,3,3,2.6,2.4,2.3,2.2,2.1,1.9,1.8,1.5,1.5,1.3,1.1,0.7))
#asthma <- data.frame(Country=asthma[1:26,1], Casesper1000=(asthma[1:26,2]+asthma[1:26,3]))
erf <- 1.56
poparray <- DataframeToArray(pop, "Population")
dampxpop <- IntArray(dampness, poparray, "Population")
asthmaarray <- DataframeToArray(asthma, "Prevalence")
dampxpopxasthma <- IntArray(dampxpop, asthmaarray, "Prevalence")
final <- data.frame(dampxpopxasthma[,c(2,3,4,6,7,8)], Result=(dampxpopxasthma[,"Prevalence"] / 100 * dampxpopxasthma[,"Population"] / (erf / 
(100 / dampxpopxasthma[,"Result"] - 1) + 1) * (erf - 1) / (100 / dampxpopxasthma[,"Result"] - 1)))

Result

Show results


See also

Keywords

Asthma, indoor air, dampness, Europe

References

  1. ↑ Global Initiative for Asthma report: Global Burden of Asthma

Related files

<mfanonymousfilelist></mfanonymousfilelist>

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