Package 'score'

Scores 'International Physical Activity Questionnaire (IPAQ)'

Description

Scores 'International Physical Activity Questionnaire (IPAQ)' short form.

Usage

ipaq(ipaqdata)

Arguments

ipaqdata

Data which consists of thirteen columns: Column 1: ID Column 2: Weight Column 3: VigDays: Number of days doing vigorous physical activity per week Column 4: VigHours: Number of hours in vigorous physical activity per day Column 5: VigMin: Number of minutes in vigorous physical activity per day Column 6: ModDays: Number of days doing moderate physical activity per week Column 7: ModHours: Number of hours in moderate physical activity per day Column 8: ModMin: Number of minutes in moderate physical activity per day Column 9: WalkDays: Number of days walking per week Column 10: WalkHours: Number of hours walking per day Column 11: WalkMin: Number of minutes in walking per day Column 12: SitHours: Number of hours sitting per day Column 13: SitMin: Number of minutes sitting per day

Value

Three additional columns [MET, kilocalories, pacat] are provided, to the data supplied to the function.

MET:	Metabolic Equivalent of Task.
kilocalories:	Kilocalories are computed from MET-minutes.
pacat:	Physical activity classification into 'Low', 'Moderate', or 'High'.

Author(s)

Jaejoon Song <[email protected]>

References

Craig, C.L., et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc, 2003. 35(8): p. 1381-95.

The International Physical Activity Questionnaire. (2015, June 1). Retrieved from
http://www.ipaq.ki.se

Examples

## Generating a random IPAQ data for illustration
set.seed(1234)
n <- 20
ID <- rep(1:n)
weight <- rtnorm(n, mean=75, sd=15, lower=40, upper=120)
VigDays <- sample(rep(0:2),n,replace=TRUE)
VigHours <- sample(rep(0:1),n,replace=TRUE)
VigMin <- sample(rep(0:60),n,replace=TRUE)
VigHours <- ifelse(VigDays==0,0,VigHours)
VigMin <- ifelse(VigDays==0,0,VigMin)
ModDays <- sample(rep(0:3),n,replace=TRUE)
ModHours <- sample(rep(0:2),n,replace=TRUE)
ModMin <- sample(rep(0:60),n,replace=TRUE)
ModHours <- ifelse(ModDays==0,0,ModHours)
ModMin <- ifelse(ModDays==0,0,ModMin)
WalkDays <- sample(rep(0:7),n,replace=TRUE)
WalkHours <- sample(rep(0:2),n,replace=TRUE)
WalkMin <- sample(rep(0:60),n,replace=TRUE)
WalkHours <- ifelse(WalkDays==0,0,WalkHours)
WalkMin <- ifelse(WalkDays==0,0,WalkMin)
SitHours <- sample(rep(1:14),n,replace=TRUE)
SitMin <- sample(rep(1:60),n,replace=TRUE)

sampleIPAQ <- data.frame(ID, weight, 
                         VigDays, VigHours, VigMin,
                         ModDays, ModHours, ModMin,
                         WalkDays, WalkHours, WalkMin,
                         SitHours, SitMin)

# Now scoring the data
output <- ipaq(ipaqdata=sampleIPAQ)

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Compares physical functional performance to normal ranges

Description

Compares physical functional performance to the age- and gender-specific normal range scores from the Rikli and Jones Senior Fitness Test Manual. Note that the manual provides normative values for seriors aged between 60-94. Comparison to the norms will only be performed for individuals aged between 60 to 94.

Usage

pfnorm(data)

Arguments

data	Data frame which consists of six columns: Column 1: Age Column 2: Gender (F: female, M: male) Column 3: Number of Steps Column 4: Number of full stands Column 5: Mean of 8 foot up and go trials Column 6: Mean of left and right armcurls

Value

Four additional columns [StepsNorm, StandNorm, UpgoNorm, ArmcurlNorm] are provided, to the data supplied to the function. The columns indicate whether the individuals' physical performance meets the norm or is lower or higher than the norm.

Author(s)

Jaejoon Song <[email protected]>

References

Rikli, R. E. and Jones, C. J. (1999). Development and validation of a functional fitness test for community-residing older adults. Journal of Aging and Physical Activity, 7, 129-61.

Examples

# Generating a random physical performance data for illustration
n <- 20
ID <- rep(1:n)
Age <- rtnorm(n, mean=75, sd=15, lower=60, upper=94)
Gender <- sample(c("F","M"),n,replace=TRUE)
NumberofSteps <- sample(rep(0:150),n,replace=TRUE)
Numberoffullstands <- sample(rep(0:20),n,replace=TRUE)
UpGo8ftmean <- rtnorm(n, mean=7.5, sd=4, lower=3, upper=30)
armcurlR_Lmean <- rnorm(n, mean=14, sd=4)


samplePerf <- data.frame(ID,Age,Gender,
                         NumberofSteps,Numberoffullstands,
                         UpGo8ftmean,armcurlR_Lmean)
                         
# Now comparing the physical performance test to the norm
normCat <- pfnorm(samplePerf)

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