library(childsds)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
data(leptin.ref)For children and adolescents up to an age of 18.5 years, leptin
standard deviation scores will be calclated based on age on years and
BMI-SDS. BMI-SDS via the x2= argument to the
sds_2d() function.
Besides, the sds_2d() function takes the leptin value
(value=), sex (sex=) and age
(age=) as arguments. These values have to be given as
vectors of the same length. In addition, it needs a reference object (in
our case ref=leptin.ref) and the item (item=).
For children younger than 6, the item is ‘leptin_until6’, for children
between 6 and 18, it is ‘leptin_6to18’. The function returns a numeric
vector of the same length containing leptin-SDS
(type="SDS") or leptin percentiles
(type="perc").
df <- data.frame(age = seq(0.5, 6.5, by = 1),
sex = sample(c("m","f"),7, replace = T),
bmisds = rnorm(7),
leptin = runif(7, min = 0.01, max = 5))
df
#> age sex bmisds leptin
#> 1 0.5 f -1.20864360 1.2999163
#> 2 1.5 f -0.64641907 4.9054107
#> 3 2.5 m -0.50969739 0.6050243
#> 4 3.5 f -0.37261199 4.4154265
#> 5 4.5 m 0.54342245 2.8370546
#> 6 5.5 m 0.06255447 3.9011665
#> 7 6.5 m 0.62800807 0.3248162
df$leptin_sds <- sds_2d(value = df$leptin,
age = df$age,
x2 = df$bmisds,
sex = df$sex, male = "m", female = "f",
item = "leptin_until6",
ref = leptin.ref)
df
#> age sex bmisds leptin leptin_sds
#> 1 0.5 f -1.20864360 1.2999163 -0.5619740
#> 2 1.5 f -0.64641907 4.9054107 1.8298199
#> 3 2.5 m -0.50969739 0.6050243 -0.2398779
#> 4 3.5 f -0.37261199 4.4154265 1.6514093
#> 5 4.5 m 0.54342245 2.8370546 1.0096744
#> 6 5.5 m 0.06255447 3.9011665 1.5220409
#> 7 6.5 m 0.62800807 0.3248162 -1.5615349For SDS adjusted for pubertal stage, you have to use the function
sds_pub2d(). Again, the leptin value (value=),
the Tanner stage (1-5, pubstat=), the BMI-SDS
(x2=) and the sex (sex=) has to be given to
the function as vectors of the same length. The ref object
is still leptin.ref and the item=lep_pub. The
reference values are valid for the age range 6-18.
sds_pub2d(value = 20,
pubstat = 2,
x2 = 1,
sex = "male",
item = "lep_pub", ref = leptin.ref)
#> [1] 1.946403df <- data.frame(age = seq(0.5, 6.5, by = 1),
sex = sample(c("m","f"),7, replace = T),
bmisds = rnorm(7),
leptin = runif(7, min = 0.01, max = 5))
df
#> age sex bmisds leptin
#> 1 0.5 f 0.02920079 0.2873527
#> 2 1.5 f -1.73193077 1.7359944
#> 3 2.5 m 1.73210377 2.6624373
#> 4 3.5 m 0.39829763 1.0020941
#> 5 4.5 f -1.20095660 2.0651460
#> 6 5.5 m -2.15357018 0.6280579
#> 7 6.5 m 1.37734223 3.4052877df$leptin_sds <- sds_2d(value = df$leptin,
age = df$age,
x2 = df$bmisds,
sex = df$sex, male = "m", female = "f",
item = "leptin_until6",
ref = leptin.ref)
df
#> age sex bmisds leptin leptin_sds
#> 1 0.5 f 0.02920079 0.2873527 -2.08585306
#> 2 1.5 f -1.73193077 1.7359944 1.11360792
#> 3 2.5 m 1.73210377 2.6624373 0.54423467
#> 4 3.5 m 0.39829763 1.0020941 -0.05146495
#> 5 4.5 f -1.20095660 2.0651460 1.10058735
#> 6 5.5 m -2.15357018 0.6280579 -0.12682670
#> 7 6.5 m 1.37734223 3.4052877 0.17222508df$leptin_perc <- sds_2d(value = df$leptin,
age = df$age,
x2 = df$bmisds,
sex = df$sex, male = "m", female = "f",
item = "leptin_until6",
type = "perc",
ref = leptin.ref)
df
#> age sex bmisds leptin leptin_sds leptin_perc
#> 1 0.5 f 0.02920079 0.2873527 -2.08585306 1.85
#> 2 1.5 f -1.73193077 1.7359944 1.11360792 86.73
#> 3 2.5 m 1.73210377 2.6624373 0.54423467 70.69
#> 4 3.5 m 0.39829763 1.0020941 -0.05146495 47.95
#> 5 4.5 f -1.20095660 2.0651460 1.10058735 86.45
#> 6 5.5 m -2.15357018 0.6280579 -0.12682670 44.95
#> 7 6.5 m 1.37734223 3.4052877 0.17222508 56.84For adults until 80 years, leptin standard deviation scores will be
calclated based on age on years and BMI. BMI is passed to the
sds_2d() function via the x2= argument.
Besides, the sds_2d() function takes the leptin value
(value=), sex (sex=) and age
(age=) as arguments. These values have to be given as
vectors of the same length. In addition, it needs a reference object (in
our case ref=leptin.ref) and the item (item=).
For adults, it is ‘lep_bmi’. The function returns a numeric vector of
the same length containing leptin-SDS (type="SDS") or
leptin percentiles (type="perc").
df <- data.frame(age = seq(20, 80, by = 10),
sex = sample(c("M","F"),7, replace = T),
bmi = runif(7, 20, 40),
leptin = runif(7, min = 0.01, max = 20))
df
#> age sex bmi leptin
#> 1 20 M 31.76071 7.358202
#> 2 30 F 25.47342 3.142323
#> 3 40 F 23.57701 3.018254
#> 4 50 M 28.98567 2.780419
#> 5 60 M 24.21903 4.581769
#> 6 70 F 22.30586 1.320357
#> 7 80 F 35.35170 10.372383
df$leptin_sds <- sds_2d(value = df$leptin,
age = df$age,
x2 = df$bmi,
sex = df$sex, male = "M", female = "F",
item = "lep_bmi",
ref = leptin.ref)
df
#> age sex bmi leptin leptin_sds
#> 1 20 M 31.76071 7.358202 -0.4867854
#> 2 30 F 25.47342 3.142323 -1.6855150
#> 3 40 F 23.57701 3.018254 -1.4226517
#> 4 50 M 28.98567 2.780419 -1.0524660
#> 5 60 M 24.21903 4.581769 0.9650217
#> 6 70 F 22.30586 1.320357 -1.7061887
#> 7 80 F 35.35170 10.372383 -1.5545634