The first function, getWGSR(), is usually called by the addWGSR() function but could be used as a stand-alone calculator for getting z-score for a given anthropometric measurement.

getWGSR(sex, firstPart, secondPart, thirdPart = NA, index = NA, standing = NA)

addWGSR(
  data,
  sex,
  firstPart,
  secondPart,
  thirdPart = NA,
  index = NA,
  standing = NULL,
  output = paste(index, "z", sep = ""),
  digits = 2
)

Arguments

sex

Name of variable specifying the sex of the subject. This must be coded as 1 = male and 2 = female. Give a quoted variable name as in (e.g.) "sex".

firstPart

Name of variable specifying:

  • Weight (kg) for BMI/A, W/A, W/H, or W/L

  • Head circumference (cm) for HC/A

  • Height (cm) for BMI/A for H/A

  • Length (cm) for L/A

  • MUAC (cm) for MUAC/A

  • Sub-scapular skinfold (mm) for SSF/A

  • Triceps skinfold (mm) for TSF/A

Give a quoted variable name as in (e.g.) "weight". Be careful with units (weight in kg; height, length, head circumference, and MUAC in cm, skinfolds in mm).

secondPart

Name of variable specifying:

  • Age (days) for H/A, HC/A, L/A, MUAC/A, SSF/A, or TSF/A

  • Height (cm) BMI/A or W/H

  • Length (cm) for W/L

Give a quoted variable name as in (e.g.) "age". Be careful with units (age in days; height and length in cm).

thirdPart

Name of variable specifying age (in days) for BMI/A. Give a quoted variable name as in (e.g.) "age". Be careful with units (age in days).

index

The index to be calculated and added to data. One of:

IndexDefinition
bfaBMI for age
hcaHead circumference for age
hfaHeight for age
lfaLength for age
mfaMUAC for age
ssaSub-scapular skinfold for age
tsaTriceps skinfold for age
wfaWeight for age
wfhWeight for height
wflWeight for length

Give a quoted index name as in (e.g.) "wfh".

standing

Variable specifying how stature was measured. If NULL then age (for "hfa" or "lfa") or height rules (for "wfh" or "wfl") will be applied. This must be coded as 1 = Standing; 2 = Supine; 3 = Unknown. All other values will be recoded to 3 = Unknown. Give a quoted variable name as in (e.g.) "measured" or a single value (e.g. "measured = 1). If no value (or NULL) is specified then height and age rules will be applied.

data

A survey dataset as a data.frame object

output

The name of the column containing the specified index to be added to the dataset. This is an optional parameter. If you do not specify a value for output then the added column will take the name of the specified index with a "z" appended.

digits

The number of decimal places for output. Defaults to 2 d.p.

Value

A data.frame of the survey dataset with the calculated z-scores added.

Details

addWGSR() adds the WHO Growth Reference z-scores to a data frame of anthropometric data for weight, height or length, MUAC, head circumference, sub-scapular skinfold, triceps skinfold, and body mass index (BMI).

Examples

# Given a male child 10 months old with a weight of 5.7 kgs, height of 64.2 # cms, and MUAC of 125 mm: # # Calculate weight-for-height getWGSR(sex = 1, firstPart = 5.7, secondPart = 64.2, index = "wfh", standing = 3)
#> [1] -2.725778
# calculate weight-for-age getWGSR(sex = 1, firstPart = 5.7, secondPart = 10, index = "wfa", standing = 3)
#> [1] 3.452888
# calculate height-for-age getWGSR(sex = 1, firstPart = 64.2, secondPart = 10, index = "hfa", standing = 3)
#> [1] 6.584276
# Calculate MUAC-for-age z-score for a girl getWGSR(sex = 1, firstPart = 20, secondPart = 62 * (365.25 / 12), index = "mfa")
#> [1] 1.992728
# Calculate weight-for-height (wfh) for the anthro3 dataset addWGSR(data = anthro3, sex = "sex", firstPart = "weight", secondPart = "height", index = "wfh")
#> ================================================================================
#> psu age sex weight height muac oedema wfhz #> 1 1 10 1 5.7 64.2 125 2 -2.73 #> 2 1 10 2 5.8 64.4 121 2 -2.04 #> 3 1 9 2 6.5 62.2 139 2 0.13 #> 4 1 11 9 6.5 64.9 129 2 NA #> 5 1 24 2 6.5 72.9 120 2 -3.44 #> 6 1 12 2 6.6 69.4 126 2 -2.26 #> 7 1 9 2 7.0 66.7 136 2 -0.71 #> 8 1 7 1 7.1 63.5 139 2 0.34 #> 9 1 9 2 7.1 66.2 144 2 -0.39 #> 10 1 16 2 7.2 69.0 131 2 -1.12 #> 11 1 13 2 7.4 68.2 137 2 -0.57 #> 12 1 11 2 7.4 70.0 132 2 -1.10 #> 13 1 14 2 7.5 64.8 125 2 0.69 #> 14 2 8 2 7.5 65.7 151 2 0.38 #> 15 2 8 1 7.5 69.1 140 2 -1.13 #> 16 2 13 1 7.6 69.2 131 2 -1.00 #> 17 2 13 2 7.6 70.0 125 2 -0.80 #> 18 2 22 2 7.6 76.2 121 2 -2.43 #> 19 2 16 1 7.7 69.6 136 2 -0.97 #> 20 2 8 2 7.8 63.3 144 2 1.64 #> 21 2 11 2 7.8 71.5 134 2 -0.92 #> 22 2 14 2 7.8 76.6 124 2 -2.21 #> 23 2 7 1 8.0 66.8 139 2 0.48 #> 24 2 8 1 8.0 69.3 147 2 -0.40 #> 25 2 24 2 8.2 70.7 125 2 -0.14 #> 26 2 10 1 8.2 71.1 145 2 -0.68 #> 27 3 15 1 8.3 70.4 133 2 -0.31 #> 28 3 14 2 8.3 71.5 137 2 -0.22 #> 29 3 14 2 8.3 72.9 141 2 -0.59 #> 30 3 17 2 8.3 73.5 136 2 -0.74 #> 31 3 15 1 8.3 76.1 133 2 -1.96 #> 32 3 13 2 8.4 71.8 143 2 -0.17 #> 33 3 20 1 8.4 77.8 132 2 -2.22 #> 34 3 29 2 8.5 75.6 127 2 -0.97 #> 35 3 21 2 8.5 75.6 133 2 -0.97 #> 36 3 21 1 8.5 76.7 123 2 -1.81 #> 37 3 17 1 8.5 77.6 137 2 -2.02 #> 38 3 15 2 8.6 74.9 134 2 -0.67 #> 39 3 24 1 8.6 77.8 137 2 -1.92 #> 40 3 12 1 8.7 72.1 156 2 -0.26 #> 41 4 27 2 8.7 75.8 127 2 -0.75 #> 42 4 25 2 8.7 80.8 129 2 -1.90 #> 43 4 25 1 8.8 81.4 125 2 -2.46 #> 44 4 24 2 8.9 74.3 142 2 -0.15 #> 45 4 30 1 9.0 77.6 132 2 -1.30 #> 46 4 22 1 9.0 82.2 135 2 -2.36 #> 47 4 16 1 9.1 76.4 145 2 -0.88 #> 48 4 24 1 9.1 80.0 126 2 -1.70 #> 49 4 17 2 9.2 74.8 144 2 0.11 #> 50 4 15 2 9.2 75.3 145 2 -0.01 #> 51 4 33 1 9.2 80.1 136 2 -1.59 #> 52 4 25 2 9.2 80.9 142 2 -1.26 #> 53 5 16 1 9.4 75.0 148 2 -0.13 #> 54 5 29 2 9.4 81.9 138 2 -1.26 #> 55 5 16 1 9.5 73.2 151 2 0.48 #> 56 5 17 1 9.6 73.5 146 2 0.52 #> 57 5 29 2 9.6 84.6 134 2 -1.70 #> 58 5 16 1 9.7 74.2 148 2 0.45 #> 59 5 20 1 9.7 80.4 142 2 -0.99 #> 60 5 34 1 9.8 80.2 138 2 -0.82 #> 61 5 21 2 9.8 80.9 145 2 -0.54 #> 62 5 20 1 9.8 82.2 139 2 -1.28 #> 63 5 29 1 9.9 78.6 142 2 -0.35 #> 64 5 25 2 9.9 82.9 138 2 -0.90 #> 65 5 15 1 10.0 75.3 157 2 0.53 #> 66 6 39 1 10.0 81.4 133 2 -0.84 #> 67 6 9 1 10.1 72.6 155 2 1.37 #> 68 6 21 1 10.1 76.7 153 2 0.31 #> 69 6 17 2 10.1 79.1 143 2 0.21 #> 70 6 25 1 10.1 79.5 140 2 -0.30 #> 71 6 13 2 10.2 74.6 157 2 1.27 #> 72 6 25 2 10.3 81.3 141 2 -0.07 #> 73 6 31 2 10.3 85.1 130 2 -1.00 #> 74 6 25 2 10.4 81.3 138 2 0.04 #> 75 6 37 1 10.6 76.2 153 2 1.00 #> 76 6 25 2 10.6 80.7 138 2 0.39 #> 77 6 26 1 10.6 83.1 142 2 -0.52 #> 78 6 36 2 10.6 84.2 135 2 -0.44 #> 79 6 37 2 10.7 84.2 150 2 -0.34 #> 80 7 34 2 10.7 85.7 146 2 -0.71 #> 81 7 47 1 10.7 89.8 131 2 -2.34 #> 82 7 12 1 10.8 82.0 147 2 -0.04 #> 83 7 25 2 10.8 83.6 141 2 -0.08 #> 84 7 31 1 10.8 83.8 158 2 -0.47 #> 85 7 34 1 10.8 84.4 144 2 -0.62 #> 86 7 27 2 10.9 79.0 153 2 1.06 #> 87 7 23 2 10.9 85.9 145 2 -0.55 #> 88 7 19 1 11.0 75.4 168 2 1.62 #> 89 7 26 2 11.0 83.2 145 2 0.22 #> 90 7 54 1 11.0 85.9 139 2 -0.79 #> 91 7 20 1 11.1 79.9 156 2 0.74 #> 92 7 23 1 11.1 84.7 146 2 -0.36 #> 93 7 43 2 11.1 86.0 142 2 -0.37 #> 94 8 31 1 11.1 87.1 143 2 -1.18 #> 95 8 40 2 11.2 95.2 137 2 -2.54 #> 96 8 18 2 11.3 75.5 161 2 2.15 #> 97 8 41 1 11.3 89.4 142 2 -1.53 #> 98 8 40 1 11.3 90.7 148 2 -1.84 #> 99 8 33 2 11.3 91.2 139 2 -1.56 #> 100 8 11 1 11.4 78.4 171 2 1.36 #> 101 8 25 1 11.4 82.2 163 2 0.57 #> 102 8 27 2 11.4 86.8 155 2 -0.26 #> 103 8 38 1 11.4 89.4 141 2 -1.41 #> 104 8 17 2 11.5 80.6 158 2 1.30 #> 105 8 31 2 11.5 85.4 153 2 0.18 #> 106 9 45 1 11.5 86.2 143 2 -0.31 #> 107 9 53 1 11.6 81.4 153 2 0.95 #> 108 9 23 2 11.6 86.3 143 2 0.05 #> 109 9 37 1 11.6 86.3 149 2 -0.23 #> 110 9 38 1 11.6 89.9 146 2 -1.31 #> 111 9 40 1 11.7 93.0 140 2 -1.91 #> 112 9 36 1 11.8 87.1 146 2 -0.40 #> 113 9 29 1 11.9 84.3 166 2 0.59 #> 114 9 26 2 12.0 81.2 164 2 1.62 #> 115 9 33 1 12.0 86.0 154 2 0.26 #> 116 9 36 1 12.0 87.5 150 2 -0.29 #> 117 9 55 2 12.0 96.2 144 2 -1.93 #> 118 10 16 1 12.1 82.3 157 2 1.25 #> 119 10 35 2 12.1 86.6 147 2 0.45 #> 120 10 43 1 12.1 91.7 151 2 -1.18 #> 121 10 38 2 12.2 80.9 175 2 1.86 #> 122 10 37 1 12.2 85.5 162 2 0.59 #> 123 10 41 2 12.2 87.6 155 2 0.14 #> 124 10 45 2 12.2 90.1 149 2 -0.43 #> 125 10 46 2 12.2 99.6 146 2 -2.46 #> 126 10 31 1 12.3 88.0 167 2 -0.11 #> 127 10 44 1 12.3 88.1 151 2 -0.13 #> 128 10 47 2 12.3 94.9 133 2 -1.37 #> 129 10 29 1 12.4 91.8 141 2 -0.89 #> 130 10 46 2 12.4 99.6 140 2 -2.26 #> 131 10 34 1 12.6 87.0 156 2 0.43 #> 132 10 38 2 12.7 85.7 152 2 1.20 #> 133 11 32 1 12.8 87.6 161 2 0.48 #> 134 11 36 1 12.8 90.4 150 2 -0.17 #> 135 11 39 1 12.8 92.7 152 2 -0.69 #> 136 11 42 1 12.8 94.0 146 2 -0.97 #> 137 11 38 2 12.9 83.4 174 2 1.90 #> 138 11 26 2 12.9 86.2 159 2 1.25 #> 139 11 35 1 12.9 90.9 154 2 -0.19 #> 140 11 41 1 12.9 91.2 160 2 -0.26 #> 141 11 32 1 12.9 91.4 148 2 -0.30 #> 142 11 49 1 13.0 93.1 152 2 -0.58 #> 143 11 30 1 13.1 84.3 161 2 1.72 #> 144 11 32 1 13.1 85.1 136 2 1.53 #> 145 11 35 1 13.1 87.5 158 2 0.78 #> 146 11 34 1 13.1 88.6 162 2 0.52 #> 147 11 45 2 13.1 91.6 150 2 0.05 #> 148 12 29 1 13.2 90.8 158 2 0.12 #> 149 12 47 2 13.2 91.4 146 2 0.18 #> 150 12 37 2 13.2 93.8 155 2 -0.33 #> 151 12 35 1 13.3 96.5 142 2 -1.02 #> 152 12 15 2 13.4 82.4 157 2 2.51 #> 153 12 38 2 13.4 93.0 152 2 0.01 #> 154 12 37 2 13.4 94.1 149 2 -0.22 #> 155 12 53 2 13.4 100.3 145 2 -1.50 #> 156 12 37 2 13.5 84.4 168 2 2.14 #> 157 12 43 1 13.5 96.1 151 2 -0.74 #> 158 12 52 1 13.5 97.0 144 2 -0.94 #> 159 12 45 2 13.5 98.0 148 2 -0.94 #> 160 12 39 2 13.5 99.1 145 2 -1.16 #> 161 12 47 2 13.6 97.0 146 2 -0.65 #> 162 13 26 2 13.7 85.7 171 2 2.00 #> 163 13 24 1 13.8 80.9 172 2 3.02 #> 164 13 38 2 13.8 93.3 153 2 0.27 #> 165 13 57 1 13.8 94.0 149 2 -0.02 #> 166 13 42 2 13.8 103.4 144 2 -1.84 #> 167 13 42 2 13.9 92.3 175 2 0.56 #> 168 13 52 1 13.9 95.5 151 2 -0.25 #> 169 13 52 1 13.9 95.7 156 2 -0.29 #> 170 13 57 2 13.9 97.2 153 2 -0.44 #> 171 13 52 2 13.9 97.8 141 2 -0.56 #> 172 13 52 2 13.9 97.9 155 2 -0.58 #> 173 13 49 2 13.9 98.2 150 2 -0.64 #> 174 13 58 2 14.0 96.6 154 2 -0.24 #> 175 13 50 1 14.0 97.9 158 2 -0.68 #> 176 13 39 2 14.1 93.7 155 2 0.43 #> 177 14 49 2 14.1 96.4 140 2 -0.12 #> 178 14 50 2 14.1 97.1 148 2 -0.26 #> 179 14 59 2 14.1 97.3 152 2 -0.30 #> 180 14 52 2 14.1 102.4 156 2 -1.37 #> 181 14 41 1 14.2 96.7 146 2 -0.24 #> 182 14 53 1 14.2 97.7 151 2 -0.46 #> 183 14 49 2 14.2 98.1 156 2 -0.38 #> 184 14 35 2 14.3 89.8 165 2 1.39 #> 185 14 50 1 14.3 93.7 152 2 0.48 #> 186 14 41 1 14.4 94.8 158 2 0.34 #> 187 14 42 1 14.5 95.1 161 2 0.36 #> 188 14 58 1 14.5 104.9 130 2 -1.79 #> 189 14 49 1 14.7 96.6 152 2 0.21 #> 190 14 52 2 14.7 96.7 154 2 0.28 #> 191 14 51 2 14.7 99.2 155 2 -0.22 #> 192 14 49 1 14.7 99.6 164 2 -0.45 #> 193 15 42 2 15.0 93.5 172 2 1.14 #> 194 15 28 2 15.1 91.5 164 2 1.62 #> 195 15 41 2 15.2 95.9 165 2 0.81 #> 196 15 53 1 15.3 95.0 166 2 1.03 #> 197 15 58 1 15.3 100.7 155 2 -0.20 #> 198 15 48 1 15.3 103.5 143 2 -0.82 #> 199 15 54 1 15.5 97.9 159 2 0.57 #> 200 15 58 1 15.5 101.3 166 2 -0.18 #> 201 15 52 2 15.6 100.0 164 2 0.27 #> 202 15 50 1 15.7 99.6 153 2 0.36 #> 203 15 53 2 15.7 103.1 158 2 -0.32 #> 204 15 43 1 15.8 91.1 179 2 2.22 #> 205 15 57 1 15.9 103.8 161 2 -0.42 #> 206 15 55 2 16.3 95.4 169 2 1.65 #> 207 16 54 2 15.3 102.0 156 2 -0.37 #> 208 16 44 1 16.3 96.2 173 2 1.54 #> 209 16 47 1 16.3 102.0 166 2 0.27 #> 210 16 57 1 16.3 108.4 138 2 -1.13 #> 211 16 52 1 16.4 103.9 152 2 -0.07 #> 212 16 52 2 16.6 97.8 144 2 1.37 #> 213 16 56 1 16.6 103.9 148 2 0.07 #> 214 16 55 1 16.7 106.3 154 2 -0.39 #> 215 16 52 1 17.0 101.3 163 2 0.93 #> 216 16 50 1 17.3 101.8 168 2 1.02 #> 217 16 53 1 17.5 102.2 168 2 1.06 #> 218 16 42 1 17.7 100.9 145 2 1.48 #> 219 16 48 2 17.8 111.3 176 2 -0.77 #> 220 16 53 1 17.9 98.7 171 2 2.10 #> 221 16 50 1 18.1 106.4 166 2 0.53
# Calculate weight-for-age (wfa) for the anthro3 dataset addWGSR(data = anthro3, sex = "sex", firstPart = "weight", secondPart = "age", index = "wfa")
#> ================================================================================
#> psu age sex weight height muac oedema wfaz #> 1 1 10 1 5.7 64.2 125 2 3.45 #> 2 1 10 2 5.8 64.4 121 2 3.95 #> 3 1 9 2 6.5 62.2 139 2 5.12 #> 4 1 11 9 6.5 64.9 129 2 NA #> 5 1 24 2 6.5 72.9 120 2 3.82 #> 6 1 12 2 6.6 69.4 126 2 5.01 #> 7 1 9 2 7.0 66.7 136 2 5.91 #> 8 1 7 1 7.1 63.5 139 2 5.84 #> 9 1 9 2 7.1 66.2 144 2 6.06 #> 10 1 16 2 7.2 69.0 131 2 5.53 #> 11 1 13 2 7.4 68.2 137 2 6.13 #> 12 1 11 2 7.4 70.0 132 2 6.33 #> 13 1 14 2 7.5 64.8 125 2 6.18 #> 14 2 8 2 7.5 65.7 151 2 6.79 #> 15 2 8 1 7.5 69.1 140 2 6.36 #> 16 2 13 1 7.6 69.2 131 2 6.02 #> 17 2 13 2 7.6 70.0 125 2 6.43 #> 18 2 22 2 7.6 76.2 121 2 5.52 #> 19 2 16 1 7.7 69.6 136 2 5.84 #> 20 2 8 2 7.8 63.3 144 2 7.26 #> 21 2 11 2 7.8 71.5 134 2 6.95 #> 22 2 14 2 7.8 76.6 124 2 6.63 #> 23 2 7 1 8.0 66.8 139 2 7.23 #> 24 2 8 1 8.0 69.3 147 2 7.13 #> 25 2 24 2 8.2 70.7 125 2 6.17 #> 26 2 10 1 8.2 71.1 145 2 7.23 #> 27 3 15 1 8.3 70.4 133 2 6.82 #> 28 3 14 2 8.3 71.5 137 2 7.38 #> 29 3 14 2 8.3 72.9 141 2 7.38 #> 30 3 17 2 8.3 73.5 136 2 7.04 #> 31 3 15 1 8.3 76.1 133 2 6.82 #> 32 3 13 2 8.4 71.8 143 2 7.64 #> 33 3 20 1 8.4 77.8 132 2 6.41 #> 34 3 29 2 8.5 75.6 127 2 6.12 #> 35 3 21 2 8.5 75.6 133 2 6.89 #> 36 3 21 1 8.5 76.7 123 2 6.44 #> 37 3 17 1 8.5 77.6 137 2 6.88 #> 38 3 15 2 8.6 74.9 134 2 7.71 #> 39 3 24 1 8.6 77.8 137 2 6.26 #> 40 3 12 1 8.7 72.1 156 2 7.76 #> 41 4 27 2 8.7 75.8 127 2 6.57 #> 42 4 25 2 8.7 80.8 129 2 6.76 #> 43 4 25 1 8.8 81.4 125 2 6.43 #> 44 4 24 2 8.9 74.3 142 2 7.14 #> 45 4 30 1 9.0 77.6 132 2 6.21 #> 46 4 22 1 9.0 82.2 135 2 7.02 #> 47 4 16 1 9.1 76.4 145 2 7.86 #> 48 4 24 1 9.1 80.0 126 2 6.94 #> 49 4 17 2 9.2 74.8 144 2 8.35 #> 50 4 15 2 9.2 75.3 145 2 8.60 #> 51 4 33 1 9.2 80.1 136 2 6.20 #> 52 4 25 2 9.2 80.9 142 2 7.45 #> 53 5 16 1 9.4 75.0 148 2 8.30 #> 54 5 29 2 9.4 81.9 138 2 7.32 #> 55 5 16 1 9.5 73.2 151 2 8.44 #> 56 5 17 1 9.6 73.5 146 2 8.46 #> 57 5 29 2 9.6 84.6 134 2 7.58 #> 58 5 16 1 9.7 74.2 148 2 8.73 #> 59 5 20 1 9.7 80.4 142 2 8.22 #> 60 5 34 1 9.8 80.2 138 2 6.88 #> 61 5 21 2 9.8 80.9 145 2 8.73 #> 62 5 20 1 9.8 82.2 139 2 8.36 #> 63 5 29 1 9.9 78.6 142 2 7.48 #> 64 5 25 2 9.9 82.9 138 2 8.41 #> 65 5 15 1 10.0 75.3 157 2 9.30 #> 66 6 39 1 10.0 81.4 133 2 6.71 #> 67 6 9 1 10.1 72.6 155 2 10.22 #> 68 6 21 1 10.1 76.7 153 2 8.66 #> 69 6 17 2 10.1 79.1 143 2 9.67 #> 70 6 25 1 10.1 79.5 140 2 8.18 #> 71 6 13 2 10.2 74.6 157 2 10.36 #> 72 6 25 2 10.3 81.3 141 2 8.95 #> 73 6 31 2 10.3 85.1 130 2 8.31 #> 74 6 25 2 10.4 81.3 138 2 9.09 #> 75 6 37 1 10.6 76.2 153 2 7.62 #> 76 6 25 2 10.6 80.7 138 2 9.37 #> 77 6 26 1 10.6 83.1 142 2 8.74 #> 78 6 36 2 10.6 84.2 135 2 8.22 #> 79 6 37 2 10.7 84.2 150 2 8.26 #> 80 7 34 2 10.7 85.7 146 2 8.54 #> 81 7 47 1 10.7 89.8 131 2 6.96 #> 82 7 12 1 10.8 82.0 147 2 10.88 #> 83 7 25 2 10.8 83.6 141 2 9.64 #> 84 7 31 1 10.8 83.8 158 2 8.45 #> 85 7 34 1 10.8 84.4 144 2 8.15 #> 86 7 27 2 10.9 79.0 153 2 9.54 #> 87 7 23 2 10.9 85.9 145 2 10.02 #> 88 7 19 1 11.0 75.4 168 2 10.18 #> 89 7 26 2 11.0 83.2 145 2 9.79 #> 90 7 54 1 11.0 85.9 139 2 6.85 #> 91 7 20 1 11.1 79.9 156 2 10.18 #> 92 7 23 1 11.1 84.7 146 2 9.78 #> 93 7 43 2 11.1 86.0 142 2 8.24 #> 94 8 31 1 11.1 87.1 143 2 8.84 #> 95 8 40 2 11.2 95.2 137 2 8.62 #> 96 8 18 2 11.3 75.5 161 2 11.27 #> 97 8 41 1 11.3 89.4 142 2 8.15 #> 98 8 40 1 11.3 90.7 148 2 8.23 #> 99 8 33 2 11.3 91.2 139 2 9.41 #> 100 8 11 1 11.4 78.4 171 2 11.92 #> 101 8 25 1 11.4 82.2 163 2 9.94 #> 102 8 27 2 11.4 86.8 155 2 10.22 #> 103 8 38 1 11.4 89.4 141 2 8.53 #> 104 8 17 2 11.5 80.6 158 2 11.71 #> 105 8 31 2 11.5 85.4 153 2 9.89 #> 106 9 45 1 11.5 86.2 143 2 8.07 #> 107 9 53 1 11.6 81.4 153 2 7.61 #> 108 9 23 2 11.6 86.3 143 2 11.00 #> 109 9 37 1 11.6 86.3 149 2 8.88 #> 110 9 38 1 11.6 89.9 146 2 8.78 #> 111 9 40 1 11.7 93.0 140 2 8.73 #> 112 9 36 1 11.8 87.1 146 2 9.22 #> 113 9 29 1 11.9 84.3 166 2 10.11 #> 114 9 26 2 12.0 81.2 164 2 11.15 #> 115 9 33 1 12.0 86.0 154 2 9.79 #> 116 9 36 1 12.0 87.5 150 2 9.48 #> 117 9 55 2 12.0 96.2 144 2 8.41 #> 118 10 16 1 12.1 82.3 157 2 12.19 #> 119 10 35 2 12.1 86.6 147 2 10.24 #> 120 10 43 1 12.1 91.7 151 2 8.96 #> 121 10 38 2 12.2 80.9 175 2 10.06 #> 122 10 37 1 12.2 85.5 162 2 9.63 #> 123 10 41 2 12.2 87.6 155 2 9.77 #> 124 10 45 2 12.2 90.1 149 2 9.42 #> 125 10 46 2 12.2 99.6 146 2 9.33 #> 126 10 31 1 12.3 88.0 167 2 10.40 #> 127 10 44 1 12.3 88.1 151 2 9.12 #> 128 10 47 2 12.3 94.9 133 2 9.37 #> 129 10 29 1 12.4 91.8 141 2 10.77 #> 130 10 46 2 12.4 99.6 140 2 9.57 #> 131 10 34 1 12.6 87.0 156 2 10.45 #> 132 10 38 2 12.7 85.7 152 2 10.69 #> 133 11 32 1 12.8 87.6 161 2 10.93 #> 134 11 36 1 12.8 90.4 150 2 10.49 #> 135 11 39 1 12.8 92.7 152 2 10.18 #> 136 11 42 1 12.8 94.0 146 2 9.90 #> 137 11 38 2 12.9 83.4 174 2 10.94 #> 138 11 26 2 12.9 86.2 159 2 12.38 #> 139 11 35 1 12.9 90.9 154 2 10.72 #> 140 11 41 1 12.9 91.2 160 2 10.12 #> 141 11 32 1 12.9 91.4 148 2 11.06 #> 142 11 49 1 13.0 93.1 152 2 9.55 #> 143 11 30 1 13.1 84.3 161 2 11.56 #> 144 11 32 1 13.1 85.1 136 2 11.32 #> 145 11 35 1 13.1 87.5 158 2 10.97 #> 146 11 34 1 13.1 88.6 162 2 11.08 #> 147 11 45 2 13.1 91.6 150 2 10.51 #> 148 12 29 1 13.2 90.8 158 2 11.82 #> 149 12 47 2 13.2 91.4 146 2 10.45 #> 150 12 37 2 13.2 93.8 155 2 11.42 #> 151 12 35 1 13.3 96.5 142 2 11.23 #> 152 12 15 2 13.4 82.4 157 2 14.84 #> 153 12 38 2 13.4 93.0 152 2 11.57 #> 154 12 37 2 13.4 94.1 149 2 11.68 #> 155 12 53 2 13.4 100.3 145 2 10.18 #> 156 12 37 2 13.5 84.4 168 2 11.80 #> 157 12 43 1 13.5 96.1 151 2 10.66 #> 158 12 52 1 13.5 97.0 144 2 9.91 #> 159 12 45 2 13.5 98.0 148 2 10.99 #> 160 12 39 2 13.5 99.1 145 2 11.59 #> 161 12 47 2 13.6 97.0 146 2 10.93 #> 162 13 26 2 13.7 85.7 171 2 13.47 #> 163 13 24 1 13.8 80.9 172 2 13.32 #> 164 13 38 2 13.8 93.3 153 2 12.07 #> 165 13 57 1 13.8 94.0 149 2 9.90 #> 166 13 42 2 13.8 103.4 144 2 11.65 #> 167 13 42 2 13.9 92.3 175 2 11.77 #> 168 13 52 1 13.9 95.5 151 2 10.38 #> 169 13 52 1 13.9 95.7 156 2 10.38 #> 170 13 57 2 13.9 97.2 153 2 10.45 #> 171 13 52 2 13.9 97.8 141 2 10.85 #> 172 13 52 2 13.9 97.9 155 2 10.85 #> 173 13 49 2 13.9 98.2 150 2 11.10 #> 174 13 58 2 14.0 96.6 154 2 10.49 #> 175 13 50 1 14.0 97.9 158 2 10.66 #> 176 13 39 2 14.1 93.7 155 2 12.34 #> 177 14 49 2 14.1 96.4 140 2 11.34 #> 178 14 50 2 14.1 97.1 148 2 11.25 #> 179 14 59 2 14.1 97.3 152 2 10.52 #> 180 14 52 2 14.1 102.4 156 2 11.08 #> 181 14 41 1 14.2 96.7 146 2 11.71 #> 182 14 53 1 14.2 97.7 151 2 10.66 #> 183 14 49 2 14.2 98.1 156 2 11.46 #> 184 14 35 2 14.3 89.8 165 2 13.05 #> 185 14 50 1 14.3 93.7 152 2 11.01 #> 186 14 41 1 14.4 94.8 158 2 11.96 #> 187 14 42 1 14.5 95.1 161 2 11.98 #> 188 14 58 1 14.5 104.9 130 2 10.64 #> 189 14 49 1 14.7 96.6 152 2 11.57 #> 190 14 52 2 14.7 96.7 154 2 11.78 #> 191 14 51 2 14.7 99.2 155 2 11.87 #> 192 14 49 1 14.7 99.6 164 2 11.57 #> 193 15 42 2 15.0 93.5 172 2 13.12 #> 194 15 28 2 15.1 91.5 164 2 15.06 #> 195 15 41 2 15.2 95.9 165 2 13.48 #> 196 15 53 1 15.3 95.0 166 2 11.94 #> 197 15 58 1 15.3 100.7 155 2 11.56 #> 198 15 48 1 15.3 103.5 143 2 12.37 #> 199 15 54 1 15.5 97.9 159 2 12.10 #> 200 15 58 1 15.5 101.3 166 2 11.79 #> 201 15 52 2 15.6 100.0 164 2 12.83 #> 202 15 50 1 15.7 99.6 153 2 12.67 #> 203 15 53 2 15.7 103.1 158 2 12.86 #> 204 15 43 1 15.8 91.1 179 2 13.47 #> 205 15 57 1 15.9 103.8 161 2 12.32 #> 206 15 55 2 16.3 95.4 169 2 13.37 #> 207 16 54 2 15.3 102.0 156 2 12.30 #> 208 16 44 1 16.3 96.2 173 2 13.97 #> 209 16 47 1 16.3 102.0 166 2 13.66 #> 210 16 57 1 16.3 108.4 138 2 12.78 #> 211 16 52 1 16.4 103.9 152 2 13.32 #> 212 16 52 2 16.6 97.8 144 2 14.00 #> 213 16 56 1 16.6 103.9 148 2 13.21 #> 214 16 55 1 16.7 106.3 154 2 13.41 #> 215 16 52 1 17.0 101.3 163 2 14.02 #> 216 16 50 1 17.3 101.8 168 2 14.56 #> 217 16 53 1 17.5 102.2 168 2 14.52 #> 218 16 42 1 17.7 100.9 145 2 15.90 #> 219 16 48 2 17.8 111.3 176 2 15.84 #> 220 16 53 1 17.9 98.7 171 2 14.98 #> 221 16 50 1 18.1 106.4 166 2 15.51
# Calculate height-for-age (hfa) for the anthro3 dataset addWGSR(data = anthro3, sex = "sex", firstPart = "height", secondPart = "age", index = "hfa")
#> ================================================================================
#> psu age sex weight height muac oedema hfaz #> 1 1 10 1 5.7 64.2 125 2 6.58 #> 2 1 10 2 5.8 64.4 121 2 7.17 #> 3 1 9 2 6.5 62.2 139 2 6.11 #> 4 1 11 9 6.5 64.9 129 2 NA #> 5 1 24 2 6.5 72.9 120 2 10.35 #> 6 1 12 2 6.6 69.4 126 2 9.60 #> 7 1 9 2 7.0 66.7 136 2 8.49 #> 8 1 7 1 7.1 63.5 139 2 6.51 #> 9 1 9 2 7.1 66.2 144 2 8.22 #> 10 1 16 2 7.2 69.0 131 2 9.01 #> 11 1 13 2 7.4 68.2 137 2 8.87 #> 12 1 11 2 7.4 70.0 132 2 10.02 #> 13 1 14 2 7.5 64.8 125 2 6.98 #> 14 2 8 2 7.5 65.7 151 2 8.06 #> 15 2 8 1 7.5 69.1 140 2 9.35 #> 16 2 13 1 7.6 69.2 131 2 8.91 #> 17 2 13 2 7.6 70.0 125 2 9.82 #> 18 2 22 2 7.6 76.2 121 2 12.24 #> 19 2 16 1 7.7 69.6 136 2 8.85 #> 20 2 8 2 7.8 63.3 144 2 6.79 #> 21 2 11 2 7.8 71.5 134 2 10.82 #> 22 2 14 2 7.8 76.6 124 2 13.18 #> 23 2 7 1 8.0 66.8 139 2 8.24 #> 24 2 8 1 8.0 69.3 147 2 9.46 #> 25 2 24 2 8.2 70.7 125 2 9.22 #> 26 2 10 1 8.2 71.1 145 2 10.20 #> 27 3 15 1 8.3 70.4 133 2 9.36 #> 28 3 14 2 8.3 71.5 137 2 10.50 #> 29 3 14 2 8.3 72.9 141 2 11.24 #> 30 3 17 2 8.3 73.5 136 2 11.28 #> 31 3 15 1 8.3 76.1 133 2 12.33 #> 32 3 13 2 8.4 71.8 143 2 10.77 #> 33 3 20 1 8.4 77.8 132 2 12.76 #> 34 3 29 2 8.5 75.6 127 2 11.33 #> 35 3 21 2 8.5 75.6 133 2 12.02 #> 36 3 21 1 8.5 76.7 123 2 12.10 #> 37 3 17 1 8.5 77.6 137 2 12.93 #> 38 3 15 2 8.6 74.9 134 2 12.20 #> 39 3 24 1 8.6 77.8 137 2 12.40 #> 40 3 12 1 8.7 72.1 156 2 10.53 #> 41 4 27 2 8.7 75.8 127 2 11.60 #> 42 4 25 2 8.7 80.8 129 2 14.35 #> 43 4 25 1 8.8 81.4 125 2 14.18 #> 44 4 24 2 8.9 74.3 142 2 11.08 #> 45 4 30 1 9.0 77.6 132 2 11.79 #> 46 4 22 1 9.0 82.2 135 2 14.86 #> 47 4 16 1 9.1 76.4 145 2 12.40 #> 48 4 24 1 9.1 80.0 126 2 13.54 #> 49 4 17 2 9.2 74.8 144 2 11.96 #> 50 4 15 2 9.2 75.3 145 2 12.41 #> 51 4 33 1 9.2 80.1 136 2 12.82 #> 52 4 25 2 9.2 80.9 142 2 14.40 #> 53 5 16 1 9.4 75.0 148 2 11.67 #> 54 5 29 2 9.4 81.9 138 2 14.56 #> 55 5 16 1 9.5 73.2 151 2 10.73 #> 56 5 17 1 9.6 73.5 146 2 10.79 #> 57 5 29 2 9.6 84.6 134 2 15.95 #> 58 5 16 1 9.7 74.2 148 2 11.25 #> 59 5 20 1 9.7 80.4 142 2 14.11 #> 60 5 34 1 9.8 80.2 138 2 12.79 #> 61 5 21 2 9.8 80.9 145 2 14.77 #> 62 5 20 1 9.8 82.2 139 2 15.04 #> 63 5 29 1 9.9 78.6 142 2 12.38 #> 64 5 25 2 9.9 82.9 138 2 15.43 #> 65 5 15 1 10.0 75.3 157 2 11.92 #> 66 6 39 1 10.0 81.4 133 2 13.01 #> 67 6 9 1 10.1 72.6 155 2 11.09 #> 68 6 21 1 10.1 76.7 153 2 12.10 #> 69 6 17 2 10.1 79.1 143 2 14.21 #> 70 6 25 1 10.1 79.5 140 2 13.19 #> 71 6 13 2 10.2 74.6 157 2 12.24 #> 72 6 25 2 10.3 81.3 141 2 14.61 #> 73 6 31 2 10.3 85.1 130 2 16.03 #> 74 6 25 2 10.4 81.3 138 2 14.61 #> 75 6 37 1 10.6 76.2 153 2 10.51 #> 76 6 25 2 10.6 80.7 138 2 14.30 #> 77 6 26 1 10.6 83.1 142 2 14.96 #> 78 6 36 2 10.6 84.2 135 2 15.14 #> 79 6 37 2 10.7 84.2 150 2 15.06 #> 80 7 34 2 10.7 85.7 146 2 16.07 #> 81 7 47 1 10.7 89.8 131 2 16.66 #> 82 7 12 1 10.8 82.0 147 2 15.72 #> 83 7 25 2 10.8 83.6 141 2 15.80 #> 84 7 31 1 10.8 83.8 158 2 14.89 #> 85 7 34 1 10.8 84.4 144 2 14.94 #> 86 7 27 2 10.9 79.0 153 2 13.25 #> 87 7 23 2 10.9 85.9 145 2 17.17 #> 88 7 19 1 11.0 75.4 168 2 11.60 #> 89 7 26 2 11.0 83.2 145 2 15.50 #> 90 7 54 1 11.0 85.9 139 2 14.19 #> 91 7 20 1 11.1 79.9 156 2 13.85 #> 92 7 23 1 11.1 84.7 146 2 16.06 #> 93 7 43 2 11.1 86.0 142 2 15.49 #> 94 8 31 1 11.1 87.1 143 2 16.58 #> 95 8 40 2 11.2 95.2 137 2 20.37 #> 96 8 18 2 11.3 75.5 161 2 12.23 #> 97 8 41 1 11.3 89.4 142 2 16.92 #> 98 8 40 1 11.3 90.7 148 2 17.67 #> 99 8 33 2 11.3 91.2 139 2 18.96 #> 100 8 11 1 11.4 78.4 171 2 13.93 #> 101 8 25 1 11.4 82.2 163 2 14.59 #> 102 8 27 2 11.4 86.8 155 2 17.26 #> 103 8 38 1 11.4 89.4 141 2 17.16 #> 104 8 17 2 11.5 80.6 158 2 14.99 #> 105 8 31 2 11.5 85.4 153 2 16.18 #> 106 9 45 1 11.5 86.2 143 2 14.99 #> 107 9 53 1 11.6 81.4 153 2 12.00 #> 108 9 23 2 11.6 86.3 143 2 17.38 #> 109 9 37 1 11.6 86.3 149 2 15.67 #> 110 9 38 1 11.6 89.9 146 2 17.42 #> 111 9 40 1 11.7 93.0 140 2 18.84 #> 112 9 36 1 11.8 87.1 146 2 16.16 #> 113 9 29 1 11.9 84.3 166 2 15.32 #> 114 9 26 2 12.0 81.2 164 2 14.47 #> 115 9 33 1 12.0 86.0 154 2 15.85 #> 116 9 36 1 12.0 87.5 150 2 16.36 #> 117 9 55 2 12.0 96.2 144 2 19.65 #> 118 10 16 1 12.1 82.3 157 2 15.48 #> 119 10 35 2 12.1 86.6 147 2 16.44 #> 120 10 43 1 12.1 91.7 151 2 17.94 #> 121 10 38 2 12.2 80.9 175 2 13.31 #> 122 10 37 1 12.2 85.5 162 2 15.26 #> 123 10 41 2 12.2 87.6 155 2 16.45 #> 124 10 45 2 12.2 90.1 149 2 17.39 #> 125 10 46 2 12.2 99.6 146 2 22.06 #> 126 10 31 1 12.3 88.0 167 2 17.05 #> 127 10 44 1 12.3 88.1 151 2 16.03 #> 128 10 47 2 12.3 94.9 133 2 19.63 #> 129 10 29 1 12.4 91.8 141 2 19.17 #> 130 10 46 2 12.4 99.6 140 2 22.06 #> 131 10 34 1 12.6 87.0 156 2 16.27 #> 132 10 38 2 12.7 85.7 152 2 15.74 #> 133 11 32 1 12.8 87.6 161 2 16.75 #> 134 11 36 1 12.8 90.4 150 2 17.84 #> 135 11 39 1 12.8 92.7 152 2 18.77 #> 136 11 42 1 12.8 94.0 146 2 19.18 #> 137 11 38 2 12.9 83.4 174 2 14.57 #> 138 11 26 2 12.9 86.2 159 2 17.04 #> 139 11 35 1 12.9 90.9 154 2 18.18 #> 140 11 41 1 12.9 91.2 160 2 17.84 #> 141 11 32 1 12.9 91.4 148 2 18.70 #> 142 11 49 1 13.0 93.1 152 2 18.18 #> 143 11 30 1 13.1 84.3 161 2 15.23 #> 144 11 32 1 13.1 85.1 136 2 15.47 #> 145 11 35 1 13.1 87.5 158 2 16.45 #> 146 11 34 1 13.1 88.6 162 2 17.09 #> 147 11 45 2 13.1 91.6 150 2 18.14 #> 148 12 29 1 13.2 90.8 158 2 18.66 #> 149 12 47 2 13.2 91.4 146 2 17.88 #> 150 12 37 2 13.2 93.8 155 2 19.92 #> 151 12 35 1 13.3 96.5 142 2 21.05 #> 152 12 15 2 13.4 82.4 157 2 16.13 #> 153 12 38 2 13.4 93.0 152 2 19.43 #> 154 12 37 2 13.4 94.1 149 2 20.07 #> 155 12 53 2 13.4 100.3 145 2 21.84 #> 156 12 37 2 13.5 84.4 168 2 15.16 #> 157 12 43 1 13.5 96.1 151 2 20.17 #> 158 12 52 1 13.5 97.0 144 2 19.92 #> 159 12 45 2 13.5 98.0 148 2 21.35 #> 160 12 39 2 13.5 99.1 145 2 22.42 #> 161 12 47 2 13.6 97.0 146 2 20.68 #> 162 13 26 2 13.7 85.7 171 2 16.79 #> 163 13 24 1 13.8 80.9 172 2 14.00 #> 164 13 38 2 13.8 93.3 153 2 19.58 #> 165 13 57 1 13.8 94.0 149 2 18.05 #> 166 13 42 2 13.8 103.4 144 2 24.32 #> 167 13 42 2 13.9 92.3 175 2 18.74 #> 168 13 52 1 13.9 95.5 151 2 19.17 #> 169 13 52 1 13.9 95.7 156 2 19.27 #> 170 13 57 2 13.9 97.2 153 2 19.99 #> 171 13 52 2 13.9 97.8 141 2 20.68 #> 172 13 52 2 13.9 97.9 155 2 20.73 #> 173 13 49 2 13.9 98.2 150 2 21.11 #> 174 13 58 2 14.0 96.6 154 2 19.62 #> 175 13 50 1 14.0 97.9 158 2 20.53 #> 176 13 39 2 14.1 93.7 155 2 19.70 #> 177 14 49 2 14.1 96.4 140 2 20.22 #> 178 14 50 2 14.1 97.1 148 2 20.48 #> 179 14 59 2 14.1 97.3 152 2 19.89 #> 180 14 52 2 14.1 102.4 156 2 22.96 #> 181 14 41 1 14.2 96.7 146 2 20.63 #> 182 14 53 1 14.2 97.7 151 2 20.20 #> 183 14 49 2 14.2 98.1 156 2 21.06 #> 184 14 35 2 14.3 89.8 165 2 18.07 #> 185 14 50 1 14.3 93.7 152 2 18.41 #> 186 14 41 1 14.4 94.8 158 2 19.67 #> 187 14 42 1 14.5 95.1 161 2 19.74 #> 188 14 58 1 14.5 104.9 130 2 23.45 #> 189 14 49 1 14.7 96.6 152 2 19.95 #> 190 14 52 2 14.7 96.7 154 2 20.13 #> 191 14 51 2 14.7 99.2 155 2 21.45 #> 192 14 49 1 14.7 99.6 164 2 21.46 #> 193 15 42 2 15.0 93.5 172 2 19.34 #> 194 15 28 2 15.1 91.5 164 2 19.58 #> 195 15 41 2 15.2 95.9 165 2 20.63 #> 196 15 53 1 15.3 95.0 166 2 18.84 #> 197 15 58 1 15.3 100.7 155 2 21.34 #> 198 15 48 1 15.3 103.5 143 2 23.51 #> 199 15 54 1 15.5 97.9 159 2 20.23 #> 200 15 58 1 15.5 101.3 166 2 21.64 #> 201 15 52 2 15.6 100.0 164 2 21.77 #> 202 15 50 1 15.7 99.6 153 2 21.38 #> 203 15 53 2 15.7 103.1 158 2 23.22 #> 204 15 43 1 15.8 91.1 179 2 17.63 #> 205 15 57 1 15.9 103.8 161 2 22.97 #> 206 15 55 2 16.3 95.4 169 2 19.25 #> 207 16 54 2 15.3 102.0 156 2 22.60 #> 208 16 44 1 16.3 96.2 173 2 20.14 #> 209 16 47 1 16.3 102.0 166 2 22.83 #> 210 16 57 1 16.3 108.4 138 2 25.28 #> 211 16 52 1 16.4 103.9 152 2 23.40 #> 212 16 52 2 16.6 97.8 144 2 20.68 #> 213 16 56 1 16.6 103.9 148 2 23.09 #> 214 16 55 1 16.7 106.3 154 2 24.37 #> 215 16 52 1 17.0 101.3 163 2 22.09 #> 216 16 50 1 17.3 101.8 168 2 22.49 #> 217 16 53 1 17.5 102.2 168 2 22.46 #> 218 16 42 1 17.7 100.9 145 2 22.69 #> 219 16 48 2 17.8 111.3 176 2 27.73 #> 220 16 53 1 17.9 98.7 171 2 20.70 #> 221 16 50 1 18.1 106.4 166 2 24.81
# Calculate MUAC-for-age (mfa) for the anthro4 dataset ## Convert age in anthro4 from months to days testData <- anthro4 testData$age <- testData$agemons * (365.25 / 12) addWGSR(data = testData, sex = "sex", firstPart = "muac", secondPart = "age", index = "mfa")
#> ================================================================================
#> pk_serial muac agemons sex age mfaz #> 1 76220 16.0 73.23203 2 2229 -0.88 #> 2 76290 18.4 93.63450 1 2850 0.07 #> 3 76310 14.4 75.69610 1 2304 -2.20 #> 4 76460 15.4 87.16222 2 2653 -1.63 #> 5 76570 18.0 139.69611 1 4252 -1.76 #> 6 76580 18.0 119.81931 2 3647 -1.04 #> 7 76620 14.6 126.52156 2 3851 -3.39 #> 8 76840 12.6 91.95893 1 2799 -4.72 #> 9 76860 14.5 74.54620 1 2269 -2.06 #> 10 77060 16.0 115.84394 1 3526 -2.28 #> 11 77250 16.5 82.89117 1 2523 -0.74 #> 12 77350 13.4 62.12731 2 1891 -2.63 #> 13 77510 13.5 64.82136 2 1973 -2.60 #> 14 77570 14.9 82.82546 2 2521 -1.88 #> 15 77760 16.0 118.14374 1 3596 -2.36 #> 16 77860 11.5 103.55647 2 3152 -4.94 #> 17 77870 13.6 76.68173 1 2334 -3.06 #> 18 77990 14.0 70.63655 2 2150 -2.30 #> 19 78040 19.0 136.24641 2 4147 -1.10 #> 20 78210 17.2 135.75359 1 4132 -2.12 #> 21 78240 17.0 72.34497 2 2202 -0.23 #> 22 78340 14.7 84.17248 2 2562 -2.06 #> 23 78370 17.0 96.19713 1 2928 -0.86 #> 24 78410 17.0 155.95894 1 4747 -3.21 #> 25 78570 17.5 115.41684 1 3513 -1.15 #> 26 78780 15.3 122.48049 1 3728 -3.14 #> 27 78800 16.0 72.31212 2 2201 -0.86 #> 28 79090 17.6 137.95482 2 4199 -1.89 #> 29 79290 19.0 139.00616 1 4231 -1.15 #> 30 79300 17.0 124.64887 1 3794 -1.82 #> 31 79500 15.0 133.22382 1 4055 -3.73 #> 32 79540 13.7 60.35318 1 1837 -2.26 #> 33 79570 16.7 73.10062 1 2225 -0.25 #> 34 79610 16.0 63.57290 1 1935 -0.46 #> 35 79760 13.5 77.04312 1 2345 -3.18 #> 36 79770 14.5 84.04107 1 2558 -2.48 #> 37 79840 17.6 91.99178 1 2800 -0.34 #> 38 79850 13.0 78.88296 2 2401 -3.33 #> 39 79860 17.0 70.86653 2 2157 -0.19 #> 40 79910 17.0 71.03080 1 2162 0.02 #> 41 79970 15.6 69.61807 1 2119 -0.94 #> 42 80010 16.0 78.39014 1 2386 -0.94 #> 43 80200 16.0 86.37372 1 2629 -1.25 #> 44 80290 16.0 134.37372 1 4090 -3.00 #> 45 80380 17.0 87.55647 1 2665 -0.57 #> 46 80490 15.0 66.03696 2 2010 -1.41 #> 47 80610 17.1 103.29363 2 3144 -1.01 #> 48 80630 14.0 93.33881 2 2841 -2.83 #> 49 80640 15.4 96.65708 2 2942 -1.87 #> 50 80660 16.0 70.43942 2 2144 -0.81 #> 51 80680 15.2 109.73306 2 3340 -2.39 #> 52 80940 17.5 66.62833 2 2028 0.23 #> 53 81060 16.0 126.45585 1 3849 -2.67 #> 54 81080 14.0 71.45791 1 2175 -2.40 #> 55 81100 15.3 87.35934 1 2659 -1.87 #> 56 81260 18.1 142.75154 1 4345 -1.83 #> 57 81540 15.5 89.59343 2 2727 -1.62 #> 58 81590 15.6 77.73306 1 2366 -1.23 #> 59 81630 17.9 126.68583 1 3856 -1.29 #> 60 81880 15.5 116.89528 1 3558 -2.76 #> 61 81890 17.0 117.65092 1 3581 -1.57 #> 62 81900 15.5 69.58521 1 2118 -1.01 #> 63 82010 13.0 64.13142 1 1952 -3.14 #> 64 82080 15.0 132.13963 2 4022 -3.33 #> 65 82190 14.0 82.46407 2 2510 -2.57 #> 66 82320 16.0 93.27310 2 2839 -1.39 #> 67 82370 15.2 99.05544 2 3015 -2.07 #> 68 82560 16.3 154.54620 2 4704 -3.44 #> 69 82670 15.2 77.40452 2 2356 -1.53 #> 70 82690 15.9 68.53388 1 2086 -0.67 #> 71 83720 13.6 60.15606 2 1831 -2.34 #> 72 84080 15.3 65.77412 2 2002 -1.18 #> 73 84220 12.6 100.23819 1 3051 -4.98 #> 74 84430 16.8 63.47433 1 1932 0.11 #> 75 84750 15.0 72.08214 1 2194 -1.51 #> 76 84990 14.0 61.79877 1 1881 -2.06 #> 77 85130 16.0 82.92403 1 2524 -1.12 #> 78 85170 16.0 80.65708 2 2455 -1.06 #> 79 86090 16.6 124.55031 1 3791 -2.11 #> 80 86300 16.3 70.37372 1 2142 -0.44 #> 81 86400 16.4 120.08214 1 3655 -2.10 #> 82 86460 15.0 95.44147 2 2905 -2.12 #> 83 86720 15.0 80.68994 1 2456 -1.86 #> 84 86970 14.6 73.75770 1 2245 -1.93 #> 85 87050 15.1 109.93018 2 3346 -2.46 #> 86 87140 15.0 110.81725 1 3373 -3.03 #> 87 87260 17.0 92.28748 1 2809 -0.73 #> 88 87450 17.2 90.67762 2 2760 -0.60 #> 89 87460 12.8 62.22587 1 1894 -3.28 #> 90 88360 17.5 91.43327 1 2783 -0.38 #> 91 88520 15.2 101.58521 1 3092 -2.50 #> 92 88690 14.3 61.53593 1 1873 -1.77 #> 93 88990 15.5 83.54826 1 2543 -1.54 #> 94 89090 17.0 112.95277 2 3438 -1.35 #> 95 89410 12.3 100.27105 1 3052 -5.27 #> 96 89710 15.0 74.97330 2 2282 -1.62 #> 97 89900 19.0 96.45996 1 2936 0.29 #> 98 90730 16.0 65.67557 1 1999 -0.51 #> 99 90740 13.0 68.36961 2 2081 -3.12 #> 100 90850 16.0 118.20944 2 3598 -2.12 #> 101 91280 16.7 115.64682 1 3520 -1.71 #> 102 91360 15.5 110.12731 1 3352 -2.52 #> 103 91610 14.7 109.73306 1 3340 -3.27 #> 104 91740 16.0 124.61602 1 3793 -2.60 #> 105 91830 12.3 63.01437 2 1918 -3.62 #> 106 91980 15.0 94.35729 2 2872 -2.09 #> 107 92360 16.6 105.75770 1 3219 -1.46 #> 108 92730 17.0 121.46201 1 3697 -1.70 #> 109 94170 16.0 83.15401 2 2531 -1.13 #> 110 94280 12.0 82.46407 1 2510 -4.93 #> 111 94760 14.0 83.87679 2 2553 -2.60 #> 112 95390 17.0 110.06160 1 3350 -1.31 #> 113 95440 16.5 67.18686 1 2045 -0.20 #> 114 95490 16.0 73.23203 2 2229 -0.88 #> 115 95530 15.7 64.52567 2 1964 -0.87 #> 116 95910 15.0 75.79466 1 2307 -1.66 #> 117 95970 18.5 128.91992 1 3924 -1.02 #> 118 96150 16.0 104.47639 2 3180 -1.70 #> 119 96400 15.0 87.95072 1 2677 -2.16 #> 120 96490 16.0 64.59138 2 1966 -0.66 #> 121 96730 19.6 149.81520 2 4560 -1.31 #> 122 96870 15.5 98.03696 1 2984 -2.10 #> 123 96970 14.2 68.27105 1 2078 -2.09 #> 124 97070 16.0 60.68173 1 1847 -0.39 #> 125 97080 17.0 108.68172 1 3308 -1.26 #> 126 97190 15.0 65.54415 1 1995 -1.29 #> 127 97450 16.5 117.88091 1 3588 -1.94 #> 128 97740 14.0 68.89528 1 2097 -2.30 #> 129 97760 18.5 83.81109 2 2551 0.28 #> 130 98160 17.8 141.37166 2 4303 -1.92 #> 131 98190 14.0 71.88501 2 2188 -2.33 #> 132 98360 14.5 72.47639 1 2206 -1.97 #> 133 98420 14.2 75.17043 1 2288 -2.37 #> 134 98640 18.0 66.52978 1 2025 0.78 #> 135 98720 13.7 82.82546 2 2521 -2.83 #> 136 98830 14.7 80.49281 2 2450 -1.97 #> 137 98900 16.0 61.79877 1 1881 -0.41 #> 138 98980 14.8 63.67146 1 1938 -1.41 #> 139 99410 15.0 69.09240 2 2103 -1.48 #> 140 99440 16.6 97.93840 2 2981 -1.14 #> 141 99610 15.8 98.46407 1 2997 -1.85 #> 142 99670 13.2 73.33060 1 2232 -3.31 #> 143 99780 17.0 93.17454 2 2836 -0.78 #> 144 99800 15.5 63.70431 1 1939 -0.84 #> 145 99920 17.5 147.31827 2 4484 -2.35 #> 146 100050 17.5 86.30801 1 2627 -0.20 #> 147 100060 14.0 70.63655 2 2150 -2.30 #> 148 100100 16.2 105.52772 1 3212 -1.76 #> 149 100120 15.4 101.71663 2 3096 -2.01 #> 150 100440 16.0 109.20739 2 3324 -1.84 #> 151 100460 15.0 110.91581 2 3376 -2.57 #> 152 100610 15.0 94.32443 1 2871 -2.42 #> 153 100820 19.0 104.80493 1 3190 0.04 #> 154 101430 15.0 78.62013 2 2393 -1.71 #> 155 101460 13.2 131.48254 2 4002 -4.49 #> 156 101710 16.7 129.77412 1 3950 -2.24 #> 157 101780 17.2 133.35524 2 4059 -1.94 #> 158 101790 15.0 98.36550 2 2994 -2.20 #> 159 101850 16.6 108.05750 2 3289 -1.43 #> 160 101920 16.7 107.63039 1 3276 -1.44 #> 161 101970 15.2 64.39425 1 1960 -1.10 #> 162 102220 19.6 143.14580 1 4357 -1.01 #> 163 102380 16.2 123.89323 1 3771 -2.41 #> 164 102390 15.2 113.21561 1 3446 -2.92 #> 165 102550 14.0 86.43942 1 2631 -3.11 #> 166 102630 13.0 67.38398 1 2051 -3.25 #> 167 102930 17.5 135.62218 1 4128 -1.91 #> 168 103060 19.0 149.02669 1 4536 -1.59 #> 169 103090 14.5 65.41273 2 1991 -1.78 #> 170 103300 16.0 113.41273 1 3452 -2.19 #> 171 103580 13.8 61.17454 2 1862 -2.21 #> 172 103590 16.0 101.94661 2 3103 -1.62 #> 173 103610 16.4 152.47638 2 4641 -3.29 #> 174 104070 14.0 66.69405 2 2030 -2.21 #> 175 104190 17.5 133.55237 2 4065 -1.78 #> 176 104360 18.0 107.23614 2 3264 -0.65 #> 177 104600 15.7 61.47023 2 1871 -0.80 #> 178 104710 16.0 62.32444 1 1897 -0.43 #> 179 104980 16.0 123.66325 2 3764 -2.31 #> 180 105360 16.5 113.24846 1 3447 -1.78 #> 181 105470 13.5 108.41889 1 3300 -4.34 #> 182 105870 15.0 69.81519 1 2125 -1.43 #> 183 105880 17.0 104.31212 2 3175 -1.09 #> 184 106400 14.0 67.84394 1 2065 -2.26 #> 185 106530 16.0 129.08418 2 3929 -2.52 #> 186 106640 13.0 61.83162 1 1882 -3.05 #> 187 106700 17.0 65.37987 2 1990 -0.04 #> 188 106950 14.5 101.25668 2 3082 -2.65 #> 189 107000 16.8 83.31827 1 2536 -0.55 #> 190 107610 14.5 65.21561 1 1985 -1.71 #> 191 107780 14.0 71.12936 2 2165 -2.31 #> 192 107810 18.3 133.61807 1 4067 -1.32 #> 193 107890 15.0 97.08419 1 2955 -2.53 #> 194 108100 15.8 85.12526 2 2591 -1.31 #> 195 108220 14.5 88.27926 2 2687 -2.31 #> 196 108310 13.0 83.05544 2 2528 -3.41 #> 197 108680 16.3 118.24230 1 3599 -2.12 #> 198 108810 17.0 123.17043 2 3749 -1.68 #> 199 109160 12.9 66.26694 1 2017 -3.31 #> 200 109180 22.0 119.06365 1 3624 0.83 #> 201 109190 13.4 61.96304 1 1886 -2.66 #> 202 109230 16.0 73.33060 2 2232 -0.88 #> 203 109280 17.0 150.14374 2 4570 -2.80 #> 204 109440 17.0 64.19713 1 1954 0.22 #> 205 109460 14.1 94.39014 2 2873 -2.78 #> 206 109480 16.2 91.53183 2 2786 -1.21 #> 207 109510 14.5 94.02875 1 2862 -2.92 #> 208 110100 13.8 101.55236 2 3091 -3.20 #> 209 110170 16.0 61.14169 1 1861 -0.40 #> 210 110190 15.5 82.72690 1 2518 -1.51 #> 211 110210 14.0 66.75975 2 2032 -2.22 #> 212 110270 17.5 125.99590 2 3835 -1.50 #> 213 110350 15.4 115.81109 2 3525 -2.44 #> 214 110370 14.0 70.37372 1 2142 -2.36 #> 215 110450 16.0 94.29158 1 2870 -1.54 #> 216 110460 15.4 66.36550 1 2020 -0.99 #> 217 110500 11.5 80.36140 2 2446 -4.59 #> 218 110610 16.0 60.61602 1 1845 -0.39 #> 219 110660 15.0 90.18481 1 2745 -2.25 #> 220 110680 14.0 79.90144 2 2432 -2.51 #> 221 110790 15.0 79.93429 1 2433 -1.83 #> 222 110840 16.5 94.25873 2 2869 -1.10 #> 223 110860 15.3 76.02464 2 2314 -1.43 #> 224 110920 17.1 112.06571 1 3411 -1.31 #> 225 110950 15.5 90.84189 1 2765 -1.83 #> 226 111120 16.0 83.41684 1 2539 -1.13 #> 227 111210 15.0 64.00000 1 1948 -1.25 #> 228 111500 18.0 135.12936 1 4113 -1.56 #> 229 111530 15.0 70.04517 2 2132 -1.51 #> 230 111790 17.9 98.85832 1 3009 -0.38 #> 231 112610 16.0 129.31416 2 3936 -2.53 #> 232 112820 16.5 106.71047 1 3248 -1.56 #> 233 112830 15.5 97.74127 2 2975 -1.83 #> 234 112950 16.0 64.85421 1 1974 -0.49 #> 235 112960 16.0 60.05750 1 1828 -0.37 #> 236 113170 12.7 64.68994 2 1969 -3.31 #> 237 113300 14.5 69.45380 1 2114 -1.85 #> 238 113360 16.5 91.00616 1 2770 -1.04 #> 239 113860 16.0 71.72074 1 2183 -0.70 #> 240 113920 14.0 83.84394 1 2552 -2.99 #> 241 114000 18.0 121.95483 1 3712 -1.06 #> 242 114210 16.4 66.29980 2 2018 -0.44 #> 243 114220 16.0 80.22998 1 2442 -1.01 #> 244 114730 17.2 104.60780 1 3184 -1.00 #> 245 114770 14.0 74.54620 1 2269 -2.54 #> 246 114880 16.0 70.76797 2 2154 -0.82 #> 247 115110 12.0 89.06776 2 2711 -4.32 #> 248 115220 14.5 98.20123 2 2989 -2.56 #> 249 115340 16.2 140.45175 2 4275 -2.88 #> 250 115600 19.0 97.64271 2 2972 0.11 #> 251 115690 14.5 66.82546 1 2034 -1.76 #> 252 115830 13.5 73.49487 1 2237 -3.01 #> 253 115920 14.0 66.23408 1 2016 -2.20 #> 254 115930 15.0 105.06776 2 3198 -2.39 #> 255 115990 20.5 130.33264 1 3967 -0.09 #> 256 116310 14.6 89.16632 2 2714 -2.25 #> 257 116320 18.0 120.57495 2 3670 -1.06