The document discusses recoding variables in an SPSS data file to conduct statistical tests. It describes computing BMI from height and weight variables, then recoding BMI into categories of underweight, normal, and overweight. The recoding is done to test for associations between weight classification and the outcome of small for gestational age (SGA) babies. Steps shown include using the compute variable and recode functions in SPSS to generate new variables for weight classification based on BMI.

1. Compute & Recode
SPSS Data
http://www.palmx.org/drtamil/spss/sga-youtube.sav

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Factors Affecting SGA
SGA
(Y/N)
(Birth
weight)
Mother’s
Nutrition
(BMI/Obesity)
•Weight
•Height
Smoking
Hypertension

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Dependent Outcome
 Birth weight of the babies
 Small for gestational age i.e. less than
2.7kg for term babies – Y/N
By Yehudamalul - Own work, CC BY-SA 3.0,

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Factors Affecting SGA
SGA
(Y/N)
(Birth
weight)
Mother’s
Nutrition
(BMI/Obesity)
•Weight
•Height
Smoking
(Y/N)
Hypertension
(Y/N)

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Recode and transform to do test
 We were asked to conduct the appropriate
statistical test to test whether there is any
association between “Classification of
Weight” (OBESCLAS) and SGA
(OUTCOME).
 So we need to compute weight and height
into BMI, then recode BMI into
classification of underweight, normal and
overweight.

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Steps to recode
To compute Body Mass Index
 formula Weight/Height2
◦ Weight in kg
◦ Height in m (so need to change ours from cm
to m by dividing with 100)
Then recode BMI into Classification of
Weight
 <20 Underweight
 20 to 24.99 Normal
 25 & > Overweight

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https://youtu.be/QrE6SuxYAuQ
Click on
“Compute
Variable”

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Type in the variable name/label

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mBMI=weight/(height/100)**2

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New variable mBMI created

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Recode
 Underweight; 0 – 19.99 ->1
 Normal; 20 – 24.99 ->2
 Overweight; 25 – Infinity ->3

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Recode into Different Variables

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New Output Variable

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Recode old into new values

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Recode old into new values

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Recode old into new values

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New variables created

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Relabel new variable