/****/
clear all
set more off
set mem 1g
set matsize 800
cd "..."
use "SLIR61FL", clear

**********************************

** WEIGHT VARIABLE
gen weight = v005/1000000

********************************************************************************

** SURVEY SET
gen psu =    v021
gen strata = v023

svyset psu [pw = weight], strata(strata) vce(linearized)
*svydes

********************************************************************************

/*
		Underweight		=	Less than 18.5
		Normal			=	Between 18.5 and 24.9
		Overweight		=	Between 25.0 and 29.9
		Obese			=	Greater than or equal to 30.0
*/

gen bmi=v445/100 
gen bmic=1 if bmi<18.5
replace bmic=2 if bmi>=18.5 & bmi<25
replace bmic=3 if bmi>=25 & bmi<30
replace bmic=4 if bmi>=30 & bmi<60
label define bmic 1"Underweight" 2"Normal" 3"Overweight" 4"Obese"
label values bmic bmic
svy: tab bmic, count percent format(%4.1f) col
*tab bmic [iw=weight]

gen ht_flag=0
replace ht_flag=1 if v438>9000
gen preg_flag=0
replace preg_flag=1 if v213==1
gen months_since_last_birth=v008-b3_01
gen recent_birth_flag=0
replace recent_birth_flag=1 if months_since_last_birth <=1

*tab bmic if ht_flag==0 & preg_flag==0 & recent_birth_flag==0 [iw=weight]

********************************************************************************

** DROP IF NOT WITHIN SAMPLE
qui regr bmic if bmic !=. & ht_flag==0 & preg_flag==0 & recent_birth_flag==0 [pw=weight]		
drop if e(sample)!=1

********************************************************************************
** CHECK 

svy: tab v190 bmic, count format(%4.0f) miss
svy: tab v190 bmic, percent format(%4.1f) row miss

*/ OPEN DATASET /*.
GET
  STATA FILE='...\IAIR72FL.DTA'.
DATASET NAME DataSet1 WINDOW=FRONT.

*******************************************************************************************************************.

** WEIGHT VARIABLE.
COMPUTE weight = v005/1000000.

WEIGHT BY weight.

*******************************************************************************************************************.

** COMPLEX SURVEY VARIABLES.
COMPUTE psu =  v021.
COMPUTE strata = v023.

*******************************************************************************************************************.

/**.
** Underweight = Less than 18.5
** Normal = Between 18.5 and 24.9
** Overweight = Between 25.0 and 29.9
** Obese = Greater than or equal to 30.0
**/.

COMPUTE bmi=v445/100.

COMPUTE bmic=$SYSMIS.
      IF bmi LT 18.5 bmic = 1.
      IF bmi GE 18.5 & bmi LT 25 bmic = 2.
      IF bmi GE 25 & bmi LT 30 bmic = 3.
      IF bmi GE 30 & bmi LT 60 bmic = 4.
EXECUTE.
VARIABLE LABELS bmic 'Nutritional status of women'.
VALUE LABELS bmic 1"Underweight" 2"Normal" 3"Overweight" 4"Obese".

*COMPUTE bmic1=$SYSMIS.
*      IF bmi LT 18.5 bmic1 = 1.
*      IF bmi GE 18.5 & bmi LT 25 bmic1 = 2.
*      IF bmi GE 25 & bmi LT 30 bmic1 = 3.
*      IF bmi GE 30 & bmi LT 60  bmic1= 4.
*EXECUTE.

*******************************************************************************************************************.

COMPUTE ht_flag=1.
      IF v438 LT 9000 ht_flag=0.
      IF v438 GT 9000 ht_flag=1.
EXECUTE.


*******************************************************************************************************************.

COMPUTE preg_flag=1.
      IF v213 NE 1 preg_flag=0.
      IF v213=1 preg_flag=1.
EXECUTE.

COMPUTE months_since_last_birth=(v008-b3_01).
EXECUTE.

COMPUTE recent_birth_flag=0.
      IF months_since_last_birth GT 1 recent_birth_flag=0.
      IF months_since_last_birth LE 1 recent_birth_flag=1.
EXECUTE.
 
*************************.

SELECT IF ht_flag=0 & preg_flag=0 & recent_birth_flag=0 & bmic LE 4.

*******************************************************************************************************************.

** CHECK.
FREQUENCIES VARIABLES=bmic
  /ORDER=ANALYSIS.

*************************.

CROSSTABS
  /TABLES=V190 BY bmic
  /FORMAT=AVALUE TABLES
  /CELLS=COUNT
  /COUNT ROUND CELL.

*************************.

CROSSTABS
  /TABLES=V190 BY bmic
  /FORMAT=AVALUE TABLES
  /CELLS=ROW
  /COUNT ROUND CELL.

*******************************************************************************************************************.