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********************************************************************************
** Data Transformation for Data Analysis  - Sample Stata Program:             **
** Created for the CSP Summer Seminar in 2005                                 **
** This program, NHANES_transform.do, makes the file 	       			**
** NHANES_transformed.dta           							**     ********************************************************************************


use NHANES
svyset [pweight=wtmec2yr],strata(sdmvstra) psu (sdmvpsu)

** Data Transformations
** Get data ready to analyse Patient Factors Associated with A1c & hisugar.

** Transform gender variable to a zero/one variable
gen female = (riagendr - 1) 

** Error Check
tab female riagendr,missing

** Rename and label education variable, code refused and don't know as missing
gen educ3=dmd140
recode educ3 7 9 = .
label define educ3l 1 "<12yr" 2 "12yr/GED" 3 ">12yrs"
label values educ3 educ3l

**Error check
tab educ3 dmd140, m

**Rename the age in years variable "ridageyr" to something more user-friendly
gen age=ridageyr 

**Race
**Group race into White, African-American, Other
gen race=ridreth2
recode race 5=4
label define racel 1 "White" 2 "African-American" 3 "Mexican-American" 4 "Other"
label values race racel

**Error Check
tab race ridreth2,missing

**collapse and label income variable 
gen income=indhhinc
recode income 77 99 12 =. 01 02 03 04 13=1 05 06 07=2 08 09 10=3 11=4
label define income 1 "<$20,000" 2 "$20,000-44,999" 3 "$45,000-74,999" 4 ">=$75,000" 
label values income income

**Make labels for DM questions
gen haveDM=diq010
recode haveDM 2=0 7 9=.
label define haveDM 1 "Yes" 0 "No"  3 "Borderline" 
label values haveDM haveDM

gen whenDM=diq040q 
recode whenDM 99999=.

** no general question re high sugar sx.  We'll use the question which asks if they have had numbness in the past 3 months. 
gen numb=diq100
recode numb 7=. 9=. 2=0

**Error check
tab numb diq100, m

**Create a three level variable for no meds, oral meds ONLY, or insulin
*diq050 are you taking insulin now?
*diq070 are you taking oral meds now?
for var diq050 diq070 : recode X 7 9=.
gen meds3=.
replace meds3=1 if diq050==2 & diq070==2
replace meds3=2 if diq070==1 & diq050==2
replace meds3=3 if diq050==1
label define meds3 1 "no meds" 2 "insulin only" 3 "oral meds"
label values meds3 meds3

**Error Checks
tab diq050 meds3, missing
tab diq070 meds3, missing 

**HbA1c
gen a1c=lbxgh

** Make an HbA1c variable with 3 Categories
gen a1c_3=a1c
recode a1c_3 1/8=1 8.1/9.5=2 9.6/30=3
lab var a1c_3 "HbA1c 3 Categories"
lab define a1c3l 1 "<= 8%" 2 ">8%-9.5%" 3 ">9.5%"
label values a1c_3 a1c_3l

**Error Check
sum a1c if a1c_3==1
sum a1c if a1c_3==2
sum a1c if a1c_3==3

**make label for overall physical activity variable
gen phys_act=paq180
recode phys_act 7 9=.
label define pa 1 "sits during the day and does not walk about very much" 2 "stands or walks about a lot during the day, but does not have to carry or lift things very often"  3 " lifts light load or has to climb stairs or hills often" 4  "does heavy work or carries heavy loads" 
label values phys_act pa

**make vigorous activity variable
gen vigorous=pad200
recode vigorous 2=0 7 9 =.
label define vigorous 1 ">=10 min vigorous activity in past 30 days" 0 "no vigorous activity in past 30 days" 3  "unable to do vigorous activity"
label values vigorous vigorous

**make moderate activity variable
gen moderate=pad320
recode moderate 2=0 7 9 =.
label define moderate 1 ">=10 min moderate activity in past 30 days" 0 "no moderate activity in past 30 days" 3  "unable to do moderate activity"
label values moderate moderate

**make t.v./computer variable
gen tv_comp=pad575
label var tv_comp "hours a day spent watching tv or on computer--all ages"
recode tv_comp 6=0 77 99=.
label define tv 0 "<1 hour"  5 "over five hours"

**Dicotomize immunization variables
**A value of 1 or greater indicates presence of antibody 
for var lbxme lbxru lbxvar \ new measles rubella varicella : gen Y=X \ replace Y=1 if Y>=1 & Y!=. \replace Y=0 if Y<1 

**Error check
for var measles rubella varicella \ var lbxme lbxru lbxvar  : bysort X : sum Y 

** Duration.  Subtract age when told had DM from current age.
gen duration=age-diq040q if diq040q!=99999

**Error check
l age diq040q duration in 1/100 if duration!=.

**Give huq010 a better name
gen healthst=huq010 
recode healthst 7=. 9=.
label define healthst 1 "excellent" 2 "very good" 3 "good" 4 "fair" 5 "poor"
label values healthst healthst

**look at health now vs. one year ago
gen health_change=huq020
recode health_change 7 9 =.
label define healthch 1 "Better" 2 "Worse" 3 "About the same" 
label values health_change healthch

**Routine Place for Health Care
gen routine_hc=huq030
recode routine_hc 2=0 7 9 =.
label define routine 1 "I have place for routine health care" 0 "No place for routine health care" 3 ">1 place for routine health care"
label values routine_hc routine

**Type place most often go for health care
gen type_hc=huq040
recode type_hc  7 9 =.
label define type 1 "Clinic or health center" 2 "Doctor's office or HMO" 3 "Hospital emergency room" 4 "Hospital outpatient department" 5 "Some other place" 
label values type_hc type

**# times received healthcare over past year
gen times_outpatient=huq050
recode times_outpatient 77 99 =.
label define times 0 "None" 1 "1" 2  "2 to 3" 3  "4 to 9"  4  "10 to 12"  5  "13 or more" 
label values times_outpatient times


**How long since last health care visit
rename huq060 since_last_visit
recode since_last_visit 7 9=.
label define since 1 "<=6 months" 2 ">6 months >1 year" 3 ">1 year <3 years" 4 ">3 years" 5 "Never"
label values since_last_visit since

**Overnight hospital patient in last year
rename huq070 inpatient
recode inpatient 7 9=. 2=0

**# times overnight hospital patient in last year
rename hud080 times_inpatient
recode times_inpatient 77 99=. 
label define timesinpt 1 "Once" 2 "Twice" 3 "3 Times" 4 "4 Times" 5 "5 Times" 6 ">=6 times"
label values times_inpatient timesinpt

**Seen mental health professional
rename huq090 mental_health
recode mental_health 7 9=. 2=0

for var mcq010 mcq090 mcq160a mcq160b mcq160c mcq160d mcq160e mcq160f mcq160g mcq160h mcq160i mcq160j mcq160k mcq030 mcq040 mcq050 mcq100 mcq110 mcq120b mcq170k \ new asthma chickenpox arthritis chf coronaryheart angina heartattack stroke emphysema goiter thyroid overweight chronbronch asthma_still asthma_attack ed_for_asthma hypertension hypertension_meds ge3ear_infect bronch_still: gen Y=X \ recode Y 7 9=. 2=0 

**age diagnosed with asthma
rename mcq020 when_asthma
recode when_asthma 99999=. 

**# school days missed due to injury/illness
gen schooldays_missed=mcq150q
recode schooldays_missed 77777 99999=.

**# work days missed due to illness/maternity
gen workdays_missed=mcq245b
recode workdays_missed 77777 99999=.

for var mcq180* \ new age_arthritis age_heart_failure age_coronary_heart_dz age_angina age_heart_attack age_stroke age_emphysema age_chron_bronch : gen Y=X \  recode Y 77777 99999=.

gen bmi=bmxbmi

**ADL
label define ADL 1 "no difficulty" 2 "some difficulty" 3 "much difficulty" 4 "unable to do" 
for var pfq060* : recode X 7 9 =. \ label values X ADL

drop  riagendr ridageyr ridreth2-indhhinc lbxgh- huq050  mcq010 mcq030- demo_mcqmerge demo_bmxmerge demo_bpxmerge 

notes: Dataset NHANES_transformed.dta was made using NHANES.dta and NHANES_transform.do
notes: New variables have all been error checked

save NHANES_transformed,replace

capture log close