Exploring the BRFSS data
Setup
Load packages
library(tidyverse)
library(ggplot2)
library(dplyr)
library(here)
library(skimr)
library(janitor)Load data
The data file has been updated according to the learner’s file labeling protocols. No columns or rows have been altered at this point.
load("c1w51_brfss2013.RData")
head(brfss2013)## X_state fmonth idate imonth iday iyear dispcode seqno
## 1 Alabama January 1092013 January 9 2013 Completed interview 2013000580
## 2 Alabama January 1192013 January 19 2013 Completed interview 2013000593
## 3 Alabama January 1192013 January 19 2013 Completed interview 2013000600
## 4 Alabama January 1112013 January 11 2013 Completed interview 2013000606
## 5 Alabama February 2062013 February 6 2013 Completed interview 2013000608
## 6 Alabama March 3272013 March 27 2013 Completed interview 2013000630
## X_psu ctelenum pvtresd1 colghous stateres cellfon3 ladult
## 1 2013000580 Yes Yes <NA> Yes Not a cellular phone <NA>
## 2 2013000593 Yes Yes <NA> Yes Not a cellular phone <NA>
## 3 2013000600 Yes Yes <NA> Yes Not a cellular phone <NA>
## 4 2013000606 Yes Yes <NA> Yes Not a cellular phone <NA>
## 5 2013000608 Yes Yes <NA> Yes Not a cellular phone <NA>
## 6 2013000630 Yes Yes <NA> Yes Not a cellular phone <NA>
## numadult nummen numwomen genhlth physhlth menthlth poorhlth hlthpln1
## 1 2 1 1 Fair 30 29 30 Yes
## 2 2 1 1 Good 0 0 NA Yes
## 3 3 2 1 Good 3 2 0 Yes
## 4 2 1 1 Very good 2 0 0 Yes
## 5 2 1 1 Good 10 2 0 Yes
## 6 1 0 1 Very good 0 0 NA Yes
## persdoc2 medcost checkup1 sleptim1 bphigh4 bpmeds bloodcho
## 1 Yes, only one No Within past year NA Yes Yes Yes
## 2 Yes, only one No Within past year 6 No <NA> Yes
## 3 Yes, only one No Within past year 9 No <NA> Yes
## 4 Yes, only one No Within past 2 years 8 No <NA> Yes
## 5 Yes, only one No 5 or more years ago 6 Yes No Yes
## 6 Yes, only one No Within past year 8 Yes Yes Yes
## cholchk toldhi2 cvdinfr4 cvdcrhd4 cvdstrk3 asthma3 asthnow
## 1 Within past year Yes No <NA> No Yes Yes
## 2 Within past year No No No No No <NA>
## 3 5 or more years ago No No No No No <NA>
## 4 Within past year Yes No No No No <NA>
## 5 Within past 2 years No No No No Yes No
## 6 Within past year Yes No No No No <NA>
## chcscncr chcocncr chccopd1 havarth3 addepev2 chckidny diabete3 veteran3
## 1 No No Yes Yes Yes Yes No No
## 2 No No No No Yes No No No
## 3 No No No Yes Yes No No No
## 4 No No No No No No No No
## 5 No Yes No No No No No No
## 6 No No No No No No No No
## marital children
## 1 Divorced 0
## 2 Married 2
## 3 Married 0
## 4 Married 0
## 5 Married 0
## 6 Divorced 0
## educa
## 1 College 4 years or more (College graduate)
## 2 College 1 year to 3 years (Some college or technical school)
## 3 College 4 years or more (College graduate)
## 4 Grade 12 or GED (High school graduate)
## 5 College 4 years or more (College graduate)
## 6 College 4 years or more (College graduate)
## employ1 income2 weight2 height3 numhhol2
## 1 Retired Less than $75,000 250 507 Yes
## 2 Employed for wages $75,000 or more 127 510 No
## 3 Employed for wages $75,000 or more 160 504 No
## 4 Retired Less than $75,000 128 504 No
## 5 Retired Less than $50,000 265 600 No
## 6 Employed for wages $75,000 or more 225 503 Yes
## numphon2 cpdemo1 cpdemo4 internet renthom1 sex
## 1 2 residential telephone numbers Yes 10 Yes Own Female
## 2 <NA> Yes 70 Yes Own Female
## 3 <NA> Yes 70 Yes Own Female
## 4 <NA> Yes 75 Yes Own Female
## 5 <NA> Yes 0 Yes Own Male
## 6 1 residential telephone number Yes 70 Yes Own Female
## pregnant qlactlm2 useequip blind decide diffwalk diffdres diffalon smoke100
## 1 <NA> Yes Yes No No Yes No Yes Yes
## 2 <NA> No No No No No No No No
## 3 <NA> Yes No No No Yes No No Yes
## 4 <NA> No No No No No No No No
## 5 <NA> No No No No No No No Yes
## 6 <NA> No No No No No No No No
## smokday2 stopsmk2 lastsmk2 usenow3 alcday5 avedrnk2
## 1 Not at all <NA> 10 years or more Not at all 201 2
## 2 <NA> <NA> <NA> Not at all 0 NA
## 3 Some days Yes <NA> Not at all 220 4
## 4 <NA> <NA> <NA> Not at all 208 2
## 5 Not at all <NA> Within the past month Not at all 210 2
## 6 <NA> <NA> <NA> Not at all 0 NA
## drnk3ge5 maxdrnks fruitju1 fruit1 fvbeans fvgreen fvorang vegetab1 exerany2
## 1 0 2 304 104 303 310 303 NA No
## 2 NA NA 305 301 310 203 202 203 Yes
## 3 20 10 301 203 202 202 310 330 No
## 4 0 2 202 306 202 310 305 204 Yes
## 5 0 3 0 302 101 310 303 101 No
## 6 NA NA 205 206 0 203 0 207 Yes
## exract11 exeroft1 exerhmm1
## 1 <NA> NA NA
## 2 Walking 105 20
## 3 <NA> NA NA
## 4 Walking 205 30
## 5 <NA> NA NA
## 6 Bicycling machine exercise 102 15
## exract21 exeroft2
## 1 <NA> NA
## 2 Household Activities (vacuuming, dusting, home repair, etc.) 101
## 3 <NA> NA
## 4 No other activity NA
## 5 <NA> NA
## 6 Gardening (spading, weeding, digging, filling) 102
## exerhmm2 strength lmtjoin3 arthdis2 arthsocl joinpain seatbelt flushot6
## 1 NA 0 Yes Yes A lot 7 Always No
## 2 10 0 <NA> <NA> <NA> NA Always Yes
## 3 NA 0 Yes Yes A little 5 Always Yes
## 4 NA 0 <NA> <NA> <NA> NA Always No
## 5 NA 0 <NA> <NA> <NA> NA Always No
## 6 30 0 <NA> <NA> <NA> NA Always Yes
## flshtmy2 tetanus pneuvac3 hivtst6
## 1 <NA> No, did not receive any tetanus since 2005 Yes No
## 2 October 2012 Yes, received Tdap No Yes
## 3 January 2013 Yes, received Tdap No Yes
## 4 <NA> No, did not receive any tetanus since 2005 No No
## 5 <NA> No, did not receive any tetanus since 2005 No No
## 6 <NA> No, did not receive any tetanus since 2005 Yes Yes
## hivtstd3 whrtst10 pdiabtst prediab1 diabage2 insulin bldsugar
## 1 NA <NA> Yes Yes <NA> NA
## 2 NA Private doctor or HMO Yes No <NA> NA
## 3 NA At home Yes No <NA> NA
## 4 NA <NA> Yes No <NA> NA
## 5 NA <NA> No No <NA> NA
## 6 NA Somewhere else Yes No <NA> NA
## feetchk2 doctdiab chkhemo3 feetchk eyeexam diabeye diabedu painact2 qlmentl2
## 1 NA NA NA <NA> <NA> <NA> 5 30
## 2 NA NA NA <NA> <NA> <NA> 0 2
## 3 NA NA NA <NA> <NA> <NA> 20 2
## 4 NA NA NA <NA> <NA> <NA> 0 6
## 5 NA NA NA <NA> <NA> <NA> NA NA
## 6 NA NA NA <NA> <NA> <NA> NA NA
## qlstres2 qlhlth2 medicare hlthcvrg delaymed
## 1 30 0 Yes 3 7 You didn't have transportation
## 2 3 25 No 2 No, I did not delay getting medical care
## 3 5 2 No 3 <NA>
## 4 4 20 No 3 No, I did not delay getting medical care
## 5 NA NA Yes 4 2 No, I did not delay getting medical care
## 6 NA NA No 1 Other
## dlyother nocov121 lstcovrg drvisits medscost carercvd
## 1 No <NA> 5 No Very satisfied
## 2 No <NA> 3 No Very satisfied
## 3 No <NA> 6 No Very satisfied
## 4 No <NA> 1 No Somewhat satisfied
## 5 No <NA> 2 No Very satisfied
## 6 don t like going No <NA> 4 No Very satisfied
## medbills ssbsugar ssbfrut2 wtchsalt longwtch dradvise asthmage asattack
## 1 No 305 305 Yes 408 Yes 56 Yes
## 2 No 203 0 No NA No NA <NA>
## 3 No 202 308 No NA No NA <NA>
## 4 No 203 315 Yes 405 No NA <NA>
## 5 No NA NA <NA> NA <NA> NA <NA>
## 6 No NA NA <NA> NA <NA> NA <NA>
## aservist asdrvist asrchkup asactlim asymptom asnoslep
## 1 0 0 3 NA Every day, but not all the time None
## 2 NA NA NA NA <NA> <NA>
## 3 NA NA NA NA <NA> <NA>
## 4 NA NA NA NA <NA> <NA>
## 5 NA NA NA NA <NA> <NA>
## 6 NA NA NA NA <NA> <NA>
## asthmed3 asinhalr harehab1 strehab1 cvdasprn aspunsaf
## 1 1 to 14 days 5 to 14 times <NA> <NA> No Yes, stomach problems
## 2 <NA> <NA> <NA> <NA> No No
## 3 <NA> <NA> <NA> <NA> No No
## 4 <NA> <NA> <NA> <NA> No No
## 5 <NA> <NA> <NA> <NA> <NA> <NA>
## 6 <NA> <NA> <NA> <NA> <NA> <NA>
## rlivpain rduchart rducstrk arttoday arthwgt
## 1 <NA> <NA> <NA> I can do some things I would like to do Yes
## 2 <NA> <NA> <NA> <NA> <NA>
## 3 <NA> <NA> <NA> I can do some things I would like to do No
## 4 <NA> <NA> <NA> <NA> <NA>
## 5 <NA> <NA> <NA> <NA> <NA>
## 6 <NA> <NA> <NA> <NA> <NA>
## arthexer arthedu imfvplac
## 1 Yes No <NA>
## 2 <NA> <NA> Workplace
## 3 Yes No A doctor´s office or health maintenance organization (HMO)
## 4 <NA> <NA> <NA>
## 5 <NA> <NA> <NA>
## 6 <NA> <NA> <NA>
## hpvadvc2 hpvadsht hadmam howlong profexam lengexam
## 1 <NA> <NA> Yes Within past 2 years Yes Within past 2 years
## 2 <NA> <NA> Yes Within past 3 years Yes Within past 3 years
## 3 <NA> <NA> Yes Within past year Yes Within past year
## 4 <NA> <NA> Yes Within past year Yes Within past 2 years
## 5 <NA> <NA> <NA> <NA> <NA> <NA>
## 6 <NA> <NA> <NA> <NA> <NA> <NA>
## hadpap2 lastpap2 hadhyst2 bldstool lstblds3 hadsigm3
## 1 Yes 5 or more years ago Yes No <NA> Yes
## 2 Yes Within past 3 years No No <NA> No
## 3 Yes Within past year Yes Yes 5 or more years ago Yes
## 4 Yes Within past 2 years No Yes 5 or more years ago Yes
## 5 <NA> <NA> <NA> No <NA> Yes
## 6 <NA> <NA> <NA> <NA> <NA> <NA>
## hadsgco1 lastsig3 pcpsaad2 pcpsadi1 pcpsare1 psatest1 psatime
## 1 Colonoscopy Within past 2 years <NA> <NA> <NA> <NA> <NA>
## 2 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 3 Colonoscopy Within past 3 years <NA> <NA> <NA> <NA> <NA>
## 4 Colonoscopy Within past 5 years <NA> <NA> <NA> <NA> <NA>
## 5 Colonoscopy Within past 2 years <NA> <NA> <NA> <NA> <NA>
## 6 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## pcpsars1 pcpsade1 pcdmdecn rrclass2 rrcognt2
## 1 <NA> <NA> NA Black or African American Never
## 2 <NA> <NA> NA White Never
## 3 <NA> <NA> NA White Never
## 4 <NA> <NA> NA White <NA>
## 5 <NA> <NA> NA <NA> <NA>
## 6 <NA> <NA> NA <NA> <NA>
## rratwrk2 rrhcare3 rrphysm2 rremtsm2 misnervs
## 1 <NA> The same as other races No No Some
## 2 The same as other races The same as other races No No A little
## 3 The same as other races The same as other races No No None
## 4 <NA> The same as other races No No A little
## 5 <NA> <NA> <NA> <NA> <NA>
## 6 <NA> <NA> <NA> <NA> <NA>
## mishopls misrstls misdeprd miseffrt miswtles misnowrk mistmnt mistrhlp
## 1 Some Some None All None 30 Yes Agree strongly
## 2 None None None None None 0 No Agree slightly
## 3 None None None None None 0 No Agree strongly
## 4 None Some None None None 0 No Agree strongly
## 5 <NA> <NA> <NA> <NA> <NA> NA <NA> <NA>
## 6 <NA> <NA> <NA> <NA> <NA> NA <NA> <NA>
## misphlpf scntmony scntmeal scntpaid scntwrk1
## 1 Disagree slightly Never Never <NA> NA
## 2 Disagree slightly Never Never Paid by the hour 35
## 3 Agree strongly Never Never Paid by the hour 40
## 4 Disagree slightly Never Never <NA> NA
## 5 <NA> Never Never <NA> NA
## 6 <NA> Never Never Paid by salary 40
## scntlpad scntlwk1 scntvot1 rcsgendr rcsrltn2 casthdx2 casthno2
## 1 Paid by salary NA Yes <NA> <NA> <NA> <NA>
## 2 <NA> NA Yes Girl Parent No <NA>
## 3 <NA> NA Yes <NA> <NA> <NA> <NA>
## 4 Paid by salary 60 Yes <NA> <NA> <NA> <NA>
## 5 Paid by the job / task 60 Yes <NA> <NA> <NA> <NA>
## 6 <NA> NA Yes <NA> <NA> <NA> <NA>
## emtsuprt lsatisfy ctelnum1 cellfon2 cadult pvtresd2 cclghous cstate
## 1 Always Very satisfied <NA> <NA> <NA> <NA> <NA> <NA>
## 2 Sometimes Satisfied <NA> <NA> <NA> <NA> <NA> <NA>
## 3 Usually Very satisfied <NA> <NA> <NA> <NA> <NA> <NA>
## 4 Usually Very satisfied <NA> <NA> <NA> <NA> <NA> <NA>
## 5 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 6 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## landline pctcell qstver qstlang
## 1 <NA> NA Only Version Landline English
## 2 <NA> NA Only Version Landline English
## 3 <NA> NA Only Version Landline English
## 4 <NA> NA Only Version Landline English
## 5 <NA> NA Only Version Landline English
## 6 <NA> NA Only Version Landline English
## mscode X_ststr X_strwt X_rawrake X_wt2rake
## 1 Inside a suburban county of the MSA 11081 40.19767 1 40.19767
## 2 Inside a suburban county of the MSA 11081 40.19767 2 80.39535
## 3 Inside a suburban county of the MSA 11081 40.19767 3 120.59302
## 4 Inside a suburban county of the MSA 11081 40.19767 2 80.39535
## 5 Inside a suburban county of the MSA 11082 60.31918 2 120.63837
## 6 Inside a suburban county of the MSA 11081 40.19767 1 40.19767
## X_imprace X_impnph X_impeduc X_impmrtl X_imphome
## 1 Black, Non-Hispanic 2 NA NA NA
## 2 White, Non-Hispanic 1 NA NA NA
## 3 White, Non-Hispanic 1 NA NA NA
## 4 White, Non-Hispanic 1 NA NA NA
## 5 White, Non-Hispanic 1 NA NA NA
## 6 Black, Non-Hispanic 1 NA NA NA
## X_chispnc X_crace1 X_impcage
## 1 <NA> <NA> <NA>
## 2 Child not of Hispanic, Latino/a, or Spanish origin White 10-14 Years old
## 3 <NA> <NA> <NA>
## 4 <NA> <NA> <NA>
## 5 <NA> <NA> <NA>
## 6 <NA> <NA> <NA>
## X_impcrac X_impcsex X_cllcpwt X_dualuse X_dualcor X_llcpwt2
## 1 <NA> <NA> NA No Dual Phone Use NA 331.4934
## 2 White, non-Hispanic Female 954.0782 No Dual Phone Use NA 662.9867
## 3 <NA> <NA> NA No Dual Phone Use NA 994.4801
## 4 <NA> <NA> NA No Dual Phone Use NA 662.9867
## 5 <NA> <NA> NA No Dual Phone Use NA 994.8540
## 6 <NA> <NA> NA No Dual Phone Use NA 331.4934
## X_llcpwt X_rfhlth X_hcvu651 X_rfhype5
## 1 238.0161 Fair or Poor Health Have health care coverage Yes
## 2 737.6942 Good or Better Health Have health care coverage No
## 3 568.5274 Good or Better Health Have health care coverage No
## 4 606.9764 Good or Better Health Have health care coverage No
## 5 629.8471 Good or Better Health <NA> Yes
## 6 272.2382 Good or Better Health Have health care coverage Yes
## X_cholchk X_rfchol X_ltasth1 X_casthm1
## 1 Had cholesterol checked in past 5 years Yes Yes Yes
## 2 Had cholesterol checked in past 5 years No No No
## 3 Did not have cholesterol checked in past 5 years No No No
## 4 Had cholesterol checked in past 5 years Yes No No
## 5 Had cholesterol checked in past 5 years No Yes No
## 6 Had cholesterol checked in past 5 years Yes No No
## X_asthms1 X_drdxar1 X_prace1
## 1 Current Diagnosed with arthritis Black or African American
## 2 Never Not diagnosed with arthritis White
## 3 Never Diagnosed with arthritis White
## 4 Never Not diagnosed with arthritis White
## 5 Former Not diagnosed with arthritis White
## 6 Never Not diagnosed with arthritis Black or African American
## X_mrace1 X_hispanc
## 1 Black or African American Not of Hispanic, Latino/a, or Spanish origin
## 2 White Not of Hispanic, Latino/a, or Spanish origin
## 3 White Not of Hispanic, Latino/a, or Spanish origin
## 4 White Not of Hispanic, Latino/a, or Spanish origin
## 5 White Not of Hispanic, Latino/a, or Spanish origin
## 6 Black or African American Not of Hispanic, Latino/a, or Spanish origin
## X_race X_raceg21 X_racegr3
## 1 Black only, non-Hispanic Non-White or Hispanic Black only, Non-Hispanic
## 2 White only, non-Hispanic Non-Hispanic White White only, Non-Hispanic
## 3 White only, non-Hispanic Non-Hispanic White White only, Non-Hispanic
## 4 White only, non-Hispanic Non-Hispanic White White only, Non-Hispanic
## 5 White only, non-Hispanic Non-Hispanic White White only, Non-Hispanic
## 6 Black only, non-Hispanic Non-White or Hispanic Black only, Non-Hispanic
## X_race_g1 X_ageg5yr X_age65yr X_age_g htin4 htm4
## 1 Black - Non-Hispanic Age 60 to 64 Age 18 to 64 Age 55 to 64 67 170
## 2 White - Non-Hispanic Age 50 to 54 Age 18 to 64 Age 45 to 54 70 178
## 3 White - Non-Hispanic Age 55 to 59 Age 18 to 64 Age 55 to 64 64 163
## 4 White - Non-Hispanic Age 60 to 64 Age 18 to 64 Age 55 to 64 64 163
## 5 White - Non-Hispanic Age 65 to 69 Age 65 or older Age 65 or older 72 183
## 6 Black - Non-Hispanic Age 45 to 49 Age 18 to 64 Age 45 to 54 63 160
## wtkg3 X_bmi5 X_bmi5cat X_rfbmi5 X_chldcnt
## 1 11340 3916 Obese Yes No children in household
## 2 5761 1822 Underweight No Two children in household
## 3 7257 2746 Overweight Yes No children in household
## 4 5806 2197 Normal weight No No children in household
## 5 12020 3594 Obese Yes No children in household
## 6 10206 3986 Obese Yes No children in household
## X_educag X_incomg
## 1 Graduated from college or technical school $50,000 or more
## 2 Attended college or technical school $50,000 or more
## 3 Graduated from college or technical school $50,000 or more
## 4 Graduated high school $50,000 or more
## 5 Graduated from college or technical school $35,000 to less than $50,000
## 6 Graduated from college or technical school $50,000 or more
## X_smoker3 X_rfsmok3 drnkany5 drocdy3_ X_rfbing5
## 1 Former smoker No No 3 No
## 2 Never smoked No Yes 0 No
## 3 Current smoker - now smokes some days Yes No 67 Yes
## 4 Never smoked No No 27 No
## 5 Former smoker No No 33 No
## 6 Never smoked No Yes 0 No
## X_drnkdy4 X_drnkmo4 X_rfdrhv4 X_rfdrmn4 X_rfdrwm4 ftjuda1_ frutda1_ beanday_
## 1 7 2 No <NA> No 13 400 10
## 2 0 0 No <NA> No 17 3 33
## 3 267 80 Yes <NA> Yes 3 43 29
## 4 53 16 No <NA> No 29 20 29
## 5 67 20 No No <NA> 0 7 100
## 6 0 0 No <NA> No 71 86 0
## grenday_ orngday_ vegeda1_ X_misfrtn
## 1 33 10 NA No missing fruit responses
## 2 43 29 43 No missing fruit responses
## 3 29 33 100 No missing fruit responses
## 4 33 17 57 No missing fruit responses
## 5 33 10 100 No missing fruit responses
## 6 43 0 100 No missing fruit responses
## X_misvegn X_frtresp
## 1 1 missing response Included - Missing Fruit Responses
## 2 No missing vegetable responses Included - Missing Fruit Responses
## 3 No missing vegetable responses Included - Missing Fruit Responses
## 4 No missing vegetable responses Included - Missing Fruit Responses
## 5 No missing vegetable responses Included - Missing Fruit Responses
## 6 No missing vegetable responses Included - Missing Fruit Responses
## X_vegresp X_frutsum X_vegesum
## 1 Not Included - Missing Fruit Responses 413 53
## 2 Included - Missing Fruit Responses 20 148
## 3 Included - Missing Fruit Responses 46 191
## 4 Included - Missing Fruit Responses 49 136
## 5 Included - Missing Fruit Responses 7 243
## 6 Included - Missing Fruit Responses 157 143
## X_frtlt1
## 1 Consumed fruit one or more times per day
## 2 Consumed fruit less than one time per day
## 3 Consumed fruit less than one time per day
## 4 Consumed fruit less than one time per day
## 5 Consumed fruit less than one time per day
## 6 Consumed fruit one or more times per day
## X_veglt1
## 1 Consumed vegetables less than one time per day
## 2 Consumed vegetables one or more times per day
## 3 Consumed vegetables one or more times per day
## 4 Consumed vegetables one or more times per day
## 5 Consumed vegetables one or more times per day
## 6 Consumed vegetables one or more times per day
## X_frt16
## 1 Included - values are in accepted range
## 2 Included - values are in accepted range
## 3 Included - values are in accepted range
## 4 Included - values are in accepted range
## 5 Included - values are in accepted range
## 6 Included - values are in accepted range
## X_veg23
## 1 Included - values are in accepted range
## 2 Included - values are in accepted range
## 3 Included - values are in accepted range
## 4 Included - values are in accepted range
## 5 Included - values are in accepted range
## 6 Included - values are in accepted range
## X_fruitex
## 1 No missing values and in accepted range
## 2 No missing values and in accepted range
## 3 No missing values and in accepted range
## 4 No missing values and in accepted range
## 5 No missing values and in accepted range
## 6 No missing values and in accepted range
## X_vegetex
## 1 Missing vegetables responses
## 2 No missing values and in accepted range
## 3 No missing values and in accepted range
## 4 No missing values and in accepted range
## 5 No missing values and in accepted range
## 6 No missing values and in accepted range
## X_totinda metvl11_ metvl21_ maxvo2_
## 1 No physical activity or exercise in last 30 days NA NA 2580
## 2 Had physical activity or exercise 35 33 2950
## 3 No physical activity or exercise in last 30 days NA NA 2765
## 4 Had physical activity or exercise 35 0 2432
## 5 No physical activity or exercise in last 30 days NA NA 2370
## 6 Had physical activity or exercise 68 50 2987
## fc60_ actin11_ actin21_ padur1_ padur2_
## 1 442 <NA> <NA> NA NA
## 2 506 Moderate Moderate 20 10
## 3 474 <NA> <NA> NA NA
## 4 417 Moderate Not Moderate or Vigorous or No Activity 30 NA
## 5 406 <NA> <NA> NA NA
## 6 512 Vigorous Moderate 15 30
## pafreq1_ pafreq2_ X_minac11 X_minac21 strfreq_ pamiss1_ pamin11_ pamin21_
## 1 NA NA NA NA 0 0 NA NA
## 2 5000 1000 100 10 0 0 100 10
## 3 NA NA NA NA 0 0 NA NA
## 4 1167 NA 35 0 0 0 35 0
## 5 NA NA NA NA 0 0 NA NA
## 6 2000 2000 30 60 0 0 60 60
## pa1min_ pavig11_ pavig21_ pa1vigm_ X_pacat1
## 1 NA NA NA Inactive
## 2 110 0 0 0 Insufficiently active
## 3 NA NA NA Inactive
## 4 35 0 0 0 Insufficiently active
## 5 NA NA NA Inactive
## 6 120 30 0 30 Insufficiently active
## X_paindx1 X_pa150r2 X_pa300r2
## 1 Did not meet aerobic recommendations 0 minutes 0 minutes
## 2 Did not meet aerobic recommendations 1-149 minutes 1-300 minutes
## 3 Did not meet aerobic recommendations 0 minutes 0 minutes
## 4 Did not meet aerobic recommendations 1-149 minutes 1-300 minutes
## 5 Did not meet aerobic recommendations 0 minutes 0 minutes
## 6 Did not meet aerobic recommendations 1-149 minutes 1-300 minutes
## X_pa30021 X_pastrng
## 1 0-300 minutes Did not meet muscle strengthening recommendations
## 2 0-300 minutes Did not meet muscle strengthening recommendations
## 3 0-300 minutes Did not meet muscle strengthening recommendations
## 4 0-300 minutes Did not meet muscle strengthening recommendations
## 5 0-300 minutes Did not meet muscle strengthening recommendations
## 6 0-300 minutes Did not meet muscle strengthening recommendations
## X_parec1 X_pastae1
## 1 Did not meet either guideline Did not meet both guidelines
## 2 Did not meet either guideline Did not meet both guidelines
## 3 Did not meet either guideline Did not meet both guidelines
## 4 Did not meet either guideline Did not meet both guidelines
## 5 Did not meet either guideline Did not meet both guidelines
## 6 Did not meet either guideline Did not meet both guidelines
## X_lmtact1
## 1 Told have arthritis and have limited usual activities
## 2 Not told they have arthritis
## 3 Told have arthritis and have limited usual activities
## 4 Not told they have arthritis
## 5 Not told they have arthritis
## 6 Not told they have arthritis
## X_lmtwrk1
## 1 Told have arthritis and have limited work
## 2 Not told they have arthritis
## 3 Told have arthritis and have limited work
## 4 Not told they have arthritis
## 5 Not told they have arthritis
## 6 Not told they have arthritis
## X_lmtscl1
## 1 Told have arthritis and social activities limited a lot
## 2 Not told they have arthritis
## 3 Told have arthritis and social activities limited a little
## 4 Not told they have arthritis
## 5 Not told they have arthritis
## 6 Not told they have arthritis
## X_rfseat2 X_rfseat3 X_flshot6
## 1 Always or almost always wear seat belt Always wear seat belt <NA>
## 2 Always or almost always wear seat belt Always wear seat belt <NA>
## 3 Always or almost always wear seat belt Always wear seat belt <NA>
## 4 Always or almost always wear seat belt Always wear seat belt <NA>
## 5 Always or almost always wear seat belt Always wear seat belt No
## 6 Always or almost always wear seat belt Always wear seat belt <NA>
## X_pneumo2 X_aidtst3 X_age80
## 1 <NA> No 60
## 2 <NA> Yes 50
## 3 <NA> Yes 55
## 4 <NA> No 64
## 5 No No 66
## 6 <NA> Yes 49str(brfss2013)## 'data.frame': 491775 obs. of 330 variables:
## $ X_state : Factor w/ 55 levels "0","Alabama",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ fmonth : Factor w/ 12 levels "January","February",..: 1 1 1 1 2 3 3 3 4 4 ...
## $ idate : int 1092013 1192013 1192013 1112013 2062013 3272013 3222013 3042013 4242013 4242013 ...
## $ imonth : Factor w/ 12 levels "January","February",..: 1 1 1 1 2 3 3 3 4 4 ...
## $ iday : Factor w/ 31 levels "1","2","3","4",..: 9 19 19 11 6 27 22 4 24 24 ...
## $ iyear : Factor w/ 2 levels "2013","2014": 1 1 1 1 1 1 1 1 1 1 ...
## $ dispcode : Factor w/ 2 levels "Completed interview",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ seqno : int 2013000580 2013000593 2013000600 2013000606 2013000608 2013000630 2013000634 2013000644 2013001305 2013001338 ...
## $ X_psu : int 2013000580 2013000593 2013000600 2013000606 2013000608 2013000630 2013000634 2013000644 2013001305 2013001338 ...
## $ ctelenum : Factor w/ 1 level "Yes": 1 1 1 1 1 1 1 1 1 1 ...
## $ pvtresd1 : Factor w/ 2 levels "Yes","No": 1 1 1 1 1 1 1 1 1 1 ...
## $ colghous : Factor w/ 1 level "Yes": NA NA NA NA NA NA NA NA NA NA ...
## $ stateres : Factor w/ 1 level "Yes": 1 1 1 1 1 1 1 1 1 1 ...
## $ cellfon3 : Factor w/ 1 level "Not a cellular phone": 1 1 1 1 1 1 1 1 1 1 ...
## $ ladult : Factor w/ 2 levels "Yes, male respondent",..: NA NA NA NA NA NA NA NA NA NA ...
## $ numadult : Factor w/ 19 levels "1","2","3","4",..: 2 2 3 2 2 1 2 1 5 2 ...
## $ nummen : Factor w/ 14 levels "0","1","2","3",..: 2 2 3 2 2 1 2 1 5 2 ...
## $ numwomen : Factor w/ 12 levels "0","1","2","3",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ genhlth : Factor w/ 5 levels "Excellent","Very good",..: 4 3 3 2 3 2 4 3 1 3 ...
## $ physhlth : int 30 0 3 2 10 0 1 5 0 0 ...
## $ menthlth : int 29 0 2 0 2 0 15 0 0 0 ...
## $ poorhlth : int 30 NA 0 0 0 NA 0 10 NA NA ...
## $ hlthpln1 : Factor w/ 2 levels "Yes","No": 1 1 1 1 1 1 1 1 1 1 ...
## $ persdoc2 : Factor w/ 3 levels "Yes, only one",..: 1 1 1 1 1 1 2 1 1 1 ...
## $ medcost : Factor w/ 2 levels "Yes","No": 2 2 2 2 2 2 2 2 2 2 ...
## $ checkup1 : Factor w/ 5 levels "Within past year",..: 1 1 1 2 4 1 1 1 1 1 ...
## $ sleptim1 : int NA 6 9 8 6 8 7 6 8 8 ...
## $ bphigh4 : Factor w/ 4 levels "Yes","Yes, but female told only during pregnancy",..: 1 3 3 3 1 1 1 1 3 3 ...
## $ bpmeds : Factor w/ 2 levels "Yes","No": 1 NA NA NA 2 1 1 1 NA NA ...
## $ bloodcho : Factor w/ 2 levels "Yes","No": 1 1 1 1 1 1 1 1 1 1 ...
## $ cholchk : Factor w/ 4 levels "Within past year",..: 1 1 4 1 2 1 1 1 1 1 ...
## $ toldhi2 : Factor w/ 2 levels "Yes","No": 1 2 2 1 2 1 2 1 1 2 ...
## $ cvdinfr4 : Factor w/ 2 levels "Yes","No": 2 2 2 2 2 2 2 2 2 2 ...
## $ cvdcrhd4 : Factor w/ 2 levels "Yes","No": NA 2 2 2 2 2 2 1 2 2 ...
## $ cvdstrk3 : Factor w/ 2 levels "Yes","No": 2 2 2 2 2 2 2 2 2 2 ...
## $ asthma3 : Factor w/ 2 levels "Yes","No": 1 2 2 2 1 2 2 2 2 2 ...
## $ asthnow : Factor w/ 2 levels "Yes","No": 1 NA NA NA 2 NA NA NA NA NA ...
## $ chcscncr : Factor w/ 2 levels "Yes","No": 2 2 2 2 2 2 2 2 2 2 ...
## $ chcocncr : Factor w/ 2 levels "Yes","No": 2 2 2 2 1 2 2 2 2 2 ...
## $ chccopd1 : Factor w/ 2 levels "Yes","No": 1 2 2 2 2 2 2 2 2 2 ...
## $ havarth3 : Factor w/ 2 levels "Yes","No": 1 2 1 2 2 2 1 1 1 2 ...
## $ addepev2 : Factor w/ 2 levels "Yes","No": 1 1 1 2 2 2 2 2 2 2 ...
## $ chckidny : Factor w/ 2 levels "Yes","No": 1 2 2 2 2 2 2 2 2 2 ...
## $ diabete3 : Factor w/ 4 levels "Yes","Yes, but female told only during pregnancy",..: 3 3 3 3 3 3 3 3 3 3 ...
## $ veteran3 : Factor w/ 2 levels "Yes","No": 2 2 2 2 2 2 2 2 2 2 ...
## $ marital : Factor w/ 6 levels "Married","Divorced",..: 2 1 1 1 1 2 1 3 1 1 ...
## $ children : int 0 2 0 0 0 0 1 0 1 0 ...
## $ educa : Factor w/ 6 levels "Never attended school or only kindergarten",..: 6 5 6 4 6 6 4 5 6 4 ...
## $ employ1 : Factor w/ 8 levels "Employed for wages",..: 7 1 1 7 7 1 1 7 7 5 ...
## $ income2 : Factor w/ 8 levels "Less than $10,000",..: 7 8 8 7 6 8 NA 6 8 4 ...
## $ weight2 : Factor w/ 570 levels "",".b","100",..: 154 30 63 31 169 128 9 1 139 73 ...
## $ height3 : int 507 510 504 504 600 503 500 505 602 505 ...
## $ numhhol2 : Factor w/ 2 levels "Yes","No": 1 2 2 2 2 1 2 2 2 2 ...
## $ numphon2 : Factor w/ 6 levels "1 residential telephone number",..: 2 NA NA NA NA 1 NA NA NA NA ...
## $ cpdemo1 : Factor w/ 2 levels "Yes","No": 1 1 1 1 1 1 1 1 1 1 ...
## $ cpdemo4 : int 10 70 70 75 0 70 40 1 60 50 ...
## $ internet : Factor w/ 2 levels "Yes","No": 1 1 1 1 1 1 1 1 1 1 ...
## $ renthom1 : Factor w/ 3 levels "Own","Rent","Other arrangement": 1 1 1 1 1 1 1 2 1 1 ...
## $ sex : Factor w/ 2 levels "Male","Female": 2 2 2 2 1 2 2 2 1 2 ...
## $ pregnant : Factor w/ 2 levels "Yes","No": NA NA NA NA NA NA 2 NA NA NA ...
## $ qlactlm2 : Factor w/ 2 levels "Yes","No": 1 2 1 2 2 2 1 1 2 2 ...
## $ useequip : Factor w/ 2 levels "Yes","No": 1 2 2 2 2 2 2 2 2 2 ...
## $ blind : Factor w/ 2 levels "Yes","No": 2 2 2 2 2 2 2 2 2 2 ...
## $ decide : Factor w/ 2 levels "Yes","No": 2 2 2 2 2 2 2 2 2 2 ...
## $ diffwalk : Factor w/ 2 levels "Yes","No": 1 2 1 2 2 2 2 1 2 2 ...
## $ diffdres : Factor w/ 2 levels "Yes","No": 2 2 2 2 2 2 2 2 2 2 ...
## $ diffalon : Factor w/ 2 levels "Yes","No": 1 2 2 2 2 2 2 2 2 2 ...
## $ smoke100 : Factor w/ 2 levels "Yes","No": 1 2 1 2 1 2 1 1 2 2 ...
## $ smokday2 : Factor w/ 3 levels "Every day","Some days",..: 3 NA 2 NA 3 NA 3 1 NA NA ...
## $ stopsmk2 : Factor w/ 2 levels "Yes","No": NA NA 1 NA NA NA NA 2 NA NA ...
## $ lastsmk2 : Factor w/ 8 levels "Within the past month",..: 7 NA NA NA 1 NA 5 NA NA NA ...
## $ usenow3 : Factor w/ 3 levels "Every day","Some days",..: 3 3 3 3 3 3 3 3 1 3 ...
## $ alcday5 : int 201 0 220 208 210 0 201 202 101 0 ...
## $ avedrnk2 : int 2 NA 4 2 2 NA 1 1 1 NA ...
## $ drnk3ge5 : int 0 NA 20 0 0 NA 0 0 0 NA ...
## $ maxdrnks : int 2 NA 10 2 3 NA 1 1 2 NA ...
## $ fruitju1 : int 304 305 301 202 0 205 320 0 0 202 ...
## $ fruit1 : int 104 301 203 306 302 206 325 320 101 202 ...
## $ fvbeans : int 303 310 202 202 101 0 330 360 202 203 ...
## $ fvgreen : int 310 203 202 310 310 203 315 315 203 201 ...
## $ fvorang : int 303 202 310 305 303 0 310 325 0 201 ...
## $ vegetab1 : int NA 203 330 204 101 207 310 308 101 203 ...
## $ exerany2 : Factor w/ 2 levels "Yes","No": 2 1 2 1 2 1 1 1 1 1 ...
## $ exract11 : Factor w/ 75 levels "Active Gaming Devices (Wii Fit, Dance, Dance revolution)",..: NA 64 NA 64 NA 6 64 64 7 64 ...
## $ exeroft1 : int NA 105 NA 205 NA 102 220 102 102 220 ...
## $ exerhmm1 : int NA 20 NA 30 NA 15 100 15 100 30 ...
## $ exract21 : Factor w/ 76 levels "Active Gaming Devices (Wii Fit, Dance, Dance revolution)",..: NA 71 NA 75 NA 18 75 75 75 18 ...
## $ exeroft2 : int NA 101 NA NA NA 102 NA NA NA 101 ...
## $ exerhmm2 : int NA 10 NA NA NA 30 NA NA NA 100 ...
## $ strength : int 0 0 0 0 0 0 205 0 102 0 ...
## $ lmtjoin3 : Factor w/ 2 levels "Yes","No": 1 NA 1 NA NA NA 2 1 2 NA ...
## $ arthdis2 : Factor w/ 2 levels "Yes","No": 1 NA 1 NA NA NA 1 2 2 NA ...
## $ arthsocl : Factor w/ 3 levels "A lot","A little",..: 1 NA 2 NA NA NA 3 1 3 NA ...
## $ joinpain : int 7 NA 5 NA NA NA 3 8 4 NA ...
## $ seatbelt : Factor w/ 6 levels "Always","Nearly always",..: 1 1 1 1 1 1 1 1 2 1 ...
## $ flushot6 : Factor w/ 2 levels "Yes","No": 2 1 1 2 2 1 2 1 1 2 ...
## $ flshtmy2 : Factor w/ 26 levels "January 2012",..: NA 10 13 NA NA NA NA 10 10 NA ...
## $ tetanus : Factor w/ 4 levels "Yes, received Tdap",..: 4 1 1 4 4 4 4 4 1 4 ...
## $ pneuvac3 : Factor w/ 2 levels "Yes","No": 1 2 2 2 2 1 2 2 2 2 ...
## [list output truncated]Part 1: Data
The Behavioral Risk Factor Surveillance System (BRFSS) - 2013 data are collected using landline (telephone, i.e., household) and cellular (cellphone, i.e., one adult). The data can be analyzed implementing stratified sampling and cluster sampling.
The stratified sampling helps to consider an causality outcome if the stratum is very similar. In this case, we can take one of the data collection methods and draw samples to form stratum, which can lead to more accurate estimate within the group.
The cluster sampling puts a population into groups which can be separated with a fixed number of draws. This method aids in diverse groups and it can be used to infernce generalizability of the population.
Reference: The BRFSS data user guide June 2013 * * *
Part 2: Research questions
Research quesion 1: What is the average number of adults (i.e., 18 years of age or older) that sleeps more or equal to 7 hours and also have above good general health? Research quesion 2: How many of the interviewed adults complete the survey? Research quesion 3: How does smoking and general exercise influence the general healthe of adults?
Part 3: Exploratory data analysis
Research question Q1: What is the average number of adults (i.e., 18 years of age or older) that sleeps more or equal to 7 hours and also have above good general health?
Answer to Q1 The data summary demonstrated that adults who sleep on average 7.19 hours reported having an excellent general health. It seems that adequate sleep time can influence general well-being. From the analysis below, It was observed that as the number of sleep time hours decrease, adults reported having a fair and poor 6.90 and 6.74, respectively.
Also, the bar chart showed that distribution of the states in the United States where Florida has the highest adults sleeping greater or equal to 7 hours and reporting above fair general health.
These two analysis can help to generalize that adults who might be sleeping the recommended number of sleep hours also are following other health beneficial activities that influence their general health. However, It is important to point out that Florida has a large retired population that may be contributing to its large number of adults.
slptime <- brfss2013 %>%
group_by(genhlth) %>%
summarize(avg_spltm = mean(sleptim1, na.rm=TRUE), cnt=n())
slptime## # A tibble: 6 × 3
## genhlth avg_spltm cnt
## <fct> <dbl> <int>
## 1 Excellent 7.19 85482
## 2 Very good 7.10 159076
## 3 Good 7.04 150555
## 4 Fair 6.90 66726
## 5 Poor 6.74 27951
## 6 <NA> 7.47 1985slptime1 <- brfss2013 %>%
group_by(genhlth, X_state) %>%
summarize(avg_spltm = mean(sleptim1, na.rm=TRUE), cnt=n()) %>%
filter(cnt > 5000)## `summarise()` has grouped output by 'genhlth'. You can override using the `.groups` argument.ggplot(data = slptime1, mapping = aes(x=factor(X_state), y=cnt))+
geom_bar(stat = "identity")+
labs(title = "States with above fair general health", subtitle = "Average sleep time count vs general health", caption = "data collected by BRFSS")+
ylab("Number of adults (sleep time)")+
xlab("State")
Research question Q2: How many of the interviewed adults complete the survey?
Answer to Q2 The analysis showed that on average there are similar number of adults who completed the survey to that who do not complete it. This finding points out that the data collected in the survey need to consider the possibility of large percent information to be either missing or incorrect.
survey <- brfss2013 %>%
select(idate, dispcode) %>%
drop_na() %>%
summarise(avg=mean(idate),
std=sd(idate),
mdian=median(idate))
head(survey)## avg std mdian
## 1 6672294 3412139 7022013survey <- brfss2013 %>%
select(idate, dispcode) %>%
drop_na()
ggplot(survey, aes(x=factor(dispcode), y=idate))+
geom_boxplot()+
labs(title = "Interviewed vs. Disposition", subtitle = "Interviews adults completing the survey", caption = "data collected by BRFSS2013")+
xlab("Final Disposition")+
ylab("# of interviewed")
Research question 3: How does smoking and general exercise influence the general health of adults?
Answer Q3 The analysis inllustrated that adults who stop smoking within the last 12 months and engaged in some form of exercise also shows good general health overall.
activity <- brfss2013 %>%
select(stopsmk2,exerany2, genhlth) %>%
drop_na() %>%
group_by(genhlth)
head(activity)## # A tibble: 6 × 3
## # Groups: genhlth [3]
## stopsmk2 exerany2 genhlth
## <fct> <fct> <fct>
## 1 Yes No Good
## 2 No Yes Good
## 3 Yes No Fair
## 4 Yes Yes Good
## 5 No Yes Very good
## 6 No No Very goodactivity <- brfss2013 %>%
select(stopsmk2,exerany2, genhlth) %>%
drop_na()
ggplot(activity, aes(stopsmk2, fill=exerany2))+
geom_bar(position = "dodge")
activity <- brfss2013 %>%
select(stopsmk2,exerany2, genhlth) %>%
drop_na()
ggplot(activity, aes(genhlth, fill=stopsmk2))+
geom_bar(position = "dodge")