Unable to knit to html file with R session termination message

I am new to using R/Rstudio but trying really hard to figure things out. Please help!

I can generate html file normally but using 55MB raw data.gz, just unable to knit my code.
Every code runs well but whenever I click to knit, it either kills the Rstudio to go to sleep the session or shows R session Error : The previous R session was abnormally terminated due to an unexpected crash. You may have lost workspace data as a result of this crash.

Now it creates knit.md file instead of html.
I am using free version of Rstudio with 1GB limit. Maybe is this the reason of this?
Thank you for reading!

Can you supply us with a minimum working example of what you are doing?

Essentially a reproducible example (reprex)

Is there any reason to think that R is decompressing the data.gz file?

It makes either knit.md file or terminate the session now..
I am using brfss2013 dataset.

Setting up environment

install.packages("ggplot2")
library(ggplot2)
library(dplyr)
library(tidyr)
load("brfss2013.gz")

Part 3: Exploratory Data Analysis

Research question 1

Based on the report, is respondent’s body weight linked to their level of education? Can we discern any difference of BMI with income variables? This is quite interesting question as it focuses on linkage between one’s body mass with their income and education status. .

# Select adequate variables from dataset and omit NAs
dd <- select(brfss2013, X_educag, X_incomg, X_bmi5cat) %>%
na.omit()
dim(dd)

We can use 'group_by' and 'summarize' to view the value counts in the '_educag' variable with the mean of body mass in the category in order to check summary statistics:
ddd <- dd %>%
mutate(X_bm=as.numeric(dd$X_bmi5cat))

ddd %>%
group_by(X_educag) %>%
summarize(mean(X_bm), count=n())

Let's apply bar graph to visualize the variables, use as.factor function:

# Specify a column type to be factor (also called categorical or enumerative)
dd$X_educag <- as.factor(dd$X_educag)
dd$X_incomg <- as.factor(dd$X_incomg)
dd$X_bmi5cat <- as.factor(dd$X_bmi5cat)

Now, let's check the graph:
# Visualize the relationship of variables
cc <- ggplot(dd, aes(x=X_educag, fill = X_incomg)) +
geom_bar() + facet_wrap(~X_bmi5cat, ncol=2)
# Enhance readability
cc <- cc + xlab("Level of education completed") + ylab("Count") + scale_fill_discrete(name="Income categories") + theme(axis.text.x = element_text(face="bold", size=7, angle=90)) + ggtitle("BMI related with the level of education and Income categories") + theme(plot.title = element_text(face = "italic", hjust = 0.5, size = 12))

cc

Research question 2

Based on the report, we can examine any linkage in high blood pressure between one’s marital status and genders. The outcome could imply any difference of high blood pressure depends on their marriage situation their genders. Would it be better to get married for the sake of healthy blood pressure? Let’s check it out..

# Select adequate variables from dataset and omit NAs
qq <- select(brfss2013,bpmeds,marital,sex) %>%
na.omit()

We can use 'filter' and 'group by' to view the 'bpmeds' value counts in the 'Married' variable in order to check summary statistics. It will tell the number of married respondents taking medicine for high blood pressure:

qq %>%
filter(marital == "Married") %>%
group_by(bpmeds) %>%
summarize(count=n())

Let's visualize the 3 variables' detail:

# Visualize in a bar plot
gg <- ggplot(qq) + aes(x=marital,fill=sex) + geom_bar() +facet_grid(.~bpmeds)
# Enhance readability
gg <- gg + theme(axis.title.x=element_blank()) + ylab("Count") + scale_fill_discrete(name="Sex") + theme(axis.text.x = element_text(face="bold", size=7, angle=45)) + ggtitle("Taking high blood pressure medicine") + theme(plot.title = element_text(face = "bold", hjust = 0.5, size = 13, color = "darkblue")) + theme(axis.title.y=element_text(angle=0, face="italic", size=11)) + theme(legend.title = element_text(face = "italic", size = 12))
gg

Research question 3

Based on the report, is length of one's sleeping time associated with respondent's marital status? The answer to this question could bring us more research inquires on the relationship of the type of marital status and respondent's health in general.

# Select adequate variables from dataset and calculate sum of sleep time omitting NAs
am <- brfss2013[,c("marital","sleptim1")]
sum(is.na(am$sleptim1))

Using group by function, we can see the number of respondents in each marital satus:

am %>%
group_by(marital) %>%
summarize(count = n())

We can also calculate respondents' mean sleep time per their marital status:

# Calculatie mean of sleep time per marital status and set new names using colnames function.
# Colnames() function in R Language is used to set the names to columns of a matrix.
am <- am[!is.na(am$sleptim1), ]
am <- aggregate(am[, "sleptim1"], list(am$marital), mean)
colnames(am) <- c('Marital_status', 'Average_sleep_time')
am <- am[am$Marital_status !=0,]

Let's visualize the 3 variables' detail:

# Visualize the relationship of variables and enhance readability.
bb <- ggplot(am,aes(x=Marital_status,y=Average_sleep_time,group = 1))+
geom_point() + geom_line() +
xlab("Marital status") + ylab("Average sleep time") +
ggtitle("Plot of sleep time per Marital status")+
theme(axis.text.x = element_text(face="bold", size=10, angle=90)) + theme(axis.title.x=element_blank()) + theme(plot.title = element_text(face = "bold", hjust = 0.5, size = 13, color = "darkblue")) + theme(axis.title.y=element_text(size=11))
bb

Do you have any reason to assume that you read in the brfss2013 dataset?

If it is loaded can you give us some ideawhat it is?

str() & head() can be usefull as can be skimR Using Skimr

I tried skimR but it showed the same error message saying terminated by crash.
So here's the str() of dataset.

str(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]

This is the head. Please help ;<

X_state fmonth idate imonth iday iyear dispcode seqno X_psu ctelenum pvtresd1 colghous
1 Alabama January 1092013 January 9 2013 Completed interview 2013000580 2013000580 Yes Yes
2 Alabama January 1192013 January 19 2013 Completed interview 2013000593 2013000593 Yes Yes
3 Alabama January 1192013 January 19 2013 Completed interview 2013000600 2013000600 Yes Yes
stateres cellfon3 ladult numadult nummen numwomen genhlth physhlth menthlth poorhlth hlthpln1
1 Yes Not a cellular phone 2 1 1 Fair 30 29 30 Yes
2 Yes Not a cellular phone 2 1 1 Good 0 0 NA Yes
3 Yes Not a cellular phone 3 2 1 Good 3 2 0 Yes
persdoc2 medcost checkup1 sleptim1 bphigh4 bpmeds bloodcho cholchk toldhi2 cvdinfr4
1 Yes, only one No Within past year NA Yes Yes Yes Within past year Yes No
2 Yes, only one No Within past year 6 No Yes Within past year No No
3 Yes, only one No Within past year 9 No Yes 5 or more years ago No No
cvdcrhd4 cvdstrk3 asthma3 asthnow chcscncr chcocncr chccopd1 havarth3 addepev2 chckidny diabete3 veteran3 marital
1 No Yes Yes No No Yes Yes Yes Yes No No Divorced
2 No No No No No No No Yes No No No Married
3 No No No No No No Yes Yes No No No Married
children educa employ1 income2 weight2
1 0 College 4 years or more (College graduate) Retired Less than $75,000 250
2 2 College 1 year to 3 years (Some college or technical school) Employed for wages $75,000 or more 127
3 0 College 4 years or more (College graduate) Employed for wages $75,000 or more 160
height3 numhhol2 numphon2 cpdemo1 cpdemo4 internet renthom1 sex pregnant qlactlm2
1 507 Yes 2 residential telephone numbers Yes 10 Yes Own Female Yes
2 510 No Yes 70 Yes Own Female No
3 504 No Yes 70 Yes Own Female Yes
useequip blind decide diffwalk diffdres diffalon smoke100 smokday2 stopsmk2 lastsmk2 usenow3 alcday5
1 Yes No No Yes No Yes Yes Not at all 10 years or more Not at all 201
2 No No No No No No No Not at all 0
3 No No No Yes No No Yes Some days Yes Not at all 220
avedrnk2 drnk3ge5 maxdrnks fruitju1 fruit1 fvbeans fvgreen fvorang vegetab1 exerany2 exract11 exeroft1 exerhmm1
1 2 0 2 304 104 303 310 303 NA No NA NA
2 NA NA NA 305 301 310 203 202 203 Yes Walking 105 20
3 4 20 10 301 203 202 202 310 330 No NA NA
exract21 exeroft2 exerhmm2 strength lmtjoin3 arthdis2 arthsocl
1 NA NA 0 Yes Yes A lot
2 Household Activities (vacuuming, dusting, home repair, etc.) 101 10 0
3 NA NA 0 Yes Yes A little
joinpain seatbelt flushot6 flshtmy2 tetanus pneuvac3 hivtst6 hivtstd3
1 7 Always No No, did not receive any tetanus since 2005 Yes No NA
2 NA Always Yes October 2012 Yes, received Tdap No Yes NA
3 5 Always Yes January 2013 Yes, received Tdap No Yes NA
whrtst10 pdiabtst prediab1 diabage2 insulin bldsugar feetchk2 doctdiab chkhemo3 feetchk eyeexam
1 Yes Yes NA NA NA NA
2 Private doctor or HMO Yes No NA NA NA NA
3 At home Yes No NA NA NA NA
diabeye diabedu painact2 qlmentl2 qlstres2 qlhlth2 medicare hlthcvrg delaymed
1 5 30 30 0 Yes 3 7 You didn't have transportation
2 0 2 3 25 No 2 No, I did not delay getting medical care
3 20 2 5 2 No 3
dlyother nocov121 lstcovrg drvisits medscost carercvd medbills ssbsugar ssbfrut2 wtchsalt longwtch dradvise
1 No 5 No Very satisfied No 305 305 Yes 408 Yes
2 No 3 No Very satisfied No 203 0 No NA No
3 No 6 No Very satisfied No 202 308 No NA No
asthmage asattack aservist asdrvist asrchkup asactlim asymptom asnoslep asthmed3
1 56 Yes 0 0 3 NA Every day, but not all the time None 1 to 14 days
2 NA NA NA NA NA
3 NA NA NA NA NA
asinhalr harehab1 strehab1 cvdasprn aspunsaf rlivpain rduchart rducstrk
1 5 to 14 times No Yes, stomach problems
2 No No
3 No No
arttoday arthwgt arthexer arthedu
1 I can do some things I would like to do Yes Yes No
2
3 I can do some things I would like to do No Yes No
imfvplac hpvadvc2 hpvadsht hadmam howlong profexam
1 Yes Within past 2 years Yes
2 Workplace Yes Within past 3 years Yes
3 A doctor´s office or health maintenance organization (HMO) Yes Within past year Yes
lengexam hadpap2 lastpap2 hadhyst2 bldstool lstblds3 hadsigm3 hadsgco1
1 Within past 2 years Yes 5 or more years ago Yes No Yes Colonoscopy
2 Within past 3 years Yes Within past 3 years No No No
3 Within past year Yes Within past year Yes Yes 5 or more years ago Yes Colonoscopy
lastsig3 pcpsaad2 pcpsadi1 pcpsare1 psatest1 psatime pcpsars1 pcpsade1 pcdmdecn
1 Within past 2 years NA
2 NA
3 Within past 3 years NA
rrclass2 rrcognt2 rratwrk2 rrhcare3 rrphysm2 rremtsm2 misnervs
1 Black or African American Never The same as other races No No Some
2 White Never The same as other races The same as other races No No A little
3 White Never The same as other races The same as other races No No None
mishopls misrstls misdeprd miseffrt miswtles misnowrk mistmnt mistrhlp misphlpf scntmony scntmeal
1 Some Some None All None 30 Yes Agree strongly Disagree slightly Never Never
2 None None None None None 0 No Agree slightly Disagree slightly Never Never
3 None None None None None 0 No Agree strongly Agree strongly Never Never
scntpaid scntwrk1 scntlpad scntlwk1 scntvot1 rcsgendr rcsrltn2 casthdx2 casthno2 emtsuprt
1 NA Paid by salary NA Yes Always
2 Paid by the hour 35 NA Yes Girl Parent No Sometimes
3 Paid by the hour 40 NA Yes Usually
lsatisfy ctelnum1 cellfon2 cadult pvtresd2 cclghous cstate landline pctcell qstver qstlang
1 Very satisfied NA Only Version Landline English
2 Satisfied NA Only Version Landline English
3 Very satisfied NA Only Version Landline English
mscode X_ststr X_strwt X_rawrake X_wt2rake X_imprace X_impnph X_impeduc
1 Inside a suburban county of the MSA 11081 40.19767 1 40.19767 Black, Non-Hispanic 2 NA
2 Inside a suburban county of the MSA 11081 40.19767 2 80.39535 White, Non-Hispanic 1 NA
3 Inside a suburban county of the MSA 11081 40.19767 3 120.59302 White, Non-Hispanic 1 NA
X_impmrtl X_imphome X_chispnc X_crace1 X_impcage X_impcrac
1 NA NA
2 NA NA Child not of Hispanic, Latino/a, or Spanish origin White 10-14 Years old White, non-Hispanic
3 NA NA
X_impcsex X_cllcpwt X_dualuse X_dualcor X_llcpwt2 X_llcpwt X_rfhlth X_hcvu651
1 NA No Dual Phone Use NA 331.4934 238.0161 Fair or Poor Health Have health care coverage
2 Female 954.0782 No Dual Phone Use NA 662.9867 737.6942 Good or Better Health Have health care coverage
3 NA No Dual Phone Use NA 994.4801 568.5274 Good or Better Health Have health care coverage
X_rfhype5 X_cholchk X_rfchol X_ltasth1 X_casthm1 X_asthms1
1 Yes Had cholesterol checked in past 5 years Yes Yes Yes Current
2 No Had cholesterol checked in past 5 years No No No Never
3 No Did not have cholesterol checked in past 5 years No No No Never
X_drdxar1 X_prace1 X_mrace1
1 Diagnosed with arthritis Black or African American Black or African American
2 Not diagnosed with arthritis White White
3 Diagnosed with arthritis White White
X_hispanc X_race X_raceg21
1 Not of Hispanic, Latino/a, or Spanish origin Black only, non-Hispanic Non-White or Hispanic
2 Not of Hispanic, Latino/a, or Spanish origin White only, non-Hispanic Non-Hispanic White
3 Not of Hispanic, Latino/a, or Spanish origin White only, non-Hispanic Non-Hispanic White
X_racegr3 X_race_g1 X_ageg5yr X_age65yr X_age_g htin4 htm4 wtkg3 X_bmi5
1 Black only, Non-Hispanic Black - Non-Hispanic Age 60 to 64 Age 18 to 64 Age 55 to 64 67 170 11340 3916
2 White only, Non-Hispanic White - Non-Hispanic Age 50 to 54 Age 18 to 64 Age 45 to 54 70 178 5761 1822
3 White only, Non-Hispanic White - Non-Hispanic Age 55 to 59 Age 18 to 64 Age 55 to 64 64 163 7257 2746
X_bmi5cat X_rfbmi5 X_chldcnt X_educag X_incomg
1 Obese Yes No children in household Graduated from college or technical school $50,000 or more
2 Underweight No Two children in household Attended college or technical school $50,000 or more
3 Overweight Yes No children in household Graduated from college or technical school $50,000 or more
X_smoker3 X_rfsmok3 drnkany5 drocdy3_ X_rfbing5 X_drnkdy4 X_drnkmo4 X_rfdrhv4 X_rfdrmn4
1 Former smoker No No 3 No 7 2 No
2 Never smoked No Yes 0 No 0 0 No
3 Current smoker - now smokes some days Yes No 67 Yes 267 80 Yes
X_rfdrwm4 ftjuda1_ frutda1_ beanday_ grenday_ orngday_ vegeda1_ X_misfrtn
1 No 13 400 10 33 10 NA No missing fruit responses
2 No 17 3 33 43 29 43 No missing fruit responses
3 Yes 3 43 29 29 33 100 No missing fruit responses
X_misvegn X_frtresp X_vegresp X_frutsum
1 1 missing response Included - Missing Fruit Responses Not Included - Missing Fruit Responses 413
2 No missing vegetable responses Included - Missing Fruit Responses Included - Missing Fruit Responses 20
3 No missing vegetable responses Included - Missing Fruit Responses Included - Missing Fruit Responses 46
X_vegesum X_frtlt1 X_veglt1
1 53 Consumed fruit one or more times per day Consumed vegetables less than one time per day
2 148 Consumed fruit less than one time per day Consumed vegetables one or more times per day
3 191 Consumed fruit less than one time per day Consumed vegetables one or more times per day
X_frt16 X_veg23
1 Included - values are in accepted range Included - values are in accepted range
2 Included - values are in accepted range Included - values are in accepted range
3 Included - values are in accepted range Included - values are in accepted range
X_fruitex X_vegetex
1 No missing values and in accepted range Missing vegetables responses
2 No missing values and in accepted range No missing values and in accepted range
3 No missing values and in accepted range No missing values and in accepted range
X_totinda metvl11_ metvl21_ maxvo2_ fc60_ actin11_ actin21_ padur1_ padur2_
1 No physical activity or exercise in last 30 days NA NA 2580 442 NA NA
2 Had physical activity or exercise 35 33 2950 506 Moderate Moderate 20 10
3 No physical activity or exercise in last 30 days NA NA 2765 474 NA NA
pafreq1_ pafreq2_ X_minac11 X_minac21 strfreq_ pamiss1_ pamin11_ pamin21_ pa1min_ pavig11_ pavig21_ pa1vigm_
1 NA NA NA NA 0 0 NA NA NA NA NA
2 5000 1000 100 10 0 0 100 10 110 0 0 0
3 NA NA NA NA 0 0 NA NA NA NA NA
X_pacat1 X_paindx1 X_pa150r2 X_pa300r2 X_pa30021
1 Inactive Did not meet aerobic recommendations 0 minutes 0 minutes 0-300 minutes
2 Insufficiently active Did not meet aerobic recommendations 1-149 minutes 1-300 minutes 0-300 minutes
3 Inactive Did not meet aerobic recommendations 0 minutes 0 minutes 0-300 minutes
X_pastrng X_parec1 X_pastae1
1 Did not meet muscle strengthening recommendations Did not meet either guideline Did not meet both guidelines
2 Did not meet muscle strengthening recommendations Did not meet either guideline Did not meet both guidelines
3 Did not meet muscle strengthening recommendations Did not meet either guideline Did not meet both guidelines
X_lmtact1 X_lmtwrk1
1 Told have arthritis and have limited usual activities Told have arthritis and have limited work
2 Not told they have arthritis Not told they have arthritis
3 Told have arthritis and have limited usual activities Told have arthritis and have limited work
X_lmtscl1 X_rfseat2
1 Told have arthritis and social activities limited a lot Always or almost always wear seat belt
2 Not told they have arthritis Always or almost always wear seat belt
3 Told have arthritis and social activities limited a little Always or almost always wear seat belt
X_rfseat3 X_flshot6 X_pneumo2 X_aidtst3 X_age80
1 Always wear seat belt No 60
2 Always wear seat belt Yes 50
3 Always wear seat belt Yes 55
[ reached 'max' / getOption("max.print") -- omitted 3 rows ]

I am at a loss. It might be a memory problem but it does not look like it.

It is just the HTML that is the problem?_ Can you produce a PDF or DOC?