The data is a subset of the 2009 survey from BRFSS, an ongoing data collection program designed to measure behavioral risk factors for the adult population (18 years of age or older) living in households.
An object of class
tbl_df (inherits from
data.frame) with 245 rows and 34 columns.
the codebook: http://ftp.cdc.gov/pub/data/brfss/codebook_09.rtf
Format: a data frame with 245 observations on the following 34 variables.
A factor with 52 levels. The labels and states corresponding to the labels are as follows: 1:Alabama, 2:Alaska, 4:Arizona, 5:Arkansas, 6:California,8:Colorado, 9:Connecticut, 10:Delaware, 11:District of Columbia,12:Florida, 13:Georgia, 15:Hawaii, 16:Idaho, 1 :Illinois,18:Indiana, 19:Iowa, 20:Kansas, 21:Kentucky, 22:Louisiana,23:Maine, 24:Maryland, 25:Massachusetts, 26:Michigan,27:Minnesota, 28:Mississippi, 2:Missouri, 30:Montana,31:Nebraska, 32:Nevada, 33:New Hampshire, 34:New Jersey, 35:NewMexico, 36:New York, 37:North Carolina, 38:North Dakota, 39:Ohio,40:Oklahoma, 41:Oregon, 42:Pennsylvania, 44:Rhode Island, 45:SouthCarolina, 46:South Dakota, 47:Tennessee, 48:Texas, 49:Utah, 50:Vermont, 51:Virginia, 53:Washington, 54:West Virginia,55:Wisconsin, 56:Wyoming, 66:Guam, 72:Puerto Rico, 78:Virgin Islands
A factor with levels
A numeric vector from 7 to 97.
The weight without shoes in pounds.
The weight without shoes in inches.
Body Mass Index (BMI). Computed by weight in Kilogram /(height in Meters * height in Meters). Missing if any of weight or height is missing.
A factor with levels
Whether pregnant now with two levels
A numeric vector giving the number of children less than 18 years of age in household.
A factor with the education levels
6 as 1: Never attended
school or only kindergarten; 2: Grades 1 through 8 (Elementary);
3: Grades 9 through 11 (Some high school); 4: Grade 12 or GED
(High school graduate); 5: College 1 year to 3 years (Some college
or technical school); 6: College 4 years or more (College
A factor showing the employment status with levels
8. The labels
mean – 1: Employed for wages; 2: Self-employed; 3: Out of work for more
than 1 year; 4: Out of work for less that 1 year; 5: A homemaker; 6: A
student; 7:Retired; 8: Unable to work.
The annual household income from all sources with
A factor with levels
5. The question for this variable is: Have you ever
served on active duty in the United States Armed Forces, either in the
regular military or in a National Guard or military reserve unit? Active
duty does not include training for the Reserves or National Guard, but
DOES include activation, for example, for the Persian Gulf War. And the
labels are meaning: 1: Yes, now on active duty; 2: Yes, on active duty
during the last 12 months, but not now; 3: Yes, on active duty in the
past, but not during the last 12 months; 4: No, training for Reserves or
National Guard only; 5: No, never served in the military.
A factor with levels
corresponding to the question: are you Hispanic or Latino?
Answer to question "in general your health is"
The number of days during the last 30 days that the respondent's physical health was not good. -7 is for "Don't know/Not sure", and -9 is for "Refused".
The number of days during the last 30 days that the respondent's mental health was not good. -7 is for "Don't know/Not sure", and -9 is for "Refused".
The number of days during the last 30 days that poor physical or mental health keep the respondent from doing usual activities, such as self-care, work, or recreation. -7 is for "Don't know/Not sure", and -9 is for "Refused".
Whether having any kind of health care
coverage, including health insurance, prepaid plans such as HMOs,
or government plans such as Medicare. The answer has two levels:
Whether providing any such care or assistance
to a friend or family member during the past month, with levels
Whether being limited in any way in any
activities because of physical, mental, or emotional problems,
Whether having had at least one drink of
any alcoholic beverage such as beer, wine, a malt beverage or
liquor during the past 30 days, with levels
The number of days during the past 30 days that the respondent had at least one drink of any alcoholic beverage. -7 is for "Don't know/Not sure", and -9 is for "Refused".
The number of drinks on the average the respondent had on the days when he/she drank, during the past 30 days. -7 is for "Don't know/Not sure", and -9 is for "Refused".
Whether having smoked at least
100 cigarettes in the entire life, with levels
The frequency of days now
smoking, with levels
NotAtAll(not at all).
having stopped smoking for one day or longer during the past 12
months because the respondent was trying to quit smoking, with
corresponding to the question: how long has it been since last
smoking cigarettes regularly? The labels mean: 3: Within the past
6 months (3 months but less than 6 months ago); 4: Within the past
year (6 months but less than 1 year ago); 5: Within the past 5
years (1 year but less than 5 years ago); 6: Within the past 10
years (5 years but less than 10 years ago); 7: 10 years or more;
8: Never smoked regularly.
The number of fruit the respondent eat every year, not counting juice. -7 is for "Don't know/Not sure", and -9 is for "Refused".
The number of servings of green salad the respondent eat every year. -7 is for "Don't know/Not sure", and -9 is for "Refused".
The number of servings of potatoes, not including french fries, fried potatoes, or potato chips, that the respondent eat every year. -7 is for "Don't know/Not sure", and -9 is for "Refused".
The number of carrots the respondent eat every year. -7 is for "Don't know/Not sure", and -9 is for "Refused".
The number of servings of vegetables the respondent eat every year, not counting carrots, potatoes, or salad. -7 is for "Don't know/Not sure", and -9 is for "Refused".
The number of fruit juices such as orange, grapefruit, or tomato that the respondent drink every year. -7 is for "Don't know/Not sure", and -9 is for "Refused".
library(MissingDataGUI) (named brfss)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
# explore the missingness with vis_miss library(naniar) vis_miss(riskfactors) # Look at the missingness in the variables miss_var_summary(riskfactors) # and now as a plot gg_miss_var(riskfactors) # Look at the missingness in bmi and poor health library(ggplot2) p <- ggplot(riskfactors, aes(x = health_poor, y = bmi)) + geom_miss_point() p # for each sex? p + facet_wrap(~sex) # for each education bracket? p + facet_wrap(~education)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.