Searching NHANES Variables and Tables
A broad overview of data collected as part of continuous NHANES is described in the survey content brochure, and the NHANES website has a variable search interface as well. This document describes how local interactive searches can be performed using downloaded and processed variable metadata information.
Manifest of available variables
The NHANES data consist of multiple tables over multiple cycles, each with a set of recorded variables. The variable names themselves are cryptic, and not useful as search terms. Fortunately, the NHANES website provides comprehensive details about these variables in the form of tables, grouped by components such as Demographics, Laboratory, etc.
The nhanesA package can download these tables and make the information
contained in them available as a data frame using the
nhanesManifest() function.
library(nhanesA)
library(phonto)
varmf <- nhanesManifest("variables")
This downloads and combines several large web pages, so it may take a
little time to run. Add verbose = TRUE to see some indication of
what is happening.
While useful, this table has limited information. The most useful component, the variable description, sometimes (but not always) records instructions and can be quite long.
sum(nchar(varmf$VarDesc) == 0)
[1] 181
After reordering the remaining rows by the length of the descriptions, the first few rows are given by
varmf <- subset(varmf, nzchar(varmf$VarDesc))
varmf <- varmf[ order(nchar(varmf$VarDesc)), ]
head(varmf)
VarName VarDesc Table TableDesc BeginYear EndYear Component UseConstraints
30996 PFCAGE Age PFC_Pool Polyfluoroalkyl Chemicals - Pooled Samples (Surplus) 2001 2002 Laboratory None
34173 SSHCB HCB SSPST_B Pesticides - Organochlorine Metabolites - Serum - Pooled Samples (Surplus) 2001 2002 Laboratory None
9926 LEAARM Arm: LEXABPI Lower Extremity Disease - Ankle Brachial Blood Pressure Index 1999 2000 Examination None
31002 PFCRACE Race PFC_Pool Polyfluoroalkyl Chemicals - Pooled Samples (Surplus) 2001 2002 Laboratory None
32851 SSBETA Beta SSNH3OL Monoclonal gammopathy of undetermined significance (MGUS) (Surplus) 1988 1994 Laboratory None
32875 SSBETA Beta SSOL_A Monoclonal gammopathy of undetermined significance (MGUS) (Surplus) 1999 2000 Laboratory None
The last few rows have considerably longer descriptions.
unique(tail(varmf, 30)$VarDesc)
[1] "The following questions ask about use of drugs not prescribed by a doctor. Please remember that your answers to these questions are strictly confidential. The first questions are about marijuana and hashish. Marijuana is also called pot or grass. Marijuana is usually smoked, either in cigarettes, called joints, or in a pipe. It is sometimes cooked in food. Hashish is a form of marijuana that is also called 'hash.' It is usually smoked in a pipe. Another form of hashish is hash oil. Have you ever, even once, used marijuana or hashish?"
[2] "Next I am going to ask you about the time {you spend/SP spends} doing different types of physical activity in a typical week. Think first about the time {you spend/he spends/she spends} doing work. Think of work as the things that {you have/he has/she has} to do such as paid or unpaid work, household chores, and yard work. Does {your/SP's} work involve vigorous-intensity activity that causes large increases in breathing or heart rate like carrying or lifting heavy loads, digging or construction work for at least 10 minutes continuously?"
[3] "The next questions are about the food eaten by {you/you and your household}. {When answering these questions, think about all the people who eat here, even if they are not related to you.} Which of these statements best describes the food eaten {by you/ in your household} in the last 12 months, that is since {DISPLAY CURRENT MONTH} of last year. 1. {I/We} always have enough to eat and the kinds of food {I/we} want; 2. {I/We} have enough to eat but not always the kinds of food {I/we} want; 3. Sometimes or often {I/we} don't have enough to eat."
[4] "There are three ways in which attacks of the sort we have been discussing can affect a person's life and activities. First, the attacks themselves can be incapacitating. Second, worry about having additional attacks can get in the way of daily activities. And, third, avoiding certain situations for fear of having additional attacks can interfere with daily activities. Think about all three of these ways in which your life and activities were affected in the past 12 months. Did these things interfere with your life or activities -- a lot, some, a little, or not at all?"
[5] "Attacks of this sort can occur in three different situations. The first are when they occur \"out of the blue\" for no reason. The second are when they occur in situations where a person has an unreasonably strong fear. For example, some people have a terrible fear of bugs or heights or being in a crowd. The third are situations where a person is in real danger, like a car accident or a bank robbery. The next question is about how many of your (# FROM CIQP14) attacks occurred in each of these three kinds of situations. First, in your lifetime, about how many attacks have you had \"out of the blue\" for no reason?"
[6] "The purpose of this next set of questions is to find out if {you generally have/SP generally has} difficulty carrying out certain activities because {you are/s/he is} too sleepy or tired. When the words 'sleepy' or 'tired' are used, it means the feeling that {you/s/he} can't keep {your/his/her} eyes open, {your/his/her} head is droopy, that {you/s/he} want to 'nod off' or that {you feel/s/he feels} the urge to take a nap. The words do not refer to the tired or fatigued feeling {you/she} may have after {you have/s/he has} exercised. {Do you/Does SP} have difficulty concentrating on the things {you do/s/he does} because {you feel/s/he feels} sleepy or tired?"
[7] "Now I want to ask you some questions about other things ________ may have done that can get people into trouble.<p>\r\n\r\nFor this set of questions I will start off by asking if [he/she] has done something at any time in [his/her] life, and then I'll ask whether [he/she] did it in the last year that is, since [[NAME EVENT]/[NAME CURRENT MONTH] of last year].<p>\r\n\r\nSome of the questions are very personal, but all of your answers are confidential and won't be repeated to anyone else.<p>\r\n\r\nThinking about [his/her] whole life, has ________ ever secretly stolen money or other things from [you (or [his/her] family)/[his/her] family] or from other people [he/she] lives with?"
[8] "These next questions are about noise at work. First we are going to ask about loud noise. Loud means so loud that {you/s/he} must speak in a raised voice to be heard by someone three feet away when not using hearing protection. After that we will ask about very loud noise. Very loud noise is noise that is so loud {you have/he has/she has} to shout to be heard by someone three feet away when not using hearing protection.\r\nHow many days per month {are you/is SP} usually exposed to loud noise at {your/his/her} job as a(n) {OCCUPATION} for {EMPLOYER}? (Loud means so loud that {you/s/he} must speak in a raised voice to be heard by someone three feet away when not using hearing protection.)"
[9] "The next questions are about physical activities including exercise, sports, and physically active hobbies that {you/SP} may have done in {your/his/her} leisure time or at school over the past 30 days. First I will ask you about vigorous activities that cause heavy sweating or large increases in breathing or heart rate. Then I will ask you about moderate activities that cause only light sweating or a slight to moderate increase in breathing or heart rate. Over the past 30 days, did {you/SP} do any vigorous activities for at least 10 minutes that caused heavy sweating, or large increases in breathing or heart rate? Some examples are running, lap swimming, aerobics classes or fast bicycling."
[10] "These next questions are about noise exposure at work. First we are going to ask about loud noise. Loud means so loud that {you/s/he} must speak in a raised voice to be heard by someone three feet away when not using hearing protection. After that we will ask about very loud noise. Very loud noise is noise that is so loud {you have/he has/she has} to shout in order to be understood by someone standing 3 feet away from {you/him/her} when not using hearing protection. {Have you/Has SP} ever had a job, or combination of jobs where {you were/s/he was} exposed to loud sounds or noise for 4 or more hours a day, several days a week? (Loud means so loud that {you/s/he} must speak in a raised voice to be heard.)"
[11] "Next I am going to ask you about the time {you spend/SP spends} doing different types of physical activity in a typical week. Please answer these questions even if {you do not consider yourself/SP does not consider himself/herself} to be a physically active person. Think first about the time {you spend/SP spends} doing work. Think of work as the things that {you have/SP has} to do such as paid or unpaid work, studying or training, household chores, and yard work. In answering the following questions, 'vigorous-intensity activities' are activities that require hard physical effort and cause large increases in breathing or heart rate, and 'moderate-intensity activities' are activities that require moderate physical effort and cause small increases in breathing or heart rate. Does {your/SP's} work involve vigorous-intensity activity that causes large increases in breathing or heart rate like carrying or lifting heavy loads, digging or construction work for at least 10 minutes continuously?"
More useful and concise descriptions are available in the per-table
documentation, which can be accessed using the nhanesCodebook()
function and summarized using the nhanesTableSummary() function. For
example, a summary of the DEMO_C table if given by the following.
nhanesTableSummary("DEMO_C", use = "both")
table varname label nobs_cb na_cb has_range nlevels skip nobs_data na_data size num cat unique
1 DEMO_C SEQN Respondent sequence number NA NA NA NA NA 10122 0 40536 TRUE FALSE TRUE
2 DEMO_C SDDSRVYR Data Release Number 10122 0 FALSE 2 FALSE 10122 0 81104 FALSE TRUE FALSE
3 DEMO_C RIDSTATR Interview/Examination Status 10122 0 FALSE 3 FALSE 10122 0 81200 FALSE TRUE FALSE
4 DEMO_C RIDEXMON Six month time period 10122 479 FALSE 3 FALSE 10122 479 81184 FALSE TRUE FALSE
5 DEMO_C RIAGENDR Gender 10122 0 FALSE 3 FALSE 10122 0 81136 FALSE TRUE FALSE
6 DEMO_C RIDAGEYR Age at Screening Adjudicated - Recode 10122 0 TRUE 3 FALSE 10122 0 81024 TRUE FALSE FALSE
7 DEMO_C RIDAGEMN Age in Months - Recode 10122 223 TRUE 2 FALSE 10122 223 81024 TRUE FALSE FALSE
8 DEMO_C RIDAGEEX Exam Age in Months - Recode 10122 692 TRUE 2 FALSE 10122 692 81024 TRUE FALSE FALSE
9 DEMO_C RIDRETH1 Race/Ethnicity - Recode 10122 0 FALSE 6 FALSE 10122 0 81424 FALSE TRUE FALSE
10 DEMO_C RIDRETH2 Linked NH3 Race/Ethnicity - Recode 10122 0 FALSE 6 FALSE 10122 0 81424 FALSE TRUE FALSE
11 DEMO_C DMQMILIT Veteran/Military Status 10122 4196 FALSE 5 FALSE 10122 4196 81192 FALSE TRUE FALSE
12 DEMO_C DMDBORN Country of Birth - Recode 10122 0 FALSE 6 FALSE 10122 0 81304 FALSE TRUE FALSE
13 DEMO_C DMDCITZN Citizenship Status 10122 0 FALSE 5 FALSE 10122 0 81256 FALSE TRUE FALSE
14 DEMO_C DMDYRSUS Length of time in US 10122 8678 FALSE 13 FALSE 10122 8678 81944 FALSE TRUE FALSE
15 DEMO_C DMDEDUC3 Education Level - Children/Youth 6-19 10122 6785 FALSE 21 FALSE 10122 6785 82368 FALSE TRUE FALSE
16 DEMO_C DMDEDUC2 Education Level - Adults 20+ 10122 5081 FALSE 8 FALSE 10122 5081 81592 FALSE TRUE FALSE
17 DEMO_C DMDEDUC Education - Recode (old version) 10122 1744 FALSE 6 FALSE 10122 1744 81400 FALSE TRUE FALSE
18 DEMO_C DMDSCHOL Now attending school? 10122 6995 FALSE 6 FALSE 10122 6995 81296 FALSE TRUE FALSE
19 DEMO_C DMDMARTL Marital Status 10122 3356 FALSE 9 FALSE 10122 3356 81408 FALSE TRUE FALSE
20 DEMO_C DMDHHSIZ Total number of people in the Household 10122 0 TRUE 3 FALSE 10122 0 81024 TRUE FALSE FALSE
21 DEMO_C INDHHINC Annual Household Income 10122 629 FALSE 16 FALSE 10122 629 82136 FALSE TRUE FALSE
22 DEMO_C INDFMINC Annual Family Income 10122 158 FALSE 16 FALSE 10122 158 82136 FALSE TRUE FALSE
23 DEMO_C INDFMPIR Family PIR 10122 587 TRUE 3 FALSE 10122 587 81024 TRUE FALSE FALSE
24 DEMO_C RIDEXPRG Pregnancy Status at Exam - Recode 10122 6992 FALSE 4 FALSE 10122 6992 81376 FALSE TRUE FALSE
25 DEMO_C DMDHRGND HH Ref Person Gender 10122 1 FALSE 3 FALSE 10122 1 81136 FALSE TRUE FALSE
26 DEMO_C DMDHRAGE HH Ref Person Age 10122 1 TRUE 3 FALSE 10122 1 81024 TRUE FALSE FALSE
27 DEMO_C DMDHRBRN HH Ref Person Country of Birth 10122 354 FALSE 6 FALSE 10122 354 81248 FALSE TRUE FALSE
28 DEMO_C DMDHREDU HH Ref Person Education Level 10122 354 FALSE 8 FALSE 10122 354 81592 FALSE TRUE FALSE
29 DEMO_C DMDHRMAR HH Ref Person Marital Status 10122 289 FALSE 9 FALSE 10122 289 81528 FALSE TRUE FALSE
30 DEMO_C DMDHSEDU HH Ref Person's Spouse Education Level 10122 4741 FALSE 8 FALSE 10122 4741 81592 FALSE TRUE FALSE
31 DEMO_C SIALANG Language of SP Interview 10122 0 FALSE 3 FALSE 10122 0 81136 FALSE TRUE FALSE
32 DEMO_C SIAPROXY Proxy used in SP Interview? 10122 0 FALSE 3 FALSE 10122 0 81136 FALSE TRUE FALSE
33 DEMO_C SIAINTRP Interpreter used in SP Interview? 10122 0 FALSE 3 FALSE 10122 0 81136 FALSE TRUE FALSE
34 DEMO_C FIALANG Language of Family Interview 10122 139 FALSE 3 FALSE 10122 139 81136 FALSE TRUE FALSE
35 DEMO_C FIAPROXY Proxy used in Family Interview? 10122 139 FALSE 3 FALSE 10122 139 81136 FALSE TRUE FALSE
36 DEMO_C FIAINTRP Interpreter used in Family Interview? 10122 139 FALSE 3 FALSE 10122 139 81136 FALSE TRUE FALSE
37 DEMO_C MIALANG Language of MEC Interview 10122 3689 FALSE 3 FALSE 10122 3689 81136 FALSE TRUE FALSE
38 DEMO_C MIAPROXY Proxy used in MEC Interview? 10122 3689 FALSE 3 FALSE 10122 3689 81136 FALSE TRUE FALSE
39 DEMO_C MIAINTRP Interpreter used in MEC Interview? 10122 3689 FALSE 3 FALSE 10122 3689 81136 FALSE TRUE FALSE
40 DEMO_C AIALANG Language of ACASI Interview 10122 5413 FALSE 3 FALSE 10122 5413 81136 FALSE TRUE FALSE
41 DEMO_C WTINT2YR Full Sample 2 Year Interview Weight 10122 0 TRUE 2 FALSE 10122 0 81024 TRUE FALSE FALSE
42 DEMO_C WTMEC2YR Full Sample 2 Year MEC Exam Weight 10122 0 TRUE 2 FALSE 10122 0 81024 TRUE FALSE FALSE
43 DEMO_C SDMVPSU Masked Variance Pseudo-PSU 10122 0 TRUE 2 FALSE 10122 0 81024 TRUE FALSE FALSE
44 DEMO_C SDMVSTRA Masked Variance Pseudo-Stratum 10122 0 TRUE 2 FALSE 10122 0 81024 TRUE FALSE FALSE
This collects information from the codebook and supplements it with information from the actual data, such as the number of non-missing observations. Combining such information across all available tables is generally time-consuming, but is considerably easier when the data are available in the form of a database.
Summarizing variables using the SQL database
Basic information about all tables can be obtained using
nhanesManifest("public"), but also from the database using a SQL
query as follows.
tableDesc <- nhanesQuery("select * from Metadata.QuestionnaireDescriptions")
subset(tableDesc, BeginYear == 1999, select = -c(DocFile, DataFile)) |> head(10)
Description TableName BeginYear EndYear DataGroup UseConstraints DatePublished
1 Acculturation ACQ 1999 2000 Questionnaire None June 2002
11 Analgesic Pain Relievers RXQ_ANA 1999 2000 Questionnaire None June 2002
12 Anti-Mullerian Hormone (AMH) & Inhibin-B (Surplus) SSAMH_A 1999 2000 Laboratory None Updated April 2022
26 Balance BAQ 1999 2000 Questionnaire None June 2002
44 Cardiovascular Fitness CVX 1999 2000 Examination None June 2004
49 Cholesterol - LDL & Triglycerides LAB13AM 1999 2000 Laboratory None Updated March 2007
69 Current Health Status HSQ 1999 2000 Questionnaire None June 2002
74 Cytomegalovirus Antibodies - Serum (Surplus) SSCMV_A 1999 2000 Laboratory None Updated April 2022
78 Dermatology DEQ 1999 2000 Questionnaire None June 2002
104 Dietary Supplement Use 30-Day - File 1, Supplement Counts DSQFILE1 1999 2000 Dietary None Updated July 2009
Having a searchable list of these table descriptions can by itself be useful. Such a table is available here, and is created using this R script. Instead of having one row per table, this list combines multiple cycles for the same base table name and description, and includes the dimensions of each dataset.
We can now apply the nhanesTableSummary() function on each of these
tables. The essential code for this, accounting for the possibility of
errors, is
table_summary <- function(x) {
try(nhanesTableSummary(x, use = "both"), silent = TRUE)
}
table_details <- sapply(sort(tablemf$TableName), table_summary, simplify = FALSE)
nhanesVarSummary <-
table_details[!sapply(table_details, inherits, "try-error")] |>
do.call(what = rbind)
This results in a fairly large data frame.
str(nhanesVarSummary)
'data.frame': 46194 obs. of 14 variables:
$ table : chr "AA_H" "AA_H" "AA_H" "AA_H" ...
$ varname : chr "SEQN" "WTSA2YR" "URX1NP" "URD1NPLC" ...
$ label : chr "Respondent sequence number" "Subsample A Weights" "1-Aminonaphthalene urine (pg/mL)" "1-Aminonaphthalene urine Comment Code" ...
$ nobs_cb : int NA 2755 2755 2755 2755 2755 2755 2755 2755 2755 ...
$ na_cb : num NA 0 277 277 267 267 263 263 423 423 ...
$ has_range: logi NA TRUE TRUE FALSE TRUE FALSE ...
$ nlevels : int NA 3 2 4 2 4 2 4 2 4 ...
$ skip : logi NA FALSE FALSE FALSE FALSE FALSE ...
$ nobs_data: int 2755 2755 2755 2755 2755 2755 2755 2755 2755 2755 ...
$ na_data : int 0 0 277 277 267 267 263 263 423 423 ...
$ size : num 11072 22088 22088 22248 22088 ...
$ num : logi TRUE TRUE TRUE FALSE TRUE FALSE ...
$ cat : logi FALSE FALSE FALSE TRUE FALSE TRUE ...
$ unique : logi TRUE FALSE FALSE FALSE FALSE FALSE ...
However, as variables are repeated for each cycle, the number of unique variables is considerably smaller, especially if we split them according to the component or data group.
rownames(tableDesc) <- tableDesc$TableName
nhanesVarSummary$DataGroup <- tableDesc[nhanesVarSummary$table, "DataGroup"]
unique(nhanesVarSummary[c("varname", "DataGroup")]) |>
xtabs(~ DataGroup, data = _)
DataGroup
Demographics Dietary Examination Laboratory Questionnaire
175 1182 4791 2766 3373
Having variable-level information in a data frame like this allows us to perform interactive searches in R quite easily. For example, we could search for variables related to blood pressure or hypertension recorded in the third cycle as follows.
nhanesVarSummary <- within(nhanesVarSummary, label <- tolower(label))
subset(nhanesVarSummary, endsWith(table, "_C") &
(grepl("hypertension", label) |
grepl("blood pressure", label)))
table varname label nobs_cb na_cb has_range nlevels skip nobs_data na_data size num cat unique DataGroup
8550 BPQ_C BPQ010 last blood pressure reading by doctor 6213 0 FALSE 8 TRUE 6213 0 50192 FALSE TRUE FALSE Questionnaire
8551 BPQ_C BPQ020 ever told you had high blood pressure 6213 75 FALSE 5 TRUE 6213 75 49928 FALSE TRUE FALSE Questionnaire
8552 BPQ_C BPQ030 told had high blood pressure - 2+ times 6213 4412 FALSE 5 FALSE 6213 4412 49928 FALSE TRUE FALSE Questionnaire
8553 BPQ_C BPQ040A taking prescription for hypertension 6213 4412 FALSE 5 FALSE 6213 4412 49928 FALSE TRUE FALSE Questionnaire
8554 BPQ_C BPQ040B told to control weight for hypertension 6213 4412 FALSE 5 FALSE 6213 4412 49928 FALSE TRUE FALSE Questionnaire
8555 BPQ_C BPQ040C told to reduce sodium for hypertension 6213 4412 FALSE 5 FALSE 6213 4412 49928 FALSE TRUE FALSE Questionnaire
8556 BPQ_C BPQ040D told to exercise more for hypertension 6213 4412 FALSE 5 FALSE 6213 4412 49928 FALSE TRUE FALSE Questionnaire
8557 BPQ_C BPQ040E told to reduce alcohol for hypertension 6213 4412 FALSE 5 FALSE 6213 4412 49928 FALSE TRUE FALSE Questionnaire
8558 BPQ_C BPQ040F told to do other things for hypertension 6213 4412 FALSE 5 FALSE 6213 4412 49928 FALSE TRUE FALSE Questionnaire
8559 BPQ_C BPQ043A told to stop smoking for hypertension 6213 6146 FALSE 4 FALSE 6213 6146 49816 FALSE TRUE FALSE Questionnaire
8753 BPX_C PEASCST1 blood pressure status 9643 0 FALSE 4 FALSE 9643 0 77376 FALSE TRUE FALSE Examination
8754 BPX_C PEASCTM1 blood pressure time in seconds 9643 306 TRUE 2 FALSE 9643 306 77192 TRUE FALSE FALSE Examination
8755 BPX_C PEASCCT1 blood pressure comment 9643 9194 FALSE 10 FALSE 9643 9194 77856 FALSE TRUE FALSE Examination
11522 CVX_C CVAARM arm selected for blood pressure monitor 4663 1451 FALSE 4 FALSE 4663 1451 37464 FALSE TRUE FALSE Examination
11523 CVX_C CVACUFF cuff size for blood pressure monitor 4663 1451 FALSE 4 FALSE 4663 1451 37528 FALSE TRUE FALSE Examination
29806 MCQ_C MCQ250F blood relatives w/hypertension/stroke 9645 4605 FALSE 5 TRUE 9645 4605 77384 FALSE TRUE FALSE Questionnaire
29844 MCQ_C MCQ260FA blood relative-hypertension-mother 9645 8974 FALSE 4 TRUE 9645 8974 77328 FALSE TRUE FALSE Questionnaire
29845 MCQ_C MCQ260FB blood relative-hypertension-father 9645 9160 FALSE 2 TRUE 9645 9160 77264 FALSE TRUE FALSE Questionnaire
29846 MCQ_C MCQ260FC blood relative-hypertension-mom's mother 9645 9468 FALSE 2 TRUE 9645 9468 77272 FALSE TRUE FALSE Questionnaire
29847 MCQ_C MCQ260FD blood relative-hypertension-mom's father 9645 9543 FALSE 2 TRUE 9645 9543 77272 FALSE TRUE FALSE Questionnaire
29848 MCQ_C MCQ260FE blood relative-hypertension-dad's mother 9645 9566 FALSE 2 TRUE 9645 9566 77272 FALSE TRUE FALSE Questionnaire
29849 MCQ_C MCQ260FF blood relative-hypertension-dad's father 9645 9582 FALSE 2 TRUE 9645 9582 77272 FALSE TRUE FALSE Questionnaire
29850 MCQ_C MCQ260FG blood relative-hypertension-brother 9645 9445 FALSE 2 TRUE 9645 9445 77264 FALSE TRUE FALSE Questionnaire
29851 MCQ_C MCQ260FH blood relative-hypertension-sister 9645 9445 FALSE 2 TRUE 9645 9445 77264 FALSE TRUE FALSE Questionnaire
29852 MCQ_C MCQ260FI blood relative-hypertension-other 9645 9475 FALSE 2 TRUE 9645 9475 77264 FALSE TRUE FALSE Questionnaire
38091 PFQ_C PFD069J hypertension or high blood pressuredays 9645 9475 TRUE 5 FALSE 9645 9475 77208 TRUE FALSE FALSE Questionnaire
As with the table descriptions, information about these variables can also be summarized and presented as searchable HTML tables. Sample code for doing this is available here, producing the following tables, grouped by data group to keep the table sizes moderate.