Getting Started with nhanesR

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What nhanesR does

nhanesR provides a structured workflow for downloading, caching, harmonizing, and analyzing data from the National Health and Nutrition Examination Survey (NHANES), including linkage to the NCHS Public-Use Linked Mortality Files (LMF).

The package handles the main friction points in working with NHANES:

File names change across cycles (e.g. total cholesterol: LAB13 -> L13_B -> L13_C -> TCHOL_D onward).
Variable names change across cycles (e.g. HDL: LBDHDL -> LBXHDD -> LBDHDD).
SI-unit duplicates appear in the same file alongside conventional-unit columns.
Mortality linkage requires fixed-width file parsing and SEQN joining across cycles.
Lab measurements are restricted by age: total cholesterol is measured in participants aged 6 and older; fasting analytes (triglycerides, glucose, insulin) require age 12 and older. Combined with the roughly 10-15% of enrolled participants who complete only the household interview and never attend the Mobile Examination Center (MEC), approximately 35-40% of participants in the DEMO file will have no lab measurements. This is expected by design, not data loss. The LMF further restricts mortality follow-up to participants aged 18 or older at the time of the survey (ELIGSTAT = 1); nhanes_survival_prep() removes ineligible participants automatically.

Installation

# Install from GitHub (includes vignettes)
remotes::install_github("dwinsemius/nhanesR",
                        build_vignettes = TRUE,
                        force           = TRUE)
library(nhanesR)

Setup and options

Three options control nhanesR behavior. The package sets defaults at load time, but any option already defined in your .Rprofile takes precedence — nhanesR only sets an option if it is not already defined.

Option	Default	Purpose
`nhanesR.cache_dir`	`file.path(tempdir(), "nhanesR")`	Root path for all cached RDS and `.dat` files
`nhanesR.verbose`	`TRUE`	Print progress messages during downloads
`nhanesR.timeout`	`120L`	HTTP request timeout in seconds

Default cache location

By default, nhanesR caches files inside R’s session-temporary directory (tempdir()). This means no files are written to your home directory without your explicit consent, but downloaded files are not retained across R sessions. To keep a persistent cache — and avoid re-downloading on every session — set nhanesR.cache_dir in your ~/.Rprofile (see below).

Downloaded files are parsed, stored as RDS, and verified with an MD5 hash sidecar on every subsequent load. Re-downloading is skipped unless refresh = TRUE is passed.

Permanent configuration via `.Rprofile`

Add any of these lines to ~/.Rprofile to persist settings across sessions:

options(
  nhanesR.cache_dir = "/data/nhanes_cache",  # e.g. a shared server path
  nhanesR.verbose   = FALSE,                  # suppress progress messages
  nhanesR.timeout   = 300L                    # 5-minute timeout
)

Checking and changing settings interactively

nhanes_cache_dir()                        # view current cache path (tempdir-based by default)
nhanes_cache_dir("~/my_nhanes_cache")    # opt in to a persistent home-directory cache
options(nhanesR.verbose = FALSE)     # suppress messages for this session

Function map

Functions are organized below by workflow stage. Each entry links to the detailed help page (?function_name) and notes which functions it typically calls or is called by.

Stage 1 — Discovery

Function	Purpose	Leads to
`nhanes_cycles()`	List all continuous NHANES cycles with metadata (years, weight variable names, LMF availability)	`nhanes_manifest()`, `nhanes_download()`
`nhanes_manifest()`	List all data files available for a cycle and component; shows file codes, descriptions, and CDC URLs	`nhanes_download()`

# All cycles with metadata
nhanes_cycles()

# Extract cycle labels for use downstream
cycles <- nhanes_cycles()[["cycle"]]

# See what Laboratory files exist for a cycle
nhanes_manifest("2015-2016", "Laboratory")

Stage 2 — Variable search

Function	Purpose	Leads to
`nhanes_search_variables()`	Search the CDC variable catalog by keyword; returns one row per unique variable name (default) or one row per cycle	`nhanes_variable_map()`
`nhanes_variable_map()`	Wraps `nhanes_search_variables()` to produce a per-cycle lookup (`cycle`, `variable_name`, `file_name`) ready for download	`nhanes_download_analyte()`

# Summarized view — which variable codes match, and in how many cycles?
nhanes_search_variables("total cholesterol", component = "Laboratory")

# Per-cycle lookup — which file holds the analyte in each cycle?
nhanes_variable_map("total cholesterol")

# Use keep_vars to exclude false positives (e.g. urine vs. serum creatinine)
nhanes_variable_map("creatinine",
                    keep_vars = c("LBXSCR", "LBDSCR", "LB2SCR"))

Stage 3 — Download

Function	Purpose	Leads to
`nhanes_download()`	Download one or more files by exact CDC base code (e.g. `"DEMO"`, `"BPX"`). Use when file names are stable across cycles.	`nhanes_harmonize()`, `nhanes_stack()`, `nhanes_merge()`
`nhanes_download_analyte()`	Download by analyte keyword; uses the variable catalog to resolve the correct CDC filename per cycle automatically. Use when file names changed across cycles.	`nhanes_harmonize()`

cycles <- nhanes_cycles()[1:10, "cycle"]   # 1999-2018

# Demographics — always "DEMO"; nhanes_download() works fine
demo_list <- nhanes_download("DEMO", cycles)

# Total cholesterol — file name changed in 1999-2004; use download_analyte()
tchol_list <- nhanes_download_analyte("total cholesterol", cycles)

# Questionnaire variable with keep_vars to filter false positives
mi_list <- nhanes_download_analyte(
  "heart attack", cycles,
  component = "Questionnaire",
  keep_vars = c("MCQ160E", "MCQ160e")
)

Invalid file codes: if an unrecognized code is passed to nhanes_download(), CDC returns HTTP 200 with an HTML error page rather than a 404. nhanesR detects this via the Content-Type header and aborts with a message directing you to nhanes_manifest() to confirm the correct name.

Stage 4 — Harmonize and stack

Function	Purpose	Leads to
`nhanes_harmonize()`	Rename per-cycle variable codes to a single common name and row-bind into one data frame. Supports unit-based matching (e.g. `"mg/dL"`) or an explicit name mapping.	`nhanes_merge()`, `nhanes_mortality_link()`
`nhanes_stack()`	Row-bind a named list of per-cycle data frames, filling absent columns with `NA`. Called internally by `nhanes_harmonize()`.	`nhanes_merge()`, `nhanes_mortality_link()`
`nhanes_merge()`	Join two or more NHANES components by `SEQN` (and optionally `cycle`), with weight-variable guidance.	`nhanes_mortality_link()`

# Unit-based: finds the mg/dL column by its label attribute
tc <- nhanes_harmonize(tchol_list,
                       unit          = "mg/dL",
                       name          = "TC_mgdl",
                       label_pattern = "total cholesterol")

# Mapping-based: explicit old-name → new-name translation
mi <- nhanes_harmonize(mi_list,
                       mapping = c(MCQ160E = "MI_history",
                                   MCQ160e = "MI_history"))

# Stack demographics (no renaming needed)
demo <- nhanes_stack(demo_list)

# Merge components
analytic <- nhanes_merge(demo, tc, mi, by = c("SEQN", "cycle"))

Stage 5 — Mortality linkage

Function	Purpose	Leads to
`nhanes_lmf_cycles()`	Character vector of cycles that have a public-use LMF	`nhanes_mortality_link()`
`nhanes_mortality_download()`	Download raw `.dat` LMF files from CDC FTP (called automatically by other mortality functions)	`nhanes_mortality_parse()`
`nhanes_mortality_parse()`	Parse `.dat` files into a named list of data frames	`nhanes_mortality_link()`
`nhanes_mortality_link()`	Left-join LMF columns onto an analytic dataset by SEQN; handles multiple cycles automatically	`nhanes_survival_prep()`

# Cycles with a public-use LMF (NHANES 1999-2018 + NHANES III)
nhanes_lmf_cycles()

# Append mortality variables — download happens automatically
analytic_mort <- nhanes_mortality_link(analytic)

Stage 6 — Survival analysis preparation

Function	Purpose	Leads to
`nhanes_survival_prep()`	Remove ineligible participants (`ELIGSTAT != 1`), create `time` and `event` columns, optionally create `event_cause` for cause-specific mortality	Downstream `survival`/`survey` modeling
`nhanes_followup_summary()`	Report median follow-up, event rate, and maximum follow-up by cycle — useful for assessing asymmetric censoring	(diagnostic)
`nhanes_ucod_labels()`	Lookup table of ICD-10 recode codes and labels accepted by the `cause` argument of `nhanes_survival_prep()`	`nhanes_survival_prep()`

# All-cause mortality, time from exam visit
surv_data <- nhanes_survival_prep(analytic_mort,
                                  origin     = "exam",
                                  time_unit  = "years",
                                  weight_var = "WTMEC2YR")

# Check follow-up by cycle (note shrinking window near 2017-2018)
nhanes_followup_summary(surv_data)

# Cause-specific: what cause codes are available?
nhanes_ucod_labels()

# Cardiovascular mortality (code "001")
surv_cvd <- nhanes_survival_prep(analytic_mort,
                                 origin = "exam",
                                 cause  = "001",
                                 weight_var = "WTMEC2YR")

Cache management

Function	Purpose
`nhanes_cache_dir()`	View or change the local cache directory; see the Setup section above for the options that govern caching behavior

Typical workflow

nhanes_cycles()                    # 1. find available cycles
  └─ nhanes_manifest()             # 2. browse files in a cycle
  └─ nhanes_search_variables()     # 2. search variable catalog
       └─ nhanes_variable_map()    # 3. per-cycle file/variable lookup
            └─ nhanes_download_analyte()   # 4. download (resolves renames)
  └─ nhanes_download()             # 4. download stable-name files (e.g. DEMO)
       └─ nhanes_harmonize()       # 5. rename + stack
       └─ nhanes_stack()           # 5. stack without renaming
            └─ nhanes_merge()      # 6. join components by SEQN
                 └─ nhanes_mortality_link()    # 7. append LMF
                      └─ nhanes_survival_prep()  # 8. create time/event
                           └─ nhanes_followup_summary()  # 9. QC

Getting Started with nhanesR

What nhanesR does

Installation

Setup and options

Default cache location

Permanent configuration via .Rprofile

Checking and changing settings interactively

Function map

Stage 1 — Discovery

Stage 2 — Variable search

Stage 3 — Download

Stage 4 — Harmonize and stack

Stage 5 — Mortality linkage

Stage 6 — Survival analysis preparation

Cache management

Typical workflow

Further reading

Permanent configuration via `.Rprofile`