Parse NHANES Linked Mortality Files into data frames

Reads the fixed-width .dat files (downloading them first if needed) and returns a named list of data frames, one per cycle.

Usage

nhanes_mortality_parse(cycles = NULL, refresh = FALSE, download = TRUE)

Arguments

cycles

Character vector of cycle labels. Defaults to all available.

refresh

Logical. Re-parse even if a cached RDS exists? Default FALSE.

download

Logical. Auto-download missing .dat files? Default TRUE.

Value

A named list of data frames. Each data frame contains:

SEQN

Respondent sequence number (join key to NHANES data).

ELIGSTAT

Eligibility: 1=eligible; 2=under 18; 3=insufficient data.

MORTSTAT

Vital status: 0=assumed alive; 1=assumed deceased.

UCOD_LEADING

Underlying cause of death (11-category ICD-10 recode).

DIABETES

Diabetes mentioned on death certificate (1=yes).

HYPERTEN

Hypertension mentioned on death certificate (1=yes).

PERMTH_INT

Months of follow-up from interview date.

PERMTH_EXM

Months of follow-up from examination date.

Details

Variable labels are attached as the "label" attribute on each column, following the haven/labelled convention.

Note

For select records, PERMTH_INT, PERMTH_EXM, and UCOD_LEADING contain synthetic (perturbed) values introduced by CDC to reduce re-identification risk. MORTSTAT and ELIGSTAT are not perturbed.

See also

nhanes_mortality_download() to download the raw .dat files; nhanes_mortality_link() to join parsed mortality data onto an analytic dataset.

Examples

# \donttest{
lmf <- nhanes_mortality_parse(c("2015-2016", "2017-2018"))
lmf[["2015-2016"]]
#> # A tibble: 9,971 × 11
#>     SEQN ELIGSTAT MORTSTAT UCOD_LEADING DIABETES HYPERTEN PERMTH_INT PERMTH_EXM
#>    <int>    <int>    <int> <chr>           <int>    <int>      <dbl>      <dbl>
#>  1 83732        1        0 NA                 NA       NA         43         42
#>  2 83733        1        0 NA                 NA       NA         41         41
#>  3 83734        1        0 NA                 NA       NA         49         48
#>  4 83735        1        0 NA                 NA       NA         49         48
#>  5 83736        1        0 NA                 NA       NA         56         56
#>  6 83737        1        0 NA                 NA       NA         49         47
#>  7 83738        2       NA NA                 NA       NA         NA         NA
#>  8 83739        2       NA NA                 NA       NA         NA         NA
#>  9 83740        2       NA NA                 NA       NA         NA         NA
#> 10 83741        1        0 NA                 NA       NA         49         48
#> # ℹ 9,961 more rows
#> # ℹ 3 more variables: WAGEGRP <int>, EDUCAT <int>, cycle <chr>
# }