Diet scoring in Life’s Essential 8

Where the diet measures came from

How diet scores become LE8 points

The AHA advisory uses modified MEPA for individual assessment and DASH or HEI-2015 for population assessment. These are alternative ways to score the same LE8 diet component. They do not add extra components to LE8.

A raw diet score, also called an index, is the total before conversion to LE8 points.

For DASH and HEI-2015, a percentile describes a score’s position in the reference population. For example, the 75th percentile marks the upper quarter of that distribution. The advisory assigns LE8 points as follows:

These bands come from the AHA LE8 advisory, Table 1. A raw HEI-2015 score of 70 is therefore different from the 70th percentile or an LE8 diet score of 70. The reference determines which LE8 band contains that raw score.

The resulting le8_diet_score contributes to the LE8 composite in the same way as the other seven components. score_le8() averages available component scores when at least min_components are present; the default is seven.

What the packaged reference represents

The advisory initially recommends NHANES 2015-2018 as the reference for population diet scoring. NHANES is the National Health and Nutrition Examination Survey. essential8 includes references derived from those survey years and the matching USDA Food Patterns Equivalents Database (FPED), which converts foods into common food-group units.

The package references describe 8,241 adults aged 20 or older, excluding known pregnancy, with two reliable dietary recalls and complete required inputs. The builder averages the same two days’ foods, nutrients, and energy before scoring. It uses the combined dietary weight (WTDR2D / 2), survey strata, and sampling units to calculate weighted cutpoints: the score values that mark the percentile boundaries.

These are estimates calculated for this package, rather than cutpoint tables published by the AHA. They describe scores based on two recalls, rather than each person’s long-term usual intake. Scoring uses the stored cutpoints; it does not download data or rank the people in your input against each other.

The DASH reference uses the package’s specific FPED adaptation, essential8_fung_fped_v1. It uses pooled intake quintiles across sexes and the food definitions listed below. An existing DASH score must match these definitions to use this reference. HEI-2015 inputs should also match the reference’s method of combining recalls.

Choose the inputs you have

Use one diet method and one type of diet input per call:

The examples use dplyr and the native pipe (|>, available in R 4.1+). We start with two packaged example adults so the other LE8 components are available. All records and added diet values are illustrative. The selected method ignores the unused MEPA columns in these records.

library(essential8)
library(dplyr)

example_file <- system.file(
  "extdata", "le8-adult-example.csv", package = "essential8"
)

adults <- read.csv(example_file) |>
  as_tibble() |>
  slice_head(n = 2) |>
  select(-starts_with("expected_")) |>
  mutate(id = c("adult_1", "adult_2"))

adults |>
  mutate(hei2015 = c(45, 70)) |>
  score_le8(diet_method = "hei2015", reference = "nhanes_2015_2018") |>
  select(id, hei2015, le8_diet_score)
#> # A tibble: 2 × 3
#>   id      hei2015 le8_diet_score
#>   <chr>     <dbl>          <dbl>
#> 1 adult_1      45             25
#> 2 adult_2      70             80

adults |>
  mutate(diet_value = c(35, 98)) |>
  score_le8(diet_method = "dash") |>
  select(id, diet_value, le8_diet_score)
#> # A tibble: 2 × 3
#>   id      diet_value le8_diet_score
#>   <chr>        <dbl>          <dbl>
#> 1 adult_1         35             25
#> 2 adult_2         98            100

Calculate DASH from raw inputs

The Fung-style score compares each of eight intakes with reference quintiles: five intake groups, each containing about one fifth of the reference population. Fruit, vegetables, nuts and legumes, whole grains, and low-fat dairy earn 1-5 points as intake increases. Sodium, red and processed meat, and sweetened beverages earn 5-1 points. The eight scores sum to dash_total.

There are two population comparisons here: intake quintiles create the DASH total, then total-score cutpoints assign the LE8 band. Both come from the packaged reference by default.

dash_inputs <- tibble(
  dash_fruits = c(1, 2),
  dash_vegetables = c(2, 3),
  dash_nuts_and_legumes = c(0.5, 1),
  dash_whole_grains = c(1, 2),
  dash_low_fat_dairy = c(1, 2),
  dash_sodium = c(3000, 2000),
  dash_red_and_processed_meat = c(1, 0.5),
  dash_sweetened_beverages = c(1, 0),
  dash_energy_kcal = c(2000, 2000)
)

adults |>
  bind_cols(dash_inputs) |>
  score_le8(diet_method = "dash", reference = "nhanes_2015_2018") |>
  select(id, dash_total, le8_diet_score)
#> # A tibble: 2 × 3
#>   id      dash_total le8_diet_score
#>   <chr>        <int>          <dbl>
#> 1 adult_1         27             80
#> 2 adult_2         36            100

Calculate HEI-2015 from raw inputs

HEI-2015 uses fixed nutrition standards to calculate its raw score. Its nine adequacy components cover fruit, vegetables, whole grains, dairy, protein foods, and the balance of unsaturated to saturated fats. Its four moderation components cover refined grains, sodium, added sugars, and saturated fats. Each component contributes up to 5 or 10 points, for a maximum total of 100. See the NCI scoring standards.

Scores between the minimum and maximum standards are proportional. For example, 0.8 cup equivalents of total fruit per 1,000 kcal earns all 5 fruit points; 0.4 earns 2.5. Higher intake beyond a component’s maximum standard does not add points. After summing the 13 components, the package compares the total with the reference to assign LE8 points.

hei_inputs <- tibble(
  hei2015_energy_kcal = c(2000, 2000),
  hei2015_total_fruits = c(1, 2),
  hei2015_whole_fruits = c(0.5, 1),
  hei2015_total_vegetables = c(2, 3),
  hei2015_greens_and_beans = c(0.2, 0.5),
  hei2015_whole_grains = c(1, 3),
  hei2015_dairy = c(2, 3),
  hei2015_total_protein_foods = c(5, 5),
  hei2015_seafood_and_plant_proteins = c(1, 2),
  hei2015_polyunsaturated_fat = c(15, 20),
  hei2015_monounsaturated_fat = c(20, 25),
  hei2015_saturated_fat = c(25, 15),
  hei2015_refined_grains = c(5, 3),
  hei2015_sodium = c(3000, 2000),
  hei2015_added_sugars = c(12, 8)
)

adults |>
  bind_cols(hei_inputs) |>
  score_le8(diet_method = "hei2015", reference = "nhanes_2015_2018") |>
  select(id, hei2015_total, le8_diet_score)
#> # A tibble: 2 × 3
#>   id      hei2015_total le8_diet_score
#>   <chr>           <dbl>          <dbl>
#> 1 adult_1          61.1             50
#> 2 adult_2         100              100

Use a different reference when needed

For existing scores or raw HEI-2015 inputs, diet_reference() defines total-score cutpoints at the 25th, 50th, 75th, and 95th percentiles:

# Teaching values only; derive real cutpoints from a suitable population.
custom <- diet_reference(
  p25 = 40, p50 = 55, p75 = 65, p95 = 80,
  method = "hei2015", label = "Example reference"
)

adults |>
  mutate(hei2015 = c(45, 70)) |>
  score_le8(diet_method = "hei2015", reference = custom) |>
  select(id, hei2015, le8_diet_score)
#> # A tibble: 2 × 3
#>   id      hei2015 le8_diet_score
#>   <chr>     <dbl>          <dbl>
#> 1 adult_1      45             25
#> 2 adult_2      70             80

A reference must match the diet method, score definition, and population. For raw DASH with a different definition, supply dash_cutpoints: a list with four intake-quintile cutpoints for each of the eight fields and four total-score cutpoints in total. A reference containing only total-score cutpoints cannot define the intake quintiles.

Explicit dash_cutpoints or hei2015_cutpoints bypass reference. With explicit DASH cutpoints, input units must match those used to derive the cutpoints. Energy is not required and sodium is not standardized. For raw HEI-2015, hei2015_cutpoints is a vector of four total-score cutpoints.

Tied cutpoints are allowed. Equality with an intake-quintile cutpoint stays in the lower quintile; equality with a total-score cutpoint enters the higher LE8 band. The four total cutpoints identify bands, not an exact percentile for every possible score.

Practical details

• Choose one method per call. Do not combine raw inputs with an existing index or observed percentile. An entirely missing diet_value column is ignored.
• For custom column names, use mappings such as dash_columns = c(fruits = "fruit_intake", energy_kcal = "calories"). hei2015_columns works the same way. Names are matched without regard to case.
• Every raw input column must be present once raw scoring is selected; an absent column is an error, so a misspelled name cannot silently produce missing diet scores. Missing values within a column are allowed.
• Missing inputs stay missing. A raw total requires all its components; min_components controls the LE8 composite, not a partial diet total. Available HEI component scores are still returned.

See ?score_le8 for the full input rules. The repository’s reference documentation records the FPED conversions, food-code lists, sample selection, and survey methods. Its build script and source manifest record how the packaged references were produced.