Create STEPS analysis configuration — steps

Builds a configuration list that specifies data paths, design variables, and report parameters for the STEPS pipeline.

steps_config(
  data_path,
  country_name = "Country Name",
  survey_year = 2024,
  age_min = 18,
  age_max = 69,
  weight_var = "wt_final",
  strata_var = "stratum",
  cluster_var = "psu",
  bp_sbp_threshold = 140,
  bp_dbp_threshold = 90,
  bmi_overweight = 25,
  bmi_obese = 30,
  glucose_threshold = 7,
  glucose_impaired_threshold = 6.1,
  chol_threshold = 5
)

Arguments

data_path: Path to raw STEPS data file (CSV or Excel).
country_name: Country name for reports (default "Country Name").
survey_year: Survey year (default 2024).
age_min: Minimum age (default 18).
age_max: Maximum age (default 69).
weight_var: Weight variable name (default "wt_final", set NULL if none).
strata_var: Strata variable name (default "stratum", set NULL if none).
cluster_var: Cluster variable name (default "psu", set NULL if none).
bp_sbp_threshold: SBP threshold for raised BP (default 140).
bp_dbp_threshold: DBP threshold for raised BP (default 90).
bmi_overweight: BMI threshold for overweight (default 25.0).
bmi_obese: BMI threshold for obesity (default 30.0).
glucose_threshold: Fasting glucose threshold in mmol/L (default 7.0).
glucose_impaired_threshold: Impaired fasting glucose threshold in mmol/L (default 6.1).
chol_threshold: Total cholesterol threshold in mmol/L (default 5.0).

Value

A list with elements:

data_path: Input file path
country_name: Country name
survey_year: Survey year
age_min, age_max: Age range
weight_var, strata_var, cluster_var: Design variable names
Threshold parameters for BP, BMI, glucose, cholesterol

Examples

if (FALSE) { # \dontrun{
  cfg <- steps_config("data/steps_2023.csv", "Senegal", 2023)
  cfg <- steps_config("data/steps.csv", "Mongolia", 2019,
                      bp_sbp_threshold = 130, bp_dbp_threshold = 80)
} # }