find_anaemia: Determine anaemia status for various population groups

In nutriverse/nutricheckr: Tools for Nutrition Assessment and Analysis

Determine anaemia status for various population groups

Description

This set of functions identifies anaemia in both individual-specific target groups and the overall population, which includes all target groups' functions.

Usage

find_anaemia_u5(x)

find_anaemia_5to11(x)

find_anaemia_12to14(x)

find_anaemia_np_women(x)

find_anaemia_pregnant(x)

find_anaemia_men(x)

find_anaemia(
  df,
  group = c("u5", "5to11", "12to14", "np_women", "pregnant", "men"),
  hb = NULL,
  add = TRUE
)

Arguments

x	A numeric vector containing haemoglobin values in grams per litre (g/L) unit format for a specific population group. The following table provides the specific command based on the respective population group. Population Command Children 6-59 months of age find_anaemia_u5 Children 5-11 years of age find_anaemia_5to11 Children 12-14 years of age find_anaemia_11to14 Non-pregnant women - 15 years and above find_anaemia_np_women Pregnant women find_anaemia_pregnant Men - 15 years and above find_anaemia_men
df	A data.frame of survey dataset with information on haemoglobin value and information on population group to which the sample comes from.
group	A character value specifying the population target group to identify anaemia from. The function can determine the anaemia status for the following groups: Population Short-form Children 6-59 months of age "u5" Children 5-11 years of age "5to11" Children 12-14 years of age "11to14" Non-pregnant women - 15 years and above "np_women" Pregnant women "pregnant" Men - 15 years and above "men" The short-form is used in the function to indicate which population group to find anaemia from.
hb	A characater value specifying the variable name in df containing the sample observation's haemoglobin level. Note that the haemoglobin values should be recorded in grams per liter (g/L) units. If NULL (default), will attempt to find variable in df that is likely to hold the haemoglobin levels information by searching for most common variable names used for haemoglobin. If none can be found, will issue an error that appropriate haemoglobin values cannot be found.
add	Logical. Should anaemia classification results be added to df? Default to TRUE which will add a variable named anaemia_status to df.

Value

If add is TRUE, a data frame with the same structure as df and with a new variable anaemia_status otherise a vector of class factor. The new variable or the resulting vector provides anaemia categories to each observation: no anaemia, mild anaemia, moderate anaemia, and severe anaemia. The following table explains the cut-off points to classify each observation accordingly:

Population	Mild	Moderate	Severe
Children 6-59 months of age	100 - 109	70 - 99	< 70
Children 5-11 years of age	110 - 114	80 - 109	< 80
Children 12-14 years of age	110 - 119	80 - 109	< 80
Non-pregnant women
15 years and above	110 - 119	80 - 109	< 80
Pregnant women	100 - 109	70 - 99	< 70
Men
15 years and above	110 - 129	80 - 109	< 80

Author(s)

Nicholus Tint Zaw

Examples

 # Create testing data
 x <- runif(20, min = 60, max = 130)

 hb <- runif(50, min = 60, max = 130)
 gender <- rep(c("male", "female"), each = 25)

 df <- data.frame(gender, hb)

 # For individual target group function;
  find_anaemia_u5(x)          # U5 Children
  find_anaemia_5to11(x)       # Children 5 - 11 years
  find_anaemia_12to14(x)      # Children 12 - 14 years
  find_anaemia_np_women(x)    # Non-pregnant Women
  find_anaemia_pregnant(x)    # Pregnant Women
  find_anaemia_men(x)         # Men


 # For overall population function;
  find_anaemia(df = df,
               hb = "hb",
               add = TRUE)

nutriverse/nutricheckr documentation built on April 1, 2022, 7:44 p.m.