Skip to contents

Calculate masculinity index and maternal mortality from a mortAAR life table list

Source: R/masculinity_maternalmortality.R
lt.sexrelation.Rd

The proportional relation between adult males and females (= Masculinity index) is interesting for a number of reasons: (1) it can point to basic problems in the datasets in that, say, one sex is grossly over- or underrepresented (Herrmann et al. 1990, 310). (2) it may hint towards cultural reasons like sex- specific mobility.
Maternal mortality is a basic indicator for the health system of a given population. Maternal mortality is defined as dying during pregnancy or within the first 42 days after birth due to complications. Recently, McFadden and colleagues 2020 have provided an updated formula to calculate it from archaeological data.

Usage

lt.sexrelation(females, males)

Arguments

females

an object of class mortaar_life_table for females

males

an object of class mortaar_life_table for males

Value

Output of masculinity index and maternal mortality.

  • Masculinity index.

    \(MI = D>=15male / D>=15female\)

  • Maternal mortality.

    \(333.33 * (D20-24female / D20-24male) * MI - 76.07\)

Details

The Masculinity index (MI) is defined for juvenile and older individuals. Note that with a higher mortality rate of adult females, an MI < 100 does not necessarily speak for an unbalanced MI in life.
Maternal mortality is calculated according to the formula provided by McFadden & Oxenham 2019 in the updated version of McFadden et al. 2020. McFadden and Oxenham show that with modern data a very high correlation is achieved by only comparing the absolute numbers of the age group 20 to 24. This has the additional advantage that for this age group anthropological aging methods are reasonable exact.

References

herrmann_prahistorische_1990mortAAR

mcfadden_oxenham_2019mortAAR

mcfadden_et_al_2020mortAAR

Examples

# Calculate Masculinity index and maternal mortality from Nitra
# dataset.
nitra_prep <- prep.life.table(nitra, group="sex", agebeg = "age_start", ageend = "age_end")
nitra_life <- life.table(nitra_prep)
lt.sexrelation(nitra_life$f, nitra_life$m)
#>      method  value                           description
#> 1        MI   0.67                     Masculinity index
#> 2 Ratio_F_M   2.36 Ratio of females to males aged 20--24
#> 3      MMR1 449.00 Maternal mortality per 100,000 births
#> 4      MMR2   4.49   Maternal mortality per 1,000 births