Help for package u5mr

Type:

Package

Title:

Under-Five Child Mortality Estimation

Version:

0.1.1

Date:

2021-09-08

Maintainer:

Myo Minn Oo <dr.myominnoo@gmail.com>

Description:

Contains functions for calculating under-five child mortality estimates using the Trussell version of the Brass method (United Nations (1990) https://www.un.org/en/development/desa/population/publications/pdf/mortality/stepguide_childmort.pdf and United Nations (1983) https://www.un.org/en/development/desa/population/publications/pdf/mortality/stepguide_childmort.pdf) as well as applying the cohort-derived methods by Rajaratnam and colleagues (Rajaratnam JK, Tran LN, Lopez AD, Murray CJL (2010) "Measuring Under-Five Mortality: Validation of New Low-Cost Methods" <doi:10.1371/journal.pmed.1000253>).

License:

GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]

Encoding:

UTF-8

LazyData:

true

LazyDataCompression:

bzip2

Depends:

R(≥ 4.0.0)

URL:

https://github.com/myominnoo/u5mr

BugReports:

https://github.com/myominnoo/u5mr/issues

Suggests:

knitr, rmarkdown

RoxygenNote:

7.1.1

Language:

en-US

Imports:

lifecycle

NeedsCompilation:

Packaged:

2021-09-08 16:28:02 UTC; minnmy

Author:

Myo Minn Oo

[aut, cre]

Repository:

CRAN

Date/Publication:

2021-09-09 09:50:02 UTC

Bangladesh 1974

Description

The data gathered by the 1974 Bangladesh Retrospective Survey of Fertility and Mortality can be used to demonstrate the estimation of child mortality from summary birth histories using the Trussell version of the BRASS method and the Coale-Demeny model life tables coale_demeny_ltm.

Usage

data(bangladesh)

Format

A data frame

Details

extracted from Display 6 on page 28 and Display 7 on page 29.

References

United Nations Population Studies (1990) Step-by-Step Guide to the Estimation of Child Mortality No.107:1-83 (United Nations)

Aggregated summary birth histories derived from microdata

Description

Fake summary data used to demonstrate the application of Cohort-derived and Period-derived methods developed by Rajaratnam et al in 2010.

Usage

data(cambodia)

Format

A data frame

Details

## codes used to derive the dataset `cambodia`

## install.packages("tidyverse", dependencies = TRUE)
## install.packages("devtools", dependencies = TRUE)
## devtools::install_github("myominnoo/mStats")

library(tidyverse)
library(mStats)
data(microdata)
cambodia <- microdata %>%
  filter(sex == 2) %>%
  filter(age >= 15 & age < 50) %>%
  egen(age, seq(15, 45, 5), new_var = "agegroup") %>%
  generate(n, 1 * wtper) %>%
  replace(ceb, ceb * wtper) %>%
  replace(cd, cd * wtper) %>%
  group_by(iso3, svdate, agegroup) %>%
  summarise(women = sum(n),
            child_born = sum(ceb),
            child_dead = sum(cd)) %>%
  rename(agegrp = agegroup) %>%
  data.frame()

Source

PLoS MEDICINE

References

Rajaratnam JK, Tran LN, Lopez AD, Murray CJL (2010) Measuring Under-Five Mortality: Validation of New Low-Cost Methods. PLOS Medicine 7(4): e1000253. (doi: 10.1371/journal.pmed.100025310.1371/journal.pmed.1000253)

Coale-Demeny Model Life Tables

Description

The Coale-Demeny life tables consist of four sets of models, each representing a distinct mortality pattern. Each model is arranged in terms of 25 mortality levels, associated with different expectations of life at birth for females in such a way that e0 of 20 years corresponds to level 1 and e0 of 80 years corresponds to level 25.

Usage

data(coale_demeny_ltm)

Format

An object of class "list"; consist of four data.frame for male, female and ⁠both sexes⁠.

Details

The four underlying mortality patterns of the Coale-Demeny models are called "North", "South", "East" and "West". They were identified through statistical and graphical analysis of a large number of life tables of acceptable quality, mainly for European countries.

Reference: United Nations (1990) "Step-by-step guide to the estimation of the child mortality" https://www.un.org/en/development/desa/population/publications/pdf/mortality/stepguide_childmort.pdf

References

United Nations Population Studies (1990) Step-by-Step Guide to the Estimation of Child Mortality No.107:1-83 (United Nations)

Coefficients for the estimation of child mortality multipliers `k(i)`

Description

This is a dataset of coefficients used to estimate multipliers k(i) in the TRUSSELL version of the BRASS method, using Coale-Demeny mortality models.

Usage

data(coeff_trussell_ki)

Format

A data frame

Details

The basic estimation equation for the Trussell method (equation 4.3) is

k(i) = a(i) + b(i) P(1)/P(2) + c(i) P(2)/P(3)

extracted from page 26, Table 4.

References

United Nations Population Studies (1990) Step-by-Step Guide to the Estimation of Child Mortality No.107:1-83 (United Nations)

Coefficients for the estimation of the time reference `t(i)`

Description

This is a dataset of coefficients used to derive the time reference t(i), for values of q(x) in the TRUSSELL version of the BRASS method, using Coale-Demeny mortality models.

Usage

data(coeff_trussell_ti)

Format

A data frame

Details

The basic estimation equation for the Trussell method (equation 4.3) is

t(i) = a(i) + b(i) P(1)/P(2) + c(i) P(2)/P(3)

The names of coefficients were changed from e, f, and g to a, b, and c.

extracted from page 27, Table 5.

References

United Nations Population Studies (1990) Step-by-Step Guide to the Estimation of Child Mortality No.107:1-83 (United Nations)

Fake data for Cambodia

Description

Fake data used to demonstrate the application of Cohort-derived and Period-derived methods developed by Rajaratnam et al in 2010.

Usage

data(microdata)

Format

A data frame

Details

iso3 - the iso3 code of the country from which your microdata come region - the region that the country belongs in country - name of the country svy_wt - sample weight given to the respondent. If no sample weights are provided, then generate this variable with a value of 1 for each respondent age - age of the respondent in years: or time since first birth of the respondent in years sex - sex of the respondent where 1 indicates male and 2 is female. ceb - number of children ever born cd - number of children that died

Source

PLoS MEDICINE

References

Panama 1976

Description

The data gathered by a survey in Panama between August and October 1976 can be used to demonstrate the estimation of child mortality from summary birth histories using the Trussell version of the BRASS method and the Coale-Demeny model life tables coale_demeny_ltm.

Usage

data(panama)

Format

A data frame

Details

extracted from Table49 on page 78.

Source

United Nations Population Division

References

United Nations (1983) Manual X: indirect techniques for demographic estimation. Population studies No. 81. New York: United Nations Department of International Economic and Social Affairs (United Nations)

Estimating under-five mortality using Maternal age cohort-derived methods

Description

u5mr_cohort() uses the maternal age cohort-derived methods (MAC) through summary birth history information and maternal age (or time since first birth) to calculate the under-five mortality estimates.

Usage

u5mr_cohort(
  data,
  women = "women",
  child_born = "child_born",
  child_dead = "child_dead",
  agegrp = "agegrp",
  iso3 = "KHM",
  svy_year = 2010
)

Arguments

data

preprocessed data

women

total number of women

child_born

children ever born

child_dead

children dead

agegrp

age grouping or time since first birth

iso3

the iso3 code of the country from which the survey data come

svy_year

end of the survey

Details

In this cohort-derived method, under-five mortality and reference time are estimated through summary birth history information from the mothers and her age or time since her first birth.

In case sample weights are available for the mothers, final variables should be multiplied by these weights before summarizing.

Computational Procedure

Two formulas were used to quantify MAC method:

5q0 component

logit(5q0_ijk) = \beta_0i + U_ij + \beta_1i x logit(CD_ijk / CEB_ijk) + \beta_2i x CEB_ijk + \beta_3i x PR1 + \beta_4i x PR2 + \epsilon_ijk

where

i = 5-year maternal age group \epsilon (15-19, 20-24, ... , 45-49) j = country k = survey CD_i = total dead children from maternal age group i CEB_i = total children ever born from maternal age group i PR1 = ratio of parity among maternal age group 15-19 and parity among maternal age group 20-24 PR2 = ratio of parity among maternal age group 20-24 and parity among maternal age group 25-29 U_ij = country-specific random effects

All coefficients vary by maternal age group, as indicated by i and the random effects also vary by country, as indicated by j.

Reference time component

reftime_ijk

= \beta_0i + \beta_1i x (CD_ijk / CEB_ijk) + \beta_2i x CEB_ijk + \beta_3i x PR1 + \beta_4i x PR2 + \epsilon_ijk

Value

data.frame

iso3 - total number of women
svy_year - total number of children ever born
agegrp - five-year age groups
ref_time - time between survey year and interpolated year
year - reference year
q5 - under-five mortality

References

Examples


## Example using fake survey data from Cambodia
data(cambodia)
camb <- u5mr_cohort(cambodia, women = "women", child_born = "child_born",
child_dead = "child_dead", agegrp = "agegrp", iso3 = "KHM", svy_year = 1234)

with(camb,
     plot(year, q5 * 1000, type = "b", pch = 19,
          col = "black", xlab = "Year", ylab = "U5MR per 1000 live births",
          main = paste0("Under-five mortality, q(5) in Bangladesh, estimated\n",
                       "using the maternal age cohort-derived method")))

Estimating under-five mortality using Coale-Demeny life table models

Description

u5mr_trussell() uses the Trussell version of the BRASS method and calculates under-five mortality estimates.

Usage

u5mr_trussell(
  data,
  women = "women",
  child_born = "child_born",
  child_dead = "child_dead",
  agegrp = "agegrp",
  model = "west",
  svy_year = 1976.5,
  sex
)

Arguments

data

processed data

women

total number of women

child_born

children ever born

child_dead

children dead

agegrp

age grouping

model

Coale-Demeny life table model: north, south, east, and west

svy_year

end of the survey

sex

indicates sex-specific estimates: both, male, and female

Details

T. J. Trussell developed the Trussell version of the Brass method to estimate child mortality using summary birth history (United Nations, 1983b, Chapter III). It is based on the Coale-Demeny life table models of either North, South, East, or West.

Computational Procedure

Step 1. Preparing the dataset

The function needs four variables from the input data:

a) agegrp: age groups representing 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, and 45-49.

b) women: the total number of women in the age group irrespective of their marital or reporting status

c) child_born: the total number of children ever borne by these women

d) child_dead: the number of children dead reported by these women

Step 1.1. Calculation of average parity per woman P(i)

P(i) = CEB(i) / FP(i)

CEB(i) is the total number of children ever borne by these women
FP(i) is the total number of women in the age group irrespective of their marital or reporting status.

Step 1.2. Calculation of the proportions dead among children ever borne D(i)

D(i) = CD(i) / CEB(i)

CD(i) is the number of children dead for women of age group i

Step 2. Calculating the multipliers k(i) and probabilities of dying by age x q(x)

k(i) = a(i) + b(i) P(1)/P(2) + c(i) P(2)/P(3)

where a(i), b(i), and c(i) are coefficients estimated by regression analysis of simulated model cases, and P(1)/P(2) and P(2)/P(3) are parity ratios.

q(x) = k(i) x D(i)

Step 3. Calculating the reference dates for q(x) and interpolating q5

Under conditions of steady mortality change over time, a reference time t(i) can be estimated for each q(x).

t(i) = a(i) + b(i) P(1)/P(2) + c(i) P(2)/P(3)

Actual dates can be obtained by subtracting t(i) from the reference date of the survey or census, expressed in decimal terms.

Step 4. Interpolating between q(x) and model life table

A common index, in this case, under-five mortality q(5) can be obtained by conversions of corresponding q(x) values to the specified family of the Coale-Demeny life table models. In a given life table family and sex, the first step is to identify the mortality levels with q(x) values that enclose the estimated value q^e(x).

q^j(x) > q^e(x) > q^j+1(x)

where q^j(x) and q^j+1(x) are the model values of q(x) for levels j and j+1, and q^e(x) is the estimated value.

The desired common index q^c(5), or q5 is given by

q^c(5) = (1.0 - h) x q^j(5) + h x q^e(5)

where h is the interpolation factor calculated in the following way:

h = q^e(x) - q^j(x) / q^j+1(x) - q^j(x)

Step 5. Finalizing the calculation

The final output is combined into a data.frame, which contains original dataset as well as statistics produced during the computational procedure.

Value

data.frame

agegrp - five-year age groups
women - total number of women
child_born - total number of children ever born
child_dead - number of children dead
pi - average parity
di - proportion of dead among children ever born
ki - multipliers
qx - probabilities of dying at age x
ti - time between survey year and interpolated year
year - reference year
h - interpolation factor
q5 - under-five mortality

References

United Nations (1990) "Step-by-step guide to the estimation of the child mortality" https://www.un.org/en/development/desa/population/publications/pdf/mortality/stepguide_childmort.pdf
United Nations (1983) "Manual X indirect techniques for demographic estimation" https://www.un.org/en/development/desa/population/publications/pdf/mortality/stepguide_childmort.pdf

Examples


## Using Bangladesh survey data to estimate child mortality
data("bangladesh")
bang_both <- u5mr_trussell(bangladesh, sex = "both", model = "south", svy_year = 1974.3)
bang_male <- u5mr_trussell(bangladesh, child_born = "male_born",
                 child_dead = "male_dead", sex = "male",
                 model = "south", svy_year = 1974.3)
bang_female <- u5mr_trussell(bangladesh, child_born = "female_born",
                 child_dead = "female_dead", sex = "female",
                 model = "south", svy_year = 1974.3)

## plotting all data points
with(bang_both,
    plot(year, q5, type = "b", pch = 19,
         ylim = c(0, .45),
         col = "black", xlab = "Reference date", ylab = "u5MR",
         main = paste0("Under-five mortality, q(5) in Bangladesh, estimated\n",
                       "using model South and the Trussell version of the Brass method")))
with(bang_both, text(year, q5, agegrp, cex=0.65, pos=3,col="purple"))
with(bang_male,
    lines(year, q5, pch = 18, col = "red", type = "b", lty = 2))
with(bang_female,
    lines(year, q5, pch = 18, col = "blue", type = "b", lty = 3))
legend("bottomright", legend=c("Both sexes", "Male", "Female"),
      col = c("Black", "red", "blue"), lty = 1:3, cex=0.8)


## Using panama survey data to estimate child mortality
data("panama")
pnm_both <- u5mr_trussell(panama, sex = "both", model = "west", svy_year = 1976.5)
pnm_male <- u5mr_trussell(panama, child_born = "male_born",
                child_dead = "male_dead", sex = "male",
                model = "west", svy_year = 1976.5)
pnm_female <- u5mr_trussell(panama, child_born = "female_born",
                child_dead = "female_dead", sex = "female",
                model = "west", svy_year = 1976.5)

## plotting all data points
with(pnm_both,
    plot(year, q5, type = "b", pch = 19,
        ylim = c(0, .2), col = "black", xlab = "Reference date", ylab = "u5MR",
         main = paste0("Under-five mortality, q(5) in Panama, estimated\n",
                       "using model West and the Trussell version of the Brass method")))
with(pnm_both, text(year, q5, agegrp, cex=0.65, pos=3,col="purple"))
with(pnm_male,
    lines(year, q5, pch = 18, col = "red", type = "b", lty = 2))
with(pnm_female,
    lines(year, q5, pch = 18, col = "blue", type = "b", lty = 3))
legend("bottomleft", legend=c("Both sexes", "Male", "Female"),
      col = c("Black", "red", "blue"), lty = 1:3, cex=0.8)

Bangladesh 1974

Description

Usage

Format

Details

References

Aggregated summary birth histories derived from microdata

Description

Usage

Format

Details

Source

References

Coale-Demeny Model Life Tables

Description

Usage

Format

Details

References

Coefficients for the estimation of child mortality multipliers k(i)

Description

Usage

Format

Details

References

Coefficients for the estimation of the time reference t(i)

Description

Usage

Format

Details

References

Fake data for Cambodia

Description

Usage

Format

Details

Source

References

Panama 1976

Description

Usage

Format

Details

Source

References

Estimating under-five mortality using Maternal age cohort-derived methods

Description

Usage

Arguments

Details

Value

References

Examples

Estimating under-five mortality using Coale-Demeny life table models

Description

Usage

Arguments

Details

Value

References

Examples

Coefficients for the estimation of child mortality multipliers `k(i)`

Coefficients for the estimation of the time reference `t(i)`