Number of households, and proportion headed by person with a disability
# Remove non-consenting participants
data <- data[data$consent == 'Yes' & !is.na(data$branch), ]
# Ns, by branch and disability status
t1 <- data %>%
mutate(is_pwd = ifelse(pwd == 1, 1, 0), branch = as.character(branch)) %>%
filter(!is.na(branch) & !is.na(is_pwd)) %>%
count(branch, is_pwd) %>%
group_by(branch) %>%
mutate(N = sum(n), prop_pwd = paste0(round(100*n/N,0), '%')) %>%
select(-N) %>%
tidyr::pivot_wider(names_from = is_pwd, values_from = c(n, prop_pwd)) %>%
select(-prop_pwd_0)
knitr::kable(t1, digits = 2, col.names = c('Branch','N not pwd', 'N pwd', '% pwd'),
caption = 'Households', align = 'lccc') %>%
kable_styling(
bootstrap_options = c("striped", "hover", "condensed", "responsive"),
font_size = 7, fixed_thead = T)
Households
Branch
|
N not pwd
|
N pwd
|
% pwd
|
Anaka
|
316
|
148
|
32%
|
Goma
|
320
|
127
|
28%
|
Gulu
|
331
|
163
|
33%
|
Kamdini
|
252
|
149
|
37%
|
Kigumba
|
285
|
79
|
22%
|
Lacor
|
231
|
142
|
38%
|
Loro
|
253
|
113
|
31%
|
Minakulu
|
351
|
127
|
27%
|
Number of individuals included in the survey (including secondary household members)
# Ns total people covered by the survey (listed in the rosters)
t2 <- data[, c('branch', 'res_gender', colnames(data)[grep("s23_", colnames(data))])] %>%
tidyr::pivot_longer(cols = c(2:ncol(.)), names_to = 'HH_member', values_to = 'gender') %>%
filter(!is.na(gender)) %>%
count(branch, gender) %>%
tidyr::pivot_wider(names_from = gender, values_from = n) %>%
group_by(branch) %>%
mutate(Females = paste0(Female,'/', (Male+Female), ' (', round(100*Female/(Male+Female)),'%)')) %>%
select(-Male)
knitr::kable(t2, digits = 2, caption = 'Individuals', align = 'lcc') %>%
kable_styling(
bootstrap_options = c("striped", "hover", "condensed", "responsive"),
font_size = 7, fixed_thead = T)
Individuals
branch
|
Female
|
Females
|
Gulu
|
1817
|
1817/2978 (61%)
|
Lacor
|
1470
|
1470/2434 (60%)
|
Anaka
|
1999
|
1999/3381 (59%)
|
Goma
|
1918
|
1918/3304 (58%)
|
Minakulu
|
1787
|
1787/3010 (59%)
|
Kamdini
|
1527
|
1527/2582 (59%)
|
Loro
|
1421
|
1421/2361 (60%)
|
Kigumba
|
1423
|
1423/2477 (57%)
|