Resumé:

Det samlede antal svangerskabsafbrydelser er igen i 2018 steget og ligger nu væsentligt over antallet af fødsler. Antallet af svangerskabsafbrydelser per 1.000 kvinder har haft en svagt stigende tendens de seneste seks år. Det er i den samme periode, at der er blevet indført adgang til medicinsk abort. Internationalt set er der tale om en meget høj hyppighed af svangerskabsafbrydelser i Grønland.

Postboks 120 3900 Nuuk Tlf. (+299) 34 51 92 Fax (+299) 32 51 30 E-mail: nun@nanoq.gl www.nanoq.gl

saved_query <- "http://betabank.stat.gl/sq/c3a16f77-dc4a-475a-b7b7-5c9c7807547b.csv"

abortions_age <- read_csv(saved_query) %>% 
  spread(unit, value = Abortions) %>% 
  clean_names()

Figurer og tabeller

abortions_age %>% 
  select(-mean_population) %>% 
  filter(time >= max(time) - 9) %>% 
  uncount(abortions) %>% 
  mutate(age_group = case_when(age < 16 ~ "< 16",
                               age >= 16 & age <= 29 ~ "16 - 29",
                               age >= 30 ~ "30 - 49"),
         age_group = fct_rev(age_group)) %>% 
  ggplot(aes(x = as.factor(time))) +
  geom_bar(aes(fill = age_group)) +
  labs(x = "År", y = "Antal pr. år",
       title = "Provokerede aborter",
       subtitle = "Figur 1: Indberettede antal svangerskabsafbrydelser, fordelt på aldersgrupper",
       fill = "Aldersgruppe") +
  guides(fill = guide_legend(reverse = TRUE))

abortions_age %>% 
  filter(time >= max(time) -9,
         age >= 15, age <= 49) %>% 
  group_by(time) %>% 
  summarise(rate = sum(abortions) / sum(mean_population) * 1000) %>% 
  ungroup() %>% 
  ggplot(aes(x = time, y = rate)) +
  geom_point() +
  geom_line() +
  expand_limits(y = 0:80) +
  labs(x = "År", y = "Rate",
       title = "Abortrate pr. 1000 kvinder blandt 15-49 årige",
       subtitle = "Figur 2: Den totale abortrate pr. 1000 kvinder i aldersgruppen 15-49 år")

table_by_age <- abortions_age %>% 
  filter(age <= 49, time >= max(time) - 4) %>% 
  mutate(Aldersgruppe = 
           cut(age, breaks = c(12, 14, 16, 18, 20, 25, 30, 35, 40, 45, 49),
               labels = c("12-13", "14-15", "16-17", "18-19", "20-24",
                          "25-29", "30-34", "35-39", "40-44","45-49"),
               include.lowest = TRUE, right = FALSE)) %>% 
  group_by(time, Aldersgruppe) %>% 
  summarise(abortions = sum(abortions),
            rate = round(abortions/ sum(mean_population) * 1000, 1)) %>% 
  ungroup()

table_by_age %>% select(-rate) %>% 
  spread(time, abortions) %>% 
  kable() %>% kable_styling()
Aldersgruppe 2014 2015 2016 2017 2018
12-13 2 0 0 0 0
14-15 29 21 24 25 20
16-17 75 72 66 57 64
18-19 100 98 116 103 86
20-24 272 250 241 280 260
25-29 196 221 218 214 244
30-34 116 136 115 118 156
35-39 51 50 60 61 78
40-44 22 15 14 24 23
45-49 1 1 1 1 0 
table_by_age %>% select(-abortions) %>% 
  spread(time, rate) %>% 
  kable() %>% kable_styling()
Aldersgruppe 2014 2015 2016 2017 2018
12-13 2.5 0.0 0.0 0.0 0.0
14-15 36.6 27.0 30.3 32.1 27.7
16-17 97.5 98.9 96.1 85.6 95.7
18-19 115.9 115.4 138.9 129.9 113.6
20-24 122.4 116.0 114.3 134.1 126.2
25-29 91.6 100.5 97.8 94.1 106.5
30-34 60.4 69.7 58.4 59.4 75.7
35-39 34.9 33.0 37.6 36.2 44.5
40-44 14.6 10.7 10.3 18.0 17.3
45-49 0.4 0.4 0.5 0.6 0.0 
g <- table_by_age %>% 
  drop_na() %>% 
  ggplot(aes(x = Aldersgruppe, y = rate, color = as.factor(time), group = time)) +
  geom_point() +
  geom_line() +
  labs(title = "Abortrate pr. 1000 i aldersgrupper", 
       subtitle = "Figur 3: Aldersgruppe 15-49 år",
       y = "Rate", color = "År") 

ggplotly(g) %>% 
  layout(legend = list(orientation = "h", x = 0.225, y = -0.25)) %>% 
  div(alignment = "center")

Data over distrikterne findes i et andet gemt spørgsmål:

table_by_district <- 
  read_csv("http://betabank.stat.gl/sq/c05dfbf7-f654-470d-b313-1cbfb2253046.csv") %>% 
  spread(unit, Abortions)

table_by_district %>% 
  mutate(district = as.factor(district),
         Abortions = as.numeric(Abortions)) %>%
  filter(time >= max(time) - 2) %>% 
  select(-`Mean population`) %>% 
  spread(time, Abortions) %>% 
  drop_na() %>% 
  arrange(fct_shift(district, -1)) %>% 
  rename(District = district) %>% 
  kable() %>% kable_styling()
District 2016 2017 2018
Aasiaat 79 75 104
Ilulissat 71 89 80
Ittoqqortoormiit 4 6 3
Maniitsoq 36 51 48
Nanortalik 9 17 18
Narsaq 15 21 13
Nuuk 343 298 336
Paamiut 17 34 24
Qaqortoq 91 94 75
Qasigiannguit 0 0 2
Qeqertarsuaq 0 0 0
Qaanaaq 15 10 20
Sisimiut 95 96 115
Tasiilaq 48 35 43
Upernavik 17 45 39
Uummannaq 15 12 11 
read_csv("http://betabank.stat.gl/sq/446fff29-9790-4a59-80cf-cd98c1017bf2.csv") %>% 
  clean_names() %>% 
  filter(time >= max(time) - 9) %>% 
  mutate(week = parse_number(length_of_pregnancy),
         length_of_pregnancy = 
           case_when(week == 4  ~ "4 weeks or under",
                     week == 18 ~ "18 weeks or over", 
                     T ~ length_of_pregnancy)) %>% 
  count(time, length_of_pregnancy, week, wt = abortions) %>% 
  rename(`Length of pregnancy` = length_of_pregnancy) %>% 
  spread(time, n) %>% 
  arrange(week) %>% 
  select(-week) %>% 
  kable() %>% 
  kable_styling()
Length of pregnancy 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
4 weeks or under 6 8 5 1 26 18 3 6 5 6
5 weeks 24 20 16 22 8 17 16 36 33 27
6 weeks 55 76 64 53 58 62 81 108 119 102
7 weeks 133 153 133 124 188 183 150 204 222 205
8 weeks 223 233 198 222 229 225 230 206 205 243
9 weeks 150 155 148 159 154 144 158 123 132 155
10 weeks 103 119 94 107 84 101 126 75 81 94
11 weeks 63 47 47 55 70 65 69 46 49 54
12 weeks 19 20 26 18 25 27 23 26 20 19
13 weeks 2 3 0 2 3 6 3 11 6 7
14 weeks 3 1 2 3 7 3 1 6 6 4
15 weeks 1 4 1 0 0 2 4 2 2 3
16 weeks 2 1 2 1 0 1 0 3 1 1
17 weeks 0 1 0 1 0 1 0 0 0 3
18 weeks or over 15 17 7 16 23 9 0 3 2 8 
read_csv("http://betabank.stat.gl/sq/446fff29-9790-4a59-80cf-cd98c1017bf2.csv") %>% 
  clean_names() %>% 
  mutate(week = parse_number(length_of_pregnancy)) %>% 
  count(time, week, wt = abortions) %>% 
  filter(time == 2009 | time == max(time)) %>% 
  ggplot(aes(x = week, y = n, color = as.factor(time))) +
  geom_point() +
  geom_line() +
  labs(title = "Fordeling af indberettede svangerskabsuger",
       subtitle = "Figur 4",
       x = "Svangerskabsuge", y = "Antal",
       color = "År")