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Social Services

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Unemployment and maternity benefits

Tabel 1: Unemployment and maternity benefits by municipality, unit, type and time

SOX006_raw <- 
  statgl_url("SOX006", lang = language) |> 
  statgl_fetch(
    municipality = px_all(),
    unit         = px_all(),
    type         = px_all(),
    time         = px_top(),
    .col_code    = T
  ) |> 
  as_tibble()

SOX006 <- 
  SOX006_raw |> 
  mutate(municipality = municipality |> fct_inorder(),
         type = type |> fct_inorder()) |>
  spread(type, value) |> 
  arrange(unit) 

SOX006 |> 
  select(-c(2, 3)) |> 
  rename(" " = 1) |> 
  statgl_table() |> 
  pack_rows(index = table(SOX006[[3]])) |> 
  pack_rows(index = table(SOX006[2])) |> 
  row_spec(c(1, 7), bold = T)

	Unemployment benefits, total	Unemployment benefit, basic	Unemployment benefit, termination	Unemployment benefit, disease	Maternity benefits
2023
Amount (1000 DKK)
Total	25.238	9.119	3.603	12.517	31.775
Kommune Kujalleq	4.718	2.453	9	2.256	3.406
Kommuneqarfik Sermersooq	6.340	2.836	20	3.484	10.182
Qeqqata Kommunia	3.622	1.140	579	1.903	5.397
Kommune Qeqertalik	5.907	2.197	1.624	2.086	4.977
Avannaata Kommunia	4.652	493	1.371	2.788	7.812
Number
Total	1.821	585	384	1.053	719
Kommune Kujalleq	292	158	3	152	84
Kommuneqarfik Sermersooq	362	141	2	232	228
Qeqqata Kommunia	349	108	110	196	120
Kommune Qeqertalik	389	127	121	184	104
Avannaata Kommunia	429	51	148	289	183

See the table in our Statbank: SOX006

Foster care

Tabel 2: Foster children by municipality and year

SOXPV004_raw <- 
  statgl_url("SOXPV004", lang = language) %>%
  statgl_fetch(
    municipality = px_all(),
    year = px_top(1),
    .col_code = TRUE
  ) %>% 
  as_tibble()



SOXPV004_raw %>% 
  mutate(municipality = municipality %>% fct_inorder()) %>% 
  spread(year, value) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  row_spec(1, bold = TRUE)

	2024
Total	401
Kommuneqarfik Sermersooq	164
Avannaata Kommunia	55
Kommune Qeqertalik	45
Qeqqata Kommunia	74
Kommune Kujalleq	63

See the table in our Statbank: SOXPV004

Public benefits

Tabel 3: Public benefits by municipality, unit, type and time

SOX004_raw <- 
  statgl_url("SOX004", lang = language) %>% 
  statgl_fetch(
    municipality = px_all(),
    unit         = px_all(),
    type         = 10,
    time         = px_top(),
    .col_code    = TRUE
  ) %>% 
  as_tibble()


SOX004 <- 
  SOX004_raw %>% 
  mutate(municipality = municipality %>% fct_inorder()) %>% 
  spread(unit, value) %>% 
  unite(combi, type, time, sep = ", ")


SOX004 %>% 
  select(-combi) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = SOX004[["combi"]] %>% table()) %>% 
  row_spec(1, bold = TRUE)

	Amount (1000 DKK)	Number
Public benefits total, 2023
Total	48.781	3.022
Kommune Kujalleq	10.194	662
Kommuneqarfik Sermersooq	18.905	945
Qeqqata Kommunia	8.854	501
Kommune Qeqertalik	6.339	454
Avannaata Kommunia	4.488	460

See the table in our Statbank: SOX004

Pensions

Tabel 4: Pensioners in December by district, gender, payment and time

SOXPEN1_raw <- 
  statgl_url("SOXPEN1", lang = language) %>% 
  statgl_fetch(
    gender    = px_all(),
    payment   = px_all(),
    time      = px_top(),
    .col_code = TRUE
  ) %>% 
  as_tibble()


SOXPEN1 <- 
  SOXPEN1_raw %>% 
  mutate(
    gender = gender %>% fct_inorder(),
    payment = payment %>% fct_inorder()
  ) %>% 
  spread(gender, value)

SOXPEN1 %>% 
  select(-time) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = SOXPEN1[["time"]] %>% table()) %>% 
  row_spec(1, bold = TRUE)

	Total	Man	Woman
2024
Total	6.718	3.459	3.259
Age pension	4.207	2.175	2.032
Early retirement pension	2.511	1.284	1.227

See the table in our Statbank: SOXPEN1

Social Care

Tabel 5: Disabled citizens

SOXFO10_raw <- 
  statgl_url("SOXFO10", lang = language) %>%
  statgl_fetch(
    "age group" = px_all(),
    gender      = px_all(),
    time        = px_top(1),
    .col_code   = TRUE
  ) %>% 
  as_tibble()



SOXFO10 <- 
  SOXFO10_raw %>% 
  filter(time == max(time)) %>% 
  mutate(
    `age group` = `age group` %>% fct_inorder(),
    gender = gender %>% fct_inorder()
  ) %>% 
  spread(gender, value)


SOXFO10 %>% 
  select(-time) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = SOXFO10[["time"]] %>% table()) %>% 
  row_spec(1, bold = TRUE)

	Total	Man	Woman
2018
Total	1.131	706	425
0-17 years	199	138	61
18-30 years	292	189	103
31-40 years	175	107	68
41-50 years	143	86	57
51-60 years	238	137	101
61+ years	84	49	35

See the table in our Statbank: SOXFO10

Additional social subsidies

Tabel 6: Rent subsidy by district, unit and time

SOXBS02_raw <- 
  statgl_url("SOXBS02", lang = language) |> 
  statgl_fetch(
    district  = px_all(),
    unit      = "Antal",
    time      = px_top(7),
    .col_code = T
  ) |> 
  as_tibble()

SOXBS02 <- 
  SOXBS02_raw |> 
  spread(time, value)

SOXBS02 |> 
  select(-unit) |> 
  rename(" " = 1) |> 
  statgl_table() |> 
  pack_rows(index = table(SOXBS02["unit"])) |> 
  row_spec(1, bold = T)

	2018	2019	2020	2021	2022	2023	2024
Number
Ilulissat	374	361	359	317	291	262	288
Ittoqotoormiit	23	32	22	19	25	17	15
Kangaatsiaq	37	35	28	35	32	27	28
Maniitsoq	316	302	293	283	279	265	270
Nanortalik	144	135	105	111	115	90	93
Narsaq	179	172	172	154	162	143	138
Nuuk	1.015	1.015	1.023	1.000	980	958	1.009
Paamiut	193	186	183	176	158	155	153
Qaqortoq	306	302	279	281	309	267	260
Qasigiannguit	126	112	106	108	93	78	84
Qeqertarsuaq	72	62	60	68	62	65	57
Qaanaaq	54	51	47	43	43	41	46
Sisimiut	533	499	509	510	495	485	521
Tasiilaq	153	153	142	144	135	140	132
Total	3.941	3.822	3.729	3.653	3.527	3.326	3.423
Upernavik	45	38	26	36	29	27	33
Uummannaq	73	71	69	68	52	47	47
Aasiaat	298	296	306	300	267	259	249

See the table in our Statbank: SOXBS02

Economically disadvantaged

Tabel 7: Economically disadvantaged by inventory variable, age, gender and year

SODOU01_raw <- 
  statgl_url("SOXOU01", lang = language) %>% 
  statgl_fetch(
    "inventory variable" = c("Andel50", "Andel60"),
    gender = px_all(),
    year = px_top(1),
    .col_code = TRUE
  ) %>% 
  as_tibble()


SODOU01 <- 
  SODOU01_raw %>% 
  mutate(`inventory variable` = `inventory variable` %>% fct_inorder()) %>% 
  arrange(desc(gender)) %>% 
  mutate(gender = gender %>% fct_inorder() %>% fct_rev()) %>% 
  spread(gender, value)
  

SODOU01 %>% 
  select(-year) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = SODOU01[["year"]] %>% table())

	Female	Male	Total
2023
fraction below 50%	4,1	5,0	4,6
fraction below 60%	7,8	8,7	8,2

See the table in our Statbank: SOXOU01

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Last updated: 22. juni 2025