Adding Indices of Deprivation 2025 in 10 categories

Author: IGRiosTC

deprivation/README.md

@@ -5,4 +5,13 @@
 | Household deprived in education | 2021 | Best-fit ward | Census 2021 | Percentage of households deprived in education. A household is classified as deprived in education if no one has at least a level 2 education and no one aged 16 to 18 years is a full-time student. | [view](data/household_education_deprived.csv) | [view](code/household_education_deprived.R) |
 | Household deprived in employment | 2021 | Best-fit ward | Census 2021 | Percentage of households deprived in employment. A household is classified as deprived in employment if any member, not a full-time student, is either unemployed or economically inactive due to long-term sickness or disability. | [view](data/household_employment_deprived.csv) | [view](code/household_employment_deprived.R) |
 | Household is deprived in health and disability | 2021 | Best-fit ward | Census 2021 | Percentage of households deprived in health and disability. A household is classified as deprived in the health dimension if any person in the household has general health that is bad or very bad or is identified as disabled. | [view](data/household_health_deprived.csv) | [view](code/household_health_deprived.R) |
-| Household is deprived in housing | 2021 | Best-fit ward | Census 2021 | Percentage of households deprived in housing. A household is classified as deprived in the housing dimension if the household's accommodation is either overcrowded, in a shared dwelling, or has no central heating. | [view](data/household_housing_deprived.csv) | [view](code/household_housing_deprived.R) |
+| Household is deprived in housing | 2021 | Best-fit ward | Census 2021 | Percentage of households deprived in housing. A household is classified as deprived in the housing dimension if the household's accommodation is either overcrowded, in a shared dwelling, or has no central heating. | [view](data/household_housing_deprived.csv) | [view](code/household_housing_deprived.R) |
+| Index of Multiple Deprivation | 2025 | Best-fit ward | Ministry of Housing, Communities & Local Government | Relative measure of deprivation. Note that these are not absolute values so a score of 40 does not indicate twice the deprivation of a ward with a score of 20. Higher average scores indicate higher relative levels of deprivation. | [view](data/index_of_multiple_deprivation.csv) | [view](code/index_of_multiple_deprivation.R) |
+| Indices of Deprivation for Income | 2025 | Best-fit ward | Ministry of Housing, Communities & Local Government | Proportion of the population in an area experiencing deprivation relating to low income.  Higher percentages indicate higher relative levels of deprivation. | [view](data/income_deprivation.csv) | [view](code/income_deprivation.R) |
+| Indices of Deprivation for Employment | 2019 | Best-fit ward | Ministry of Housing, Communities & Local Government | Proportion of the working age population (18 to 66) in an area involuntarily excluded from the labour market. Higher percentages indicate higher relative levels of deprivation. | [view](data/employment_deprivation.csv) | [view](code/employment_deprivation.R) |
+| Indices of Deprivation for Education, Skills and Training | 2025 | Best-fit ward | Ministry of Housing, Communities & Local Government | Relative measure of the lack of attainment and skills in the local population. Note that these are not absolute values so a score of 40 does not indicate twice the deprivation of a ward with a score of 20. Higher average scores indicate higher relative levels of deprivation. | [view](data/education_deprivation.csv) | [view](code/education_deprivation.R) |
+| Indices of Deprivation for Health Deprivation and Disability | 2025 | Best-fit ward | Ministry of Housing, Communities & Local Government | Relative measure of the risk of premature death and the impairment of quality of life through poor physical or mental health. Note that these are not absolute values so a double score does not indicate double the risk. Higher negative scores indicate lower levels of deprivation and higher positive scores indicate higher levels of deprivation. | [view](data/health_deprivation.csv) | [view](code/health_deprivation.R) |
+| Indices of Deprivation for Crime | 2025 | Best-fit ward | Ministry of Housing, Communities & Local Government | Relative measure of the risk of personal and material victimisation at a local level for violence, harassment, burglary, theft, criminal damage, public order and anti-social behaviour. Note that these are not absolute values so a double score value does not indicate double the risk.  Higher negative scores indicate lower levels of deprivation and higher positive scores indicate higher levels of deprivation. | [view](data/crime_deprivation.csv) | [view](code/crime_deprivation.R) |
+| Indices of Deprivation for Barriers to Housing and Services | 2025 | Best-fit ward | Ministry of Housing, Communities & Local Government | Relative measure of the physical and financial accessibility of housing and local services. Note that these are not absolute values so a score of 20 does not indicate twice the deprivation of a ward with a score of 10. Higher scores indicate higher relative levels of deprivation. | [view](data/housing_deprivation.csv) | [view](code/housing_deprivation.R) |
+| Indices of Deprivation for Living Environment Deprivation | 2025 | Best-fit ward | Ministry of Housing, Communities & Local Government | Relative measure of the quality of the local environment including quality of housing, energy performance, private outdoor space, road traffic accidents, air quality and noise pollution. Note that these are not absolute values so a score of 30 does not indicate twice the deprivation of a ward with a score of 15. Higher scores indicate higher relative levels of deprivation. | [view](data/environment_deprivation.csv) | [view](code/environment_deprivation.R) |
+| Children aged 0 to 15 living in income deprived families | 2025 | Best-fit ward | Ministry of Housing, Communities & Local Government | Proportion of children aged 0–15 years living in income deprived households as a proportion of all children aged 0–15 years. Higher percentages indicate higher relative levels of deprivation. | [view](data/income_deprivation_children.csv) | [view](code/income_deprivation_children.R) |

deprivation/code/crime_deprivation.R

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+# English Indices of Deprivation 2025 #
+# Indices of Deprivation: Crime #
+
+# Source: Ministry of Housing, Communities and Local Government
+# Publisher URL: https://www.gov.uk/government/statistics/english-indices-of-deprivation-2025
+# Licence: Open Government Licence 3.0
+
+# MHCLG does not publish the Indices of Deprivation at ward level. 
+# Ward level data produced according to the Appendix A. How to aggregate to different geographies of the English Indices of Deprivation 2019 Research report
+
+library(sf) ; library(tidyverse) ; library(janitor) ; library(jsonlite)
+
+la<-"Trafford"
+
+#df <- read_csv("https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/833982/File_7_-_All_IoD2019_Scores__Ranks__Deciles_and_Population_Denominators.csv") %>%
+df <- read_csv("https://assets.publishing.service.gov.uk/media/691ded56d140bbbaa59a2a7d/File_7_IoD2025_All_Ranks_Scores_Deciles_Population_Denominators.csv") %>%
+
+  clean_names() %>%
+  filter(`local_authority_district_name_2024`==la) %>% 
+  select(lsoa21cd = "lsoa_code_2021", score = "crime_score", population = "total_population_mid_2022") %>% 
+  mutate(indicator="Indices of Deprivation: Crime")
+
+# LSOA to ward lookup #
+
+# Source: ONS Open Geography Portal 
+# Publisher URL: http://geoportal.statistics.gov.uk/
+# Licence: Open Government Licence 3.0
+
+# Best-fit lookup between LSOAs and wards
+#lookup <- read_csv("https://opendata.arcgis.com/datasets/8c05b84af48f4d25a2be35f1d984b883_0.csv") %>% 
+
+lookup <- fromJSON(paste0("https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LSOA21_WD25_LAD25_EW_LU_v2/FeatureServer/0/query?where=LAD25NM%20%3D%20'", URLencode(toupper("Trafford"), reserved = TRUE), "'&outFields=LSOA21CD,LSOA21NM,WD25CD,WD25NM,LAD25CD,LAD25NM&outSR=4326&f=json"), flatten = TRUE) %>% 
+  pluck("features") %>% 
+  as_tibble() %>% 
+  select(lsoa21cd = attributes.LSOA21CD, area_code = attributes.WD25CD, area_name = attributes.WD25NM)
+
+#IoD lsoa to ward
+
+iod_ward <- left_join(df, lookup, by = "lsoa21cd") %>%
+  group_by(area_code, area_name, indicator) %>%
+  summarise(ward_score=sum(score*population)/sum(population)) %>%
+  ungroup %>%
+  mutate(period="2025",unit ="Score", measure = "Weighted Score", value = round(ward_score, digits = 2)) %>%
+  select(area_code, area_name, indicator, period, measure, unit, value)
+
+write_csv (iod_ward, "../data/health_deprivation.csv")

deprivation/code/education_deprivation.R

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+# English Indices of Deprivation 2025 #
+# Indices of Deprivation: Education, Skills and Training #
+
+# Source: Ministry of Housing, Communities and Local Government
+# Publisher URL: https://www.gov.uk/government/statistics/english-indices-of-deprivation-2025
+# Licence: Open Government Licence 3.0
+
+# MHCLG does not publish the Indices of Deprivation at ward level. 
+# Ward level data produced according to the Appendix A. How to aggregate to different geographies of the English Indices of Deprivation 2019 Research report
+
+library(sf) ; library(tidyverse) ; library(janitor) ; library(jsonlite)
+
+la<-"Trafford"
+
+#df <- read_csv("https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/833982/File_7_-_All_IoD2019_Scores__Ranks__Deciles_and_Population_Denominators.csv") %>%
+df <- read_csv("https://assets.publishing.service.gov.uk/media/691ded56d140bbbaa59a2a7d/File_7_IoD2025_All_Ranks_Scores_Deciles_Population_Denominators.csv") %>%
+
+  clean_names() %>%
+  filter(`local_authority_district_name_2024`==la) %>% 
+  select(lsoa21cd = "lsoa_code_2021", score = "education_skills_and_training_score", population = "total_population_mid_2022") %>% 
+  mutate(indicator="Indices of Deprivation: Education, Skills and Training")
+
+# LSOA to ward lookup #
+
+# Source: ONS Open Geography Portal 
+# Publisher URL: http://geoportal.statistics.gov.uk/
+# Licence: Open Government Licence 3.0
+
+# Best-fit lookup between LSOAs and wards
+#lookup <- read_csv("https://opendata.arcgis.com/datasets/8c05b84af48f4d25a2be35f1d984b883_0.csv") %>% 
+
+lookup <- fromJSON(paste0("https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LSOA21_WD25_LAD25_EW_LU_v2/FeatureServer/0/query?where=LAD25NM%20%3D%20'", URLencode(toupper("Trafford"), reserved = TRUE), "'&outFields=LSOA21CD,LSOA21NM,WD25CD,WD25NM,LAD25CD,LAD25NM&outSR=4326&f=json"), flatten = TRUE) %>% 
+  pluck("features") %>% 
+  as_tibble() %>% 
+  select(lsoa21cd = attributes.LSOA21CD, area_code = attributes.WD25CD, area_name = attributes.WD25NM)
+
+#IoD lsoa to ward
+
+iod_ward <- left_join(df, lookup, by = "lsoa21cd") %>%
+  group_by(area_code, area_name, indicator) %>%
+  summarise(ward_score=sum(score*population)/sum(population)) %>%
+  ungroup %>%
+  mutate(period="2025",unit ="Score", measure = "Weighted Score", value = round(ward_score, digits = 1)) %>%
+  select(area_code, area_name, indicator, period, measure, unit, value)
+
+write_csv (iod_ward, "../data/education_deprivation.csv")

deprivation/code/employment_deprivation.R

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+# English Indices of Deprivation 2025 #
+# Indices of Deprivation: Employment#
+
+# Source: Ministry of Housing, Communities and Local Government
+# Publisher URL: https://www.gov.uk/government/statistics/english-indices-of-deprivation-2025
+# Licence: Open Government Licence 3.0
+
+# MHCLG does not publish the Indices of Deprivation at ward level. 
+# Ward level data produced according to the Appendix A. How to aggregate to different geographies of the English Indices of Deprivation 2019 Research report
+
+library(sf) ; library(tidyverse) ; library(janitor)
+
+la<-"Trafford"
+
+#df <- read_csv("https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/833982/File_7_-_All_IoD2019_Scores__Ranks__Deciles_and_Population_Denominators.csv") %>%
+df <- read_csv("https://assets.publishing.service.gov.uk/media/691ded56d140bbbaa59a2a7d/File_7_IoD2025_All_Ranks_Scores_Deciles_Population_Denominators.csv") %>%
+
+  clean_names() %>%
+  filter(`local_authority_district_name_2024`==la) %>% 
+  select(lsoa21cd = "lsoa_code_2021", score = "employment_score_rate", population = "working_age_population_18_66_for_use_with_employment_deprivation_domain_mid_2022") %>% 
+  mutate(indicator="Indices of Deprivation: Employment")
+
+# LSOA to ward lookup #
+
+# Source: ONS Open Geography Portal 
+# Publisher URL: http://geoportal.statistics.gov.uk/
+# Licence: Open Government Licence 3.0
+
+# Best-fit lookup between LSOAs and wards
+#lookup <- read_csv("https://opendata.arcgis.com/datasets/8c05b84af48f4d25a2be35f1d984b883_0.csv") %>% 
+
+lookup <- fromJSON(paste0("https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LSOA21_WD25_LAD25_EW_LU_v2/FeatureServer/0/query?where=LAD25NM%20%3D%20'", URLencode(toupper("Trafford"), reserved = TRUE), "'&outFields=LSOA21CD,LSOA21NM,WD25CD,WD25NM,LAD25CD,LAD25NM&outSR=4326&f=json"), flatten = TRUE) %>% 
+  pluck("features") %>% 
+  as_tibble() %>% 
+  select(lsoa21cd = attributes.LSOA21CD, area_code = attributes.WD25CD, area_name = attributes.WD25NM)
+
+#IoD lsoa to ward
+
+iod_ward <- left_join(df, lookup, by = "lsoa21cd") %>%
+  group_by(area_code, area_name, indicator) %>%
+  summarise(ward_score=sum(score*population)/sum(population)) %>%
+  ungroup %>%
+  mutate(period="2025",unit ="Persons", measure = "Percentage", value = round(ward_score * 100, digits = 1)) %>%
+  select(area_code, area_name, indicator, period, measure, unit, value)
+
+write_csv (iod_ward, "../data/employment_deprivation.csv")

deprivation/code/environment_deprivation.R

@@ -0,0 +1,46 @@
+# English Indices of Deprivation 2025 #
+# Indices of Deprivation: Crime #
+
+# Source: Ministry of Housing, Communities and Local Government
+# Publisher URL: https://www.gov.uk/government/statistics/english-indices-of-deprivation-2025
+# Licence: Open Government Licence 3.0
+
+# MHCLG does not publish the Indices of Deprivation at ward level. 
+# Ward level data produced according to the Appendix A. How to aggregate to different geographies of the English Indices of Deprivation 2019 Research report
+
+library(sf) ; library(tidyverse) ; library(janitor) ; library(jsonlite)
+
+la<-"Trafford"
+
+#df <- read_csv("https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/833982/File_7_-_All_IoD2019_Scores__Ranks__Deciles_and_Population_Denominators.csv") %>%
+df <- read_csv("https://assets.publishing.service.gov.uk/media/691ded56d140bbbaa59a2a7d/File_7_IoD2025_All_Ranks_Scores_Deciles_Population_Denominators.csv") %>%
+
+  clean_names() %>%
+  filter(`local_authority_district_name_2024`==la) %>% 
+  select(lsoa21cd = "lsoa_code_2021", score = "living_environment_score", population = "total_population_mid_2022") %>% 
+  mutate(indicator="Indices of Deprivation: Living Environment")
+
+# LSOA to ward lookup #
+
+# Source: ONS Open Geography Portal 
+# Publisher URL: http://geoportal.statistics.gov.uk/
+# Licence: Open Government Licence 3.0
+
+# Best-fit lookup between LSOAs and wards
+#lookup <- read_csv("https://opendata.arcgis.com/datasets/8c05b84af48f4d25a2be35f1d984b883_0.csv") %>% 
+
+lookup <- fromJSON(paste0("https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LSOA21_WD25_LAD25_EW_LU_v2/FeatureServer/0/query?where=LAD25NM%20%3D%20'", URLencode(toupper("Trafford"), reserved = TRUE), "'&outFields=LSOA21CD,LSOA21NM,WD25CD,WD25NM,LAD25CD,LAD25NM&outSR=4326&f=json"), flatten = TRUE) %>% 
+  pluck("features") %>% 
+  as_tibble() %>% 
+  select(lsoa21cd = attributes.LSOA21CD, area_code = attributes.WD25CD, area_name = attributes.WD25NM)
+
+#IoD lsoa to ward
+
+iod_ward <- left_join(df, lookup, by = "lsoa21cd") %>%
+  group_by(area_code, area_name, indicator) %>%
+  summarise(ward_score=sum(score*population)/sum(population)) %>%
+  ungroup %>%
+  mutate(period="2025",unit ="Score", measure = "Weighted Score", value = round(ward_score, digits = 1)) %>%
+  select(area_code, area_name, indicator, period, measure, unit, value)
+
+write_csv (iod_ward, "../data/environment_deprivation.csv")

deprivation/code/health_deprivation.R

@@ -0,0 +1,46 @@
+# English Indices of Deprivation 2025 #
+# Indices of Deprivation: Health Deprivation and Disability #
+
+# Source: Ministry of Housing, Communities and Local Government
+# Publisher URL: https://www.gov.uk/government/statistics/english-indices-of-deprivation-2025
+# Licence: Open Government Licence 3.0
+
+# MHCLG does not publish the Indices of Deprivation at ward level. 
+# Ward level data produced according to the Appendix A. How to aggregate to different geographies of the English Indices of Deprivation 2019 Research report
+
+library(sf) ; library(tidyverse) ; library(janitor) ; library(jsonlite)
+
+la<-"Trafford"
+
+#df <- read_csv("https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/833982/File_7_-_All_IoD2019_Scores__Ranks__Deciles_and_Population_Denominators.csv") %>%
+df <- read_csv("https://assets.publishing.service.gov.uk/media/691ded56d140bbbaa59a2a7d/File_7_IoD2025_All_Ranks_Scores_Deciles_Population_Denominators.csv") %>%
+
+  clean_names() %>%
+  filter(`local_authority_district_name_2024`==la) %>% 
+  select(lsoa21cd = "lsoa_code_2021", score = "health_deprivation_and_disability_score", population = "total_population_mid_2022") %>% 
+  mutate(indicator="Indices of Deprivation: Health Deprivation and Disability")
+
+# LSOA to ward lookup #
+
+# Source: ONS Open Geography Portal 
+# Publisher URL: http://geoportal.statistics.gov.uk/
+# Licence: Open Government Licence 3.0
+
+# Best-fit lookup between LSOAs and wards
+#lookup <- read_csv("https://opendata.arcgis.com/datasets/8c05b84af48f4d25a2be35f1d984b883_0.csv") %>% 
+
+lookup <- fromJSON(paste0("https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LSOA21_WD25_LAD25_EW_LU_v2/FeatureServer/0/query?where=LAD25NM%20%3D%20'", URLencode(toupper("Trafford"), reserved = TRUE), "'&outFields=LSOA21CD,LSOA21NM,WD25CD,WD25NM,LAD25CD,LAD25NM&outSR=4326&f=json"), flatten = TRUE) %>% 
+  pluck("features") %>% 
+  as_tibble() %>% 
+  select(lsoa21cd = attributes.LSOA21CD, area_code = attributes.WD25CD, area_name = attributes.WD25NM)
+
+#IoD lsoa to ward
+
+iod_ward <- left_join(df, lookup, by = "lsoa21cd") %>%
+  group_by(area_code, area_name, indicator) %>%
+  summarise(ward_score=sum(score*population)/sum(population)) %>%
+  ungroup %>%
+  mutate(period="2025",unit ="Score", measure = "Weighted Score", value = round(ward_score, digits = 2)) %>%
+  select(area_code, area_name, indicator, period, measure, unit, value)
+
+write_csv (iod_ward, "../data/health_deprivation.csv")