ESC LHIN Report Mapping Neighbourhoods ESC LHIN | Mapping Neighbourhoods Summary of Work
Overview of the LHIN Geography The Erie St. Clair Local Health Integration Network (ESC LHIN) covers a geographical area from Grand Bend to Windsor, and services the regions of Chatham-Kent, Sarnia/Lambton, and Windsor/Essex. The LHIN is home to approximately 640,000 people, with almost half residing in large urban population centers and the remaining residing outside these areas, in either small urban or rural areas.
Across the LHIN, there are 5 hospitals: Chatham-Kent Health Alliance, Bluewater Health, Hotel-Dieu Grace Healthcare, Erie Shores Healthcare, and Windsor Regional Hospital. The LHIN funds approximately 83 local health providers who service the region. Sub-Regions Within the LHIN, there are six sub-regions: Windsor, Tecumseh Lakeshore Amherstburg LaSalle, Essex South Shore, Chatham City Centre, Rural Kent, and Lambton (see map). These sub-regions were formalized based on existing care patterns and through engagement with patients, providers and community members. Indigenous On-Reserve Populations There are a number of Indigenous and Métis communities in Erie St. Clair, including: Bkejwanong Territory (Walpole Island), Chippewas of Kettle and Stony Point, Aamjiwnaang First Nation, Delaware Nation (Moravian Town) and Caldwell First Nation. Additionally, many Métis peoples reside in communities throughout Erie St. Clair.
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Mapping Neighbourhood Project Background & Summary Starting in 2017, the Population Health Solutions Lab (the Lab) partnered with the ESC LHIN, public health units and other local partners to develop, test and validate appropriate and meaningful mid-level geographies as a basis for analysis and joint health planning in the region.
This mid-level geography, termed ‘neighbourhoods’ use Census geographies as building blocks. They also contain 7,000 to 50,000 population size, but generally fall in the range of 10,000 to 20,000 population, as defined by the 2016 Census.
This phase of the Mapping Neighbourhoods project did not include neighbourhood mapping for Lambton County.
Approach to Mapping To allow for optimal adaption of local context within the ESC LHIN, different approaches to neighbourhood mapping were undertaken in Windsor-Essex County (Windsor, Essex South Shore, and Tecumseh Lakeshore Amherstburg LaSalle LHIN sub-regions) and the Municipality of Chatham-Kent (Rural Kent and Chatham City Centre LHIN sub-region). Nevertheless, in both areas, alignment to municipality boundaries was determined to be of greater importance than other geographical boundaries (e.g. sub-region).
Through a series of meetings, insights were gathered from geospatial and data experts from three organizations who had completed copious work in population health assessment and geospatial mapping of these community: (1) Chatham-Kent Public Health Unit; (2) United Way Windsor-Essex County; and (3) Windsor-Essex County Health Unit. Municipality of Chatham-Kent In Chatham-Kent, wards were determined to be an important geographical boundary and were subsequently used as a starting point for creating neighbourhoods. Dissemination areas (DAs), a level of geography defined by Statistics Canada for the Census were grouped together to align as closely as possible with ward boundaries. In the Chatham specifically, Ward 6 was split into four separate neighbourhoods based on a variety of factors including the following: population size and density; physical barriers such as streets and rivers; data on socioeconomic status from the Ontario Marginalization Index; and knowledge of local community context. In total, 9 new neighbourhoods or Community Health Planning Areas (CHPA) were created in Chatham-Kent. Through local insight, this naming convention was selected as it allows for alignment with the current ward numbering system.
Table 1: Original and new neighbourhoods/CHPAs in Chatham-Kent.
Original Change New Neighbourhood Neighbourhood Ward 1- West Kent Combined DAs to form one neighbourhood. Included DA CHPA – 1 35360307 from Ward 2 based on similar population demographic/density. Ward 2- South Kent Combined DAs to form one neighbourhood. Moved DA CHPA – 2 35360342 into CK8 based on similar population demographic/density. Ward 3- East Kent Combined DAs to form one neighbourhood. CHPA – 3
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Ward 4- North Kent Combined DAs to form one neighbourhoods. CHPA – 4 Ward 5- Wallaceburg Combined DAs to form one neighbourhoods. CHPA – 5 Ward 6- Chatham Split ward into four neighbourhoods based on ward CHPA – 6a alignment, population size, density, etc. (aligned to DAs). CHPA – 6b CHPA – 6c East-West division: Sandys Street/Lacroix Street. CHPA – 6d
North-South division: Grand Avenue West/Grand Avenue East.
Windsor-Essex County (City of Windsor and Essex County) Through consultations with United Way Windsor-Essex County and Windsor-Essex County Health Unit, municipalities were determined to be an important geographical boundary for neighbourhoods to align to. A municipality-by-municipality approach was utilized in Windsor-Essex County.
For the City of Windsor, the City’s Planning Districts were determined to be an appropriate starting point for neighbourhood creation. Census tracts (CTs), a level of geography defined by Statistics Canada for the Census were grouped together to align as closely as possible with existing planning district boundaries. For the municipalities in Essex County, areas were further divided by CTs (Amherstburg, Lakeshore, and LaSalle) or DAs (Essex, Kingsville, Leamington, and Tecumseh) to isolate the more densely populated pockets or towns from the rest of the municipality. To illustrate, in the Town of Essex, the northeast corner of the municipality is more densely populated than the rest. Thus, DAs in this pocket were grouped together and separated from the less densely populated area in the town, resulting in the creation of two neighbourhoods in the Town of Essex.
Like Chatham-Kent, the approach to creating neighbourhoods in Windsor-Essex County included the following factors: population size and density; physical barriers such as streets and rivers; data on socioeconomic status from the Ontario Marginalization Index; and knowledge of local community context. In total, 29 new neighbourhoods were created in Windsor-Essex County.
Table 2: Original and new neighbourhoods in Windsor-Essex.
Original Change New Neighbourhood Amherstburg Split into two neighbourhoods – rural and urban. Grouped by A1 census tracts (CT). A2 Essex Split into two neighbourhoods – rural and urban. Grouped by DAs. E1 E2 Kingsville Split into two neighbourhoods – rural and urban. Grouped by DAs. K1 K2 Leamington Split into two neighbourhoods – rural and urban. Grouped by DAs. LE1 LE2 Lakeshore Split into three neighbourhoods – one rural and two urban. L1 Grouped by census tracts (CT). L2 L3 Tecumseh Split into two neighbourhoods – rural and urban. Grouped by DAs. T1 T2
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LaSalle Split into three neighbourhoods – one rural and two urban. LS1 Grouped by census tracts (CT). LS2 LS3 East Riverside Combined most CTs to form one neighbourhood. W1
Moved DAs 35370292, 3537093, 35370294, 35370295 from W1 to W2 based on similar demographics. Riverside Combined CTS to form one neighbourhood. W2
Moved DAs 35370292, 3537093, 35370294, 35370295 from W1 to W2 based on similar demographics. East Windsor Combined with a portion of Forest Glade (area west of Jefferson W3 Blvd) to form one neighbourhood. Forest Glade Split along Lauzon Road. Area east of this road formed one W3 neighbourhood and area west of the road formed parts of W11 and W10 W3. W11 Sandwich Combined with CTs that align to Ojibway and Malden to form one W4 neighbourhood. Ojibway Combined with CTs that align to Malden and Sandwich to form one W4 neighbourhood. Malden Combined with CTs that align to Ojibway and Sandwich to form one W4 neighbourhood. Roseland Combined with part of Devonshire (area south of Division Road W5 East) to form one neighbourhood. Devonshire Area south of Division Road East combined with W5 to form one W5 neighbourhood. W7
Area north of this road combined with CTs that align with Remington Park and some of Walker Farm and South Windsor to form one neighbourhood. South Combined CTs to form one neighbourhood (except DA 35370146 W6 Windsor which is part of W7). Remington Combined with CTs that align to most of Devonshire and some of W7 Park Walkerfarm and South Windsor to form one neighbourhood. Walker Farm Combined CTs to form one neighbourhood (except DA 35370135 W7 which is part of W11). W11 South Combined CTs to form one neighbourhood. W8 Cameron University Combined CTs to form one neighbourhood. W9 Sandwich Combined with CTs that align to a portion of Forest Glade (area east W10 South of Lauzon Road) to form one neighbourhood. Fontainbleu Combined with CTs that align to a portion of Forest Glade and W11 Walkerfarm to form one neighbourhood. Walkerville Divided along Moy Avenue. Area west of this road combined with W12 W13. Area east of this road combined with W12. W13 South Combined with portion of Walkerville to form one neighbourhood. W12 Walkerville
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South Central Combined with CTs that align to City Centre and a portion of W13 Walkerville to form one neighbourhood. City Centre Combined with CTs that align to South Central and a portion of W13 Walkerville to form one neighbourhood.
Qualitative Feedback Neighbourhood maps were developed for Chatham-Kent and Windsor-Essex County. Neighbourhoods were defined using standard Census geographies, and had a minimum population size of 7,000 with an average size of 13,000. To ensure that the newly created neighbourhood maps were valid and possessed local significance, feedback was sought from stakeholders who were familiar with communities within Windsor-Essex and Chatham-Kent in the form of a map worksheet. A project background PowerPoint presentation, an instruction guide and map worksheets, as well as an interactive web tool illustrating the proposed neighbourhoods were provided to orient individuals to the feedback process and the approach.
Overall, feedback was received about the neighbourhood maps from six groups/individuals. This feedback was synthesized and presented to the internal working group. The group and the Lab reviewed the decisions through a one-hour teleconference/zoom call and selected which feedback should be accepted. In Windsor-Essex, geography recommendations were given to recombine areas based on demographic similarity and population size. In Chatham-Kent, recommendations were given to recombine areas based on material deprivation, obtaining a better balance of population counts across the city neighbourhoods, and better alignment with DA geographies and ward boundaries. Final recommendations can be found in Appendix A. Neighbourhood name recommendations were also discussed (Appendix A). In Chatham-Kent specifically, consensus was reached to name the neighbourhoods “Community Health Planning Areas” (CHPA). This naming convention will allow for the alignment of neighbourhood numbering system with the current ward numbering system. It was suggested that referring to these neighbourhoods as CHPAs avoids the complex process of identifying neighbourhood names.
Testing The primary deliverable of the mapping neighbourhoods project are shapefiles and geo-conversion files (from Census geography to neighbourhood). To ensure there are no technical or methodological issues with these files, the ESC LHIN and its partners tested the newly created geographies with data. A testing guidelines document was provided to the ESC LHIN which outlined the purpose of testing, how neighbourhoods can be validated with data, what data should be used to test neighbourhoods, and what outputs should be shared back. In mid-March, shapefiles and geoconversion files were shared with the ESC LHIN to conduct testing with data (completed within roughly one week). Testing Procedure Testing was completed by the Decision Support team of the ESC LHIN. Testing was completed using the PCCF+ conversion file on three indicators – population count from the 2006 and 2016 Census; hospitalizations from the Discharge Abstracts Database for 2015, 2016, and 2017; and premature mortality from Vital Statistics from 2013, 2014, and 2015. Data from a neighbourhood was considered to be ‘suppress’ if cell size was 1-5, ‘use with caution’ if cell size was 6-19 for numerator or 6-29 for denominator, or ‘valid’ if cell size equal to 0. See Appendix B for detailed methodology.
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Results There was little to no suppression for hospitalization when combining multiple years of data. In the instances where suppression occurred (2015, 2016 and 2017), it was often for the male and/or female age group 10-19. Similarly, there was little to no suppression for premature mortality when combining multiple years of data. In the instances where suppression occurred (2013, 2014, and 2015), it was often for the male and/or female age group 20-44. It is important to note that this may present issues for reporting indicators on these specific age groups given the small population sizes. This means that the analyst would need to decide: is it more important to stratify by neighborhood or by age groups/sex. We feel this is a reasonable expectation for this type of small area analysis. See Appendix B for detailed results.
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Appendix A – Geography and Name Decisions Geography recommendations that were accepted during the qualitative feedback phase of the Mapping Neighbourhoods project.
Neighbourhood/CHPA Feedback Accepted Label WI Move DAs 35370292, 3537093, 35370294, 35370295 from W1 to W2. W12 Divide along Moy Avenue up until Tecumseh Road East; area west of Moy Avenue will become W13. DA 35370220 part of W12. LS1 Split into two along Malden Road. L2 Split into two along East Puce Road. CK Walpole Island is a First Nation reserve. Please separate and indicate. CK2 Move DA 35360414 from CK2 to CK7. CK4 Move DA 35360395 from CK4 to CK8. CK4 Move DAs 35360505, 35360406, and 35360408 from CK4 to CK9. CK6 Move DAs 35360495, 35360497, 35360255, 35360249, 35360250, 35360247, 35360251, 35360361, 35360360, 35360499, 35360501, and 35360362 from CK6 to CK7.
Sandy St/Orangewood Blvd (continuation of Lacroix St) was selected as streets to split North Chatham. CK9 Move DAs 35360227, 35360229, 35360228, 35360330, 35360397, 35360399, 35360401, 35360322, 35360321, 35360502, 35360342 from CK9 to CK8.
Lacroix St was selected as the street to split up South Chatham.
Name recommendations that were accepted during the qualitative feedback phase of the Mapping Neighbourhoods project.
Neighbourhood/CHPA Decisions
Label CK1 CHPA - 5 CK2 CHPA - 4
CK3 CHPA - 3 Kent
- CK4 CHPA - 2 CK5 CHPA - 1 CK6 CHPA - 6a
Chatham CK7 CHPA - 6b CK8 CHPA - 6c CK9 CHPA - 6d A1 A2 E1 E2 K1
EssexCounty K2 L1
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L2 L3 LE1 LE2 LS1 LS2 LS3 T1 T2 W1 W2 W3 W4 W5 W6 W7
Windsor W8 W9 W10 W11 W12 W13
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Appendix B – Testing Methodology and Results The following is a description about how the match between Postal Codes and Canadian geographic areas were established using PCCF+ package (version 6D of the PCCF+) from Statistics Canada.
The PCCF+ received from Statistics Canada has files the LHIN used to match postal codes and geographic areas. The PCCF+ content files was installed on a directory.
The first major step was to convert the input txt file in the “Sample” directory into a SAS data using PCCFplus_6D SAS program. This data is in text format and contains 6-character Postal Codes (no space) with up-to 15-character and ID numbers. Each postal codes is associated with a unique IDs. You can have repeated postal codes but with different ID number.
Still on the PCCFplus_6D SAS program, the program was modified to:
• Set the installation folder path • Specify the input data library and input file • Output data library and file name (final data)
This final data was linked to the Neighbourhood Conversion File. Analyses and counts were performed on this final data.
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All Cause Hospitalization. Inpatient Discharges
Table 1: Number of Neighbourhoods for all causes of Hospitalizations by Age and Sex in Windsor and Chatham sub regions, CY2015 CY2016 CY2017
Sex agegrp Valid Total %Valid 00-09 38 38 100.0% ALL 10--19 38 38 100.0% 20-44 38 38 100.0% 45-64 38 38 100.0% 65+ 38 38 100.0%
Table 2: Number of Neighbourhoods for all causes of Hospitalizations by Age in Females in Windsor and Chatham sub regions, CY2015 CY2016 CY2017
Sex agegrp Valid Total %Valid 00-09 38 38 100.0% 10--19 38 38 100.0% FEMALE 20-44 38 38 100.0% 45-64 38 38 100.0% 65+ 38 38 100.0%
Table 3: Number of Neighbourhoods for all causes of Hospitalizations by Age in Males in Windsor and Chatham sub regions, CY2015 CY2016 CY2017
Sex agegrp Valid Total %Valid 00-09 38 38 100.0% 10--19 38 38 100.0% MALE 20-44 38 38 100.0% 45-64 38 38 100.0% 65+ 38 38 100.0% Table 4: Number of Neighbourhoods for all causes of Hospitalizations by Age and Sex in Windsor and Chatham sub regions, CY2015
Sex agegrp Valid Total %Valid 00-09 38 38 100.0% ALL 10--19 38 38 100.0% 20-44 38 38 100.0% 45-64 38 38 100.0% 65+ 38 38 100.0%
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Table 5: Number of Neighbourhoods for all causes of Hospitalizations by Age in Females in Windsor and Chatham sub regions, CY2015
Sex agegrp Caution Suppress Valid %Caution %Suppress %Valid Total
00-09 4 38 0.0% 10.5% 100.0% 38 10--19 2 36 0.0% 5.2% 94.7% 38 FEMALE 20-44 38 0.0% 0.0% 100.0% 38 45-64 38 0.0% 0.0% 100.0% 38 65+ 38 0.0% 0.0% 100.0% 38
Table 6: Number of Neighbourhoods for all causes of Hospitalizations by Age in Males in Windsor and Chatham sub regions, CY2015
Sex agegrp Caution Suppress Valid %Caution %Suppress %Valid Total 00-09 38 0.0% 0.0% 100.0% 38 10--19 2 36 0.0% 5.2% 38 MALE 20-44 38 0.0% 0.0% 100.0% 38 45-64 38 0.0% 0.0% 100.0% 38 65+ 38 0.0% 0.0% 100.0% 38
Table 7: Number of Neighbourhoods for all causes of Hospitalizations by Age and Sex in Windsor and Chatham sub regions, CY2016
Sex agegrp Valid Total %Valid 00-09 38 38 100.0% ALL 10--19 38 38 100.0% 20-44 38 38 100.0% 45-64 38 38 100.0% 65+ 38 38 100.0%
Table 8: Number of Neighbourhoods for all causes of Hospitalizations by Age in Females in Windsor and Chatham sub regions, CY2016
Sex agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 38 38 0.0% 0.0% 100.0% 10--19 1 37 38 0.0% 2.63% 97.3% FEMALE 20-44 38 38 0.0% 0.0% 100.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
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Table 9: Number of Neighbourhoods for all causes of Hospitalizations by Age in Males in Windsor and Chatham sub regions, CY2016
Sex agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 38 38 0.0% 0.0% 100.0% 10--19 3 35 38 0.0% 7.8% 92.1% FEMALE 20-44 38 38 0.0% 0.0% 100.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 10: Number of Neighbourhoods for all causes of Hospitalizations by Age and Sex in Windsor and Chatham sub regions, CY2017
Sex agegrp Valid Total %Valid 00-09 38 38 100.0% ALL 10--19 38 38 100.0% 20-44 38 38 100.0% 45-64 38 38 100.0% 65+ 38 38 100.0%
Table 11: Number of Neighbourhoods for all causes of Hospitalizations by Age in Females in Windsor and Chatham sub regions, CY2017
Sex agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 38 38 0.0% 0.0% 100.0% 10--19 1 37 38 0.0% 2.63% 97.3% FEMALE 20-44 38 38 0.0% 0.0% 100.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 12: Number of Neighbourhoods for all causes of Hospitalizations by Age in Males in Windsor and Chatham sub regions, CY2017
Sex agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 38 38 0.0% 0.0% 100.0% 10--19 3 35 38 0.0% 7.8% 92.1% MALE 20-44 38 38 0.0% 0.0% 100.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
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Premature Mortality
Data used for testing Premature Mortality Ontario Mortality Data Discharges, Intellihealth, Extracted: March, 2019
Table 13: Number of Neighbourhoods by flag type, stratified by Age and Sex CY2013 CY2014 CY2015
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid
00-09 6 32 38 15.0% 0.0% 84.0% ALL 10--19 17 21 38 44.0% 0.0% 55.0% 20-44 1 37 38 0.0% 2.6% 97.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 14: Number of Neighbourhoods by flag type, stratified by Age in Females CY2013 CY2014 CY2015
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid
00-09 13 25 38 7.0% 0.0% 65.0% FEMALE 10--19 27 11 38 71.0% 0.0% 28.0% 20-44 4 34 38 0.0% 10.0% 89.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 15: Number of Neighbourhoods by flag type, stratified by Age in Males CY2013 CY2014 CY2015
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid
00-09 16 22 38 42.1% 0.0% 57.0% MALE 10--19 12 16 38 31.5% 0.0% 42.0% 20-44 2 36 38 0.0% 5.2% 94.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 16: Number of Neighbourhoods by flag type, stratified by Age CY2013
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid
00-09 20 18 38 0.52 0.0% 47.0% ALL 10--19 32 6 38 0.84 0.0% 15.0% 20-44 4 34 38 0.0% 10.5% 89.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
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Table 17: Number of Neighbourhoods by flag type, stratified by Age in Females CY2013
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 26 12 38 64.0% 0.0% 31.0% FEMALE 10--19 35 3 38 92.0% 0.0% 7.0% 20-44 13 25 38 34.0% 0.0% 65.0% 45-64 1 37 38 0.0% 2.0% 97.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 18: Number of Neighbourhoods by flag type, stratified by Age in Males CY2013
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 31 7 38 81.0% 0.0% 18.0% MALE 10--19 34 4 38 89.0% 0.0% 10.0% 20-44 6 32 38 16.0% 0.0% 84.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 19: Number of Neighbourhoods by flag type, stratified by Age CY2014
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 22 16 38 57.0% 0.0% 42.0% ALL 10--19 24 14 38 63.0% 0.0% 36.0% 20-44 3 35 38 0.0% 7.0% 92.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 20: Number of Neighbourhoods by flag type, stratified by Age in Females CY2014
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 30 8 38 78.0% 0.0% 21.0% FEMALE 10--19 32 6 38 84.0% 0.0% 15.0% 20-44 17 21 38 44.0% 0.0% 55.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
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Table 21: Number of Neighbourhoods by flag type, stratified by Age in Males CY2014
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 25 13 38 65.0% 0.0% 34.0% MALE 10--19 30 8 38 78.0% 0.0% 21.0% 20-44 6 32 38 15.0% 0.0% 84.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 22: Number of Neighbourhoods by flag type, stratified by Age CY2015
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 20 18 38 52.0% 0.0% 47.0% ALL 10--19 29 9 38 76.0% 0.0% 23.0% 20-44 7 31 38 18.0% 0.0% 81.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 23: Number of Neighbourhoods by flag type, stratified by Age in Females CY2015
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid 00-09 27 11 38 71.0% 0.0% 28.0% FEMALE 10--19 36 2 38 94.0% 0.0% 5.0% 20-44 12 26 38 31.0% 0.0% 68.0% 45-64 1 37 38 0.0% 2.0% 97.0% 65+ 38 38 0.0% 0.0% 100.0%
Table 24: Number of Neighbourhoods by flag type, stratified by Age in Males CY2015
agegrp Caution Suppress Valid Total %Caution %Suppress %Valid
00-09 29 9 38 76.0% 0.0% 23.0% MALE 10--19 30 8 38 78.0% 0.0% 21.0% 20-44 12 26 38 31.0% 0.0% 68.0% 45-64 38 38 0.0% 0.0% 100.0% 65+ 38 38 0.0% 0.0% 100.0%
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Table 25: Census 2006 count age and sex stratification (Female+Male)
Neighbourhood_ID Age group Total Pop
A1 0 to 9 Total 1075 10 to 19 Total 1270 20 to 44 Total 2845 45 to 64 Total 2545 65+ Total 890
A2 0 to 9 Total 1265 10 to 19 Total 1570 20 to 44 Total 3565 45 to 64 Total 2825 65+ Total 1485
CK1 0 to 9 Total 750 10 to 19 Total 875 20 to 44 Total 1980 45 to 64 Total 1755 65+ Total 890
CK2 0 to 9 Total 895 10 to 19 Total 1165 20 to 44 Total 2530 45 to 64 Total 2465 65+ Total 1480
CK3 0 to 9 Total 1045 10 to 19 Total 1245 20 to 44 Total 2500 45 to 64 Total 2290 65+ Total 1345
CK4 0 to 9 Total 920 10 to 19 Total 1260 20 to 44 Total 2725 45 to 64 Total 3160 65+ Total 1570
CK5 0 to 9 Total 995 10 to 19 Total 1105 20 to 44 Total 2600 45 to 64 Total 1835 65+ Total 1045
CK6 0 to 9 Total 715 10 to 19 Total 935 20 to 44 Total 2180 45 to 64 Total 2095 65+ Total 1055
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Neighbourhood_ID Age group Total Pop
CK7 0 to 9 Total 1315 10 to 19 Total 1600 20 to 44 Total 3670 45 to 64 Total 3020 65+ Total 1630
CK8 0 to 9 Total 1085 10 to 19 Total 1255 20 to 44 Total 3255 45 to 64 Total 2590 65+ Total 1495
CK9 0 to 9 Total 1145 10 to 19 Total 1180 20 to 44 Total 2710 45 to 64 Total 2020 65+ Total 1235
E1 0 to 9 Total 810 10 to 19 Total 990 20 to 44 Total 2230 45 to 64 Total 1925 65+ Total 1140
E2 0 to 9 Total 1440 10 to 19 Total 1925 20 to 44 Total 4085 45 to 64 Total 3740 65+ Total 1740
K1 0 to 9 Total 925 10 to 19 Total 1245 20 to 44 Total 2725 45 to 64 Total 2115 65+ Total 945
K2 0 to 9 Total 1440 10 to 19 Total 1655 20 to 44 Total 4065 45 to 64 Total 3575 65+ Total 2175
L1 0 to 9 Total 1640 10 to 19 Total 2105 20 to 44 Total 4530 45 to 64 Total 4370 65+ Total 1575
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Neighbourhood_ID Age group Total Pop
L2 0 to 9 Total 1070 10 to 19 Total 1200 20 to 44 Total 2420 45 to 64 Total 2035 65+ Total 570
L3 0 to 9 Total 1835 10 to 19 Total 1680 20 to 44 Total 4420 45 to 64 Total 2655 65+ Total 1005
LE1 0 to 9 Total 2910 10 to 19 Total 3040 20 to 44 Total 7620 45 to 64 Total 5180 65+ Total 3885
LE2 0 to 9 Total 985 10 to 19 Total 1195 20 to 44 Total 2320 45 to 64 Total 1485 65+ Total 595
LS1 0 to 9 Total 2035 10 to 19 Total 2200 20 to 44 Total 4900 45 to 64 Total 3430 65+ Total 955
LS2 0 to 9 Total 695 10 to 19 Total 840 20 to 44 Total 1705 45 to 64 Total 1220 65+ Total 570
LS3 0 to 9 Total 645 10 to 19 Total 805 20 to 44 Total 1765 45 to 64 Total 1605 65+ Total 675
T1 0 to 9 Total 1915 10 to 19 Total 2845 20 to 44 Total 5575 45 to 64 Total 5425 65+ Total 1830
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Neighbourhood_ID Age group Total Pop
T2 0 to 9 Total 790 10 to 19 Total 1025 20 to 44 Total 2150 45 to 64 Total 2030 65+ Total 670
W1 0 to 9 Total 1415 10 to 19 Total 1190 20 to 44 Total 3720 45 to 64 Total 2660 65+ Total 1520
W2 0 to 9 Total 2105 10 to 19 Total 2515 20 to 44 Total 7135 45 to 64 Total 5760 65+ Total 3635
W3 0 to 9 Total 2650 10 to 19 Total 2660 20 to 44 Total 8240 45 to 64 Total 5520 65+ Total 3730
W4 0 to 9 Total 1635 10 to 19 Total 1905 20 to 44 Total 5770 45 to 64 Total 2845 65+ Total 1875
W5 0 to 9 Total 2830 10 to 19 Total 2370 20 to 44 Total 6560 45 to 64 Total 3720 65+ Total 2530
W6 0 to 9 Total 1665 10 to 19 Total 2300 20 to 44 Total 4850 45 to 64 Total 4235 65+ Total 2980
W7 0 to 9 Total 2185 10 to 19 Total 2255 20 to 44 Total 5750 45 to 64 Total 3450 65+ Total 1470
ESC LHIN | Mapping Neighbourhoods | Page 20 of 47
Neighbourhood_ID Age group Total Pop
W8 0 to 9 Total 830 10 to 19 Total 815 20 to 44 Total 1920 45 to 64 Total 1210 65+ Total 780
W9 0 to 9 Total 1175 10 to 19 Total 1410 20 to 44 Total 5650 45 to 64 Total 2660 65+ Total 1850
W10 0 to 9 Total 1510 10 to 19 Total 1925 20 to 44 Total 4695 45 to 64 Total 3920 65+ Total 1370
W11 0 to 9 Total 2370 10 to 19 Total 2375 20 to 44 Total 6280 45 to 64 Total 4405 65+ Total 2575
W12 0 to 9 Total 1480 10 to 19 Total 1860 20 to 44 Total 5395 45 to 64 Total 3625 65+ Total 1790
W13 0 to 9 Total 3345 10 to 19 Total 3550 20 to 44 Total 12665 45 to 64 Total 7635 65+ Total 4815
ESC LHIN | Mapping Neighbourhoods | Page 21 of 47
Table 26: Census 2006 count age and sex stratification Female
Neighbourhood_ID Age group Total Pop
A1 0 to 9 Female 510 10 to 19 Female 675 20 to 44 Female 1405 45 to 64 Female 1195 65+ Female 485
A2 0 to 9 Female 605 10 to 19 Female 785 20 to 44 Female 1820 45 to 64 Female 1455 65+ Female 870
CK1 0 to 9 Female 385 10 to 19 Female 445 20 to 44 Female 965 45 to 64 Female 900 65+ Female 490
CK2 0 to 9 Female 425 10 to 19 Female 595 20 to 44 Female 1240 45 to 64 Female 1260 65+ Female 765
CK3 0 to 9 Female 535 10 to 19 Female 620 20 to 44 Female 1250 45 to 64 Female 1130 65+ Female 735
CK4 0 to 9 Female 455 10 to 19 Female 615 20 to 44 Female 1305 45 to 64 Female 1545 65+ Female 840
CK5 0 to 9 Female 500 10 to 19 Female 575 20 to 44 Female 1255 45 to 64 Female 920 65+ Female 565
CK6 0 to 9 Female 355 10 to 19 Female 465 20 to 44 Female 1135 45 to 64 Female 1140 65+ Female 585
ESC LHIN | Mapping Neighbourhoods | Page 22 of 47
Neighbourhood_ID Age group Total Pop
CK7 0 to 9 Female 665 10 to 19 Female 800 20 to 44 Female 1945 45 to 64 Female 1575 65+ Female 1045
CK8 0 to 9 Female 555 10 to 19 Female 605 20 to 44 Female 1645 45 to 64 Female 1295 65+ Female 870
CK9 0 to 9 Female 600 10 to 19 Female 585 20 to 44 Female 1430 45 to 64 Female 1015 65+ Female 755
E1 0 to 9 Female 400 10 to 19 Female 440 20 to 44 Female 1150 45 to 64 Female 970 65+ Female 700
E2 0 to 9 Female 650 10 to 19 Female 920 20 to 44 Female 1975 45 to 64 Female 1865 65+ Female 925
K1 0 to 9 Female 455 10 to 19 Female 585 20 to 44 Female 1255 45 to 64 Female 995 65+ Female 520
K2 0 to 9 Female 720 10 to 19 Female 815 20 to 44 Female 1975 45 to 64 Female 1845 65+ Female 1210
L1 0 to 9 Female 820 10 to 19 Female 1000 20 to 44 Female 2235 45 to 64 Female 2145 65+ Female 815
ESC LHIN | Mapping Neighbourhoods | Page 23 of 47
Neighbourhood_ID Age group Total Pop
L2 0 to 9 Female 510 10 to 19 Female 595 20 to 44 Female 1230 45 to 64 Female 1020 65+ Female 290
L3 0 to 9 Female 875 10 to 19 Female 825 20 to 44 Female 2255 45 to 64 Female 1315 65+ Female 570
LE1 0 to 9 Female 1430 10 to 19 Female 1490 20 to 44 Female 3515 45 to 64 Female 2605 65+ Female 2295
LE2 0 to 9 Female 440 10 to 19 Female 560 20 to 44 Female 1015 45 to 64 Female 660 65+ Female 320
LS1 0 to 9 Female 970 10 to 19 Female 1040 20 to 44 Female 2535 45 to 64 Female 1685 65+ Female 460
LS2 0 to 9 Female 320 10 to 19 Female 435 20 to 44 Female 900 45 to 64 Female 635 65+ Female 305
LS3 0 to 9 Female 305 10 to 19 Female 395 20 to 44 Female 895 45 to 64 Female 800 65+ Female 320
T1 0 to 9 Female 950 10 to 19 Female 1385 20 to 44 Female 2930 45 to 64 Female 2740 65+ Female 990
ESC LHIN | Mapping Neighbourhoods | Page 24 of 47
Neighbourhood_ID Age group Total Pop
T2 0 to 9 Female 390 10 to 19 Female 515 20 to 44 Female 1075 45 to 64 Female 990 65+ Female 335
W1 0 to 9 Female 725 10 to 19 Female 565 20 to 44 Female 1925 45 to 64 Female 1415 65+ Female 860
W2 0 to 9 Female 975 10 to 19 Female 1245 20 to 44 Female 3545 45 to 64 Female 3000 65+ Female 2095
W3 0 to 9 Female 1335 10 to 19 Female 1305 20 to 44 Female 4210 45 to 64 Female 2770 65+ Female 2315
W4 0 to 9 Female 775 10 to 19 Female 925 20 to 44 Female 2815 45 to 64 Female 1460 65+ Female 1090
W5 0 to 9 Female 1350 10 to 19 Female 1145 20 to 44 Female 3315 45 to 64 Female 1890 65+ Female 1450
W6 0 to 9 Female 810 10 to 19 Female 1085 20 to 44 Female 2460 45 to 64 Female 2220 65+ Female 1690
W7 0 to 9 Female 1105 10 to 19 Female 1125 20 to 44 Female 2995 45 to 64 Female 1725 65+ Female 840
ESC LHIN | Mapping Neighbourhoods | Page 25 of 47
Neighbourhood_ID Age group Total Pop
W8 0 to 9 Female 425 10 to 19 Female 410 20 to 44 Female 1020 45 to 64 Female 610 65+ Female 405
W9 0 to 9 Female 575 10 to 19 Female 705 20 to 44 Female 2660 45 to 64 Female 1290 65+ Female 1130
W10 0 to 9 Female 740 10 to 19 Female 915 20 to 44 Female 2345 45 to 64 Female 2055 65+ Female 735
W11 0 to 9 Female 1165 10 to 19 Female 1185 20 to 44 Female 3310 45 to 64 Female 2325 65+ Female 1555
W12 0 to 9 Female 770 10 to 19 Female 930 20 to 44 Female 2715 45 to 64 Female 1790 65+ Female 1045
W13 0 to 9 Female 1660 10 to 19 Female 1735 20 to 44 Female 6155 45 to 64 Female 3795 65+ Female 2845
ESC LHIN | Mapping Neighbourhoods | Page 26 of 47
Table 27: Census 2006 count age and sex stratification Male
Neighbourhood_ID Age group Total pop
A1 0 to 9 Male 565 10 to 19 Male 615 20 to 44 Male 1420 45 to 64 Male 1325 65+ Male 450
A2 0 to 9 Male 630 10 to 19 Male 830 20 to 44 Male 1720 45 to 64 Male 1360 65+ Male 590
CK1 0 to 9 Male 365 10 to 19 Male 430 20 to 44 Male 980 45 to 64 Male 840 65+ Male 365
CK2 0 to 9 Male 455 10 to 19 Male 595 20 to 44 Male 1275 45 to 64 Male 1235 65+ Male 670
CK3 0 to 9 Male 510 10 to 19 Male 600 20 to 44 Male 1265 45 to 64 Male 1135 65+ Male 575
CK4 0 to 9 Male 460 10 to 19 Male 630 20 to 44 Male 1415 45 to 64 Male 1640 65+ Male 710
CK5 0 to 9 Male 515 10 to 19 Male 530 20 to 44 Male 1320 45 to 64 Male 910 65+ Male 465
CK6 0 to 9 Male 375 10 to 19 Male 480 20 to 44 Male 1060 45 to 64 Male 955 65+ Male 430
ESC LHIN | Mapping Neighbourhoods | Page 27 of 47
Neighbourhood_ID Age group Total pop
CK7 0 to 9 Male 670 10 to 19 Male 790 20 to 44 Male 1765 45 to 64 Male 1450 65+ Male 585
CK8 0 to 9 Male 555 10 to 19 Male 650 20 to 44 Male 1630 45 to 64 Male 1265 65+ Male 650
CK9 0 to 9 Male 575 10 to 19 Male 585 20 to 44 Male 1275 45 to 64 Male 965 65+ Male 435
E1 0 to 9 Male 405 10 to 19 Male 545 20 to 44 Male 1125 45 to 64 Male 960 65+ Male 445
E2 0 to 9 Male 750 10 to 19 Male 970 20 to 44 Male 2090 45 to 64 Male 1885 65+ Male 800
K1 0 to 9 Male 490 10 to 19 Male 655 20 to 44 Male 1450 45 to 64 Male 1125 65+ Male 420
K2 0 to 9 Male 745 10 to 19 Male 840 20 to 44 Male 2090 45 to 64 Male 1760 65+ Male 925
L1 0 to 9 Male 890 10 to 19 Male 1095 20 to 44 Male 2315 45 to 64 Male 2245 65+ Male 790
ESC LHIN | Mapping Neighbourhoods | Page 28 of 47
Neighbourhood_ID Age group Total pop
L2 0 to 9 Male 565 10 to 19 Male 600 20 to 44 Male 1190 45 to 64 Male 1025 65+ Male 315
L3 0 to 9 Male 945 10 to 19 Male 870 20 to 44 Male 2190 45 to 64 Male 1365 65+ Male 470
LE1 0 to 9 Male 1505 10 to 19 Male 1555 20 to 44 Male 4025 45 to 64 Male 2600 65+ Male 1540
LE2 0 to 9 Male 520 10 to 19 Male 595 20 to 44 Male 1320 45 to 64 Male 825 65+ Male 310
LS1 0 to 9 Male 1055 10 to 19 Male 1125 20 to 44 Male 2390 45 to 64 Male 1735 65+ Male 430
LS2 0 to 9 Male 360 10 to 19 Male 410 20 to 44 Male 800 45 to 64 Male 600 65+ Male 250
LS3 0 to 9 Male 340 10 to 19 Male 405 20 to 44 Male 880 45 to 64 Male 795 65+ Male 330
T1 0 to 9 Male 955 10 to 19 Male 1465 20 to 44 Male 2585 45 to 64 Male 2670 65+ Male 790
ESC LHIN | Mapping Neighbourhoods | Page 29 of 47
Neighbourhood_ID Age group Total pop
T2 0 to 9 Male 395 10 to 19 Male 500 20 to 44 Male 1040 45 to 64 Male 1040 65+ Male 385
W1 0 to 9 Male 690 10 to 19 Male 625 20 to 44 Male 1810 45 to 64 Male 1265 65+ Male 655
W2 0 to 9 Male 1115 10 to 19 Male 1320 20 to 44 Male 3640 45 to 64 Male 2765 65+ Male 1535
W3 0 to 9 Male 1380 10 to 19 Male 1335 20 to 44 Male 4060 45 to 64 Male 2660 65+ Male 1435
W4 0 to 9 Male 880 10 to 19 Male 1010 20 to 44 Male 2895 45 to 64 Male 1420 65+ Male 725
W5 0 to 9 Male 1490 10 to 19 Male 1195 20 to 44 Male 3270 45 to 64 Male 1780 65+ Male 1085
W6 0 to 9 Male 840 10 to 19 Male 1175 20 to 44 Male 2360 45 to 64 Male 2085 65+ Male 1330
W7 0 to 9 Male 1060 10 to 19 Male 1180 20 to 44 Male 2790 45 to 64 Male 1685 65+ Male 630
ESC LHIN | Mapping Neighbourhoods | Page 30 of 47
Neighbourhood_ID Age group Total pop
W8 0 to 9 Male 435 10 to 19 Male 430 20 to 44 Male 915 45 to 64 Male 600 65+ Male 390
W9 0 to 9 Male 665 10 to 19 Male 675 20 to 44 Male 2925 45 to 64 Male 1300 65+ Male 700
W10 0 to 9 Male 790 10 to 19 Male 1020 20 to 44 Male 2345 45 to 64 Male 1895 65+ Male 670
W11 0 to 9 Male 1230 10 to 19 Male 1210 20 to 44 Male 2925 45 to 64 Male 2060 65+ Male 1065
W12 0 to 9 Male 720 10 to 19 Male 900 20 to 44 Male 2685 45 to 64 Male 1810 65+ Male 750
W13 0 to 9 Male 1690 10 to 19 Male 1870 20 to 44 Male 6400 45 to 64 Male 3835 65+ Male 1960
ESC LHIN | Mapping Neighbourhoods | Page 31 of 47
Table 28: Census 2016 count age and sex stratification (Female+Male)
Neighbourhood_ID Age group Total pop
A1 0 to 9 Total 1305 10 to 19 Total 1605 20 to 44 Total 4570 45 to 64 Total 3920 65+ Total 1960
A2 0 to 9 Total 940 10 to 19 Total 1210 20 to 44 Total 3900 45 to 64 Total 2980 65+ Total 2020
CK1 0 to 9 Total 1015 10 to 19 Total 1115 20 to 44 Total 4145 45 to 64 Total 3055 65+ Total 2115
CK2 0 to 9 Total 1520 10 to 19 Total 1495 20 to 44 Total 5685 45 to 64 Total 4055 65+ Total 2645
CK3 0 to 9 Total 1055 10 to 19 Total 1330 20 to 44 Total 4485 45 to 64 Total 3435 65+ Total 2375
CK4 0 to 9 Total 1510 10 to 19 Total 1540 20 to 44 Total 6365 45 to 64 Total 4695 65+ Total 3345
CK5 0 to 9 Total 1315 10 to 19 Total 1500 20 to 44 Total 4625 45 to 64 Total 3175 65+ Total 1995
CK6 0 to 9 Total 660 10 to 19 Total 815 20 to 44 Total 3285 45 to 64 Total 2240 65+ Total 1965
ESC LHIN | Mapping Neighbourhoods | Page 32 of 47
Neighbourhood_ID Age group Total pop
CK7 0 to 9 Total 1540 10 to 19 Total 1735 20 to 44 Total 5815 45 to 64 Total 4040 65+ Total 2735
CK8 0 to 9 Total 1240 10 to 19 Total 1295 20 to 44 Total 4550 45 to 64 Total 3295 65+ Total 2070
CK9 0 to 9 Total 1095 10 to 19 Total 1055 20 to 44 Total 4320 45 to 64 Total 2440 65+ Total 2130
E1 0 to 9 Total 815 10 to 19 Total 970 20 to 44 Total 3125 45 to 64 Total 2090 65+ Total 1495
E2 0 to 9 Total 1135 10 to 19 Total 1430 20 to 44 Total 4815 45 to 64 Total 4440 65+ Total 2545
K1 0 to 9 Total 910 10 to 19 Total 945 20 to 44 Total 2975 45 to 64 Total 2260 65+ Total 1155
K2 0 to 9 Total 1495 10 to 19 Total 1550 20 to 44 Total 6150 45 to 64 Total 3985 65+ Total 3160
L1 0 to 9 Total 1505 10 to 19 Total 1785 20 to 44 Total 5495 45 to 64 Total 4740 65+ Total 2485
ESC LHIN | Mapping Neighbourhoods | Page 33 of 47
Neighbourhood_ID Age group Total pop
L2 0 to 9 Total 800 10 to 19 Total 1210 20 to 44 Total 2615 45 to 64 Total 2385 65+ Total 1015
L3 0 to 9 Total 2105 10 to 19 Total 2280 20 to 44 Total 6120 45 to 64 Total 4045 65+ Total 1910
LE1 0 to 9 Total 2500 10 to 19 Total 2505 20 to 44 Total 9565 45 to 64 Total 5730 65+ Total 4565
LE2 0 to 9 Total 860 10 to 19 Total 915 20 to 44 Total 2480 45 to 64 Total 1720 65+ Total 760
LS1 0 to 9 Total 1735 10 to 19 Total 2295 20 to 44 Total 5245 45 to 64 Total 4675 65+ Total 1775
LS2 0 to 9 Total 940 10 to 19 Total 1240 20 to 44 Total 3750 45 to 64 Total 2840 65+ Total 1870
LS3 0 to 9 Total 695 10 to 19 Total 780 20 to 44 Total 2400 45 to 64 Total 1795 65+ Total 1010
T1 0 to 9 Total 1515 10 to 19 Total 2100 20 to 44 Total 6245 45 to 64 Total 5440 65+ Total 3215
ESC LHIN | Mapping Neighbourhoods | Page 34 of 47
Neighbourhood_ID Age group Total pop
T2 0 to 9 Total 580 10 to 19 Total 870 20 to 44 Total 2410 45 to 64 Total 2125 65+ Total 1250
W1 0 to 9 Total 1005 10 to 19 Total 1545 20 to 44 Total 5140 45 to 64 Total 3700 65+ Total 3130
W2 0 to 9 Total 1945 10 to 19 Total 1900 20 to 44 Total 8070 45 to 64 Total 6115 65+ Total 4180
W3 0 to 9 Total 2315 10 to 19 Total 2335 20 to 44 Total 9045 45 to 64 Total 6095 65+ Total 4415
W4 0 to 9 Total 1460 10 to 19 Total 1360 20 to 44 Total 4775 45 to 64 Total 3310 65+ Total 1855
W5 0 to 9 Total 2445 10 to 19 Total 3170 20 to 44 Total 8465 45 to 64 Total 5510 65+ Total 3575
W6 0 to 9 Total 1505 10 to 19 Total 1995 20 to 44 Total 6220 45 to 64 Total 4625 65+ Total 3210
W7 0 to 9 Total 1675 10 to 19 Total 2070 20 to 44 Total 5485 45 to 64 Total 4330 65+ Total 2135
ESC LHIN | Mapping Neighbourhoods | Page 35 of 47
Neighbourhood_ID Age group Total pop
W8 0 to 9 Total 1400 10 to 19 Total 1970 20 to 44 Total 4115 45 to 64 Total 2755 65+ Total 1315
W9 0 to 9 Total 1115 10 to 19 Total 1170 20 to 44 Total 4005 45 to 64 Total 2750 65+ Total 1775
W10 0 to 9 Total 1790 10 to 19 Total 1680 20 to 44 Total 5940 45 to 64 Total 3715 65+ Total 2360
W11 0 to 9 Total 2010 10 to 19 Total 2050 20 to 44 Total 7310 45 to 64 Total 4795 65+ Total 3290
W12 0 to 9 Total 1370 10 to 19 Total 1325 20 to 44 Total 4720 45 to 64 Total 3990 65+ Total 1980
W13 0 to 9 Total 3050 10 to 19 Total 2985 20 to 44 Total 11180 45 to 64 Total 8520 65+ Total 5080
ESC LHIN | Mapping Neighbourhoods | Page 36 of 47
Table 29: Census 2016 count age and sex stratification Female
Neighbourhood_ID Age group Total pop
A1 0 to 9 Female 655 10 to 19 Female 745 20 to 44 Female 1715 45 to 64 Female 1885 65+ Female 1000
A2 0 to 9 Female 450 10 to 19 Female 570 20 to 44 Female 1375 45 to 64 Female 1565 65+ Female 1135
CK1 0 to 9 Female 570 10 to 19 Female 570 20 to 44 Female 1355 45 to 64 Female 1550 65+ Female 1145
CK2 0 to 9 Female 650 10 to 19 Female 700 20 to 44 Female 1555 45 to 64 Female 2035 65+ Female 1395
CK3 0 to 9 Female 570 10 to 19 Female 640 20 to 44 Female 1350 45 to 64 Female 1695 65+ Female 1245
CK4 0 to 9 Female 595 10 to 19 Female 750 20 to 44 Female 1715 45 to 64 Female 2340 65+ Female 1715
CK5 0 to 9 Female 635 10 to 19 Female 735 20 to 44 Female 1620 45 to 64 Female 1575 65+ Female 1055
CK6 0 to 9 Female 350 10 to 19 Female 425 20 to 44 Female 1010 45 to 64 Female 1200 65+ Female 1155
ESC LHIN | Mapping Neighbourhoods | Page 37 of 47
Neighbourhood_ID Age group Total pop
CK7 0 to 9 Female 790 10 to 19 Female 825 20 to 44 Female 2095 45 to 64 Female 2170 65+ Female 1555
CK8 0 to 9 Female 665 10 to 19 Female 635 20 to 44 Female 1710 45 to 64 Female 1670 65+ Female 1210
CK9 0 to 9 Female 525 10 to 19 Female 520 20 to 44 Female 1335 45 to 64 Female 1245 65+ Female 1245
E1 0 to 9 Female 350 10 to 19 Female 465 20 to 44 Female 1125 45 to 64 Female 1040 65+ Female 855
E2 0 to 9 Female 535 10 to 19 Female 710 20 to 44 Female 1635 45 to 64 Female 2230 65+ Female 1325
K1 0 to 9 Female 370 10 to 19 Female 490 20 to 44 Female 975 45 to 64 Female 1050 65+ Female 585
K2 0 to 9 Female 710 10 to 19 Female 750 20 to 44 Female 2000 45 to 64 Female 2030 65+ Female 1715
L1 0 to 9 Female 665 10 to 19 Female 845 20 to 44 Female 1805 45 to 64 Female 2360 65+ Female 1215
ESC LHIN | Mapping Neighbourhoods | Page 38 of 47
Neighbourhood_ID Age group Total pop
L2 0 to 9 Female 370 10 to 19 Female 585 20 to 44 Female 1005 45 to 64 Female 1200 65+ Female 500
L3 0 to 9 Female 1095 10 to 19 Female 1110 20 to 44 Female 2530 45 to 64 Female 2045 65+ Female 1025
LE1 0 to 9 Female 1130 10 to 19 Female 1240 20 to 44 Female 3140 45 to 64 Female 2945 65+ Female 2615
LE2 0 to 9 Female 435 10 to 19 Female 410 20 to 44 Female 900 45 to 64 Female 785 65+ Female 370
LS1 0 to 9 Female 845 10 to 19 Female 1095 20 to 44 Female 2240 45 to 64 Female 2350 65+ Female 920
LS2 0 to 9 Female 430 10 to 19 Female 610 20 to 44 Female 1345 45 to 64 Female 1480 65+ Female 1055
LS3 0 to 9 Female 370 10 to 19 Female 345 20 to 44 Female 845 45 to 64 Female 935 65+ Female 490
T1 0 to 9 Female 730 10 to 19 Female 1050 20 to 44 Female 2275 45 to 64 Female 2830 65+ Female 1765
ESC LHIN | Mapping Neighbourhoods | Page 39 of 47
Neighbourhood_ID Age group Total pop
T2 0 to 9 Female 285 10 to 19 Female 450 20 to 44 Female 835 45 to 64 Female 1080 65+ Female 655
W1 0 to 9 Female 675 10 to 19 Female 770 20 to 44 Female 1860 45 to 64 Female 2025 65+ Female 1740
W2 0 to 9 Female 875 10 to 19 Female 905 20 to 44 Female 3035 45 to 64 Female 3180 65+ Female 2375
W3 0 to 9 Female 1135 10 to 19 Female 1045 20 to 44 Female 3590 45 to 64 Female 3125 65+ Female 2590
W4 0 to 9 Female 685 10 to 19 Female 680 20 to 44 Female 2310 45 to 64 Female 1680 65+ Female 1015
W5 0 to 9 Female 1190 10 to 19 Female 1550 20 to 44 Female 3040 45 to 64 Female 2725 65+ Female 2085
W6 0 to 9 Female 755 10 to 19 Female 960 20 to 44 Female 2105 45 to 64 Female 2440 65+ Female 1755
W7 0 to 9 Female 850 10 to 19 Female 1050 20 to 44 Female 2375 45 to 64 Female 2170 65+ Female 1190
ESC LHIN | Mapping Neighbourhoods | Page 40 of 47
Neighbourhood_ID Age group Total pop
W8 0 to 9 Female 755 10 to 19 Female 945 20 to 44 Female 1880 45 to 64 Female 1315 65+ Female 700
W9 0 to 9 Female 580 10 to 19 Female 530 20 to 44 Female 2485 45 to 64 Female 1360 65+ Female 1045
W10 0 to 9 Female 695 10 to 19 Female 795 20 to 44 Female 2125 45 to 64 Female 1935 65+ Female 1210
W11 0 to 9 Female 940 10 to 19 Female 975 20 to 44 Female 2700 45 to 64 Female 2535 65+ Female 1935
W12 0 to 9 Female 645 10 to 19 Female 665 20 to 44 Female 2495 45 to 64 Female 2060 65+ Female 1070
W13 0 to 9 Female 1585 10 to 19 Female 1435 20 to 44 Female 5455 45 to 64 Female 4140 65+ Female 2790
ESC LHIN | Mapping Neighbourhoods | Page 41 of 47
Table 30: Census 2016 count age and sex stratification Male
Neighbourhood_ID Age group Total pop
A1 0 to 9 Male 670 10 to 19 Male 845 20 to 44 Male 1625 45 to 64 Male 1975 65+ Male 960
A2 0 to 9 Male 475 10 to 19 Male 625 20 to 44 Male 1310 45 to 64 Male 1400 65+ Male 885
CK1 0 to 9 Male 535 10 to 19 Male 590 20 to 44 Male 1315 45 to 64 Male 1475 65+ Male 950
CK2 0 to 9 Male 725 10 to 19 Male 795 20 to 44 Male 1615 45 to 64 Male 2110 65+ Male 1245
CK3 0 to 9 Male 500 10 to 19 Male 740 20 to 44 Male 1335 45 to 64 Male 1735 65+ Male 1140
CK4 0 to 9 Male 735 10 to 19 Male 740 20 to 44 Male 1740 45 to 64 Male 2365 65+ Male 1650
CK5 0 to 9 Male 720 10 to 19 Male 745 20 to 44 Male 1570 45 to 64 Male 1600 65+ Male 940
CK6 0 to 9 Male 380 10 to 19 Male 445 20 to 44 Male 900 45 to 64 Male 1015 65+ Male 815
ESC LHIN | Mapping Neighbourhoods | Page 42 of 47
Neighbourhood_ID Age group Total pop
CK7 0 to 9 Male 765 10 to 19 Male 875 20 to 44 Male 1905 45 to 64 Male 1915 65+ Male 1125
CK8 0 to 9 Male 640 10 to 19 Male 680 20 to 44 Male 1605 45 to 64 Male 1625 65+ Male 885
CK9 0 to 9 Male 600 10 to 19 Male 540 20 to 44 Male 1315 45 to 64 Male 1180 65+ Male 880
E1 0 to 9 Male 435 10 to 19 Male 510 20 to 44 Male 985 45 to 64 Male 1005 65+ Male 640
E2 0 to 9 Male 625 10 to 19 Male 715 20 to 44 Male 1770 45 to 64 Male 2145 65+ Male 1215
K1 0 to 9 Male 475 10 to 19 Male 480 20 to 44 Male 1085 45 to 64 Male 1205 65+ Male 580
K2 0 to 9 Male 825 10 to 19 Male 835 20 to 44 Male 2040 45 to 64 Male 1950 65+ Male 1435
L1 0 to 9 Male 705 10 to 19 Male 935 20 to 44 Male 1870 45 to 64 Male 2440 65+ Male 1235
ESC LHIN | Mapping Neighbourhoods | Page 43 of 47
Neighbourhood_ID Age group Total pop
L2 0 to 9 Male 430 10 to 19 Male 625 20 to 44 Male 940 45 to 64 Male 1185 65+ Male 505
L3 0 to 9 Male 1070 10 to 19 Male 1165 20 to 44 Male 2345 45 to 64 Male 1995 65+ Male 915
LE1 0 to 9 Male 1275 10 to 19 Male 1295 20 to 44 Male 3235 45 to 64 Male 2790 65+ Male 1975
LE2 0 to 9 Male 500 10 to 19 Male 500 20 to 44 Male 1050 45 to 64 Male 925 65+ Male 385
LS1 0 to 9 Male 910 10 to 19 Male 1180 20 to 44 Male 2170 45 to 64 Male 2350 65+ Male 850
LS2 0 to 9 Male 485 10 to 19 Male 620 20 to 44 Male 1150 45 to 64 Male 1310 65+ Male 800
LS3 0 to 9 Male 315 10 to 19 Male 415 20 to 44 Male 830 45 to 64 Male 895 65+ Male 505
T1 0 to 9 Male 785 10 to 19 Male 1025 20 to 44 Male 2105 45 to 64 Male 2535 65+ Male 1445
ESC LHIN | Mapping Neighbourhoods | Page 44 of 47
Neighbourhood_ID Age group Total pop
T2 0 to 9 Male 325 10 to 19 Male 440 20 to 44 Male 850 45 to 64 Male 1085 65+ Male 600
W1 0 to 9 Male 700 10 to 19 Male 770 20 to 44 Male 1720 45 to 64 Male 1710 65+ Male 1395
W2 _0_to_9_Male 935 _10_to_19_Male 995 _20_to_44_Male 2995 _45_to_64_Male 2975 __65__Male 1800
W3 _0_to_9_Male 1220 _10_to_19_Male 1240 _20_to_44_Male 3325 _45_to_64_Male 2940 __65__Male 1855
W4 _0_to_9_Male 735 _10_to_19_Male 740 _20_to_44_Male 2630 _45_to_64_Male 1680 __65__Male 830
W5 _0_to_9_Male 1195 _10_to_19_Male 1650 _20_to_44_Male 2815 _45_to_64_Male 2730 __65__Male 1485
W6 _0_to_9_Male 790 _10_to_19_Male 1025 _20_to_44_Male 2140 _45_to_64_Male 2180 __65__Male 1460
W7 _0_to_9_Male 825 _10_to_19_Male 1015 _20_to_44_Male 2170 _45_to_64_Male 2155 __65__Male 955
ESC LHIN | Mapping Neighbourhoods | Page 45 of 47
Neighbourhood_ID Age group Total pop
W8 _0_to_9_Male 800 _10_to_19_Male 1015 _20_to_44_Male 1575 _45_to_64_Male 1450 __65__Male 620
W9 _0_to_9_Male 545 _10_to_19_Male 590 _20_to_44_Male 3055 _45_to_64_Male 1435 __65__Male 720
W10 0 to 9 Male 775 10 to 19 Male 905 20 to 44 Male 2040 45 to 64 Male 1800 65+ Male 1145
W11 0 to 9 Male 1010 10 to 19 Male 1035 20 to 44 Male 2485 45 to 64 Male 2290 65+ Male 1365
W12 0 to 9 Male 670 10 to 19 Male 680 20 to 44 Male 2345 45 to 64 Male 1950 65+ Male 895
W13 0 to 9 Male 1555 10 to 19 Male 1550 20 to 44 Male 5340 45 to 64 Male 4435 65+ Male 2295
ESC LHIN | Mapping Neighbourhoods | Page 46 of 47
ESC LHIN | Mapping Neighbourhoods | Page 47 of 47