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Use of GLA survey of
Londoners results in NHS
NEL
23 March 2023 LPSN Introduction to the Survey of Londoners
NEL Insights Team
• Integrated care systems (ICSs) are partnerships of organisations that come together to plan
and deliver joined up health and care services, and to improve the lives of people who live
and work in their area. NEL includes NHS organizations, the local authorities in the area as
well as place based partnerships and provider collaboratives.
• The ICSs bring partner organisations together to:
• improve outcomes in population health and healthcare
• tackle inequalities in outcomes, experience and access
• enhance productivity and value for money
• help the NHS support broader social and economic development.
• The GLA survey of London allows a detailed window into a number of areas not commonly
seen by the constituent organizations of NEL, and allows us to think about population
health as it stretches across wider determinants of health.
• NEL funded a “boost” sample to increase the resolution of the survey within NEL and allow
borough level analysis. 4,265 of the 8,630 responses came from NEL.
GLA Survey of Londoners in NEL
GLA Survey of Londoners | Insight project
Aim
To explore the experience and circumstances of people living in
NEL captured in the GLA survey, NEL and local authority public
health leads formed a steering and project group to:
• Identify key questions and conduct analysis
• Present key findings and conclusions
• Suggest future analysis and reflect on the benefit of the survey
Steering group
• Ellen Bloomer (NEL)
• Mike Brannan (Barking & Dagenham)
• Benhildah Dube (Barking & Dagenham)
• Diana Divajeva (Hackney)
• Lynne Kitson (Newham)
• Anthony Wakhisi (Havering)
• Michael Cheetham (NEL Insights)
• Natasha Hobbs (NEL Insights)
Analysts from the Insights Team
• Catherine Fell
• Julie Braithwaite
• Taran Jassi
Analytical rounds
1. Analysis of single questions - how do individuals within NEL
respond to the questions asked in the survey
2. Analysis of vulnerability in different domains – are individuals
in NEL particularly vulnerable to particular stressors and what
are the characteristics of those groups
3. Analysis of demographics of selected questions – what is the
demographic break down of the response to key questions
4. Statistical modelling of variables affecting financial
vulnerability and identification of risk factors for financial
vulnerability.
5. Topic modelling of free text responses – what are people
telling us in their own words.
Analysis is at NEL level – although individual questions in the
survey can be disaggregated to supply useful insight at local
authority level we have been advised by GLA not to combine
questions at the borough level meaning that rounds 2,3 and 4 had
to be done at NEL level. In addition we carried out the topic
modelling at NEL level due to only about half of responses
containing a free text comment.
Keyfinding:20%ofNELresidentshavenothadenoughmoneytobuyfood
Keyanalyticalfindings& conclusions| Demographicsof selectedquestions
• Large numbers (hundreds of thousands of individuals depending on the metric) struggle with financial and food security,
winter heating, housing, or loneliness within NEL, and may struggle with multiple issues. Examples include:
• 20% of NEL residents have not had enough money to buy food when needed in the last year. This is more often true for
those from ethnic minorities (e.g. 29% for black people against 12% for White British people), young people (31% for
those in the 16-24 age group), or long lasting health conditions (29%) as well as those who don’t speak English well or
were born outside the UK.
• 15% of residents have been unable to adequately heat their home. Notable differences from this include those with a
long lasting health condition (25%), those who don’t speak English well (37%) and those with a caring responsibility.
• 14% of residents consider their housing to be poor or very poor quality. This is a more common view among those who
are in the Asian, mixed or other ethnic groups (between 18-25%) or those with a long lasting health condition (21%).
• 20% of NEL residents with loans struggle to keep up with debt repayments. This is more noticeable in those of Black,
Asian or mixed ethnic groups (22-27%), or for those with a long lasting health condition (27%), those who don’t speak
English well (38%) and those who are young (35% for those 16-24).
• 28% of residents feel lonely some or often/all the time. This is especially so for the young (39% of those 16-24), those
with a long lasting health condition (39%).
Our analysis indicated that there were certain population groups who were
significantly more vulnerable to having difficulties in the financial domain,
namely:
• Non-white ethnic populations especially those within the black
ethnicity cohort who are Non-natal Londoners
• Single and young parents, especially where these factors are combined.
• Those with a life-limiting illness
• Unpaid Carers
• Younger people (under 24yrs of age)
Whilst descriptively we see a slight variation due to gender, our analysis
indicates that this is due to the higher prevalence of financial vulnerability
risk factors within the female population due social norms and other
influences rather than gender itself being a significant risk factor for
vulnerability.
Regression
Model
Marginal
Analysis
Input Variables Modelling Stage
Dependent Modelling
Variable
Fuel poverty
Food insecurity
Debt burden
Low savings
Demographic
• Age
• Ethnicity
Social/Risk
• Family status
• Disability &
Caring status
Conclusions
Financial vulnerability | Key findings
Gender
We excluded gender from our analysis. While we found slight
variation between male and females looking at the data
descriptively when we isolated the effect of gender on
financial vulnerability there was no significant difference
between men and women.
Looking at the data descriptively however, we see that several
risks for financial vulnerability are associated with a higher
proportion of women e.g. unpaid carers and single parents.
Statisticalmodellingoffinancialvulnerability| Gender
Ethnicity
We found that patterns of financial vulnerability varied
across ethnic groupings between Natal Londoners (those
who have always lived here) and Non-natal Londoners (those
who have moved here to live) with ethnicity having a
significantly smaller effect for Natal Londoners.
Our analysis indicated that White Non-Natal Londoners are
over 25% less likely to be financially vulnerable than their
Natal peers while Black Non-natal Londoners were 50% more
likely to have difficulties in this domain when compared to
their Natal peers.
Note: the 50% line on this and the following charts indicates
that an individual in particular group is more likely than not
to be financially vulnerable.
Statisticalmodellingoffinancialvulnerability| Ethnicity
Keyanalyticalfindings& conclusions| Freetextanalysis
• A topic modelling approach was used to extract common topics from the short free text question at the
end of the survey, asking respondents for anything else they wished to add.
• Respondents appear to show positive sentiment towards London as a whole but negativity towards their
local areas.
• Multiple topics found in free text responses are not covered in the survey. For example there are no/not
many questions on traffic and road use, issues with the surrounding area and policing and crime. These are
topics we found to exist within the responses.
• Older age bands are more negative towards public services compared to younger age bands.
• Sentiment towards the topic of housing varies with age, older age bands are more positive compared to
younger age bands.
• All demographics show negative sentiment towards the topic regarding local councils.
Biterm topic model |results
Topic
Number
Number of
responses (%
of total
responses)
Description of topic
Positive (% of
responses)
Negative (% of
responses)
1 141 (4%) Responses discuss public services like healthcare and policing, as well as public infrastructure. 42% 48%
2 312 (9%) Respondents discuss their local area and issues such as noise and cleanliness of their surrounding area. 32% 57%
3 753 (22%) How the respondents feel about London and their likes and dislikes about the city. 58% 31%
4 105 (3%) Focuses on cycling and cyclists in London as well as the general environmental infrastructure 49% 40%
5 458 (13%) Respondents discuss what London has to offer, focusing on what it offers culturally e.g. museums and galleries and in regards
to public transport e.g. freedom pass.
69% 25%
6 559 (16%) Respondents discuss housing and rent in London, with a focus on high costs and expensive housing. 34% 53%
7 62 (2%) This topic is a mix of parents discussing raising children in London and abuse suffered in London e.g. racism 39% 50%
8 453 (13%) Respondents discuss driving in London with a focus in congestion charge, traffic, changes to roads and pollution 23% 64%
9 165 (5%) This topic discusses the role of local councils in housing and areas in London but with an emphasis on new developments,
social housing and desired improvements.
30% 51%
10 161 (5%) This topic is mixed but is mainly comprised of personal reflections of living in London, personal circumstances and reflections on
the survey itself.
43% 47%
11 235 (7%) Respondents discuss crime in London with an emphasis on knife crime, safety, drugs and policing. 23% 67%
The GLA survey provided insight not available from other sources
• The GLA survey of Londoners is a rich source of data and shows the importance of this kind of snapshot
for understanding the NEL population. It has been used as evidence in our response to the cost of living
crisis, and forms an important resource for understanding our population as we develop our population
health management approaches.
• Linked individual level responses provide insight that needs careful analysis to extract the right message –
e.g. gender is not a significant variable in determining financial vulnerability but variables commonly
linked to gender are.
• The free text field can be useful for identifying topics of interest to residents. It can also be used to help
identify topic areas that should be covered in future structured surveys and gives a place for the voice of
our residents to come through in their own words.

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Survey of Londoners - 1

  • 1. Use of GLA survey of Londoners results in NHS NEL 23 March 2023 LPSN Introduction to the Survey of Londoners NEL Insights Team
  • 2. • Integrated care systems (ICSs) are partnerships of organisations that come together to plan and deliver joined up health and care services, and to improve the lives of people who live and work in their area. NEL includes NHS organizations, the local authorities in the area as well as place based partnerships and provider collaboratives. • The ICSs bring partner organisations together to: • improve outcomes in population health and healthcare • tackle inequalities in outcomes, experience and access • enhance productivity and value for money • help the NHS support broader social and economic development. • The GLA survey of London allows a detailed window into a number of areas not commonly seen by the constituent organizations of NEL, and allows us to think about population health as it stretches across wider determinants of health. • NEL funded a “boost” sample to increase the resolution of the survey within NEL and allow borough level analysis. 4,265 of the 8,630 responses came from NEL. GLA Survey of Londoners in NEL
  • 3. GLA Survey of Londoners | Insight project Aim To explore the experience and circumstances of people living in NEL captured in the GLA survey, NEL and local authority public health leads formed a steering and project group to: • Identify key questions and conduct analysis • Present key findings and conclusions • Suggest future analysis and reflect on the benefit of the survey Steering group • Ellen Bloomer (NEL) • Mike Brannan (Barking & Dagenham) • Benhildah Dube (Barking & Dagenham) • Diana Divajeva (Hackney) • Lynne Kitson (Newham) • Anthony Wakhisi (Havering) • Michael Cheetham (NEL Insights) • Natasha Hobbs (NEL Insights) Analysts from the Insights Team • Catherine Fell • Julie Braithwaite • Taran Jassi Analytical rounds 1. Analysis of single questions - how do individuals within NEL respond to the questions asked in the survey 2. Analysis of vulnerability in different domains – are individuals in NEL particularly vulnerable to particular stressors and what are the characteristics of those groups 3. Analysis of demographics of selected questions – what is the demographic break down of the response to key questions 4. Statistical modelling of variables affecting financial vulnerability and identification of risk factors for financial vulnerability. 5. Topic modelling of free text responses – what are people telling us in their own words. Analysis is at NEL level – although individual questions in the survey can be disaggregated to supply useful insight at local authority level we have been advised by GLA not to combine questions at the borough level meaning that rounds 2,3 and 4 had to be done at NEL level. In addition we carried out the topic modelling at NEL level due to only about half of responses containing a free text comment.
  • 5. Keyanalyticalfindings& conclusions| Demographicsof selectedquestions • Large numbers (hundreds of thousands of individuals depending on the metric) struggle with financial and food security, winter heating, housing, or loneliness within NEL, and may struggle with multiple issues. Examples include: • 20% of NEL residents have not had enough money to buy food when needed in the last year. This is more often true for those from ethnic minorities (e.g. 29% for black people against 12% for White British people), young people (31% for those in the 16-24 age group), or long lasting health conditions (29%) as well as those who don’t speak English well or were born outside the UK. • 15% of residents have been unable to adequately heat their home. Notable differences from this include those with a long lasting health condition (25%), those who don’t speak English well (37%) and those with a caring responsibility. • 14% of residents consider their housing to be poor or very poor quality. This is a more common view among those who are in the Asian, mixed or other ethnic groups (between 18-25%) or those with a long lasting health condition (21%). • 20% of NEL residents with loans struggle to keep up with debt repayments. This is more noticeable in those of Black, Asian or mixed ethnic groups (22-27%), or for those with a long lasting health condition (27%), those who don’t speak English well (38%) and those who are young (35% for those 16-24). • 28% of residents feel lonely some or often/all the time. This is especially so for the young (39% of those 16-24), those with a long lasting health condition (39%).
  • 6. Our analysis indicated that there were certain population groups who were significantly more vulnerable to having difficulties in the financial domain, namely: • Non-white ethnic populations especially those within the black ethnicity cohort who are Non-natal Londoners • Single and young parents, especially where these factors are combined. • Those with a life-limiting illness • Unpaid Carers • Younger people (under 24yrs of age) Whilst descriptively we see a slight variation due to gender, our analysis indicates that this is due to the higher prevalence of financial vulnerability risk factors within the female population due social norms and other influences rather than gender itself being a significant risk factor for vulnerability. Regression Model Marginal Analysis Input Variables Modelling Stage Dependent Modelling Variable Fuel poverty Food insecurity Debt burden Low savings Demographic • Age • Ethnicity Social/Risk • Family status • Disability & Caring status Conclusions Financial vulnerability | Key findings
  • 7. Gender We excluded gender from our analysis. While we found slight variation between male and females looking at the data descriptively when we isolated the effect of gender on financial vulnerability there was no significant difference between men and women. Looking at the data descriptively however, we see that several risks for financial vulnerability are associated with a higher proportion of women e.g. unpaid carers and single parents. Statisticalmodellingoffinancialvulnerability| Gender
  • 8. Ethnicity We found that patterns of financial vulnerability varied across ethnic groupings between Natal Londoners (those who have always lived here) and Non-natal Londoners (those who have moved here to live) with ethnicity having a significantly smaller effect for Natal Londoners. Our analysis indicated that White Non-Natal Londoners are over 25% less likely to be financially vulnerable than their Natal peers while Black Non-natal Londoners were 50% more likely to have difficulties in this domain when compared to their Natal peers. Note: the 50% line on this and the following charts indicates that an individual in particular group is more likely than not to be financially vulnerable. Statisticalmodellingoffinancialvulnerability| Ethnicity
  • 9. Keyanalyticalfindings& conclusions| Freetextanalysis • A topic modelling approach was used to extract common topics from the short free text question at the end of the survey, asking respondents for anything else they wished to add. • Respondents appear to show positive sentiment towards London as a whole but negativity towards their local areas. • Multiple topics found in free text responses are not covered in the survey. For example there are no/not many questions on traffic and road use, issues with the surrounding area and policing and crime. These are topics we found to exist within the responses. • Older age bands are more negative towards public services compared to younger age bands. • Sentiment towards the topic of housing varies with age, older age bands are more positive compared to younger age bands. • All demographics show negative sentiment towards the topic regarding local councils.
  • 10. Biterm topic model |results Topic Number Number of responses (% of total responses) Description of topic Positive (% of responses) Negative (% of responses) 1 141 (4%) Responses discuss public services like healthcare and policing, as well as public infrastructure. 42% 48% 2 312 (9%) Respondents discuss their local area and issues such as noise and cleanliness of their surrounding area. 32% 57% 3 753 (22%) How the respondents feel about London and their likes and dislikes about the city. 58% 31% 4 105 (3%) Focuses on cycling and cyclists in London as well as the general environmental infrastructure 49% 40% 5 458 (13%) Respondents discuss what London has to offer, focusing on what it offers culturally e.g. museums and galleries and in regards to public transport e.g. freedom pass. 69% 25% 6 559 (16%) Respondents discuss housing and rent in London, with a focus on high costs and expensive housing. 34% 53% 7 62 (2%) This topic is a mix of parents discussing raising children in London and abuse suffered in London e.g. racism 39% 50% 8 453 (13%) Respondents discuss driving in London with a focus in congestion charge, traffic, changes to roads and pollution 23% 64% 9 165 (5%) This topic discusses the role of local councils in housing and areas in London but with an emphasis on new developments, social housing and desired improvements. 30% 51% 10 161 (5%) This topic is mixed but is mainly comprised of personal reflections of living in London, personal circumstances and reflections on the survey itself. 43% 47% 11 235 (7%) Respondents discuss crime in London with an emphasis on knife crime, safety, drugs and policing. 23% 67%
  • 11. The GLA survey provided insight not available from other sources • The GLA survey of Londoners is a rich source of data and shows the importance of this kind of snapshot for understanding the NEL population. It has been used as evidence in our response to the cost of living crisis, and forms an important resource for understanding our population as we develop our population health management approaches. • Linked individual level responses provide insight that needs careful analysis to extract the right message – e.g. gender is not a significant variable in determining financial vulnerability but variables commonly linked to gender are. • The free text field can be useful for identifying topics of interest to residents. It can also be used to help identify topic areas that should be covered in future structured surveys and gives a place for the voice of our residents to come through in their own words.

Editor's Notes

  1. NEL collects data on health… we’ve got good data from primary care, acute care, MH, community etc. We’re starting to build quite good pictures of certain demographic characteristics – but we don’t have access to certain things relevant to all determinants of health – very health data focused view of population health. Survey of London adds data on community, work, food, finance, and so on. Views on your local area Friends, family and other people you meet Respect Being part of the community Volunteering, Civic Participation and Trustworthiness Work Food Personal Finance Accessible Support Digital Exclusion Personal Wellbeing About your household Demographics
  2. Did this as a system piece - partly to make sure that we could get useful output for the whole system from this work, partly to work as a system.
  3. At the time we were doing this analysis – summer 22, cost of living was becoming an issue, steering group identified this as an area for exploration
  4. A logistic regression model was used to identify variables associated with financial vulnerability defined by a combination of questions covering fuel poverty, food insecurity, debt burden and savings. A number of population groups are particularly financially vulnerable according to our analysis: this includes: Non-white ethnic populations especially those within the black ethnicity cohort not born in London. Single and young parents, especially where these factors are combined. Those with a life-limiting illness Unpaid Carers Younger people under 24yrs of age. This last conclusion should be treated with a degree of caution as we cannot easily unpick those young people living independently from those living with parents or guardians for whom some of the metrics determining financial vulnerability are less relevant. Gender does not appear to be in itself a significant factor in financial vulnerability: however many of the factors identified are associated with roles more often undertaken by women (e.g. unpaid carers, single parents). Household income was excluded from the definition of financial vulnerability as we could not identify disposable income.
  5. With appropriate information governance the output of this survey might be (anonymously) linked to the primary and acute data held by NEL and open up a range of other analyses. However this needs to be balanced against the willingness of individuals to participate.