In 2019, people from most ethnic minority groups were more likely than White British people to live in the most deprived neighbourhoods.

Between 2018 and 2022, people in households in the ‘other’, Asian and black ethnic groups were the most likely to be in persistent low income, both before and after housing costs, out of all ethnic groups.

For a case study of England, global principal component analysis (PCA) is applied to a suite of neighborhood-scale energy vulnerability indicators.

PCA reduces a large multivariate set of vulnerability factors into a reduced number of principal components, retaining key statistical information and spatial patterns. The components have loading values associated with each of the vulnerability indicators in the input data set. Loadings tell us about the type (negative or positive) and strength of the relationship between an indicator and a principal component, providing information about the patterns of vulnerability within the data set that each component is likely to represent. These global component loadings can be mapped to provide an understanding of the spatial distribution of the vulnerability represented by each principal component and the locales in which vulnerability is likely to be enhanced as a result.

This dataset contains three principal components which account for 62.4 percent of the variance in the 21 energy vulnerability indicators identified. The first component has strong positive association with precarious and transient families but a strong inverse relationship with retirement and older age groups. The second component has a strong positive relationship with disability, illness, and the provision of care. The third component has a positive relationship with the energy efficiency and availability of networked and domestic energy infrastructures. The principal components are mapped at the Lower Super Output Area (LSOA) scale, an administrative area unit with a mean population of 1,500 persons.

An investigation was carried out into the process involved in designing and building affordable community-driven vertical greening systems (VGS) prototypes in a low-income neighbourhood of Lagos, Nigeria. Prototypes are intended to improve indoor thermal comfort conditions and potentially provide substrate to grow edible and medicinal plants. Data, relating to 2 prototypes built in 2014 and their evaluation, comprises:the narrative / information about community participation in the design and construction of the 2 prototypes;the monitoring procedure used to collect thermal performance data;the analysis of the data collected on thermal performance;the community acceptability survey related to the prototypes.A summary is provided of a community-acceptability survey undertaken following a second round of 2 prototypes, built in the same neighbourhood in the year 2016. Research restults based upon these data are published at https://doi.org/10.1016/j.buildenv.2018.01.022

In order to bring a thorough and comprehensive understanding of social, economic and environmental sustainability challenges faced by cities and local communities in the developing countries, the SHLC team conducted a major household survey followed by a neighbourhood focus group interview in seven Asian and African countries from late 2021 to early 2022. In each country the study includes two case study cities: one large city and one smaller regional cities. Within each case study cities, neighbourhoods were identified and categorised into five income and wealth bands: the rich, upper middle income, middle income, lower middle and low income neighbourhoods. A household survey was carried out face to face by trained interviewers with a random adult member of the household. The 20 page common questionnaire was designed and adopted by all teams, which cover topics of housing, residence, living conditions, migration, education, health, neighbourhood infrastructure, facilities, governance and relations, income and employments, gender equality and impacts from Covid-19. The sample was distributed in the city to representative the five neighbourhood types. The survey was completed in 13 of the 14 case study cities (fieldwork in Chongqing in China was delayed by the Covid-19 lockdowns and implemented in August 2023). The target sample for each city was 1000; the total sample in the database (SPSS and STATA) include 14245 households. The survey was followed by focus group interviews. A carefully designed and agreed common interview guide was used by all team. The target was to have one focus group for one neighbourhood in each income band in each city. A total of 74 focus group interviews were conducted (Fieldwork in Datong and Chongqing in China was delayed). The transcripts are the qualitative data shared here.

The CLARISSA Cash Plus intervention represented an innovative social protection scheme for tackling social ills, including the worst forms of child labour (WFCL). A universal and unconditional ‘cash plus’ programme, it combined community mobilisation, case work, and cash transfers (CTs). It was implemented in a high-density, low-income neighbourhood in Dhaka to build individual, family, and group capacities to meet needs. This, in turn, was expected to lead to a corresponding decrease in deprivation and community-identified social issues that negatively affect wellbeing, including WFCL. Four principles underpinned the intervention: Unconditionality, Universality, Needs-centred and people-led, and Emergent and open-ended.The intervention took place in Dhaka – North Gojmohol – over a 27-month period, between October 2021 and December 2023, to test and study the impact of providing unconditional and people‑led support to everyone in a community. Cash transfers were provided between January and June 2023 in monthly instalments, plus one investment transfer in September 2023. A total of 1,573 households received cash, through the Upay mobile financial service. Cash was complemented by a ‘plus’ component, implemented between October 2021 and December 2023. Referred to as relational needs-based community organising (NBCO), a team of 20 community mobilisers (CMs) delivered case work at the individual and family level and community mobilisation at the group level. The intervention was part of the wider CLARISSA programme, led by the Institute of Development Studies (IDS) and funded by UK’s Foreign, Commonwealth & Development Office (FCDO). The intervention was implemented by Terre des hommes (Tdh) in Bangladesh and evaluated in collaboration with the BRAC Institute of Governance and Development (BIGD) and researchers from the University of Bath and the Open University, UK.The evaluation of the CLARISSA Social Protection pilot was rooted in contribution analysis that combined multiple methods over more than three years in line with emerging best practice guidelines for mixed methods research on children, work, and wellbeing. Quantitative research included bi-monthly monitoring surveys administered by the project’s community mobilisers (CMs), including basic questions about wellbeing, perceived economic resilience, school attendance, etc. This was complimented by baseline, midline, and endline surveys, which collected information about key outcome indicators within the sphere of influence of the intervention, such as children’s engagement with different forms of work and working conditions, with schooling and other activities, household living conditions and sources of income, and respondents’ perceptions of change. Qualitative tools were used to probe topics and results of interest, as well as impact pathways. These included reflective diaries written by the community mobilisers; three rounds of focus group discussions (FGDs) with community members; three rounds of key informant interviews (KIIs) with members of case study households; and long-term ethnographic observation.Quantitative DataThe quantitative evaluation of the CLARISSA Cash Plus intervention involved several data collection methods to gather information about household living standards, children’s education and work, and social dynamics. The data collection included a pre-intervention census, four periodic surveys, and 13 rounds of bi-monthly monitoring surveys, all conducted between late 2020 and late 2023. Details of each instrument are as follows:Census: Conducted in October/November 2020 in the target neighbourhood of North Gojmohol (n=1,832) and the comparison neighbourhood of Balurmath (n=2,365)Periodic surveys: Baseline (February 2021, n=752 in North Gojmohol), Midline 1 (before cash) (October 2022, n=771 in North Gojmohol), Midline 2 (after 6 rounds of cash) (July 2023, n=769 in North Gojmohol), and Endline (December 2023, n=750 in North Gojmohol and n=773 in Balumath)Bi-monthly monitoring data (13 rounds): Conducted between December 2021 and December 2023 in North Gojmohol (average of 1,400 households per round)The present repository summarizes this information, organized as follows:1.1 Bimonthly survey (household): Panel dataset comprising 13 rounds of bi-monthly monitoring data at the household level (average of 1,400 households per round, total of 18,379 observations)1.2 Bimonthly survey (child): Panel dataset comprising 13 rounds of bi-monthly monitoring data at the child level (aged 5 to 16 at census) (average of 940 children per round, total of 12,213 observations)2.1 Periodic survey (household): Panel dataset comprising 5 periodic surveys (census, baseline, midline 1, midline 2, endline) at the household level (average of 750 households per period, total of 3,762 observations)2.2 Periodic survey (child): Panel dataset comprising 4 periodic surveys (baseline, midline 1, midline 2, endline) at the child level (average of 3,100 children per period, total of 12,417 observations)3.0 Balurmat - North Gojmohol panel: Balanced panel dataset comprising 558 households in North Gojmohol and 773 households in Balurmath, observed both at 2020 census and 2023 endline (total of 2,662 observations)4.0 Questionnaires: Original questionnaires for all datasetsAll datasets are provided in Stata format (.dta) and Excel format (.xlsx) and are accompanied by their respective dictionary in Excel format (.xlsx).Qualitative DataThe qualitative study was conducted in three rounds: the first round of IDIs and FGDs took place between December 2022 and January 2023; the second round took place from April to May 2023; and the third round took place from November to December 2023. KIIs were taken during the 2nd round of study in May 2023.The sample size by round and instrument type is shown below:RoundsIDIs with childrenIDIs with parentsIDIs with CMsFGDsKIIs1st Round (12/2022 – 01/2023)3026-06-2nd Round ( 04/2023 – 05/2023)3023-06053rd Round (11/2023 – 12/2023)26250307-The files in this archive contain the qualitative data and include six types of transcripts:· 1.1 Interviews with children in case study households (IDI): 30 families in round 1, 30 in round 2, and 26 in round 3· 1.2 Interviews with parents in case study households (IDI): 26 families in round 1, 23 in round 2, and 25 in round 3· 1.3 Interviews with community mobiliser (IDI): 3 CM in round 3· 2.0 Key informant interviews (KII): 5 in round 2· 3.0 Focus group discussions (FGD): 6 in round 1, 6 in round 2, and 7 in round 3· 4.0 Community mobiliser micro-narratives (556 cases)Additionally, this repository includes a comprehensive list of all qualitative data files ("List of all qualitative data+MC.xlsx").

This research selected three cities as case studies in Brazil (Pelotas, Belo Horizonte, and Brasilia) and three cities as case studies in the UK (Edinburgh, Manchester and Glasgow). The case study cities represented a broad spectrum of urban areas, in terms of demography (mixed tenures by age), inequality (health and social disparities between high and low income groups), topography (different types of urban densities and form) and urban development (varying levels of physical transformation and change). Within each of the case study cities, three neighbourhoods were selected as study sites reflecting a diversity in population density and income levels (measures guided by previous research examining neighbourhood satisfaction amongst older adults). The neighbourhoods comprised a mix of low, medium and high income and low, medium and high-density areas. Neighbourhood level analysis has been chosen because: (i) the greatest time spent by older adults in retirement is at home and in the immediate neighbourhood locality, (ii) older adults are increasingly dependent upon social relationships in the neighbourhood as they age; and (iii) older adults have important psychological and emotional bonds and association with the neighbourhood (as community). As part of the first work package of the research, a total number of 180 semi-structured interviews (30 per case study city; 10 per neighbourhood) were conducted with older adults to explore the in-depth experiences of ageing-in-place. The interviews identified how sense of place is negotiated and constructed (meaning, identity, belonging), identifying everyday behaviours within the built environment, and the importance of specific social and cultural supports.Ageing populations in Brazil and the UK have generated new challenges in how to best design living environments that support and promote everyday social engagement for older people. The ageing-in-place agenda posits that the preferred environment to age is the community, enabling older people to retain a sense of independence, safety and belonging. Encouraging older adults to remain in their communities has contributed to planning and design concepts such as Age-Friendly Cities and Communities, Lifelong Homes and Liveable Neighbourhoods. However, current urban planning and development models have overlooked the notion of sense of place, articulated through supports for active living, social participation and meaningful involvement in the community. Integrating sense of place into the built environment is essential for supporting active ageing, ensuring that older adults can continue to make a positive contribution in their communities and potentially reducing health and social care costs. This project has three core aims: (i) to investigate how sense of place is experienced by older people from different social settings living in diverse neighbourhoods in Brazil and the UK; (ii) to translate these experiences into designs for age friendly communities that support sense of place; and (iii) to better articulate the role of older adults as active placemakers in the design process by involving the community at all stages of the research. We will undertake fieldwork in a total of 18 neighbourhoods (of varying densities and income levels) across 6 case study cities in Brazil (Pelotas, Porto Alegre, and Brasilia) and the UK (Edinburgh, Manchester and Glasgow). We will use a range of methods to achieve the project aims, including sense of place surveys and semi-structured interviews alongside experiential methods including 'go along' walks, photo and video diaries and community mapping exercises to capture the place-based needs of older adults. The new data generated will answer the following research questions: (i) How is sense of place experienced by older adults from different social classes living in diverse neighbourhoods in Brazil and the UK? (ii) What services, amenities and features are needed to create age friendly communities that promote healthy cities and active ageing in different urban and cultural contexts? (iii) How can communities be designed to better integrate the sense of place needs of older adults across different urban and cultural contexts? A community-based participatory approach will be adopted to the research, bringing together all stakeholders in a process of collaborative dialogue and co-design to challenge the hierarchical power relationships that exist when planning 'for' and not 'with' older people. The results will be used to co-create place-making tools and resources which are essential for designing age friendly environments for older adults. Findings will be disseminated to community, policymaker, practitioner and academic audiences through ongoing and end of project knowledge translation activities. We carried out semi-structured interviews in three cities in the UK and three cities in Brazil. Please see the document 'Context and Methods' for detailed information on methodology.

Housing Benefit can be claimed by a person if they are liable to pay rent and if they are on a low income. Council Tax Benefit is designed to help people on low-income to pay their Council Tax. The data are broken down by gender, age and marital status.

Source: Department for Work and Pensions (DWP)

Publisher: Neighbourhood Statistics

Geographies: Lower Layer Super Output Area (LSOA), Middle Layer Super Output Area (MSOA), Local Authority District (LAD), County/Unitary Authority, Government Office Region (GOR), National

Geographic coverage: England and Wales

Time coverage: 2005

Type of data: Administrative data

Notes: The two benefits are not listed separately in this dataset.

ID 2007 Income Deprivation Affecting Children supplementary index (number of children in households in receipt of means tested low income benefits) Source: Communities and Local Government (CLG): ID 2007 Publisher: Neighbourhood Statistics Geographies: Lower Layer Super Output Area (LSOA) Geographic coverage: England Time coverage: 2007 (using 2005 data) Type of data: Administrative data (with statistical transformations applied)

The 'Climate Just' Map Tool shows the geography of England’s vulnerability to climate change at a neighbourhood scale.

The Climate Just Map Tool shows which places may be most disadvantaged through climate impacts. It aims to raise awareness about how social vulnerability combined with exposure to hazards, like flooding and heat, may lead to uneven impacts in different neighbourhoods, causing climate disadvantage.

Climate Just Map Tool includes maps on:

• Flooding (river/coastal and surface water)
• Heat
• Fuel poverty.

The flood and heat analysis for England is based on an assessment of social vulnerability in 2011 carried out by the University of Manchester. This has been combined with national datasets on exposure to flooding, using Environment Agency data, and exposure to heat, using UKCP09 data.

Data is available at Middle Super Output Area (MSOA) level across England. Summaries of numbers of MSOAs are shown in the file named Climate Just-LA_summaries_vulnerability_disadvantage_Dec2014.xls

Indicators include:

Climate Just-Flood disadvantage_2011_Dec2014.xlsx

Fluvial flood disadvantage index
Pluvial flood disadvantage index (1 in 30 years)
Pluvial flood disadvantage index (1 in 100 years)
Pluvial flood disadvantage index (1 in 1000 years)

Climate Just-Flood_hazard_exposure_2011_Dec2014.xlsx

Percentage of area at moderate and significant risk of fluvial flooding
Percentage of area at risk of surface water flooding (1 in 30 years)
Percentage of area at risk of surface water flooding (1 in 100 years)
Percentage of area at risk of surface water flooding (1 in 1000 years)

Climate Just-SSVI_indices_2011_Dec2014.xlsx

Sensitivity - flood and heat
Ability to prepare - flood
Ability to respond - flood
Ability to recover - flood
Enhanced exposure - flood
Ability to prepare - heat
Ability to respond - heat
Ability to recover - heat
Enhanced exposure - heat
Socio-spatial vulnerability index - flood
Socio-spatial vulnerability index - heat

Climate Just-SSVI_indicators_2011_Dec2014.xlsx

% children < 5 years old
% people > 75 years old
% people with long term ill-health/disability (activities limited a little or a lot)
% households with at least one person with long term ill-health/disability (activities limited a little or a lot)
% unemployed
% in low income occupations (routine & semi-routine)
% long term unemployed / never worked
% households with no adults in employment and dependent children
Average weekly household net income estimate (equivalised after housing costs) (Pounds)
% all pensioner households
% households rented from social landlords
% households rented from private landlords
% born outside UK and Ireland
Flood experience (% area associated with past events)
Insurance availability (% area with 1 in 75 chance of flooding)
% people with % unemployed
% in low income occupations (routine & semi-routine)
% long term unemployed / never worked
% households with no adults in employment and dependent children
Average weekly household net income estimate (equivalised after housing costs) (Pounds)
% all pensioner households
% born outside UK and Ireland
Flood experience (% area associated with past events)
Insurance availability (% area with 1 in 75 chance of flooding)
% single pensioner households
% lone parent household with dependent children
% people who do not provide unpaid care
% disabled (activities limited a lot)
% households with no car
Crime score (IMD)
% area not road
Density of retail units (count /km2)
% change in number of local VAT-based units
% people with % not home workers
% unemployed
% in low income occupations (routine & semi-routine)
% long term unemployed / never worked
% households with no adults in employment and dependent children
Average weekly household net income estimate (Pounds)
% all pensioner households
% born outside UK and Ireland
Insurance availability (% area with 1 in 75 chance of flooding)
% single pensioner households
% lone parent household with dependent children
% people who do not provide unpaid care
% disabled (activities limited a lot)
% households with no car
Travel time to nearest GP by walk/public transport (mins - representative time)
% of at risk population (no car) outside of 15 minutes by walk/public transport to nearest GP
Number of GPs within 15 minutes by walk/public transport
Number of GPs within&nb

There is a major gap in funding required for conservation, especially in low income countries. Given the significant contribution of taxpayers in industrialized countries to funding conservation overseas, and donations from membership organisation, understanding the preferences of ordinary people in a high income country for different attributes of conservation projects is valuable for future marketing of conservation. We conducted a discrete choice experiment with visitors to a UK zoo, while simultaneously conducting a revealed preference study through a real donation campaign on the same sample. Respondents showed the highest willingness to pay for projects that have local community involvement in management (95% confidence interval £9.82 to £15.83), and for improvement in threatened species populations (£2.97 - £13.87). Both of these were significantly larger than the willingness to pay for projects involving provision of alternative livelihoods, or improving the condition of conservation sites. Results of the simultaneous donation campaign showed that respondents were very willing to donate the suggested £1 or above donation (88% made a donation, n = 1798); there was no effect of which of the two campaigns they were exposed to (threatened species management or community involvement in management). The small number of people who did not make a donation had a higher stated willingness to pay within the choice experiment, which may suggest hypothetical bias. Conservationists increasingly argue that conservation should include local communities in management (for both pragmatic and moral reasons). It is heartening that potential conservation donors seem to agree.

Abstract copyright UK Data Service and data collection copyright owner. This study investigates the alarming rise of urban poverty in China; in particular the patterns of urban poverty and the institutional causes are examined. The researchers look for evidence of institutional innovations that have emerged as individuals and organisations seek to negotiate more secure access to vital civic goods and services. A case study approach was used due to the complexity of the issue and the size of the Chinese urban population. Six cities were chosen and four neighbourhoods in each city were investigated. These cities were distributed in the costal, central and western region respectively, including Guangzhou, Nanjing, Harbin, Wuhan, Kumin, and Xi’an. Further information is available from the ESRC Award webpage. Main Topics: The questionnaire has sections on:demographic informationhousehold income and expendituresocial benefits/welfarehousingemployment situationneighbourhood profilecommuting and relocation One-stage stratified or systematic random sample Face-to-face interview

The Index of multiple deprivation (IMD) combines information from the English Indices of deprivation (IoD). It is the Government's official measure of relative deprivation for LSOAs (Lower layer super output areas). LSOAs are small geographical areas of approximately 1,700 people. There are 128 LSOAs in Calderdale. The IoD is a set of relative measures of deprivation for LSOAs across England, based on seven different domains of deprivation: Income, Employment, Education skills and training, Health and disability, Crime, Barriers to housing and services, and Living environment. There are also seven domain level indices and two supplementary indices - Income deprivation affecting children index (IDACI) and Income deprivation affecting older people index (IDAOPI). It is published every three to five years. IMD 2019 results were published on 26 September 2019. Calderdale results are available, using the dashboard link on this page. More information is available at Ministry of Housing, Communities and Local government: English Indices of deprivation 2019. See also: * IoD Infographic and themed factsheets below * IoD opendata for LSOAs (Lower layer super output areas) and wards below * IoD 2019 factsheets for each ward can be found on the individual ward factsheets. * Children's Centre Boundary areas data set for a postcode checker tool which includes IMD 2019 decile for each LSOA in the children's centre reach area. * Calderdale areas by postcode dataset for a list of postcodes in Calderdale, their ward, and the IMD 2019 decile for their LSOA. * Exploring local income deprivation - new animation by the Office for National Statistics about income deprivation at neighbourhood level as shown by the English Index of Income Deprivation 2019