Measuring chaos

This blog explores how data can be used to identify and track poverty in health and economic systems and enables local places to see where their area sits on key measures using a set of interactive maps.

26 July 2022

By Rosie Fogden

11 minute read

This summer, CPP and our Inclusive Growth Network are working with The King’s Fund on how local government can work with health and care systems to tackle poverty. As part of this work, we are exploring how data can be used to focus longer term strategy and daily operations on poverty. This blog reviews some of the data and tools that are already out there and enables local places to see where their area sits on key existing poverty measures using a set of interactive maps.

Why measure poverty?

Rising inflation and economic turmoil is pushing more and more people into poverty as those on low incomes experience higher inflation and falling real wages. This is a huge problem for our health service as we know that poverty leads to worse health outcomes;

It is also a problem for local governments and businesses as poor health and poverty negatively affect the local economy through reduced economic activity and productivity. The numbers of people who are long term sick has grown significantly since the start of the pandemic and nearly 900,000 working age people in the UK are now currently neither in work nor looking for work, posing serious challenges for businesses looking to recruit. Collaborating on tackling poverty should be a top priority for health and economic leaders but to do so they need a baseline from which to measure progress and incentivise joint action. Front line teams additionally require up to date data in order to best target daily interventions and concentrate service delivery.

How is poverty defined and measured?

While people’s experience of poverty can vastly differ, poverty is at its core about economic insecurity and not having enough money to live on. Child Poverty Action Group (CPAG) define poverty as being unable to live at the standard that most other people would expect, while the Joseph Roundtree Foundation (JRF) - another authoritative voice on poverty - define it as “not being able to heat your home, pay rent, or buy the essentials for your children.” Poverty can manifest itself in different ways such as: homelessness, chronic stress about paying bills, digital exclusion, reduced opportunities for children and many more and this variety in experience means that any policy discussion about poverty should include people who have experienced it.

Most commonly, poverty is measured with reference to average income with people who have less than 60% of the median considered to live in poverty. This approach captures the exclusionary nature of living in poverty and is practical as income is relatively easy to measure. Measures like food security, material deprivation and the Minimum Income Standard (MIS) additionally aim to capture the cost-of-living aspect of poverty more directly.

How useful are existing measures?

As the table below shows, the most commonly referred to data on poverty – Households below average income (HBAI) – aren’t available at lower-level geographies, limiting their usefulness for local anti-poverty strategies. The best public information available locally are the official statistics on Children in Low Income Families (CiLIF) which combine a number of sources with the HBAI including benefit data. As HBAI and CiLIF are based on national survey data, the statistics are updated on an annual basis which limits their use as operational data for identifying populations in immediate need. However,

Map 1 below shows the proportion of under 18s who DWP has identified as living in an absolute low-income household by local authority in 2020 -2021. It spotlights places like Middlesbrough Bradford and Pendle and presents poverty as being more concentrated than the 2019 English Indices of Deprivation suggests (Map 2).

More timely metrics tend to be proxies for poverty rather than direct measures, such as financial security and benefit claimant data. These will not give a full picture of poverty in a place but could enable front line teams to respond to changes in their areas. Map 3 shows the proportion of working age people claiming Universal Credit in April 2022 and additionally highlights coastal places like Hastings, Thanet, Hartlepool and Blackpool.

The fast-rising inflation that the UK is currently experiencing places greater demands on the data and makes interpretation more difficult. While useful, the CiLIF data remains relative to average income which means everyone’s living standards can go down without the measure changing. Relative poverty has very real impacts, including on health as Marmot has shown, but the current HBAI statistics suggest that poverty is falling when we know that median incomes have decreased and the price of essentials are rising, making the cost of living unaffordable for increasing numbers of people. Our statistics are clearly missing something important.

More absolute measures like material deprivation should theoretically give a better picture of the number struggling to meet basic needs, but are sensitive to the criteria used to define deprivation, which will change over time. DWP data are based on a set of questions designed in 2004 which are currently being reviewed by LSE’s Centre of Analysis of Social Exclusion and likely to be out dated. Loughborough University’s Minimum Income Standard (MIS) has a more robust method, setting the items required to participate in society via regular public consultation, but these updates are infrequent and in addition the MIS is not considered a measure of poverty, but the income required to afford a minimum acceptable standard of living.

What other tools are available at local level?

Yet there are some pre-existing tools that bring together a range of relevant information at place level and could help to identify those at risk of falling into poverty.

One example is CPP’s Cost of Living Vulnerability Index, which brings together six indicators of poverty and work based vulnerability to rapidly rising prices: fuel poverty, food insecurity, child poverty, claimant count, economic inactivity and low pay. This index shows which local populations are vulnerable to being pushed into poverty, as well as highlighting those already experiencing high levels of deprivation. However, while these indicators are all at local authority level, several are based on academic analysis rather than official statistics, which means regular updates may be less reliably available. Nonetheless, local and central government partners have found this a really useful tool and an updated version is in the pipeline for autumn 2022.

Lowell and Urban Institute’s Financial Vulnerability Index is more frequently updated with new scores available each quarter. This tool is closely focussed on the levels of debt and financial product usage and can be used to identify places experiencing financial distress. The University of Nottingham Track the Economy (TE) dashboard also uses commercial data, this time Fable consumer spend data, and combines it with data from Public Health England to enable policy makers to monitor local economic responses to changes in health. This kind of data is much more timely, but it is usually not free or publicly available and is sometimes less directly related to poverty. The use of dashboards can also lead to data overload, making it harder to focus public debate and prioritise action.

What else is possible?

This blog focuses on how health and economic development leaders can make use of place level metrics, but both health and local authority systems hold a lot of individual level data. With the right data sharing agreements in place, there is scope to use this information to flag ‘at risk’ people at key intervention points such as GP and hospital visits or job centre appointments. Localised credit and financial vulnerability data could also be used for this purpose, although it is unlikely to be free. Some places are already trialling these approaches, and this is something we will explore in the coming weeks.

Table 1: Existing poverty metrics





Data owner




Relative low income

Households Below Average Income publication (HBAI)

Households with income (pay and benefits) below 60% of the median. Available as before and after housing costs.

Family Resources Survey





Absolute low income

Households with income below 60% of the median in 2011. This holds the bar for poverty constant over time but is ultimately still a relative measure.

Material deprivation

Based on access to a basket of 15 different goods and services set by independent academic analysis from 2004. These criteria are currently under review

Food security

Food insecure households have a risk of, or lack of access to, sufficient, varied food.

Children in low-income households

Children in Low Income Families (CiLIF) official statistics

Counts of children aged under 16 living in low income families before housing costs, on both relative and absolute measures. Results are calibrated to regional HBAI

ONS population estimates, HBAI and UC Claimant data



Local authority, MSOA, ward

Public, via stat Xplore

Households below the Minimum Income Standard

Households below a Minimum Income Standard

Individuals living in households with an income below the MIS, as set bi-annually by Loughborough University's Centre for Research in Social Policy (CRSP)

MIS applied to population weights from HBAI

JRF (think tank)



Private - owned by JRF


English Indices of deprivation

Relative (ranked) levels of deprivation in neighbourhoods across England based on: income, employment, health, education, crime, housing and living environment.

39 indicators from various sources weighted across seven sub-domains


Every 4-5 years. Most recent data is 2019

Local authority, LEP, CCG, LSOA


People on Universal Credit

Official Statistics for people on Universal Credit

The number people who have started Universal Credit, which is available to people who are out of work or on low incomes and includes support for the cost of housing, children and childcare, and financial support for people with disabilities, carers and people too ill to work.

UC Claimant data



Region, Local authority, MSOA, LSOA, ward (and more)

Public, via stat xplore

Financial Vulnerability

Lowell and Urban Institute financial vulnerability index

Standardised score based on six components: (1) % carrying defaulted debt, (2) % claiming work-related social benefits, (3) % holding a high-cost loan, (4) % relying heavily on credit, (5) % lacking emergency savings, and (6) % using alternative financial products.

Lowell’s operational data, UK Financial Lives survey, DWP and ONS data

Lowell (private debt collection company)


Region, constituency

Private – owned by Lowell