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Modelling the Impact of Fuel Poverty and Energy Efficiency on Health

University of Exeter Medical School
Date: 2018


Fuel poverty poses a distinct societal and healthcare burden. Official fuel poverty statistics show that around 11% of households in England are affected. These health and housing inequalities persist despite the knowledge that cold homes increase the risk of damp- and cold-related morbidity and mortality. This has been articulated in a number of landmark publications such as the 1980 Black Report, the 1998 Acheson Report and the 2010 Marmot Report, which called for improved household energy efficiency across the social gradient. Well-designed home energy efficiency improvements (e.g. sealing homes to prevent heat loss and improvements to insulation, glazing, heating and ventilation) have the potential to reduce the cost of heating homes and improve people’s health and wellbeing. However, policies supporting schemes for increasing energy efficiency are continuing without a full understanding of the health benefits or the extent of some unintended consequences such as reduced air quality in unventilated homes. Furthermore, there is a lack of evidence linking historical energy efficiency interventions with health outcomes at the population level. 

Key research Question

This research project aimed to contribute to the evidence on the impact of fuel poverty policies on health at the population level. It was guided by two primary objectives: 

  1. To investigate how area-level household energy efficiency is associated with hospital admission rates for cardiovascular and respiratory diseases on a national population scale; and  

  1. To utilise detailed dwelling-level data on 500,000 homes in Devon to assess the association between home energy efficiency measures, the risk of fuel poverty and hospital admission rates. 

Summary of activity

Considered a novel exploratory pilot study, the research worked with partners from health, energy efficiency and academic organisations to utilise population-level secondary data analysis techniques to explore the relationships between fuel poverty/home energy efficiency and hospital admission rates for cardiovascular and respiratory diseases at the area level across England. 

Two streams of analysis were undertaken. The first used national (England) data on home energy efficiency and related data on hospital admissions for relevant health outcomes (asthma, Chronic Obstructive -Pulmonary Disease [COPD] and cardiovascular disease [CVD]). The second used a novel property-level dataset for the county of Devon on home energy efficiency and fuel poverty (aggregated to the small-area level) and also investigated associations with hospital admissions. The approach used for each analysis comprised carrying out a small-area (Local Super Output Area) ecological cross-sectional study. This type of approach integrates a number of datasets based on a common geographical area and investigates associations between area-level measures (e.g. the average energy performance of homes and the hospital admission rate within an area). 



The research identified a range of limitations that restricted the ability of the analyses to indicate causal associations between area-level energy efficiency metrics and hospital admission rates. In general, there were quite mixed findings regarding the key relationships of interest. There were a number of instances in both the national and the local analyses where there was a suggestion of a positive association, i.e. higher admission rates in areas where the average home energy efficiency was greater. There were a smaller number of instances where an inverse association was observed. 

One of the clearest findings was a small but significant association in the form of an increase of around 0.5–1.0% in hospital admission rates for asthma, COPD and CVD per 1 point increase in the mean Energy Performance Certificate rating across England in the national analysis. The Devon analysis suggested that a higher average Standard Assessment Procedure rating (i.e. a higher percentage of properties rated A–C) at the postcode level was associated with higher admission rates for asthma, COPD and CVD. However, these associations disappeared in models that adjusted for all other factors. Also, in the Devon analysis a higher probability of fuel poverty was associated with a lower admission rate for CVD in fully adjusted models, but there were specific limitations on the use of this variable in adjusted models.  

It is possible that the area-level analyses and the definitions of health outcomes used in this study concealed potential benefits of energy efficiency measures in more vulnerable populations (i.e. those residing in cold homes and/or with a chronic disease). The study design only considered relationships at the aggregate (area) level, which were based on ‘average’ measures of housing energy efficiency and population hospital admission rates; it could not reveal relationships between conditions in individual homes and individual-level hospital admissions. 

The study adds to the body of literature that supports the need for better-designed home improvement funding schemes and higher-quality measures that address the whole property. 


  • From a research point of view, the findings support the need for larger-scale longitudinal natural experiments and/or more complex study designs that can account for the impact of specific types of intervention. These studies should also further investigate the sectoral impact of efficiency measures (for example, by tenure or demographic subgroup), as well as the potential for new experimental and technological monitoring techniques. 

  • Further development of fuel poverty models such as the Energy Saving Trust’s Home Analytics Portal may hold promise for targeting vulnerable populations and benefiting health and social care. However, concomitant cost–benefit analyses of these approaches are required. 

  • The research further highlights the need for greater intersectoral collaboration between a range of health and housing stakeholders. 

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