Housing and household vulnerabilities to summer overheating: A Latent Classification for England
Year: 2025
Type: article
Study design: Observational Study
Abstract: Increasing global warming and climate change pose a challenge for minimising overheating in buildings and the demand for mechanical cooling, particularly for the most vulnerable populations. A thorough understanding of the factors that influence overheating can facilitate the design of healthier and safer housing under a warming climate. Diverse social and material characteristics are known to shape vulnerability to indoor overheating. However, to date, there is a lack of research that centres understanding of social vulnerabilities by focusing on how their subjective experiences of overheating vary. In response, this research investigates subjective overheating vulnerabilities analysing the largest recent sample of English dwellings, comprising 11,152 households. Methodologically, using Latent Class Analysis, four classes are derived which highlight specific housing characteristics that increase the likelihood of a household experiencing overheating. We highlight the crucial role of specific building characteristics (e.g. flats, insulated solid walls) and tenancy arrangements (e.g. social and private renting) in exacerbating overheating risks, especially when vulnerable groups reside in them. Particularly, households with low incomes, older or retired members and younger individuals are more likely to report the risk of overheating. By revealing relationships between housing and household characteristics regarding subjective overheating, we highlight the multifaceted nature of the indoor overheating issue with implications for domestic policymakers considering low-carbon building schemes and regulations on thermal comfort.
Source: Energy Research & Social Science
Authors: Lin Zhang, Caitlin Robinson, Lenka Hasova
Institution: University of Bristol
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,450
Funder: UK Research and Innovation
Award: G314603897
OpenAlex ID: W4410424541
