Using Active Lives data to estimate national and local sport volunteering rates in England

Sociodemographic characteristics and spatial distribution

Bibliographic Data

ID22430247
AuthorsJames Liley (0000-0002-0049-8238, Durham University), Caroline Dodd-Reynolds (Durham University, corresponding author), Lindsay Findlay-King (0000-0001-5199-1797, Northumbria University), Iain Lindsey (0000-0003-3404-6616, Durham University), Jochen Einbeck (0000-0002-9457-2020, Durham University)
Year2026
Pages1-23
Publication date2026-06-10
Open AccessYes
TypeARTICLE
VenueInternational Journal of Sport Policy and Politics (JOURNAL)
Journal identifiersISSN: 1940-6940 • E-ISSN: 1940-6959
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/19406940.2026.2685490
OpenAlexW7164374303
LanguageEN
References cited39

This article advances current understanding of national and local sport volunteering rates and the socio-demographic profiles of sport volunteers. Since 2015 national insights into sport volunteering in England have drawn upon particular questions within the national Active Lives Adult Survey. This data set often contains missing values and at the local level becomes too sparse to reliably estimate volunteering rates. In the context of declining sport volunteering and a shift towards localism in sport and physical activity policy, improved insight is needed to inform volunteering policy and promotion. Here we address this challenge through novel statistical imputation of Active Lives data, whereby predictive models were constructed and used to explore the effect of variables on volunteering rates by local authority (LA) area. Our results provide estimated volunteer rates for the whole English population and the range of factors that make people more likely to volunteer in sport. We also show the geographical spread of LA volunteering rates (LAVRs) and examine relationships between LAVR areas and distribution of sociodemographic and other factors that previous analysis has not been able to explore. These new understandings, and the possibilities for further use of our analysis, bring significant implications for the direction of national sport policies and advance decentralised policy approaches that are focused on distinctive local influences on sport volunteering. We also provide the basis for this original imputation modelling to be applied to other areas within largescale sport and physical activity datasets globally.

Localism · National Policy · Population · Nonprofit Sector and Volunteering · Sport and Mega-Event Impacts · Tourism, Volunteerism, and Development

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