Health impact, and economic value, of meeting housing quality standards: a retrospective longitudinal data linkage study
Authors: Rodgers Sarah E , Bailey Rowena , Johnson Rhodri , Poortinga Wouter , Smith Robert , Berridge Damon , Anderson Pippa , Phillips Ceri , Lannon Simon , Jones Nikki , Dunstan Frank D , Morgan Jonathan , Evans Sandra Y , Every Pam , Lyons Ronan A 
Published: July 2018

BackgroundPoor-quality housing adversely affects residents’ health but there is a paucity of high-quality evidence to support this.ObjectiveThis research investigated the health impact of bringing housing to a national quality standard.DesignA natural experiment of improvements to housing quality analysed using repeated measures of health-care utilisation and economic outcomes at an individual person level.SettingCarmarthenshire, UK.ParticipantsA total of 32,009 residents registered for a minimum of 60 days at 8558 social homes that received housing improvements between January 2005 and March 2015.InterventionsMultiple internal and external housing improvements, including wall and loft insulation, windows and doors, heating system upgrades, new kitchens and bathrooms, garden path safety improvements and electrical system upgrades (adding power sockets, and extractor fans in kitchens and bathrooms).Main outcome measuresEmergency hospital admissions for cardiorespiratory conditions and injuries. Primary health-care utilisation for respiratory and common mental health disorders, emergency department injury attendances and health-care utilisation costs.Data sourcesCarmarthenshire County Council home address and intervention records were anonymously linked within the Secure Anonymous Information Linkage databank to demographic information from the Welsh Demographic Service data set; hospital admission data from the Patient Episode Dataset for Wales; primary care contacts and prescribed medications from general practice data; emergency department attendances from the Emergency Department Data Set; and deaths from the Office for National Statistics mortality register.MethodsThe study used a longitudinal panel design to examine changes in standard of eight housing cointervention from intervention records, and linked to individuals registered at intervention homes. Health outcomes were obtained retrospectively for each individual in a dynamic cohort and were captured for up to 123 consecutive months. An additional local authority region could not be utilised as a comparator owing to different reporting pressures resulting in the recording of a different intervention. The exposure group for each cointervention was compared with an internal reference group of people living in homes that did not receive the cointervention during their tenancy. A multilevel modelling approach was used to account for repeated observations for individuals living in intervention homes. Counts of health outcomes were analysed using negative binomial regression models to determine the effect of each cointervention that reached housing quality standards during an individual’s period of tenancy, compared with those living in properties that did not. We adjusted for potential confounding factors and for background trends in the regional general population. A cost–consequences analysis was conducted as part of the health economic evaluation.ResultsResidents aged ≥ 60 years living in homes in which electrical systems were upgraded were associated with 39% fewer admissions than those living in homes in which they were not [incidence rate ratio (IRR) 0.61, 95% confidence interval (CI) 0.53 to 0.72;p < 0.01]. Reduced admissions were also associated with windows and doors (IRR 0.71, 95% CI 0.63 to 0.81;p < 0.01), wall insulation (IRR 0.75, 95% CI 0.67 to 0.84;p < 0.01) and gardens and estates (IRR 0.73, 95% CI 0.64 to 0.83;p < 0.01) for those living in homes in which these cointervention were upgraded. There were no associations of change in emergency admissions with upgrading heating (IRR 0.91, 95% CI 0.82 to 1.01;p = 0.072), loft insulation (IRR 0.98, 95% CI 0.86 to 1.11;p = 0.695), kitchens (IRR 0.98, 95% CI 0.83 to 1.17;p = 0.843) or bathrooms (IRR 0.93, 95% CI 0.81 to 1.06;p = 0.287).LimitationsThere was no randomisation, there were incomplete data on the scale of the intervention for individual households and there were no estimates for the impact of the whole programme.ConclusionsThis complex interdisciplinary study found that hospital admissions could be avoided through improving housing quality standards.Future workAt their initiation, future non-health projects should have a built-in evaluation to allow intervention exposures to be randomly allocated to residents, with the simultaneous analysis of multiple health outcomes in one statistical model.FundingThe National Institute for Health Research Public Health Research programme.