Health impact, and economic value, of meeting housing quality standards: a retrospective longitudinal data linkage study

Abstract

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.

The health impacts of energy performance investments in low-income areas: a mixed-methods approach

“…The lifespans of the different elements range from 12 years for boiler upgrades and replacements to 42 years for insulation (see Table 14). 91 Considering that the shortest lifespan of an element was 12 years, residents remaining in the property after the improvements will have benefited from the elements installed. Extrapolating beyond the study period seems inappropriate for the base case scenario, given the uncertainty about the health benefits that remain with an individual if they move out of properties over time.…”

“…39,53,61 Extensive consultation and involvement throughout a housing improvement programme may help to minimise disruption to residents. 91 …”

“…The lack of association with emergency hospital admissions indicated that benefits do not appear in the hospital statistics within the follow-up period and that future evaluations should focus on less-severe conditions that may be treated in primary care settings, although recent research suggests that housing interventions may not necessarily change established patterns in primary health-care utilisation in populations with a long-term lack of well-being. 91 Furthermore, we acknowledge the data limitations, including the lack of depth of the routine data. For instance, using routine data means that we cannot understand how people's lives have changed in their home; this needed the additional studies that were completed as part of this research (see Chapter 3).…”

A Profile of the SAIL Databank on the UK Secure Research Platform

“…It has enabled largescale evaluations of the impact of health and social exposures, natural experiments and policy interventions to be undertaken, involving billions of records and calculations. These include development of total or segmented population e-cohorts, embedded trials and studies into health and educational impacts of natural experiments, including changing density of alcohol outlets, targeted area regeneration, free school breakfasts, living with mental health and alcohol problems, and the impact of large-scale housing improvements [26][27][28][29][30][31]. SAIL has over 1,200 registered data users, and the data have been used in over 300 projects, with approximately 30 new projects each year.…”

The Role of Health in Households’ Balancing Act for Lifestyles Compatible with the Paris Agreement—Qualitative Results from Mannheim, Germany

“…Furthermore, the intake of highly processed food in general increases, e.g., cardiovascular health risks and goes along with high GHGs emissions from processing and packing [31][32][33]. In the housing sector, better insulation of houses can save energy and at the same time reduce cold-and heat-related morbidity and mortality [34][35][36].…”