Cohort Profile: The Housing Regeneration and Health Study

Rodgers, Sarah; Heaven, Martin; Lacey, Arron; Poortinga, Wouter; Dunstan, Frank David John; Jones, Kerina; Palmer, S.R.; Phillips, Ceri; Smith, Robert S.; John, Ann; Davies, Gwyn; Lyons, Ronan A.

doi:10.1093/ije/dys200

Cited by 12 publications

(15 citation statements)

References 16 publications

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“…Anonymous data linkage of routinely collected health data, which is less vulnerable to such biases, has not, to our knowledge, been used before to examine the impact of energy efficiency improvements (see Chapter 2). 73 In addition, less is known about the wider psychosocial impact of energy efficiency improvements. There is a distinct lack of good-quality quantitative evidence regarding the pathways and processes that may contribute to better health in the longer term (see Chapter 3).…”

Section: Resultsmentioning

confidence: 99%

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

et al. 2018

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BackgroundCold homes and fuel poverty contribute to health inequalities in ways that could be addressed through energy efficiency interventions.ObjectivesTo determine the health and psychosocial impacts of energy performance investments in low-income areas, particularly hospital admissions for cardiorespiratory conditions, prevalence of respiratory symptoms and mental health status, hydrothermal conditions and household energy use, psychosocial outcomes, cost consequences to the health system and the cost utility of these investments.DesignA mixed-methods study comprising data linkage (25,908 individuals living in 4968 intervention homes), a field study with a controlled pre-/post-test design (intervention,n = 418; control,n = 418), a controlled multilevel interrupted time series analysis of internal hydrothermal conditions (intervention,n = 48; control,n = 40) and a health economic assessment.SettingLow-income areas across Wales.ParticipantsResidents who received energy efficiency measures through the intervention programme and matched control groups.Main outcome measuresPrimary outcomes – emergency hospital admissions for cardiorespiratory conditions, self-reported respiratory symptoms, mental health status, indoor air temperature and indoor relative humidity. Secondary outcomes – emergency hospital admissions for chronic obstructive pulmonary disease-related cardiorespiratory conditions, excess winter admissions, health-related quality of life, subjective well-being, self-reported fuel poverty, financial stress and difficulties, food security, social interaction, thermal satisfaction and self-reported housing conditions.MethodsAnonymously linked individual health records for emergency hospital admissions were analysed using mixed multilevel linear models. A quasi-experimental controlled field study used a multilevel repeated measures approach. Controlled multilevel interrupted time series analyses were conducted to estimate changes in internal hydrothermal conditions following the intervention. The economic evaluation comprised cost–consequence and cost–utility analyses.Data sourcesThe Patient Episode Database for Wales 2005–14, intervention records from 28 local authorities and housing associations, and scheme managers who delivered the programme.ResultsThe study found no evidence of changes in physical health. However, there were improvements in subjective well-being and a number of psychosocial outcomes. The household monitoring study found that the intervention raised indoor temperature and helped reduce energy use. No evidence was found of substantial increases in indoor humidity levels. The health economic assessment found no explicit cost reductions to the health service as a result of non-significant changes in emergency admissions for cardiorespiratory conditions.LimitationsThis was a non-randomised intervention study with household monitoring and field studies that relied on self-response. Data linkage focused on emergency admissions only.ConclusionAlthough there was no evidence that energy performance investments provide physical health benefits or reduce health service usage, there was evidence that they improve social and economic conditions that are conducive to better health and improved subjective well-being. The intervention has been successful in reducing energy use and improving the living conditions of households in low-income areas. The lack of association of emergency hospital admissions with energy performance investments means that we were unable to evidence cost saving to health-service providers.Future workOur research suggests the importance of incorporating evaluations with follow-up into intervention research from the start.FundingThe National Institute for Health Research Public Health Research programme.

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Section: Resultsmentioning

confidence: 99%

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

et al. 2018

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“…65 The study reported here focuses on the impact on the utilisation of secondary health-care services, including emergency admissions of people living in homes that received the housing intervention compared with people living in homes before interventions were implemented. 66 …”

Section: Economic Evaluations Lmentioning

confidence: 99%

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

et al. 2018

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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.

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“…Methods to evaluate the impact of natural experiments have been enhanced by the development of anonymised electronic record-linkage in secure databanks that facilitate the use of administrative data in public health research (Fone et al 2012(Fone et al , 2013Rodgers et al 2012;White et al 2014). Data linkage methods allow spatially referenced exposures to be linked to existing cohort studies and to populate age-sex registers for defining new cohorts with full information on small-area migration.…”

Section: Introductionmentioning

confidence: 99%

“…Data linkage methods allow spatially referenced exposures to be linked to existing cohort studies and to populate age-sex registers for defining new cohorts with full information on small-area migration. These new rich sources of data are facilitating a new approach to the longitudinal analysis of natural experiments (Fone et al 2013;Rodgers et al 2012;White et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Using Routinely Collected Administrative Data in Public Health Research: Geocoding Alcohol Outlet Data

Fry

Rodgers

Morgan

et al. 2016

Appl. Spatial Analysis

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We describe our process of geocoding alcohol outlets to create a national longitudinal exposure dataset for Wales, United Kingdom from 2006 to 2011. We investigated variation in the availability of data items and the quality of alcohol outlet addresses held within unitary authorities. We used a standard geocoding method augmented with a manual matching procedure to achieve a fully spatially referenced dataset. We found higher quality addresses are held for outlets based in urban areas, resulting in the automatic geocoding of 68 % of urban outlets, compared to 48 % in rural areas. Missing postcodes and a lack of address structure contributed to a lower geocoding proportion. An urban rural bias was removed with the development of a manual matching procedure. Only one-half of the unitary authorities provided data on on/off sales and opening times, which are important availability factors. The resulting outlet dataset is suitable for contributing to the evidence-base of alcohol availability and alcohol-related harm. Local government should be encouraged to use standardised data fields, including addresses, to enable accurate geocoding of alcohol outlets and facilitate research that aims to prevent alcohol-related harm. Standardising data collection would enable efficient secondary data reuse using record linkage techniques, allowing Appl. Spatial Analysis (2017) 10:301-315

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Cohort Profile: The Housing Regeneration and Health Study

Cited by 12 publications

References 16 publications

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

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

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

Using Routinely Collected Administrative Data in Public Health Research: Geocoding Alcohol Outlet Data

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