Household energy efficiency and health: Area-level analysis of hospital admissions in England.

INTRODUCTION: Fuel poverty affects up to 35% of European homes, which represents a significant burden on society and healthcare systems. Draught proofing homes to prevent heat loss, improved glazing, insulation and heating (energy efficiency measures) can make more homes more affordable to heat. This has prompted significant investment in energy efficiency upgrades for around 40% of UK households to reduce the impact of fuel poverty. Despite some inconsistent evidence, household energy efficiency interventions can improve cardiovascular and respiratory health outcomes. However, the health benefits of these interventions have not been fully explored; this is the focus of this study. METHODS: In this cross sectional ecological study, we conducted two sets of analyses at different spatial resolution to explore population data on housing energy efficiency measures and hospital admissions at the area-level (counts grouped over a 3-year period). Housing data were obtained from three data sets covering housing across England (Household Energy Efficiency Database), Energy Performance Certificate (EPC) and, in the South West of England, the Devon Home Analytics Portal. These databases provided data aggregated to Lower Area Super Output Area and postcode level (Home Analytics Portal only). These datasets provided measures of both state (e.g. EPC ratings) and intervention (e.g. number of boiler replacements), aggregated spatially and temporally to enable cross-sectional analyses with health outcome data. Hospital admissions for adult (over 18 years) asthma, chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD) were obtained from the Hospital Episode Statistics database for the national (1st April 2011 to 31st March 2014) and Devon, South West of England (1st April 2014 to 31st March 2017) analyses. Descriptive statistics and regression models were used to describe the associations between small area household energy efficiency measures and hospital admissions. Three main analyses were undertaken to investigate the relationships between; 1) household energy efficiency improvements (i.e. improved glazing, insulation and boiler upgrades); 2) higher levels of energy efficiency ratings (measured by Energy Performance Certificate ratings); 3) energy efficiency improvements and ratings (i.e. physical improvements and rating assessed by the Standard Assessment Procedure) and hospital admissions. RESULTS: In the national analyses, household energy performance certificate ratings ranged from 37 to 83 (mean 61.98; Standard Deviation 5.24). There were a total of 312,837 emergency admissions for asthma, 587,770 for COPD and 839,416 for CVD. While analyses for individual energy efficiency metrics (i.e. boiler upgrades, draught proofing, glazing, loft and wall insulation) were mixed; a unit increase in mean energy performance rating was associated with increases of around 0.5% in asthma and CVD admissions, and 1% higher COPD admission rates. Admission rates were also influenced by the type of dwelling, tenure status (e.g. home owner versus renting), living in a rural area, and minimum winter temperature. DISCUSSION: Despite a range of limitations and some mixed and contrasting findings across the national and local analyses, there was some evidence that areas with more energy efficiency improvements resulted in higher admission rates for respiratory and cardiovascular diseases. This builds on existing evidence highlighting the complex relationships between health and housing. While energy efficiency measures can improve health outcomes (especially when targeting those with chronic respiratory illness), reduced household ventilation rates can impact indoor air quality for example and increase the risk of diseases such as asthma. Alternatively, these findings could be due to the ecological study design, reverse causality, or the non-detection of more vulnerable subpopulations, as well as the targeting of areas with poor housing stock, low income households, and the lack of "whole house approaches" when retrofitting the existing housing stock. CONCLUSION: To be sustainable, household energy efficiency policies and resulting interventions must account for whole house approaches (i.e. consideration of the whole house and occupant lifestyles). These must consider more alternative 'greener' and more sustainable measures, which are capable of accounting for variable lifestyles, as well as the need for adequate heating and ventilation. Larger natural experiments and more complex modelling are needed to further investigate the impact of ongoing dramatic changes in the housing stock and health. STUDY IMPLICATIONS: This study supports the need for more holistic approaches to delivering healthier indoor environments, which must consider a dynamic and complex system with multiple interactions between a range of interrelated factors. These need to consider the drivers and pressures (e.g. quality of the built environment and resident behaviours) resulting in environmental exposures and adverse health outcomes.

Emergency hospital admissions for the elderly: insights from the Devon Predictive Model.

BACKGROUND: In the UK, people aged 85 and over are the fastest growing population group and are predicted to double in number by 2030. Emergency hospital admissions are also rising. METHODS: All emergency admissions for the registered population in Devon to all English hospitals were analysed by age, and admission rates per thousand registered were calculated. The Devon Predictive Model (DPM) was built, using local data, to predict emergency admissions in the following 12 months. This model was compared with the Combined Predictive Model over five risk categories. RESULTS: The registered Devon population on 31 March 2011 was 761 652 with 65 892 emergency admissions in 2010/2011. The DPM had 89 variables including several local factors which strengthened the model. Three of the four most powerful predictors were age 85-89, 90-94 and 95 and over. The positive predictive value for the DPM was better than the CPM's in all five risk categories. Half (49.6%) of all emergency admissions were from those aged 65 or over. Admissions rose progressively and significantly in each successive elderly age band. At age 85 and over there were 420 emergency admissions per thousand registered. CONCLUSIONS: Age, especially 85 and over, has been undervalued as a risk factor for emergency hospital admissions.