Housing Characteristics and Hospital Admissions due to Falls on Stairs: A National Birth Cohort Study.

OBJECTIVE: To assess associations between housing characteristics and risk of hospital admissions related to falls on/from stairs in children, to help inform prevention measures. STUDY DESIGN: An existing dataset of birth records linked to hospital admissions up to age 5 for a cohort of 3,925,737 children born in England between 2008 and 2014, was linked to postcode-level housing data from Energy Performance Certificates. Association between housing construction age, tenure (eg, owner occupied), and built form and risk of stair-fall-related hospital admissions was estimated using Poisson regression. We stratified by age (<1 and 1-4 years), and adjusted for geographic region, Index of Multiple Deprivation, and maternal age. RESULTS: Incidence was higher in both age strata for children in neighborhoods with homes built before 1900 compared with homes built in 2003 or later (incidence rate ratio [IRR] 1.40, 95% confidence interval [CI] 1.10-1.77 [age <1 year], 1.20, 95% CI 1.05-1.36 [age 1-4 years]). For ages 1-4 years, incidence was higher for those in neighborhoods with housing built 1900-1929, compared with 2003 or later (IRR 1.26, 95% CI 1.13-1.41), or with predominantly social-rented homes compared with owner occupied (IRR 1.21, 95% CI 1.13-1.29). Neighborhoods with predominantly houses compared with flats had higher incidence (IRR 1.24, 95% CI 1.08-1.42 [<1 year] and IRR 1.16, 95% CI 1.08-1.25 [1-4 years]). CONCLUSION: Changes in building regulations may explain reduced fall incidence in newer homes compared with older homes. Fall prevention campaigns should consider targeting neighborhoods with older or social-rented housing. Future analyses would benefit from data linkage to individual homes, as opposed to local area level.

The potential of urban trees to reduce heat-related mortality in London.

Increasing temperatures and more frequent heatwave events pose threats to population health, particularly in urban environments due to the urban heat island (UHI) effect. Greening, in particular planting trees, is widely discussed as a means of reducing heat exposure and associated mortality in cities. This study aims to use data from personal weather stations (PWS) across the Greater London Authority to understand how urban temperatures vary according to tree canopy coverage and estimate the heat-health impacts of London's urban trees. Data from Netatmo PWS from 2015-2022 were cleaned, combined with official Met Office temperatures, and spatially linked to tree canopy coverage and built environment data. A generalized additive model was used to predict daily average urban temperatures under different tree canopy coverage scenarios for historical and projected future summers, and subsequent health impacts estimated. Results show areas of London with higher canopy coverage have lower urban temperatures, with average maximum daytime temperatures 0.8 °C and minimum temperatures 2.0 °C lower in the top decile versus bottom decile canopy coverage during the 2022 heatwaves. We estimate that London's urban forest helped avoid 153 heat attributable deaths from 2015-2022 (including 16 excess deaths during the 2022 heatwaves), representing around 16% of UHI-related mortality. Increasing tree coverage 10% in-line with the London strategy would have reduced UHI-related mortality by a further 10%, while a maximal tree coverage would have reduced it 55%. By 2061-2080, under RCP8.5, we estimate that London's current tree planting strategy can help avoid an additional 23 heat-attributable deaths a year, with maximal coverage increasing this to 131. Substantial benefits would also be seen for carbon storage and sequestration. Results of this study support increasing urban tree coverage as part of a wider public health effort to mitigate high urban temperatures.

Association Between Early External Ventricular Drain Insertion and Functional Outcomes 6 Months Following Moderate-to-Severe Traumatic Brain Injury.

Traumatic brain injury (TBI) is a leading global cause of morbidity and mortality. Intracranial hypertension following moderate-to-severe TBI (m-sTBI) is a potentially modifiable secondary cerebral insult and one of the central therapeutic targets of contemporary neurocritical care. External ventricular drain (EVD) insertion is a common therapeutic intervention used to control intracranial hypertension and attenuate secondary brain injury. However, the optimal timing of EVD insertion in the setting of m-sTBI is uncertain and practice variation is widespread. Therefore, we aimed to assess if there is an association between timing of EVD placement and functional neurological outcome at 6 months post m-sTBI. We pooled individual patient data for all relevant harmonizable variables from the Erythropoietin in Traumatic Brain Injury (EPO-TBI) and Prophylactic Hypothermia Trial to Lessen Traumatic Brain Injury (POLAR) randomized control trials, and the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) Core Study version 3.0 and Australia-Europe NeuroTrauma Effectiveness Research in TBI (Oz-ENTER) prospective observational studies to create a combined dataset. The Glasgow Coma Scale (GCS) score was used to define TBI severity and we included all patients admitted to an intensive care unit with a GCS ≤12, who were 15 years or older and underwent EVD placement within 7 days of injury. We used hierarchical multi-variable logistic regression models to study the association between EVD insertion within 24 h of injury (early) compared with EVD insertion more than 24 h after injury (late) and 6-month functional neurological outcome measured using the Glasgow Outcome Score Extended (GOSE). In total, 2536 patients were assessed. Of these, 502 (20%) underwent early EVD insertion and 145 (6%) underwent late EVD insertion. Following adjustment for the IMPACT (International Mission for Prognosis and Analysis of Clinical Trials in TBI) score extended (Core + CT), sex, injury severity score, study and treatment site, patients receiving a late EVD had higher odds of death or severe disability (GOSE 1-4) at 6 months follow-up than those receiving an early EVD adjusted odds ratio; 95% confidence interval, 2.14; 1.22-3.76; p = 0.008. Our study suggests that in patients with m-sTBI where an EVD is needed, early (≤ 24 h post-injury) insertion may result in better long-term functional outcomes. This finding supports future prospective investigation in this area.

The Effects of Repeated-Sprint Training on Physical Fitness and Physiological Adaptation in Athletes: A Systematic Review and Meta-Analysis.

BACKGROUND: Repeated-sprint training (RST) is a common training method for enhancing physical fitness in athletes. To advance RST prescription, it is important to understand the effects of programming variables on physical fitness and physiological adaptation. OBJECTIVES: This study (1) quantifies the pooled effects of running RST on changes in 10 and 20 m sprint time, maximal oxygen consumption (VO2max), Yo-Yo Intermittent Recovery Test Level 1 (YYIR1) distance, repeated-sprint ability (RSA), countermovement jump (CMJ) height and change of direction (COD) ability in athletes, and (2) examines the moderating effects of program duration, training frequency, weekly volume, sprint modality, repetition distance, number of repetitions per set and number of sets per session on changes in these outcome measures. METHODS: Pubmed, SPORTDiscus and Scopus databases were searched for original research articles up to 04 July 2023, investigating RST in healthy, able-bodied athletes, between 14 and 35 years of age, and a performance calibre of trained or above. RST interventions were limited to repeated, maximal running (land-based) sprints of ≤ 10 s duration, with ≤ 60 s recovery, performed for 2-12 weeks. A Downs and Black checklist was used to assess the methodological quality of the included studies. Eligible data were analysed using multi-level mixed-effects meta-analysis, with standardised mean changes determined for all outcomes. Standardised effects [Hedges G (G)] were evaluated based on coverage of their confidence (compatibility) intervals (CI) using a strength and conditioning specific reference value of G = 0.25 to declare an improvement (i.e. G > 0.25) or impairment (i.e. G < - 0.25) in outcome measures. Applying the same analysis, the effects of programming variables were then evaluated against a reference RST program, consisting of three sets of 6 × 30 m straight-line sprints performed twice per week for 6 weeks (1200 m weekly volume). RESULTS: 40 publications were included in our investigation, with data from 48 RST groups (541 athletes) and 19 active control groups (213 athletes). Across all studies, the effects of RST were compatible with improvements in VO2max (G 0.56, 90% CI 0.32-0.80), YYIR1 distance (G 0.61, 90% CI 0.43-0.79), RSA decrement (G - 0.61, 90% CI - 0.85 to - 0.37), linear sprint times (10 m: G - 0.35, 90% CI - 0.48 to - 0.22; 20 m: G - 0.48, 90% CI - 0.69 to - 0.27), RSA average time (G - 0.34, 90% CI - 0.49 to - 0.18), CMJ height (G 0.26, 90% CI 0.13-0.39) and COD ability (G - 0.32, 90% CI - 0.52 to - 0.12). Compared with the reference RST program, the effects of manipulating training frequency (+ 1 session per week), program duration (+ 1 extra training week), RST volume (+ 200 m per week), number of reps (+ 2 per set), number of sets per session (+ 1 set) or rep distance (+ 10 m per rep) were either non-substantial or comparable with an impairment in at least one outcome measure per programming variable. CONCLUSIONS: Running-based RST improves speed, intermittent running performance, VO2max, RSA, COD ability and CMJ height in trained athletes. Performing three sets of 6 × 30 m sprints, twice per week for 6 weeks is effective for enhancing physical fitness and physiological adaptation. Additionally, since our findings do not provide conclusive support for the manipulation of RST variables, further work is needed to better understand how programming factors can be manipulated to augment training-induced adaptations. STUDY REGISTRATION: Open Science Framework registration https://doi.org/10.17605/OSF.IO/RVNDW .

Analysis of inequalities in personal exposure to PM2.5: A modelling study for the Greater London school-aged population.

Exposure to air pollution can lead to negative health impacts, with children highly susceptible due to their immature immune and lung systems. Childhood exposure may vary by socio-economic status (SES) due to differences in both outdoor and indoor air pollution levels, the latter of which depends on, for example, building quality, overcrowding and occupant behaviours; however, exposure estimates typically rely on the outdoor component only. Quantifying population exposure across SES requires accounting for variations in time-activity patterns, outdoor air pollution concentrations, and concentrations in indoor microenvironments that account for pollution-generating occupant behaviours and building characteristics. Here, we present a model that estimates personal exposure to PM2.5 for ~1.3 million children aged 4-16 years old in the Greater London region from different income groups. The model combines 1) A national time-activity database, which gives the percentage of each group in different residential and non-residential microenvironments throughout a typical day; 2) Distributions of modelled outdoor PM2.5 concentrations; 3) Detailed estimates of domestic indoor concentrations for different housing and occupant typologies from the building physics model, EnergyPlus, and; 4) Non-domestic concentrations derived from a mass-balance approach. The results show differences in personal exposure across socio-economic groups for children, where the median daily exposure across all scenarios (winter/summer and weekends/weekdays) is 17.2 µg/m3 (95%CIs: 12.1 µg/m3-41.2 µg/m3) for children from households in the lowest income quintile versus 14.5 µg/m3 (95%CIs: 11.5 µg/m3 - 27.9 µg/m3) for those in the highest income quintile. Though those from lower-income homes generally fare worse, approximately 57 % of London's school-aged population across all income groups, equivalent to 761,976 children, have a median daily exposure which exceeds guideline 24-h limits set by the World Health Organisation. The findings suggest residential indoor sources of PM2.5 are a large contributor to personal exposure for school children in London. Interventions to reduce indoor exposure in the home (for example, via the maintenance of kitchen extract ventilation and transition to cleaner cooking fuels) should therefore be prioritised along with the continued mitigation of outdoor sources in Greater London.

Urban-rural disparity in global estimation of PM2·5 household air pollution and its attributable health burden.

BACKGROUND: Polluting fuels and inefficient stove technologies are still a leading cause of premature deaths worldwide, particularly in low-income and middle-income countries. Previous studies of global household air pollution (HAP) have neither considered the estimation of PM2·5 at national level nor the corresponding attributable mortality burden. Additionally, the effects of climate and ambient air pollution on the global estimation of HAP-PM2·5 exposure for different urban and rural settings remain largely unknown. In this study, we include climatic effects to estimate the HAP-PM2·5 exposure from different fuel types and stove technologies in rural and urban settings separately and the related attributable global mortality burden. METHODS: Bayesian hierarchical models were developed to estimate an annual average HAP-PM2·5 personal exposure and HAP-PM2·5 indoor concentration (including both outdoor and indoor sources). Model variables were selected from sample data in 282 peer-reviewed studies drawn and updated from the WHO Global HAP dataset. The PM2·5 exposure coefficients from the developed model were applied to the external datasets to predict the HAP-PM2·5 exposure globally (personal exposure in 62 countries and indoor concentration in 69 countries). Attributable mortality rate was estimated using a comparative risk assessment approach. Using weighted averages, the national level 24 h average HAP-PM2·5 exposure due to polluting and clean fuels and related death rate per 100 000 population were estimated. FINDINGS: In 2020, household use of polluting solid fuels for cooking and heating led to a national-level average personal exposure of 151 µg/m3 (95% CI 133-169), with rural households having an average of 171 µg/m3 (153-189) and urban households an average of 92 µg/m3 (77-106). Use of clean fuels gave rise to a national-level average personal exposure of 69 µg/m3 (62-76), with a rural average of 76 µg/m3 (69-83) and an urban average of 49 µg/m3 (46-53). Personal exposure-attributable premature mortality (per 100 000 population) from the use of polluting solid fuels at national level was on average 78 (95% CI 69-87), with a rural average of 82 (73-90) and an urban average of 66 (57-75). The average attributable premature mortality (per 100 000 population) from the use of clean fuels at the national level is 62 (54-70), with a rural average of 66 (58-74) and an urban average of 52 (47-57). The estimated HAP-PM2·5 indoor concentration shows that the use of polluting solid fuels resulted in a national-level average of 412 µg/m3 (95% CI 353-471), with a rural average of 514 µg/m3 (446-582) and an urban average of 149 µg/m3 (126-173). The use of clean fuels (gas and electricity) led to an average PM2·5 indoor concentration of 135 µg/m3 (117-153), with a rural average of 174 µg/m3 (154-195) and an urban average of 71 µg/m3 (63-80). Using time-weighted HAP-PM2·5 indoor concentrations, the attributable premature death rate (per 100 000 population) from the use of polluting solid fuels at the national level is on average 78 (95% CI 72-84), the rural average being 84 (78-91) and the urban average 60 (54-66). From the use of clean fuels, the average attributable premature death rate (per 100 000 population) at the national level is 59 (53-64), the rural average being 68 (62-74) and the urban average 45 (41-50). INTERPRETATION: A shift from polluting to clean fuels can reduce the average PM2·5 personal exposure by 53% and thereby lower the death rate. For all fuel types, the estimated average HAP-PM2·5 personal exposure and indoor concentrations exceed the WHO's Interim Target-1 average annual threshold. Policy interventions are urgently needed to greatly increase the use of clean fuels and stove technologies by 2030 to achieve the goal of affordable clean energy access, as set by the UN in 2015, and address health inequities in urban-rural settings. FUNDING: Wellcome Trust, The Lancet Countdown, the Engineering and Physical Sciences Research Council, and the Natural Environment Research Council.

SARS-CoV-2 tests, confirmed infections and COVID-19-related hospital admissions in children and young people: birth cohort study.

BACKGROUND: There have been no population-based studies of SARS-CoV-2 testing, PCR-confirmed infections and COVID-19-related hospital admissions across the full paediatric age range. We examine the epidemiology of SARS-CoV-2 in children and young people (CYP) aged <23 years. METHODS: We used a birth cohort of all children born in Scotland since 1997, constructed via linkage between vital statistics, hospital records and SARS-CoV-2 surveillance data. We calculated risks of tests and PCR-confirmed infections per 1000 CYP-years between August and December 2020, and COVID-19-related hospital admissions per 100 000 CYP-years between February and December 2020. We used Poisson and Cox proportional hazards regression models to determine risk factors. RESULTS: Among the 1 226 855 CYP in the cohort, there were 378 402 tests (a rate of 770.8/1000 CYP-years (95% CI 768.4 to 773.3)), 19 005 PCR-confirmed infections (179.4/1000 CYP-years (176.9 to 182.0)) and 346 admissions (29.4/100 000 CYP-years (26.3 to 32.8)). Infants had the highest COVID-19-related admission rates. The presence of chronic conditions, particularly multiple types of conditions, was strongly associated with COVID-19-related admissions across all ages. Overall, 49% of admitted CYP had at least one chronic condition recorded. CONCLUSIONS: Infants and CYP with chronic conditions are at highest risk of admission with COVID-19. Half of admitted CYP had chronic conditions. Studies examining COVID-19 vaccine effectiveness among children with chronic conditions and whether maternal vaccine during pregnancy prevents COVID-19 admissions in infants are urgently needed.

Projecting the impacts of housing on temperature-related mortality in London during typical future years.

Climate change means the UK will experience warmer winters and hotter summers in the future. Concurrent energy efficiency improvements to housing may modify indoor exposures to heat or cold, while population aging may increase susceptibility to temperature-related mortality. We estimate heat and cold mortality and energy consumption in London for typical (non-extreme) future climates, given projected changes in population and housing. Building physics models are used to simulate summertime and wintertime indoor temperatures and space heating energy consumption of London dwellings for 'baseline' (2005-2014) and future (2030s, 2050s) periods using data from the English Housing Survey, historical weather data, and projected future weather data with temperatures representative of 'typical' years. Linking to population projections, we calculate future heat and cold attributable mortality and energy consumption with demolition, construction, and alternative scenarios of energy efficiency retrofit. At current retrofit rates, around 168-174 annual cold-related deaths per million population would typically be avoided by the 2050s, or 261-269 deaths per million under ambitious retrofit rates. Annual heat deaths would typically increase by 1 per million per year under the current retrofit rate, and 12-13 per million under ambitious rates without population adaptation to heat. During typical future summers, an estimated 38-73% of heat-related deaths can be avoided using external shutters on windows, with their effectiveness lower during hotter weather. Despite warmer winters, ambitious retrofit rates are necessary to reduce typical annual energy consumption for heating below baseline levels, assuming no improvement in heating system efficiencies. Concerns over future overheating in energy efficient housing are valid but increases in heat attributable mortality during typical and hot (but not extreme) summers are more than offset by significant reductions in cold mortality and easily mitigated using passive measures. More ambitious retrofit rates are critical to reduce energy consumption and offer co-benefits for reducing cold-related mortality.

Systemic inequalities in indoor air pollution exposure in London, UK.

Deprived communities in many cities are exposed to higher levels of outdoor air pollution, and there is increasing evidence of similar disparities for indoor air pollution exposure. There is a need to understand the drivers for this exposure disparity in order to develop effective interventions aimed at improving population health and reducing health inequities. With a focus on London, UK, this paper assembles evidence to examine why indoor exposure to PM2.5, NOx and CO may disproportionately impact low-income groups. In particular, five factors are explored, namely: housing location and ambient outdoor levels of pollution; housing characteristics, including ventilation properties and internal sources of pollution; occupant behaviours; time spent indoors; and underlying health conditions. Evidence is drawn from various sources, including building physics models, modelled outdoor air pollution levels, time-activity surveys, housing stock surveys, geographical data, and peer-reviewed research. A systems framework is then proposed to integrate these factors, highlighting how exposure to high levels of indoor air pollution in low-income homes is in large part due to factors beyond the control of occupants, and is therefore an area of systemic inequality. POLICY RELEVANCE: There is increasing public and political awareness of the impact of air pollution on public health. Strong scientific evidence links exposure to air pollution with morbidity and mortality. Deprived communities may be more affected, however, with limited evidence on how deprivation may influence their personal exposure to air pollution, both outdoors and indoors. This paper describes different factors that may lead to low-income households being exposed to higher levels of indoor air pollution than the general population, using available data and models for London (i.e. living in areas of higher outdoor air pollution, in poor-quality housing, undertaking more pollution-generating activities indoors and spending more time indoors). A systems approach is used to show how these factors lead to systemic exposure inequalities, with low-income households having limited opportunities to improve their indoor air quality. This paper can inform actions and public policies to reduce environmental health inequalities, considering both indoor and outdoor air.

Impact of COVID-19 lockdown on NO2 and PM2.5 exposure inequalities in London, UK.

Amid the COVID-19 pandemic, a nationwide lockdown was imposed in the United Kingdom (UK) on March 23, 2020. These sudden control measures led to radical changes in human activities in the Greater London Area (GLA). During this lockdown, transportation use was significantly reduced and non-key workers were required to work from home. This study aims to understand how population exposure to PM2.5 and NO2 changed spatially and temporally across London, in different microenvironments, following the lockdown period relative to the previous three-year average in the same calendar period. Our research shows that population exposure to NO2 declined significantly (52.3% ± 6.1%), while population exposure to PM2.5 showed a smaller relative reduction (15.7% ± 4.1%). Changes in population activity had the strongest relative influence on exposure levels during morning rush hours, when prior to the lockdown a large percentage of people would normally commute or be at the workplace. In particular, a very high exposure decrease was observed for both pollutants (approximately 66% for NO2 and 19% for PM2.5) at 08:00am, consistent with the radical changes in population commuting. The infiltration of outdoor air pollution into housing modifies the degree of exposure change both temporally and spatially. Moreover, this study shows that the impacts on air pollution exposure vary across groups with different socioeconomic status (SES), with a disproportionate positive effect on the areas of the city home to more economically deprived communities.

Air Pollution, housing and respirfatory tract Infections in Children: NatIonal birth Cohort study (PICNIC): study protocol.

INTRODUCTION: Respiratory tract infections (RTIs) are the most common reason for hospital admission among children <5 years in the UK. The relative contribution of ambient air pollution exposure and adverse housing conditions to RTI admissions in young children is unclear and has not been assessed in a UK context. METHODS AND ANALYSIS: The aim of the PICNIC study (Air Pollution, housing and respiratory tract Infections in Children: NatIonal birth Cohort Study) is to quantify the extent to which in-utero, infant and childhood exposures to ambient air pollution and adverse housing conditions are associated with risk of RTI admissions in children <5 years old. We will use national administrative data birth cohorts, including data from all children born in England in 2005-2014 and in Scotland in 1997-2020, created via linkage between civil registration, maternity and hospital admission data sets. We will further enhance these cohorts via linkage to census data on housing conditions and socioeconomic position and small area-level data on ambient air pollution and building characteristics. We will use time-to-event analyses to examine the association between air pollution, housing characteristics and the risk of RTI admissions in children, calculate population attributable fractions for ambient air pollution and housing characteristics, and use causal mediation analyses to explore the mechanisms through which housing and air pollution influence the risk of infant RTI admission. ETHICS, EXPECTED IMPACT AND DISSEMINATION: To date, we have obtained approval from six ethics and information governance committees in England and two in Scotland. Our results will inform parents, national and local governments, the National Health Service and voluntary sector organisations of the relative contribution of adverse housing conditions and air pollution to RTI admissions in young children. We will publish our results in open-access journals and present our results to the public via parent groups and social media and on the PICNIC website. Code and metadata will be published on GitHub.

The CUSSH programme: supporting cities' transformational change towards health and sustainability.

This paper describes a global research programme on the complex systemic connections between urban development and health. Through transdisciplinary methods the Complex Urban Systems for Sustainability and Health (CUSSH) project will develop critical evidence on how to achieve the far-reaching transformation of cities needed to address vital environmental imperatives for planetary health in the 21st Century. CUSSH's core components include: (i) a review of evidence on the effects of climate actions (both mitigation and adaptation) and factors influencing their implementation in urban settings; (ii) the development and application of methods for tracking the progress of cities towards sustainability and health goals; (iii) the development and application of models to assess the impact on population health, health inequalities, socio-economic development and environmental parameters of urban development strategies, in order to support policy decisions; (iv) iterative in-depth engagements with stakeholders in partner cities in low-, middle- and high-income settings, using systems-based participatory methods, to test and support the implementation of the transformative changes needed to meet local and global health and sustainability objectives; (v) a programme of public engagement and capacity building. Through these steps, the programme will provide transferable evidence on how to accelerate actions essential to achieving population-level health and global climate goals through, amongst others, changing cities' energy provision, transport infrastructure, green infrastructure, air quality, waste management and housing.

Household overcrowding and risk of SARS-CoV-2: analysis of the Virus Watch prospective community cohort study in England and Wales.

Background: Household overcrowding is associated with increased risk of infectious diseases across contexts and countries. Limited data exist linking household overcrowding and risk of COVID-19. We used data collected from the Virus Watch cohort to examine the association between overcrowded households and SARS-CoV-2. Methods: The Virus Watch study is a household community cohort of acute respiratory infections in England and Wales. We calculated overcrowding using the measure of persons per room for each household. We considered two primary outcomes: PCR-confirmed positive SARS-CoV-2 antigen tests and laboratory-confirmed SARS-CoV-2 antibodies. We used mixed-effects logistic regression models that accounted for household structure to estimate the association between household overcrowding and SARS-CoV-2 infection. Results:26,367 participants were included in our analyses. The proportion of participants with a positive SARS-CoV-2 PCR result was highest in the overcrowded group (9.0%; 99/1,100) and lowest in the under-occupied group (4.2%; 980/23,196). In a mixed-effects logistic regression model, we found strong evidence of an increased odds of a positive PCR SARS-CoV-2 antigen result (odds ratio 2.45; 95% CI:1.43-4.19; p-value=0.001) and increased odds of a positive SARS-CoV-2 antibody result in individuals living in overcrowded houses (3.32; 95% CI:1.54-7.15; p-value<0.001) compared with people living in under-occupied houses. Conclusion:Public health interventions to prevent and stop the spread of SARS-CoV-2 should consider the risk of infection for people living in overcrowded households and pay greater attention to reducing household transmission.

Exposure to indoor air pollution across socio-economic groups in high-income countries: A scoping review of the literature and a modelling methodology.

Disparities in outdoor air pollution exposure between individuals of differing socio-economic status is a growing area of research, widely explored in the environmental health literature. However, in developed countries, around 80% of time is spent indoors, meaning indoor air pollution may be a better proxy for personal exposure. Building characteristics - such as build quality, volume and ventilation - and occupant behaviour, mean indoor air pollution may also vary across socio-economic groups, leading to health inequalities. Much of the existing literature has focused on inequalities in exposure to outdoor air pollution, and there is thus a lack of an evidence base reviewing data for indoor environments. In this study, a scoping review of the literature on indoor air pollution exposures across different socio-economic groups is performed, examining evidence from both monitoring and modelling studies in the developed world. The literature was reviewed, identifying different indoor pollutants, definitions for socio-economic status and pre- and post- housing interventions. Based on the review, the study proposes a modelling methodology for evaluating the effects of environmental policies on different socio-economic populations. Using a sample size calculation, obstacles in obtaining sufficiently large samples of monitored data are demonstrated. A modelling framework for the rapid quantification of daily home exposure is then outlined as a proof of concept. While significant additional research is required to examine inequalities in indoor exposures, modelling approaches may provide opportunities to quantify exposure disparities due to housing and behaviours across populations of different socio-economic status.

A tool for assessing the climate change mitigation and health impacts of environmental policies: the Cities Rapid Assessment Framework for Transformation (CRAFT).

Background: A growing number of cities, including Greater London, have set ambitious targets, including detailed policies and implementation plans, to reach global goals on sustainability, health, and climate change. Here we present a tool for a rapid assessment of the magnitude of impact of specific policy initiatives to reach these targets. The decision-support tool simultaneously quantifies the environmental and health impacts of specified selected policies. Methods: The 'Cities Rapid Assessment Framework for Transformation (CRAFT)' tool was applied to Greater London. CRAFT quantifies the effects of ten environmental policies on changes in (1) greenhouse gas (GHG) emissions, (2) exposures to environmental hazards, (3) travel-related physical activity, and (4) mortality (the number of attributable deaths avoided in one typical year). Publicly available data and epidemiological evidence were used to make rapid quantitative estimates of these effects based on proportional reductions in GHG emissions and environmental exposures from current baseline levels and to compute the mortality impacts. Results: The CRAFT tool estimates that, of roughly 50,000 annual deaths in Greater London, the modelled hazards (PM 2.5 (from indoor and outdoor sources), outdoor NO 2, indoor radon, cold, overheating) and low travel-related physical activity are responsible for approximately 10,000 premature environment-related deaths. Implementing the selected polices could reduce the annual mortality number by about 20% (~1,900 deaths) by 2050. The majority of these deaths (1,700) may be avoided through increased uptake in active travel. Thus, out of ten environmental policies, the 'active travel' policy provides the greatest health benefit. Also, implementing the ten policies results in a GHG reduction of around 90%. Conclusions: The CRAFT tool quantifies the effects of city policies on reducing GHG emissions, decreasing environmental health hazards, and improving public health. The tool has potential value for policy makers through providing quantitative estimates of health impacts to support and prioritise policy options.

What individual and neighbourhood-level factors increase the risk of heat-related mortality? A case-crossover study of over 185,000 deaths in London using high-resolution climate datasets.

OBJECTIVE: Management of the natural and built environments can help reduce the health impacts of climate change. This is particularly relevant in large cities where urban heat island makes cities warmer than the surrounding areas. We investigate how urban vegetation, housing characteristics and socio-economic factors modify the association between heat exposure and mortality in a large urban area. METHODS: We linked 185,397 death records from the Greater London area during May-Sept 2007-2016 to a high resolution daily temperature dataset. We then applied conditional logistic regression within a case-crossover design to estimate the odds of death from heat exposure by individual (age, sex) and local area factors: land-use type, natural environment (vegetation index, tree cover, domestic garden), built environment (indoor temperature, housing type, lone occupancy) and socio-economic factors (deprivation, English language, level of employment and prevalence of ill-health). RESULTS: Temperatures were higher in neighbourhoods with lower levels of urban vegetation and with higher levels of income deprivation, social-rented housing, and non-native English speakers. Heat-related mortality increased with temperature increase (Odds Ratio (OR), 95% CI = 1.039, 1.036-1.043 per 1 °C temperature increase). Vegetation cover showed the greatest modification effect, for example the odds of heat-related mortality in quartiles with the highest and lowest tree cover were OR, 95%CI 1.033, 1.026-1.039 and 1.043, 1.037-1.050 respectively. None of the socio-economic variables were a significant modifier of heat-related mortality. CONCLUSIONS: We demonstrate that urban vegetation can modify the mortality risk associated with heat exposure. These findings make an important contribution towards informing city-level climate change adaptation and mitigation policies.

A Comparative Analysis of Global Datasets and Initiatives for Urban Health and Sustainability.

Globally, urban populations are growing rapidly, and in most cases their demands for resources are beyond current limits of sustainability. Cities are therefore critical for achieving national and international sustainability objectives, such as greenhouse gas reduction. Improving sustainability may also provide opportunities for urban population health co-benefits by reducing unhealthy exposures and behaviours. However, there is currently sparse empirical evidence on the degree to which city characteristics are associated with variations in health-related exposures, behaviours and sustainability. This paper examines the feasibility of aggregating empirical data relating to sustainability and health for global cities. An initial scoping review of existing English-language datasets and networks is performed. Resulting datasets are analysed for data types, collection method, and the distribution of contributing cities across climates, population sizes, and wealth. The review indicates datasets are populated using inconsistent methodologies and metrics and have poor overlap of cities between them. Data and organisations tend to be biased towards larger and wealthier cities, and concentrated in Europe and North America. Therefore, despite vast amounts of available data, limitations of reliability, representativeness, and disparate sources mean researchers are faced with significant obstacles when aggregating data to analyse the sustainability and health of globally representative samples of cities.

The Challenge of Urban Heat Exposure under Climate Change: An Analysis of Cities in the Sustainable Healthy Urban Environments (SHUE) Database.

The so far largely unabated emissions of greenhouse gases (GHGs) are expected to increase global temperatures substantially over this century. We quantify the patterns of increases for 246 globally-representative cities in the Sustainable Healthy Urban Environments (SHUE) database. We used an ensemble of 18 global climate models (GCMs) run under a low (RCP2.6) and high (RCP8.5) emissions scenario to estimate the increase in monthly mean temperatures by 2050 and 2100 based on 30-year averages. Model simulations were from the Coupled Model Inter-comparison Project Phase 5 (CMIP5). Annual mean temperature increases were 0.93 degrees Celsius by 2050 and 1.10 degrees Celsius by 2100 under RCP2.6, and 1.27 and 4.15 degrees Celsius under RCP8.5, but with substantial city-to-city variation. By 2100, under RCP2.6 no city exceeds an increase in Tmean > 2 degrees Celsius (relative to a 2017 baseline), while all do under RCP8.5, some with increases in Tmean close to, or even greater than, 7 degrees Celsius. The increases were greatest in cities of mid to high latitude, in humid temperate and dry climate regions, and with large seasonal variation in temperature. Cities are likely to experience large increases in hottest month mean temperatures under high GHG emissions trajectories, which will often present substantial challenges to adaptation and health protection.

Environmental Risks of Cities in the European Region: Analyses of the Sustainable Healthy Urban Environments (SHUE) Database.

INTRODUCTION: In an increasingly urbanized world, cities are a key focus for action on health and sustainability. The Sustainable Healthy Urban Environments (SHUE) project aims to provide a shared information resource to support such action. Its aim is to test the feasibility and methods of assembling data about the characteristics of a globally distributed sample of cities and the populations within them for comparative analyses, and to use such data to assess how policies may contribute to sustainable urban development and human health. METHODS: As a first illustration of the database, we present analyses of selected parameters on climate change, air pollution and flood risk for 64 cities in the WHO European Region. RESULTS: Under a high greenhouse gas emissions trajectory (RCP8.5), the analyses suggest damaging temperature rises in European cities that are among the highest of any cities in the global database, while air pollution (PM2.5) levels are appreciably above the WHO guideline level for all but a handful of cities. In several areas, these environmental hazards are compounded by flood risk. DISCUSSION: Such evidence, though preliminary and based on limited data, underpins the need for urgent action on climate change (adaptation and mitigation) and risks relating to air pollution and other environmental hazards.

Application of an indoor air pollution metamodel to a spatially-distributed housing stock.

Estimates of population air pollution exposure typically rely on the outdoor component only, and rarely account for populations spending the majority of their time indoors. Housing is an important modifier of air pollution exposure due to outdoor pollution infiltrating indoors, and the removal of indoor-sourced pollution through active or passive ventilation. Here, we describe the application of an indoor air pollution modelling tool to a spatially distributed housing stock model for England and Wales, developed from Energy Performance Certificate (EPC) data and containing information for approximately 11.5 million dwellings. First, we estimate indoor/outdoor (I/O) ratios and total indoor concentrations of outdoor air pollution for PM2.5 and NO2 for all EPC dwellings in London. The potential to estimate concentration from both indoor and outdoor sources is then demonstrated by modelling indoor background CO levels for England and Wales pre- and post-energy efficient adaptation, including heating, cooking, and smoking as internal sources. In London, we predict a median I/O ratio of 0.60 (99% CIs; 0.53-0.73) for outdoor PM2.5 and 0.41 (99%CIs; 0.34-0.59) for outdoor NO2; Pearson correlation analysis indicates a greater spatial modification of PM2.5 exposure by housing (ρ = 0.81) than NO2 (ρ = 0.88). For the demonstrative CO model, concentrations ranged from 0.4-9.9 ppm (99%CIs)(median = 3.0 ppm) in kitchens and 0.3-25.6 ppm (median = 6.4 ppm) in living rooms. Clusters of elevated indoor concentration are found in urban areas due to higher outdoor concentrations and smaller dwellings with reduced ventilation potential, with an estimated 17.6% increase in the number of living rooms and 63% increase in the number of kitchens exceeding recommended exposure levels following retrofit without additional ventilation. The model has the potential to rapidly calculate indoor pollution exposure across large housing stocks and estimate changes to exposure under different pollution or housing policy scenarios.