This publication of the SHMI relates to discharges in the reporting period March 2023 - February 2024. The SHMI is the ratio between the actual number of patients who die following hospitalisation at the trust and the number that would be expected to die on the basis of average England figures, given the characteristics of the patients treated there. The SHMI covers patients admitted to hospitals in England who died either while in hospital or within 30 days of being discharged. To help users of the data understand the SHMI, trusts have been categorised into bandings indicating whether a trust's SHMI is 'higher than expected', 'as expected' or 'lower than expected'. For any given number of expected deaths, a range of observed deaths is considered to be 'as expected'. If the observed number of deaths falls outside of this range, the trust in question is considered to have a higher or lower SHMI than expected. The expected number of deaths is a statistical construct and is not a count of patients. The difference between the number of observed deaths and the number of expected deaths cannot be interpreted as the number of avoidable deaths or excess deaths for the trust. The SHMI is not a measure of quality of care. A higher than expected number of deaths should not immediately be interpreted as indicating poor performance and instead should be viewed as a 'smoke alarm' which requires further investigation. Similarly, an 'as expected' or 'lower than expected' SHMI should not immediately be interpreted as indicating satisfactory or good performance. Trusts may be located at multiple sites and may be responsible for 1 or more hospitals. A breakdown of the data by site of treatment is also provided, as well as a breakdown of the data by diagnosis group. Further background information and supporting documents, including information on how to interpret the SHMI, are available on the SHMI homepage (see Related Links).

Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

The Excess Winter Mortality Index (EWD Index) shows excess winter deaths as a Percentage Ratio of the number of deaths expected in the (eight) warmer months either side of Winter (01 December to 31 March). So the data’s yearly time period is from 01 August to 31 July the following year. In other words, EWD is the ratio of extra deaths from all causes during the winter months compared to average non-winter deaths. The EWD Index is partly dependent on the proportion of Older People in the population, as most excess winter deaths affect Older People. This indicator covers all ages, but there is no standardisation in its calculation by age or any other factor. So figures for an area can be influenced for example by the proportion of Older People. This dataset is updated annually. Source: Office for Health Improvement and Disparities (OHID) Public Health Outcomes Framework (PHOF), indicator 90360 / E14. Age breakouts, confidence intervals and metadata are shown on the PHE (PHOF) site. Note: Please be advised that the ONS currently has this dataset under consultation for review (as of 09/01/2025) so may not be updated annually until the review has concluded. The full notice can be found on the ONS link for the Winter Mortality publication - please see link in the Additional Information Section.

The dataset consists of quantitative data derived mainly from international datasets (ILO, WHO), supplemented by data from national datasets and modelled data to complete missing values. It shows the statistical data we collated and used to calculate estimates of Covid-19 deaths among migrant health care workers and includes details on how missing information was imputed. It includes spreadsheet estimates for India, Nigeria, Mexico, and the UK for excess and reported Covid-19 deaths amongst foreign-born workers and for all workers in the human health and social work sector and in three specific health occupations: doctors, nurses, and midwives. For each group the spreadsheets provide a basic estimate and an age-sex standardised estimate.

This project aims to give proper attention to the place of migrant workers in health care systems during the Covid-19 pandemic. Migrant workers are of substantial and growing significance in many countries' health and care systems and are key to realising the global goal of universal health care, so it is vital that we understand much better how Covid-19 is impacting on them.

The project's overarching research questions are, in the relation to Covid-19, what risks do migrant health care workers experience, what are the pressures on resilient and sustainable health care workforces, and how are stakeholders responding to these risks and pressures?

We develop a research method to estimate Covid-19 migrant health care worker mortality rates and trial the method, undertaking statistical analysis and modelling using quantitative data drawn from WHO and OECD data and other demographic and bio-statistical data as available.

In addition to strengthening the methodological techniques and empirical evidence base on the risks of Covid-19 infection and death among migrant health care workers our project also tracks, through documentary analysis, collective responses to such risks and challenges to sustainable health workforces for universal health coverage.

This project is attuned to the urgent need for high quality data and for 'real world' solutions-focused Covid-19 research forged from collaboration. We are focused on the immediate application of proof-of concept findings to a rapidly-evolving global health crisis.

Final multivariable logistic regression risk factor analysis n = 186.

Follow-up distributions for cases and non-cases (years).

Single variable risk factor analysis.

Hazard Ratio for cases compared to non-cases unadjusted and adjusted for variables shown.

Predicted excess AAA deaths and emergency operations in the national surveillance cohort over 30y period.

This data originates from the Public Health Outcomes tool currently presents data for available indicators for upper tier local authority levels, collated by Public Health England (PHE). The data currently published here are the baselines for the Public Health Outcomes Framework, together with more recent data where these are available. The baseline period is 2010 or equivalent, unless these data are unavailable or not deemed to be of sufficient quality. The first data were published in this tool as an official statistics release in November 2012. Future official statistics updates will be published as part of a quarterly update cycle in August, November, February and May. The definition, rationale, source information, and methodology for each indicator can be found within the spreadsheet. Data included in the spreadsheet: 0.1i - Healthy life expectancy at birth0.1ii - Life Expectancy at 650.1ii - Life Expectancy at birth0.2i - Slope index of inequality in life expectancy at birth based on national deprivation deciles within England0.2ii - Number of upper tier local authorities for which the local slope index of inequality in life expectancy (as defined in 0.2iii) has decreased0.2iii - Slope index of inequality in life expectancy at birth within English local authorities, based on local deprivation deciles within each area0.2iv - Gap in life expectancy at birth between each local authority and England as a whole0.2v - Slope index of inequality in healthy life expectancy at birth based on national deprivation deciles within England0.2vii - Slope index of inequality in life expectancy at birth within English regions, based on regional deprivation deciles within each area1.01i - Children in poverty (all dependent children under 20)1.01ii - Children in poverty (under 16s)1.02i - School Readiness: The percentage of children achieving a good level of development at the end of reception1.02i - School Readiness: The percentage of children with free school meal status achieving a good level of development at the end of reception1.02ii - School Readiness: The percentage of Year 1 pupils achieving the expected level in the phonics screening check1.02ii - School Readiness: The percentage of Year 1 pupils with free school meal status achieving the expected level in the phonics screening check1.03 - Pupil absence1.04 - First time entrants to the youth justice system1.05 - 16-18 year olds not in education employment or training1.06i - Adults with a learning disability who live in stable and appropriate accommodation1.06ii - % of adults in contact with secondary mental health services who live in stable and appropriate accommodation1.07 - People in prison who have a mental illness or a significant mental illness1.08i - Gap in the employment rate between those with a long-term health condition and the overall employment rate1.08ii - Gap in the employment rate between those with a learning disability and the overall employment rate1.08iii - Gap in the employment rate for those in contact with secondary mental health services and the overall employment rate1.09i - Sickness absence - The percentage of employees who had at least one day off in the previous week1.09ii - Sickness absence - The percent of working days lost due to sickness absence1.10 - Killed and seriously injured (KSI) casualties on England's roads1.11 - Domestic Abuse1.12i - Violent crime (including sexual violence) - hospital admissions for violence1.12ii - Violent crime (including sexual violence) - violence offences per 1,000 population1.12iii- Violent crime (including sexual violence) - Rate of sexual offences per 1,000 population1.13i - Re-offending levels - percentage of offenders who re-offend1.13ii - Re-offending levels - average number of re-offences per offender1.14i - The rate of complaints about noise1.14ii - The percentage of the population exposed to road, rail and air transport noise of 65dB(A) or more, during the daytime1.14iii - The percentage of the population exposed to road, rail and air transport noise of 55 dB(A) or more during the night-time1.15i - Statutory homelessness - homelessness acceptances1.15ii - Statutory homelessness - households in temporary accommodation1.16 - Utilisation of outdoor space for exercise/health reasons1.17 - Fuel Poverty1.18i - Social Isolation: % of adult social care users who have as much social contact as they would like1.18ii - Social Isolation: % of adult carers who have as much social contact as they would like1.19i - Older people's perception of community safety - safe in local area during the day1.19ii - Older people's perception of community safety - safe in local area after dark1.19iii - Older people's perception of community safety - safe in own home at night2.01 - Low birth weight of term babies2.02i - Breastfeeding - Breastfeeding initiation2.02ii - Breastfeeding - Breastfeeding prevalence at 6-8 weeks after birth2.03 - Smoking status at time of delivery2.04 - Under 18 conceptions2.04 - Under 18 conceptions: conceptions in those aged under 162.06i - Excess weight in 4-5 and 10-11 year olds - 4-5 year olds2.06ii - Excess weight in 4-5 and 10-11 year olds - 10-11 year olds2.07i - Hospital admissions caused by unintentional and deliberate injuries in children (aged 0-14 years)2.07i - Hospital admissions caused by unintentional and deliberate injuries in children (aged 0-4 years)2.07ii - Hospital admissions caused by unintentional and deliberate injuries in young people (aged 15-24)2.08 - Emotional well-being of looked after children2.09i - Smoking prevalence at age 15 - current smokers (WAY survey)2.09ii - Smoking prevalence at age 15 - regular smokers (WAY survey)2.09iii - Smoking prevalence at age 15 - occasional smokers (WAY survey)2.09iv - Smoking prevalence at age 15 years - regular smokers (SDD survey)2.09v - Smoking prevalence at age 15 years - occasional smokers (SDD survey)2.12 - Excess Weight in Adults2.13i - Percentage of physically active and inactive adults - active adults2.13ii - Percentage of physically active and inactive adults - inactive adults2.14 - Smoking Prevalence2.14 - Smoking prevalence - routine & manual2.15i - Successful completion of drug treatment - opiate users2.15ii - Successful completion of drug treatment - non-opiate users2.16 - People entering prison with substance dependence issues who are previously not known to community treatment2.17 - Recorded diabetes2.18 - Admission episodes for alcohol-related conditions - narrow definition2.19 - Cancer diagnosed at early stage (Experimental Statistics)2.20i - Cancer screening coverage - breast cancer2.20ii - Cancer screening coverage - cervical cancer2.21i - Antenatal infectious disease screening – HIV coverage2.21iii - Antenatal Sickle Cell and Thalassaemia Screening - coverage2.21iv - Newborn bloodspot screening - coverage2.21v - Newborn Hearing screening - Coverage2.21vii - Access to non-cancer screening programmes - diabetic retinopathy2.21viii - Abdominal Aortic Aneurysm Screening2.22iii - Cumulative % of the eligible population aged 40-74 offered an NHS Health Check2.22iv - Cumulative % of the eligible population aged 40-74 offered an NHS Health Check who received an NHS Health Check2.22v - Cumulative % of the eligible population aged 40-74 who received an NHS Health check2.23i - Self-reported well-being - people with a low satisfaction score2.23ii - Self-reported well-being - people with a low worthwhile score2.23iii - Self-reported well-being - people with a low happiness score2.23iv - Self-reported well-being - people with a high anxiety score2.23v - Average Warwick-Edinburgh Mental Well-Being Scale (WEMWBS) score2.24i - Injuries due to falls in people aged 65 and over2.24ii - Injuries due to falls in people aged 65 and over - aged 65-792.24iii - Injuries due to falls in people aged 65 and over - aged 80+3.01 - Fraction of mortality attributable to particulate air pollution3.02 - Chlamydia detection rate (15-24 year olds)3.02 - Chlamydia detection rate (15-24 year olds)3.03i - Population vaccination coverage - Hepatitis B (1 year old)3.03i - Population vaccination coverage - Hepatitis B (2 years old)3.03iii - Population vaccination coverage - Dtap / IPV / Hib (1 year old)3.03iii - Population vaccination coverage - Dtap / IPV / Hib (2 years old)3.03iv - Population vaccination coverage - MenC3.03ix - Population vaccination coverage - MMR for one dose (5 years old)3.03v - Population vaccination coverage - PCV3.03vi - Population vaccination coverage - Hib / Men C booster (5 years)3.03vi - Population vaccination coverage - Hib / MenC booster (2 years old)3.03vii - Population vaccination coverage - PCV booster3.03viii - Population vaccination coverage - MMR for one dose (2 years old)3.03x - Population vaccination coverage - MMR for two doses (5 years old)3.03xii - Population vaccination coverage - HPV3.03xiii - Population vaccination coverage - PPV3.03xiv - Population vaccination coverage - Flu (aged 65+)3.03xv - Population vaccination coverage - Flu (at risk individuals)3.04 - People presenting with HIV at a late stage of infection3.05i - Treatment completion for TB3.05ii - Incidence of TB3.06 - NHS organisations with a board approved sustainable development management plan3.07 - Comprehensive, agreed inter-agency plans for responding to health protection incidents and emergencies4.01 - Infant mortality4.02 - Tooth decay in children aged 54.03 - Mortality rate from causes considered preventable4.04i - Under 75 mortality rate from all cardiovascular diseases4.04ii - Under 75 mortality rate from cardiovascular diseases considered preventable4.05i - Under 75 mortality rate from cancer4.05ii - Under 75 mortality rate from cancer considered preventable4.06i - Under 75 mortality rate from liver disease4.06ii - Under 75 mortality rate from liver disease considered preventable4.07i - Under 75 mortality rate from respiratory disease4.07ii - Under 75 mortality rate from respiratory disease considered preventable4.08 - Mortality

Bathing facilities and health phronesis: tackling English obesity. Mixed methods sequential research in five phases.
Research questions and hypotheses • RQ1: Does the geospatial distribution of swimming facilities impact health? (Nomothetic). (H10: Pools is insignificant vs. H1A: Pools is significant) • RQ2: Is the construction of swimming pools adequate for national health need? (Nomothetic). (H20: Forecast pool construction stable vs. H2A: Forecast pool construction increases) • RQ3: What policy learning emerges from idiosyncratic cases? (Idiographic & qualitative) Approach After problematisation (1) and structured literature review (2), the study conducted cross-sectional analysis of excess mortality and swimming pools (3a & 3b) and longitudinal analysis of pool construction (3c-e). Cross-sectional investigation involved factor analysis (3a) to explore and regression to analysis (3b) to investigate English mortality and its covariates (3b). The For the time series analysis, the study analysed 120 years of English pool construction data using autoregressive distributed lag models - ARIMA (3c), ADL (3d) and ECM (3e).
Data Cross sectional analysis Deaths (DV, Yd): ONS standardised mortality ratio (2013-2017). Observed total deaths from all causes (by five year age and gender band) as a percentage of expected deaths.
Access Leisure (IV, X1): reflects accessibility to 727 leisure centres, swimming baths or 2,738 health clubs in kilometres. Liverpool University’s Consumer Data Research Centre, Access to Healthy Assets and Hazards (AHAH) index. Obesity (IV, X2): percentage of adult population with a body mass index (BMI) of 30 kg/m2 or higher, age-standardized, WHO 2389 NCD_BMI_30 (2020). Deprivation (IV, X3): deprivation score for English small areas, sourced from Index of Multiple Deprivation (2019). Environment (IV, X4) measures accessible blue and green space, sourced via SE (2020), data constitutes an element of AHAH (2017).
Pools (IV, X5): reflects pools per 10,000 in 2018. Data extracted from SE Active Places Power (APP) Time series analysis Pools constructed (PC & ∆PC): English swimming pools constructed each year during a 120 year period since 1900, SE Active Places Power (2020) database. English output (GDP & ∆GDP): Bank of England millennium of macroeconomic data UK (2017) provides historical macroeconomic and financial statistics.
English population (Pop & ∆Pop): English population and population growth 1900-2020, Office for National Statistics (ONS): Total population (2018).

This data shows premature deaths (Age under 75) from Cardiovascular Disease, numbers and rates by gender, as 3-year moving-averages. Cardiovascular Disease include heart diseases and stroke, and others. Socio-economic and lifestyle factors are associated with circulatory disease deaths and inequalities in circulatory disease rates. Modifiable risk factors include smoking, excess weight, diet, and physical inactivity. Directly Age-Standardised Rates (DASR) are shown in the data, where numbers are sufficient, so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates. A limitation on using mortalities as a proxy for prevalence of health conditions is that mortalities may give an incomplete view of health conditions in an area, as ill-health might not lead to premature death. Data source: NHS Digital (now part of NHS England) Compendium hub, dataset unique identifier P00395. This data is updated annually. Note: Compendium Mortality Consultation 2022 NHS Digital is currently analysing the results of the consultation that closed on 14 September 2022. In the meantime the next publication is on hold. 6 February 2023 10:55 AM

NetCDF files of data generated and used as part of Marais et al. (2023) submitted for review to AGU's GeoHealth journal. The data used, but not generated in this work are not available elsewhere and so provided here with permission from the data developers at the UK Centre for Ecology and Hydrology (UKCEH).

A brief summary of the datasets used and generated in this work is included below. Additional details are provided as metadata in the individual NetCDF files.

Datasets used in this work: Datasets used and not generated in this work are high-spatial-resolution senstive habitat maps and total reactive nitrogen deposition data derived for the present day.

UKCEH sensitive habitat maps at 1 km resolution. UKCEH CBED nitrogen deposition to forests and to open vegetation at 5 km resolution.

Datasets generated as part of this work: Datasets generated as part of this work include air quality concentrations, nitrogen deposition and excess deaths for the present-day (2019) and by 2030 following adoption of currently legislated or maximum technically feasible control measures.

GEOS-Chem annual mean ambient surface concentrations of fine particulate matter (PM2.5). GEOS-Chem annual mean ambient surface concentrations of ammonia (NH3). GEOS-Chem annual total wet and dry reactive nitrogen deposition. UK administrative area adult premature mortality.