Human leukocyte antigen associations with renal function among ethnic minorities in the United Kingdom.

Human leukocyte antigens (HLA) have been associated with renal function, but previous studies report contradictory findings. There has been a lack of research into how HLA affects renal function in Black, Asian and Minority Ethnic (BAME) people in the UK, despite BAME people being disproportionately affected by renal dysfunction. This study included >27 000 UK Biobank subjects of six ethnicities (>12 100 Irish, >5400 Indian, >4000 Black Caribbean, >3000 Black African, >1600 Pakistani, and >1400 Chinese) aged 39 to 73. Subjects' high-resolution HLA genotypes were imputed using HLA*IMP:02 software. Regression analysis was used to compare 108 imputed HLA alleles with two measures of estimated glomerular filtration rate (eGFR): one based on serum creatinine; one based on serum cystatin. Secondary analysis compared CKD stage 2 subjects to healthy controls. Nine imputed HLA alleles were associated with eGFR (adjusted P < .05). Six associations were based on creatinine in Black African subjects: HLA-B*53:01 (beta = -2.628, adjusted P = 4.69 × 10-4 ); C*04:01 (beta = -1.667, adjusted P = .0269); DPA1*02:01 (beta = -1.569, adjusted P = .0182); and DPA1*02:02 (beta = -1.716, adjusted P = .0251) were linked to decreased renal function, while DRB1*03:01 (beta = 3.200, adjusted P = 3.99 × 10-3 ) and DPA1*01:03 (beta = 2.276, adjusted P = 2.31 × 10-5 ) were linked to increased renal function. Two of these (HLA-B*53:01 and C*04:01) are commonly inherited together. In Irish subjects, HLA-DRB1*04:01 (beta = 1.075, adjusted P = .0138) was linked to increased eGFR (based on cystatin); in Indian subjects, HLA-DRB1*03:01 (beta = -1.72, adjusted P = 4.78 × 10-3 ) and DQB1*02:01 (beta = -1.755, adjusted P = 2.26 × 10-3 )were associated with decreased eGFR (based on cystatin). No associations were found in the other three ethnic groups. Nine HLA alleles appear to be associated with kidney function in BAME people in the UK. This could have applications for the diagnosis and treatment of renal disease and could help reduce health inequalities in the UK.

The use of locally based aggregate measures in urban health policy making in European urban areas.

Background: National and international policy makers require data at the local level to inform evidence-based policy making and evaluate the impact of policies; however, much data are only published at national level. Data collected at local level could be used to create aggregate measures to help inform health policy. Interviews were conducted with representatives of governmental public health agencies in eight European countries to assess the availability of local data and the extent to which local data was used to help decision making in nine urban areas (UAs). Respondents commented on the barriers to the use of aggregate measures at the local level for health policy decision making. In many of the cities data were available at UA level and in some cases at sub-urban level, however, aggregate measures using local data were rarely used to help inform decision making. The main reasons for this were; poor data quality, a lack of experience in the use of aggregate measures and communication barriers between policy makers and data analysts. A 'top down' approach to decision making also limited the use of local data in the decision making process. Health data are available at urban level within European cities but aggregate measures using these data are rarely used to inform health policy decision making at the local level. Improved communication between local public health data analysts could help increase the use of these data.

Developing a European urban health indicator system: results of EURO-URHIS 1.

Introduction: More than half of the world's population now live in cities, including over 70% in Europe. Cities bring opportunities but can be unhealthy places to live. The poorest urban dwellers live in the worst environments and are at the greatest risk of poor health outcomes. EURO-URHIS 1 set out to compile a cross-EU inventory of member states use of measures of urban health in order to support policymakers and improve public health policy. Following a literature review to define terms and find an appropriate model to guide urban health research, EURO-URHIS Urban Areas in all EU member states except Luxembourg, as well as Croatia, Turkey, Macedonia, Iceland and Norway, were defined and selected in collaboration with project partners. Following piloting of the survey tool, a the EURO-URHIS 45 data collection tool was sent out to contacts in all countries with identified EUA's, asking for data on 45 Urban Health Indicators (UHI) and 10 other indicators. 60 questionnaires were received from 30 countries, giving information on local health indicator availability, definitions and sources. Telephone interviews were also conducted with 14 respondents about their knowledge of sources of urban health data and barriers or problems experienced when collecting the data. Most participants had little problem identifying the sources of data, though some found that data was not always routinely recorded and was held by diverse sources or not at local level. Some participants found the data collection instrument to not be user-friendly and with UHI definitions that were sometimes unclear. However, the work has demonstrated that urban health and its measurement is of major relevance and importance for Public Health across Europe. The current study has constructed an initial system of European UHIs to meet the objectives of the project, but has also clearly demonstrated that further development work is required. The importance and value of examining UHIs has been confirmed, and the scene has been set for further studies on this topic.

The use of epidemiological measures to estimate the impact of primary prevention interventions on CHD, stroke and cancer outcomes: experiences from Herefordshire, UK.

BACKGROUND: CHD, stroke and cancers are the major causes of mortality in the UK and are responsible for significant amounts of morbidity and healthcare costs. This study examines the proportion of CHD, stroke and cancer owing to specific risk factors in Herefordshire, UK. It estimates the population impact of a number of interventions being implemented to reduce these risk factors, through the NHS Health Check program and the Herefordshire Health Improvement Plan. The present study also aims to demonstrate the value of epidemiological measures in providing evidence-based public health information in policy-making to aid decision makers when prioritizing investments and optimal use of resources. METHODS: The epidemiological measures-'Population Attributable Risk' and 'Population Impact Measures'-were used to assess the impact of interventions to reduce the burden of CHD, stroke and cancer. RESULTS: Implementation of the NHS Health Check program will prevent 63 CHD events, 90 MI events and 125 stroke events, and one lung cancer over a period of 5 years. Reducing specific risk factors by 5% annually through the Health Improvement Plan will prevent 65 CHD events, 25 MI events, 140 stroke events, four lung cancer, one breast cancer and four colorectal cancer cases in Herefordshire if targets are met over a period of 5 years. CONCLUSION: Physical inactivity and obesity are the major causes of CHD and stroke events (incidence and mortality) in Herefordshire. Their impact is greater than the combined effect of hypercholesterolemia and hypertension. Epidemiological measures used in this study proved to be excellent tools in providing evidence-based public health information. Their use is strongly recommended to support prioritization of primary prevention interventions.

Population Impact Analysis: a framework for assessing the population impact of a risk or intervention.

BACKGROUND: To describe an organizing framework, Population Impact Analysis, for applying the findings of systematic reviews of public health literature to estimating the impact on a local population, with the aim of implementing evidence-based decision-making. METHODS: A framework using population impact measures to demonstrate how resource allocation decisions may be influenced by using evidence-based medicine and local data. An example of influenza vaccination in the over 65s in Trafford to reduce hospital admissions for chronic obstructive pulmonary disease (COPD) is used. RESULTS: The number of COPD admissions due to non-vaccination of the over 65 in Trafford was 16.4 (95% confidence interval: 13.5; 19.5) and if vaccination rates were taken up to 90%, 11.5 (95% confidence interval: 9.3; 13.8) admissions could have been prevented. A total of 705 (95% confidence interval: 611; 861) people would have to be vaccinated against influenza to prevent one hospital admission. CONCLUSIONS: Population Impact Analysis can help the 'implementation' aspect of evidence for population health. It has been developed to support public health policy makers at both local and national/international levels in their role of commissioning services.