Contribution of avoidable mortality to life expectancy inequalities in Wales: a decomposition by age and by cause between 2002 and 2020.

OBJECTIVES: To explore the contribution of avoidable mortality to life expectancy inequalities in Wales during 2002-2020. DESIGN: Observational study. SETTING: Wales, 2002-20, including early data from the COVID-19 pandemic. METHODS: We used routine statistics for 2002-2020 on population and deaths in Wales stratified by age, sex, deprivation quintile and cause of death. We estimated the contribution of avoidable causes of death and specific age-categories using the Arriaga decomposition method to highlight priorities for action. RESULTS: Life expectancy inequalities rose 2002-20 amongst both sexes, driven by serial decreases in life expectancy amongst the most deprived quintiles. The contributions of amenable and preventable mortality to life expectancy inequalities changed relatively little between 2002 and 2020, with larger rises in non-avoidable causes. Key avoidable mortality conditions driving the life expectancy gap in the most recent period of 2018-2020 for females were circulatory disease, cancers, respiratory disease and alcohol- and drug-related deaths, and also injuries for males. CONCLUSIONS: Life expectancy inequalities widened during 2002-20, driven by deteriorating life expectancy in the most deprived quintiles. Sustained investment in prevention post-COVID-19 is needed to address growing health inequity in Wales; there remains a role for the National Health Service in ensuring equitable healthcare access to alongside wider policies that promote equity.

Comparison of perceived and modelled geographical access to accident and emergency departments: a cross-sectional analysis from the Caerphilly Health and Social Needs Study.

BACKGROUND: Assessment of the spatial accessibility of hospital accident and emergency departments as perceived by local residents has not previously been investigated. Perceived accessibility may affect where, when, and whether potential patients attend for treatment. Using data on 11,853 respondents to a population survey in Caerphilly county borough, Wales, UK, we present an analysis comparing the accessibility of accident and emergency departments as reported by local residents and drive-time to the nearest accident and emergency department modelled using a geographical information system (GIS). RESULTS: Median drive-times were significantly shorter in the lowest perceived access category and longer in the best perceived access category (p < 0.001). The perceived access and GIS modelled drive-time variables were positively correlated (Spearman's rank correlation coefficient, r = 0.38, p < 0.01). The strongest correlation was found for respondents living in areas in which nearly all households had a car or van (r = 0.47, p < 0.01). Correlations were stronger among respondents reporting good access to public transport and among those reporting a recent accident and emergency attendance for injury treatment compared to other respondents. Correlation coefficients did not vary substantially by levels of household income. Drive-time, road distance and straight-line distance were highly inter-correlated and substituting road distance or straight-line distance as the GIS modelled spatial accessibility measure only marginally decreased the magnitude of the correlations between perceived and GIS modelled access. CONCLUSION: This study provides evidence that the accessibility of hospital-based health care services as perceived by local residents is related to measures of spatial accessibility modelled using GIS. For studies that aim to model geographical separation in a way that correlates well with the perception of local residents, there may be minimal advantage in using sophisticated measures. Straight-line distance, which can be calculated without GIS, may be as good as GIS-modelled drive-time or distance for this purpose. These findings will be of importance to health policy makers and local planners who seek to obtain local information on access to services through focussed assessments of residents' concerns over accessibility and GIS modelling.

Council tax valuation bands, socio-economic status and health outcome: a cross-sectional analysis from the Caerphilly Health and Social Needs Study.

UNLABELLED: Council tax valuation bands (CTVBs) are a categorisation of household property value in Great Britain. The aim of the study was to assess the CTVB as a measure of socio-economic status by comparing the strength of the associations between selected health and lifestyle outcomes and CTVBs with two measures of socio-economic status: the National Statistics Socio-Economic Classification (NS-SEC) and the 2001 UK census-based Townsend deprivation index. METHODS: Cross-sectional analysis of data on 12,092 respondents (adjusted response 62.7%) to the Caerphilly Health and Social Needs Study, a postal questionnaire survey undertaken in Caerphilly county borough, south-east Wales, UK. The CTVB was assigned to each individual by matching the sampling frame to the local authority council tax register. Crude and age-gender adjusted odds ratios for each category of CTVB, NS-SEC and fifth of the ward distribution of Townsend scores were estimated for smoking, poor diet, obesity, and limiting long-term illness using logistic regression. Mean mental (MCS) and physical (PCS) component summary scores of the Short-Form SF-36 health status questionnaire were estimated in general linear models. RESULTS: There were significant trends in odds ratios across the CTVB categories for all outcomes, most marked for smoking and mental and physical health status. The adjusted odds ratio for being a smoker in the lowest versus highest CTVB category was 3.80 (95% CI: 3.06, 4.71), compared to 3.00 (95% CI: 2.30, 3.90) for the NS-SEC 'never worked and long-term unemployed' versus 'higher managerial and professional' categories, and 1.61 (95% CI: 1.42, 1.83) for the most deprived versus the least deprived Townsend fifth. The difference in adjusted mean MCS scores was 5.9 points on the scale for CTVB, 9.2 for NS-SEC and 3.2 for the Townsend score. The values for the adjusted mean PCS scores were 6.3 points for CTVB, 11.3 for NS-SEC, and 2.5 for the Townsend score. CONCLUSION: CTVBs assigned to individuals were strongly associated with the health and lifestyle outcomes modelled in this study. CTVBs are readily available for all residential properties and deserve further consideration as a proxy for socio-economic status in epidemiological studies in Great Britain.

Using local authority data for action on health inequalities: the Caerphilly Health and Social Needs Study.

BACKGROUND: Primary care organisations in the United Kingdom have been given new and challenging population health responsibilities to improve health and address health inequality in local communities through partnership working with local authorities. This requires robust health and social needs assessment data for effective local planning. AIM: To assess the use and value of local authority data shared through partnership working between Caerphilly Local Health Group and Caerphilly County Borough Council. DESIGN OF STUDY: Cross-sectional analysis of aggregate electoral division data. SETTING: Caephilly County Borough, south-east Wales. METHOD: Local authority datasets identified were categorised into one of six domains: income, unemployment, housing, health, education, and social services. Data were presented at electoral division level as rates in thematic maps and correlations between the variables within and between each domain were explored using Spearman's rank correlation coefficient, with particular focus on children in families. Local planning documents were scrutinised to ascertain the use and value of the data. RESULTS: A broad range of data described a comprehensive picture of health and social inequalities within the borough. Multiple deprivation tended to cluster in electoral divisions, particularly for data relating to children, painting an overwhelming picture of inequality in life chances. The data were used in a wide range of local partnership planning initiatives, including the Health Improvement Programme, Children's Services Plan, and a successful Healthy Living Centre bid. CONCLUSION: Local authority data can help primary care organisations in a population approach to needs assessment for use in local partnership planning targeted at reducing health inequalities.

Systematic review of the use and value of computer simulation modelling in population health and health care delivery.

BACKGROUND: The objective of the review was to evaluate the extent, quality and value of computer simulation modelling in population health and health care delivery. METHODS: A narrative systematic review was carried out of world literature from 1980 to 1999, searching Medline, INSPEC, Embase, HealthSTAR, Science Citation Index, CINAHL, MathSci, INFORMS Online and SIGLE databases, and researchers in the field were contacted. Papers were included if they contained a computer simulation model of individuals in a stochastic system and the topic or setting related to population health or health service delivery. RESULTS: A total of 182 papers met the inclusion criteria. Simulation modelling has been undertaken in a wide range of health care topic areas, including hospital scheduling and organization, communicable disease, screening, costs of illness and economic evaluation. However, the quality of published papers was variable and few reported on the outcomes of implementation of models, so that the value of modelling could not be assessed. CONCLUSION: Simulation modelling is a powerful method for modelling both small and large populations to inform policy makers in the provision of health care. It has been applied to a wide variety of health care problems. Although the number of modelling papers has grown substantially over recent years, further research is required to assess the value of modelling.