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Abstract Small area health data are not always available on a consistent and robust routine basis across nations, necessitating the employment of small area estimation methods to generate local-scale data or the use of proxy measures. Geodemographic indicators are widely marketed as a potential proxy for many health indicators. This paper tests the extent to which the inclusion of geodemographic indicators in small area estimation methodology can enhance small area estimates of limiting long-term illness (LLTI). The paper contributes to international debates on small area estimation methodologies in health research and the relevance of geodemographic indicators to the identification of health care needs. We employ a multilevel methodology to estimate small area LLTI prevalence in England, Scotland and Wales. The estimates were created with a standard geographically-based model and with a cross-classified model of individuals nested separately in both spatial groupings and non-spatial geodemographic clusters. LLTI prevalence was estimated as a function of age, sex and deprivation. Estimates from the cross-classified model additionally incorporated residuals relating to the geodemographic classification. Both sets of estimates were compared against direct estimates from the 2011 Census. Geodemographic clusters remain relevant to understanding LLTI even after controlling for age, sex and deprivation. Incorporating a geodemographic indicator significantly improves concordance between the small area estimates and the Census. Small area estimates are however consistently below the equivalent Census measures, with the LLTI prevalence in urban areas characterised as 'blue collar' and 'struggling families' being markedly lower. We conclude that the inclusion of a geodemographic indicator in small area estimation can improve estimate quality and enhance understanding of health inequalities. We recommend the inclusion of geodemographic indicators in public releases of survey data to facilitate better small area estimation but caution against assumptions that geodemographic indicators can, on their own, provide a proxy measure of health status. Highlights • A novel cross-classified extension to small area estimation methodology. • Small area estimation of health indicators can be enhanced by geodemographic data. • Geodemographics and deprivation independently impact small area health estimates. • Deprived urban communities have much worse health than expected. [ABSTRACT FROM AUTHOR]

Small area health data are not always available on a consistent and robust routine basis across nations, necessitating the employment of small area estimation methods to generate local-scale data or the use of proxy measures. Geodemographic indicators are widely marketed as a potential proxy for many health indicators. This paper tests the extent to which the inclusion of geodemographic indicators in small area estimation methodology can enhance small area estimates of limiting long-term illness (LLTI). The paper contributes to international debates on small area estimation methodologies in health research and the relevance of geodemographic indicators to the identification of health care needs. We employ a multilevel methodology to estimate small area LLTI prevalence in England, Scotland and Wales. The estimates were created with a standard geographically-based model and with a cross-classified model of individuals nested separately in both spatial groupings and non-spatial geodemographic clusters. LLTI prevalence was estimated as a function of age, sex and deprivation. Estimates from the cross-classified model additionally incorporated residuals relating to the geodemographic classification. Both sets of estimates were compared against direct estimates from the 2011 Census. Geodemographic clusters remain relevant to understanding LLTI even after controlling for age, sex and deprivation. Incorporating a geodemographic indicator significantly improves concordance between the small area estimates and the Census. Small area estimates are however consistently below the equivalent Census measures, with the LLTI prevalence in urban areas characterised as 'blue collar' and 'struggling families' being markedly lower. We conclude that the inclusion of a geodemographic indicator in small area estimation can improve estimate quality and enhance understanding of health inequalities. We recommend the inclusion of geodemographic indicators in public releases of survey data to facilitate better small area estimation but caution against assumptions that geodemographic indicators can, on their own, provide a proxy measure of health status. • A novel cross-classified extension to small area estimation methodology. • Small area estimation of health indicators can be enhanced by geodemographic data. • Geodemographics and deprivation independently impact small area health estimates. • Deprived urban communities have much worse health than expected. [ABSTRACT FROM AUTHOR]

Abstract Using Census-derived data for consistent spatial units, this paper explores how the population of Britain in 1991, 2001 and 2011 was spatially structured by self-reported health including exploring the trajectories of change. This paper uses consistent small area units to examine the changing spatial structure of census-derived Limiting, Long-Term Illness (LLTI) in Britain over the twenty year period and utilises the 2011 Office for National Statistics Output Area Classification (OAC) as a geodemographic indicator. The results allow the geography of change to be captured, highlighting how health is inextricably linked to geography, demonstrating quantitatively a complex, yet distinctive, spatial organisation of health inequalities within Britain. Overall decreasing unevenness values, coupled with increased positive spatial association suggests that neighbouring areas have become more similar over time – the distinction between areas characterised by poor health or by good health is decreasing. Highlights • Health inequalities are distinctively spatially organised within Britain. • Britain is now more visibly divided by its geography of long-term illness. • Distinct spatial concentrations of good and poor health correspond with area type. [ABSTRACT FROM AUTHOR]

How do we make a difference? This paper traces the connections made between quantified knowledge, population health, and social justice by examining the efforts of population scientists to assess sexuality as a point of difference within population-based data systems, including on national health and social surveys, electronic medical records, and the Census. Population scientists emphasize the importance of measuring social difference in order to identify and remedy structural disadvantage. This evaluation requires the assessment of difference and the comparison of distinct groups across standardized outcome measures. In quantifying social difference, however, population scientists obscure or minimize several difficulties in creating comparable populations. I explore some of these challenges by highlighting three central tensions: the separation of difference from other aspects and categories of social experience, the reduction of difference through the use of one over several possible measures, and the enactment of difference as quantified knowledge loops back into society. As a theoretical inquiry into the form of social difference as it is conceptualized, operationalized, and materialized across the science-society nexus, this paper identifies the various commitments made during processes of scientific evaluation. By attending to the values and priorities that exist within and through practices of quantification, I aim to address the problem of measuring social difference as it pertains to the issues of social justice and health equity. [ABSTRACT FROM AUTHOR]

Census-based deprivation indices have been widely used in Aotearoa/New Zealand, Canada and UK to measure area-based socio-economic inequalities. This paper examines the indicators used in census-based area deprivation indices using a political ecology approach. We question whether the current indicators of deprivation derived from census data are meaningful for the all age groups and minority groups in the population, with a particular focus on deprivation indicators used in New Zealand, Canada and the United Kingdom. We comparatively reviewed methodological papers and reports that describe the indicators of deprivation in Aotearoa/New Zealand, Canada and the UK from 1975 to 2014. We consider the relationship between the notion of standards of living and measurements of deprivation and explore how hegemonic cultural constructs are implicit in measures of deprivation that privilege a Eurocentric, ageist and gender normative construction of statistics. We argue for more political ecological analyses to studying the relationship between social inequalities, geographies, health inequities and political economy to transform structures of oppression and inequality. This requires turning the analytical gaze on the wealthy and privileged instead of defaulting into deficit models to account for inequality. Studies of deprivation and inequality would benefit from understanding the processes and operations of power in the (re)production of socio-economic and health inequities to inform holistic strategies for social justice. [ABSTRACT FROM AUTHOR]

Abstract This paper reports research exploring how trends in local labour market conditions during the period 2007–2011 (early stages of the 'great recession') relate to reported mental illness for individuals. It contributes to research on spatio-temporal variation in the wider determinants of health, exploring how the lifecourse of places relates to socio-geographical inequalities in health outcomes for individuals. This study also contributes to the renewed research focus on the links between labour market trends and population health, prompted by the recent global economic recession. We report research using the Scottish Longitudinal Study (SLS), a 5.3% representative sample of the Scottish population, derived from census data (https://sls.lscs.ac.uk/). In Scotland, (2011) census data include self-reported mental health. SLS data were combined with non-disclosive information from other sources, including spatio-temporal trends in labour market conditions (calculated using trajectory modelling) in the 32 local authority areas in Scotland. We show that, for groups of local authorities in Scotland over the period 2007–2011, trends in employment varied. These geographically variable trends in employment rates were associated with inequalities in self-reported mental health across the country, after controlling for a number of other individual and neighbourhood risk factors. For residents of regions that had experienced relatively high and stable levels of employment the odds ratio for reporting a mental illness was significantly lower than for the 'reference group', living in areas with persistently low employment rates. In areas where employment declined markedly from higher levels, the odds ratio was similar to the reference group. The findings emphasise how changes in local economic conditions may influence people's health and wellbeing independently of their own employment status. We conclude that, during the recent recession, the economic life course of places across Scotland has been associated with individual mental health outcomes. Highlights • The Scottish Longitudinal Study was used to study mental illness reported in 2011. • The analysis of individuals controlled for personal and local neighbourhood variables. • Local Authority employment trend 2007–11 was associated with reported mental health. • Economic lifecourses of places relate to inequalities in mental health outcomes. [ABSTRACT FROM AUTHOR]

Abstract A shortage of physicians in local public hospitals is often a heated political issue. When local politicians have the authority to intervene in the management of a public hospital, they may increase the employment of physicians during election years in order to alleviate the shortage. We test this hypothesis empirically using a census of city hospitals in Japan from 2002 to 2011 (N = 4583). Our results support the hypothesis that the number of physicians increases in election years. This effect is stronger in cities with a greater population of elderly residents. We also find that physicians tend to come from university hospitals in the same region. Overall, this paper provides direct evidence of political intervention on physician employment. Highlights • A shortage of hospital physicians was a heated political issue in Japan. • We examine how the timing of mayoral elections affected local public hospitals in Japan. • The number of physicians increased in election years. • The effect was stronger in cities with a greater population of elderly residents. • We find that physicians came from university hospitals in the same region. [ABSTRACT FROM AUTHOR]

Research indicates that experiences in health and social services vary depending on identity. For Indigenous groups, identity and affiliation is complex. This paper explores ethnicity and knowledge of tribal (iwi) affiliations for Māori (the Indigenous peoples of Aotearoa New Zealand), and links this to health and social service outcomes in administrative data, the national Census, and Māori social survey data. While many initiatives have sought to connect Māori to iwi - where such knowledge has been severed by colonization - we find surprisingly few differences in data between those who named tribal affiliations and those who did not, across sole- and mixed-Māori ethnicity groups. Those who did not name an iwi were less likely to live in overcrowded homes, but were less likely to own that home, and more likely to be a smoker. Unsurprisingly, those who did not name tribal affiliations were less likely to find Māori culture as important, although many still did. These groups also had slightly less contact with social networks and support, plus felt lonelier. The results also point to sole-ethnic identification as Māori as a key marker of experiences of inequity and suggest that connections to tribal affiliations are more complicated than a binary of "connected" or "disconnected". However, in some indicator areas, affiliation differences should be followed up with future work. We argue these results give further weight to the need for good quality data and indicators designed with Māori populations in mind to measure and monitor inequity. • Health and social service outcomes vary by identity, including for Indigenous groups. • A focus for Indigenous health and wellbeing has been on identity re-connection. • We explore affiliation with iwi (tribes) for Māori across administrative, census and survey data. • There were few differences between those who named their iwi (tribal) affiliations and those who did not. • The main indicator of wellbeing was instead solely identifying as Māori compared to mixed-identifying Māori. [ABSTRACT FROM AUTHOR]

Under what conditions do local political elites in new democracies promote citizen health? To address the question, this paper advances hypotheses grounded in prominent political science debates and assesses them against comprehensive, granular data from the most recent South African national census. The evidence rejects the hypotheses that relatively great partisan competition and relatively great popular participation boost local population health. The evidence provides conditional support for the hypotheses that local health outcomes are enhanced in municipalities where the national ruling party commands relatively great citizen backing and where hereditary chiefs are strong. In particular, where local strongholds of the national ruling party coincide with strong chiefly authority, the predicted probability of infant and under-five death over all households is reduced, as is the predicted probability of infant and under-five death among majority Black African households, holding other things equal. In these nuanced ways, the actors holding power at the local level matter for the survival of babies and children in South Africa. The paper contributes to scholarship on institutions in new democracies, chiefly authority, the conditions for infant and under-five survival, and the political determinants of health. In doing so, it demonstrates the value of drilling down to the local level to probe the political determinants of population health. • Weighs factors flagged in political science debates as affecting citizen wellbeing. • Analysis for South Africa uses granular census data, augmented by municipal data. • Under some conditions, the odds of infant and child death vary with local context. • Local context is municipal support for national ruling party and chiefly power. • The study shows the value of probing the local political determinants of health. [ABSTRACT FROM AUTHOR]

Censuses have traditionally been a key source of localised information on the state of a nation's health. Many countries are now adopting alternative approaches to the traditional census, placing such information at risk. The purpose of this paper is to inform debate about whether existing social surveys could provide an adequate 'base' for alternative model-based small area estimates of health data in a post traditional census era. Using a case study of 2011 UK Census questions on self-assessed health and limiting long term illness, we examine the extent to which the results from three large-scale surveys - the Health Survey for England, the Crime Survey for England and Wales and the Integrated Household Survey - conform to census output. Particularly in the case of limiting long term illness, the question wording renders comparisons difficult. However, with the exception of the general health question from the Health Survey for England all three surveys meet tests for convergent validity. [ABSTRACT FROM AUTHOR]

Although local policies aimed at reducing childhood health inequities can benefit from local data, sample size constraints in population representative health surveys often prevent rigorous evaluations of child health disparities and health care patterns at local levels. Electronic Health Records (EHRs) offer a possible solution as they contain large amounts of information on pediatric patients within a health system. In this paper, we consider the suitability of using EHRs from a large health system to study local children's health by evaluating the extent to which the EHRs capture the county's child population. First, we compare the demographic characteristics of Duke University Health System pediatric patients who live in Durham County, NC (USA) to the child population estimates in the 2015–2019 American Community Survey. We then examine geographic variation in census tract rates of children captured in the EHR data and estimate negative binomial models to assess how tract characteristics are associated with these rates. We also perform these analyses for the subset of pediatric patients who have a well-child encounter. We find that the demographic characteristics of pediatric patients captured by the EHRs are similar to those of the county's child population. Although the county rate of children captured in the EHRs is high, there is variation across census tracts. On average, census tracts with higher concentrations of non-Hispanic Black residents have lower capture rates and tracts with higher concentrations of poverty have higher capture rates, with the poorest tracts showing the largest racial gap in rates of children captured by EHRs. Our findings suggest that EHRs from a large health system can be used to assess children's population health, but that EHR-based evaluations of children's health disparities and health care patterns should account for differences in who is captured by the EHRs based on census tract characteristics. • EHRs from a large health system are suitable for studying local children's health. • Local children in EHRs are demographically similar to county population estimates. • Rates of children captured in health system differ by census tract characteristics. • EHR-based analyses should adjust for local differences in capture rates. [ABSTRACT FROM AUTHOR]

There has been considerable discussion in health geography and related areas of neighbourhood effects on health: the idea that people''s health in one geographical area may be influenced not only by the composition of that area''s population, but also by the area''s geographical context. Hence, the healthiness or otherwise of the neighbourhood may have an important effect on local people''s health. Although neighbourhoods and their boundaries are sometimes obvious to local residents, it is more common to find considerable disagreement on the size and contents of a neighbourhood. In this paper, we use British census Enumeration Districts as building blocks to construct alternative zonal systems, and experiment to see if neighbourhoods defined in different ways have similar implications for health. The well known modifiable areal unit problem shows that analytical conclusions may differ substantially according to how data are aggregated. Boundaries can be drawn to maximize equality of size, compactness of shape, homogeneity in social composition, accordance with ‘natural’ boundaries, and probably many other factors; which of these criteria are more effective in defining zones relevant to health? One conclusion is that the effect of neighbourhood conditions should be looked at using several different ways to define neighbourhoods, and that the size and composition of these neighbourhoods may be different in different parts of a study area. [Copyright &y& Elsevier]

Significant variation in disability-related social security benefits receipt might highlight sub-populations and groups with unmet needs and also have implications for areal indicators of disadvantage that are largely derived from uptake of benefits. In this paper we examine Disability Living Allowance (DLA), a non means-tested contribution towards disability-related living costs for disabled people aged less than sixty-five. ology: Three census-based measures of self-reported health (number of chronic physical disabilities; activity limitation (a little; a lot); and chronic poor mental health) were linked to contemporaneous DLA records. The 2011 Census returns provided individual demographic, socio-economic, social and area-level characteristics. DLA uptake was modelled using logistic regression, stratified into 0–15 and 16–64 year old age groups. Overall, 118329 (8.4%) of this population received DLA. Poor health outcomes were the main determinants for uptake, which was higher amongst females, those non-married and those of lower socio-economic status: for example those with no qualifications compared against third level education (OR ad = 1.80: 95%CI = 1.75–1.85); and those social renting compared against those in more expensive owner occupation (OR adj = 1.92: 1.83–2.02). Uptake was lower amongst Protestants than Catholics (OR adj = 0.75: 0.74–0.77) and amongst immigrants (OR adj = 0.36: 0.34–0.39) and slightly lower in rural communities. Poor health is the predominant determinant of disability benefits uptake but other social and socioeconomic factors have influence. These findings may assist in the reshaping of outreach programmes leading to better targeting of benefits, and therefore a more indirect influence on the derivation of area deprivation measures in the United Kingdom. • Uptake of disability-related benefits is high in Northern Ireland; with. • Mobility-related disability more likely to attract benefits than poor mental health. • Social and socio-economic factors may partly determine benefit uptake; and. • This social patterning may indicate areas of unmet need. [ABSTRACT FROM AUTHOR]