Socioenvironmental sugar promotion and geographical inequalities in dental health of 5-year-old children in England.

OBJECTIVES: To investigate the relationship between socioenvironmental sugar promotion and geographical inequalities in the prevalence of dental caries amongst 5-year-olds living across small areas within England. METHODS: Ecological data from the National Dental Epidemiology Programme (NDEP) 2018-2019, comprising information on the percentage of 5-year-olds with tooth decay (≥1 teeth that are decayed into dentine, missing due to decay, or filled), and untreated tooth decay (≥1 decayed but untreated teeth), in lower-tier local authorities (LAs) of England. These were analysed for association with a newly developed Index of Sugar-Promoting Environments Affecting Child Dental Health (ISPE-ACDH). The index quantifies sugar-promoting determinants within a child's environment and provides standardized scores for the index, and its component domains that is, neighbourhood-, school- and family-environment, with the highest scores representing the highest levels of sugar promotion in lower-tier LAs (N = 317) of England. Linear regressions, including unadjusted models separately using index and each domain, and models adjusted for domains were built for each dental outcome. RESULTS: Participants lived across 272 of 317 lower-tier LAs measured within the index. The average percentage of children with tooth decay and untreated tooth decay was 22.5 (SD: 8.5) and 19.6 (SD: 8.3), respectively. The mean index score was (0.1 [SD: 1.01]). Mean domain scores were: neighbourhood (0.02 [SD: 1.03]), school (0.1 [SD: 1.0]), and family (0.1 [SD: 0.9]). Unadjusted linear regressions indicated that the LA-level percentage of children with tooth decay increased by 5.04, 3.71, 4.78 and 5.24 with increased scores of the index, and neighbourhood, school and family domains, respectively. An additional model, adjusted for domains, showed that this increased percentage predicted by neighbourhood domain attenuated to 1.37, and by family domain it increased to 6.33. Furthermore, unadjusted models indicated that the LA-level percentage of children with untreated tooth decay increased by 4.72, 3.42, 4.45 and 4.97 with increased scores of the index, and neighbourhood, school, and family domains, respectively. The model, adjusted for domains, showed that this increased percentage predicted by neighbourhood domain attenuated to 1.24 and by family domain rose to 6.47. School-domain was not significantly associated with either outcome in adjusted models. CONCLUSIONS: This study reveals that socioenvironmental sugar promotion, particularly within neighbourhood- and family-environments, may contribute to geographical inequalities in dental caries in children. Further research involving data on individual-level dental outcomes and confounders is required.

Effects of ethnic density on the risk of compulsory psychiatric admission for individuals attending secondary care mental health services: evidence from a large-scale study in England.

BACKGROUND: Black, Asian and minority ethnicity groups may experience better health outcomes when living in areas of high own-group ethnic density - the so-called 'ethnic density' hypothesis. We tested this hypothesis for the treatment outcome of compulsory admission. METHODS: Data from the 2010-2011 Mental Health Minimum Dataset (N = 1 053 617) was linked to the 2011 Census and 2010 Index of Multiple Deprivation. Own-group ethnic density was calculated by dividing the number of residents per ethnic group for each lower layer super output area (LSOA) in the Census by the LSOA total population. Multilevel modelling estimated the effect of own-group ethnic density on the risk of compulsory admission by ethnic group (White British, White other, Black, Asian and mixed), accounting for patient characteristics (age and gender), area-level deprivation and population density. RESULTS: Asian and White British patients experienced a reduced risk of compulsory admission when living in the areas of high own-group ethnic density [odds ratios (OR) 0.97, 95% credible interval (CI) 0.95-0.99 and 0.94, 95% CI 0.93-0.95, respectively], whereas White minority patients were at increased risk when living in neighbourhoods of higher own-group ethnic concentration (OR 1.18, 95% CI 1.11-1.26). Higher levels of own-group ethnic density were associated with an increased risk of compulsory admission for mixed-ethnicity patients, but only when deprivation and population density were excluded from the model. Neighbourhood-level concentration of own-group ethnicity for Black patients did not influence the risk of compulsory admission. CONCLUSIONS: We found only minimal support for the ethnic density hypothesis for the treatment outcome of compulsory admission to under the Mental Health Act.

Is social media use associated with children's well-being? Results from the UK Household Longitudinal Study.

INTRODUCTION: There are concerns about young people's increasing use of social media and the effects this has on overall life satisfaction. Establishing the significance of social media use requires researchers to take simultaneous account of other factors that might be influential and it is essential to adopt a longitudinal perspective to investigate temporal patterns. METHOD: Measures of happiness for children aged 10-15 from 7 waves of the UK Household Longitudinal Study were examined (n = 7596). Multilevel models were used to assess the relative association between these measures, children's social media use and individual, household and community characteristics. RESULTS: High use of social media was found to be significantly associated with change in happiness scores but was not associated with worsening life satisfaction trajectories. The most consistent factor was gender, with girls experiencing the largest decline in happiness between two time points (0.18 points) and being more likely to have a worsening trajectory over time (OR 1.77, 95% CI 1.36-2.32). Parental mental health, household support and household income were also important. CONCLUSION: Moderate use of social media does not play an important role in shaping children's life satisfaction. Higher levels of use is associated with lower levels of happiness, especially for girls but more research is needed to understand how this technology is being used. As well as focusing on high levels of social media use, policy makers should also concentrate on particular demographic groupings and factors affecting the social fabric of the households in which children grow up.

Moving beyond randomized controlled trials in the evaluation of compulsory community treatment.

Compulsory community treatment for people with severe mental illness remains controversial due to conflicting research evidence. Recently, there have been challenges to the conventional view that trial-based evidence should take precedence. This paper adds to these challenges in three ways. First, it emphasizes the need for critiques of trials to engage with conceptual and not just technical issues. Second, it develops a critique of trials centred on both how we can have knowledge and what it is we can have knowledge of. Third, it uses this critique to develop a research strategy that capitalizes on the information in large-scale datasets.

The utility of geodemographic indicators in small area estimates of limiting long-term illness.

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.

Evaluating the effects of community treatment orders (CTOs) in England using the Mental Health Services Dataset (MHSDS): protocol for a national, population-based study.

INTRODUCTION: Supervised community treatment (SCT) for people with serious mental disorders has become accepted practice in many countries around the world. In England, SCT was adopted in 2008 in the form of community treatment orders (CTOs). CTOs have been used more than expected, with significant variations between people and places. There is conflicting evidence about the effectiveness of SCT; studies based on randomised controlled trials (RCTs) have suggested few positive impacts, while those employing observational designs have been more favourable. Robust population-based studies are needed, because of the ethical challenges of undertaking further RCTs and because variation across previous studies may reflect the effects of sociospatial context on SCT outcomes. We aim to examine spatial and temporal variation in the use, effectiveness and cost of CTOs in England through the analysis of routine administrative data. METHODS AND ANALYSIS: Four years of data from the Mental Health Services Dataset (MHSDS) will be analysed using multilevel models. Models based on all patients eligible for CTOs will be used to explore variation in their use. A subset of CTO-eligible patients comprising a treatment group (CTO patients) and a matched control group (non-CTO patients) will be used to examine variation in the association between CTO use and study outcomes. Primary outcome will be total time in hospital. Secondary outcomes will include time to first readmission and mortality. Outputs from these models will be used to populate predictive models of healthcare resource use. ETHICS AND DISSEMINATION: Ethical approval has been granted by the National Health Service Data Access and Advisory Group and Warwick University. To ensure patient confidentiality and to meet data governance requirements, analyses will be carried out in a secure microdata laboratory using de-identified data. Study findings will be disseminated through academic channels and shared with mental health policy-makers and other stakeholders.

The tobacco endgame: The neglected role of place and environment.

An increasing number of countries across the world are planning for the eradication of the tobacco epidemic. The actions necessary to realise this ambition have been termed the tobacco endgame. The focus of this paper is on the intersection between the tobacco endgame with place, a neglected theme in recent academic and policy debates. We begin with an overview of the key themes in the literature on endgame strategies before detailing the international landscape of engame initiatives, paying particular attention to the opportunities and challenges of endgame strategies in low and middle income countries. Finally, we critically assess the current endgame debates and suggest a novel agenda for integrating geographical perspectives into research on the endgame that provides enhanced understanding of the challenges associated with this important global health vision.

A realist approach to the evaluation of complex mental health interventions.

Conventional approaches to evidence that prioritise randomised controlled trials appear increasingly inadequate for the evaluation of complex mental health interventions. By focusing on causal mechanisms and understanding the complex interactions between interventions, patients and contexts, realist approaches offer a productive alternative. Although the approaches might be combined, substantial barriers remain.Declaration of interestAll authors had financial support from the National Institute for Health Research Health Services and Delivery Research Programme while completing this work. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the National Health Service, the National Institute for Health Research, the Medical Research Council, Central Commissioning Facility, National Institute for Health Research Evaluation, Trials and Studies Coordinating Centre, the Health Services and Delivery Research Programme or the Department of Health. S.P.S. is part funded by Collaboration for Leadership in Applied Health Research and Care West Midlands. K.B. is editor of the British Journal of Psychiatry.

Size and clustering of ethnic groups and rates of psychiatric admission in England.

Aims and methodTo compare rates of admission for different types of severe mental illness between ethnic groups, and to test the hypothesis that larger and more clustered ethnic groups will have lower admission rates. This was a descriptive study of routinely collected data from the National Health Service in England. RESULTS: There was an eightfold difference in admission rates between ethnic groups for schizophreniform and mania admissions, and a fivefold variation in depression admissions. On average, Black and minority ethnic (BME) groups had higher rates of admission for schizophreniform and mania admissions but not for depression. This increased rate was greatest in the teenage years and early adulthood. Larger ethnic group size was associated with lower admission rates. However, greater clustering was associated with higher admission rates.Clinical implicationsOur findings support the hypothesis that larger ethnic groups have lower rates of admission. This was a between-group comparison rather than within each group. Our findings do not support the hypothesis that more clustered groups have lower rates of admission. In fact, they suggest the opposite: groups with low clustering had lower admission rates. The BME population in the UK is increasing in size and becoming less clustered. Our results suggest that both of these factors should ameliorate the overrepresentation of BME groups among psychiatric in-patients. However, this overrepresentation continues, and our results suggest a possible explanation, namely, changes in the delivery of mental health services, particularly the marked reduction in admissions for depression.Declaration of interestNone.

Integrating national surveys to estimate small area variations in poor health and limiting long-term illness in Great Britain.

OBJECTIVES: This study aims to address, for the first time, the challenges of constructing small area estimates of health status using linked national surveys. The study also seeks to assess the concordance of these small area estimates with data from national censuses. SETTING: Population level health status in England, Scotland and Wales. PARTICIPANTS: A linked integrated dataset of 23 374 survey respondents (16+ years) from the 2011 waves of the Health Survey for England (n=8603), the Scottish Health Survey (n=7537) and the Welsh Health Survey (n=7234). PRIMARY AND SECONDARY OUTCOME MEASURES: Population prevalence of poorer self-rated health and limiting long-term illness. A multilevel small area estimation modelling approach was used to estimate prevalence of these outcomes for middle super output areas in England and Wales and intermediate zones in Scotland. The estimates were then compared with matched measures from the contemporaneous 2011 UK Census. RESULTS: There was a strong positive association between the small area estimates and matched census measures for all three countries for both poorer self-rated health (r=0.828, 95% CI 0.821 to 0.834) and limiting long-term illness (r=0.831, 95% CI 0.824 to 0.837), although systematic differences were evident, and small area estimation tended to indicate higher prevalences than census data. CONCLUSIONS: Despite strong concordance, variations in the small area prevalences of poorer self-rated health and limiting long-term illness evident in census data cannot be replicated perfectly using small area estimation with linked national surveys. This reflects a lack of harmonisation between surveys over question wording and design. The nature of small area estimates as 'expected values' also needs to be better understood.

Variation in compulsory psychiatric inpatient admission in England: a cross-classified, multilevel analysis.

BACKGROUND: The increasing rate of compulsory admission to psychiatric inpatient beds in England is worrying. Studying variation between places and services could be key to identifying targets for interventions to reverse this trend. We modelled spatial variation in compulsory admissions in England using national patient-level data and quantified the extent to which patient, local-area, and service-setting characteristics accounted for this variation. METHODS: This study is a cross-sectional, multilevel analysis of the 2010-11 Mental Health Minimum Data Set (MHMDS). Data from eight provider trusts were excluded, including three independent provider trusts that lacked spatial identification codes. We excluded patients detained under sections of the Mental Health Act concerned only with conveyance to, or assessment in, a registered Place of Safety, or for short-term (≤72 h) assessment only, as these do not in themselves necessarily mean that the person will be admitted to an inpatient mental health bed. MHMDS contained reasonably complete data for a limited number of patient characteristics, namely age, sex, and ethnicity; however, several patient-level variables could not be included in our analysis because of high levels of missing data. Multilevel models were applied with MLwiN to estimate variation in compulsory admission, starting with null (unconditional) models that partitioned total variance in compulsory admission between each level in the model. The primary outcome was compulsory admission to a psychiatric inpatient bed, compared with people admitted voluntarily or receiving only community-based care. FINDINGS: Data were available for 1 238 188 patients, covering 64 National Health Service provider trusts (93%) and 31 865 census lower super output areas (LSOAs; 98%). 7·5% and 5·6% of the variance in compulsory admission occurred at LSOA level and provider trust levels, respectively, after adjusting for patient characteristics. Black patients were almost three times more likely to be admitted compulsorily than were white patients (odds ratio [OR] 2·94, 95% CI 2·90-2·98). Compulsory admission was greater in more deprived areas (OR 1·22, 1·18-1·27) and in areas with more non-white residents (OR 1·51, 1·43-1·59), after adjusting for confounders. INTERPRETATION: Rates of compulsory admission to inpatient psychiatric beds vary significantly between local areas and services, independent of patient, area, and service characteristics. Compulsory admission rates seem to reflect local factors, especially socioeconomic and ethnic population composition. Understanding how these factors condition access to, and use of, mental health care is likely to be important for developing interventions to reduce compulsion. FUNDING: National Institute for Health Research Health Services and Delivery Research Programme.

Rates of voluntary and compulsory psychiatric in-patient treatment in England: an ecological study investigating associations with deprivation and demographics.

BACKGROUND: Individual variables and area-level variables have been identified as explaining much of the variance in rates of compulsory in-patient treatment. AIMS: To describe rates of voluntary and compulsory psychiatric in-patient treatment in rural and urban settings in England, and to explore the associations with age, ethnicity and deprivation. METHOD: Secondary analysis of 2010/11 data from the Mental Health Minimum Dataset. RESULTS: Areas with higher levels of deprivation had increased rates of in-patient treatment. Areas with high proportions of adults aged 20-39 years had the highest rates of compulsory in-patient treatment as well as the lowest rates of voluntary in-patient treatment. Urban settings had higher rates of compulsory in-patient treatment and ethnic density was associated with compulsory treatment in these areas. After adjusting for age, deprivation and urban/rural setting, the association between ethnicity and compulsory treatment was not statistically significant. CONCLUSIONS: Age structure of the adult population and ethnic density along with higher levels of deprivation can account for the markedly higher rates of compulsory in-patient treatment in urban areas.

Using geocoded survey data to improve the accuracy of multilevel small area synthetic estimates.

This paper examines the secondary data requirements for multilevel small area synthetic estimation (ML-SASE). This research method uses secondary survey data sets as source data for statistical models. The parameters of these models are used to generate data for small areas. The paper assesses the impact of knowing the geographical location of survey respondents on the accuracy of estimates, moving beyond debating the generic merits of geocoded social survey datasets to examine quantitatively the hypothesis that knowing the approximate location of respondents can improve the accuracy of the resultant estimates. Four sets of synthetic estimates are generated to predict expected levels of limiting long term illnesses using different levels of knowledge about respondent location. The estimates were compared to comprehensive census data on limiting long term illness (LLTI). Estimates based on fully geocoded data were more accurate than estimates based on data that did not include geocodes.

Small area synthetic estimates of smoking prevalence during pregnancy in England.

BACKGROUND: Complete and accurate data on maternal smoking prevalence during pregnancy are not available at a local geographical scale in England. We employ a synthetic estimation approach to predict the expected prevalence of smoking during pregnancy and smoking at delivery by Primary Care Trust (PCT). METHODS: Multilevel logistic regression models were used with data from the 2010 Infant Feeding Survey and 2011 Census to predict the probability of mothers (a) smoking at any point during pregnancy and (b) smoking at delivery, according to age, deprivation, and the ethnic profile of the home area. These probabilities were applied to demographic information on mothers giving birth from 2010/11 Hospital Episode Statistics data to produce expected counts, and prevalence figures, of smokers by PCT, with Bayesian 95 % credible intervals. The expected prevalence of smoking at delivery by PCT was compared with midwife-collected Smoking at the Time of Delivery (SATOD) data using a Bland-Altman plot. RESULTS: The expected prevalence of smoking during pregnancy by PCT ranged from 8.1 % (95 % CI 5.6-1.0) to 31.6 % (27.5-34.8). The expected prevalence of smoking at delivery ranged from 2.5 % (1.4-4.0) to 17.1 % (13.7-20.4). Figures for expected smoking prevalence at delivery showed some agreement with SATOD, though SATOD data were generally higher than the synthetic estimates (mean difference 2.99 %). CONCLUSIONS: It is possible to derive good estimates of expected smoking prevalence during pregnancy for small areas, potentially at much lower cost than conducting large surveys. Such data may be useful to help plan and commission smoking cessation services and monitor their effectiveness.

The convergent validity of three surveys as alternative sources of health information to the 2011 UK census.

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.

The spatial and temporal development of binge drinking in England 2001-2009: an observational study.

Binge drinking has been linked to escalating costs of hospitalisation and to premature mortality, and implicated in a range of acute and chronic health problems as well as crime, violence and other negative aspects of the wider well-being agenda. Variously defined, it can be characterised as brief periods of heavy drinking (across one day or evening) within a longer time-frame of lower consumption or even abstinence (across a week or several weeks). In England the current binge drinking epidemic has become particularly salient in the past decade and has been seen largely in terms of excessive consumption by younger people, particularly women in urban centres. It has also been linked to the liberalisation of licencing laws and the promotion of 24 h club cultures. This paper presents an observational study of the regional development of binge drinking between 2001 and 2009 as evidenced in the Health Survey for England. We innovate by using two different definitions of binge drinking within a multivariate multilevel modelling framework, with a focus on the random effects attributable to the year of study and region. We control for age, sex, ethnicity, marital status and individual socio-economic status, and confounding by neighbourhood deprivation and urbanisation. The paper identifies pronounced regional geographies that persist in the face of controls and vary little over time, and strong spatio-temporal gender differences which reflect the definition of binge drinking.

Smoking cessation in England: intentionality, anticipated ease of quitting and advice provision.

Smoking prevalence in England continues to reduce but further reduction is increasingly difficult. Cessation policy has successfully targeted those who want to quit but further reduction will need to shift attention to more difficult 'core smoker' populations. Following the established 'stages of change' perspective, this paper considers the characteristics of people who do not intend to quit smoking, anticipate difficulties in quitting and have not received advice about quitting. We deploy multilevel models of data drawn from the Health Survey for England years 2002-2004, and the NHS Primary Care Trust Patient Surveys for 2004 and 2005. It was found that variations in intentionality and anticipated ease of quitting are associated with individual factors such as smoking intensity, parental smoking, age/length of time as a smoker and the nature of the advice-giving consultation. Household composition and household income are also implicated in the intention to quit and anticipated difficulties in quitting. Once individual and household factors are taken into account the only identifiable area-level variation is reduced intentionality towards quitting in rural areas. We conclude by arguing that further gains in smoking cessation must focus on understanding the characteristics of 'hard-to-engage' populations.

Fat nation: deciphering the distinctive geographies of obesity in England.

Much attention is focused on obesity by both the media and by public health. As a health risk, obesity is recognised as a contributing factor to numerous health problems. Recent evidence points to a growth in levels of obesity in many countries and particular attention is usually given to rising levels of obesity among younger people. England is no exception to these generalisations with recent studies revealing a clear geography to what has been termed an 'obesity epidemic.' This paper examines the complexities inherent in the geography of adult obesity in England. Existing knowledge about the sub-national geography of obesity is examined and assessed. Multilevel synthetic estimation is then used to construct an age-sex-ethnicity disaggregated geography of obesity. These differing geographies are compared and contrasted with pre-existing findings and explored at multiple scales. A complex picture of the geography of obesity in England is revealed.

Can the 12-item General Health Questionnaire be used to measure positive mental health?

BACKGROUND: Well-being is an important determinant of health and social outcomes. Measures of positive mental health states are needed for population-based research. The 12-item General Health Questionnaire (GHQ-12) has been widely used in many settings and languages, and includes positively and negatively worded items. Our aim was to test the hypothesis that the GHQ-12 assesses both positive and negative mental health and that these domains are independent of one another. METHOD: Exploratory (EFA) and confirmatory (CFA) factor analyses were conducted using data from the British Household Panel Survey (BHPS) and the Health Survey for England (HSE). Regression models were used to assess whether associations with individual and household characteristics varied across positive and negative mental health dimensions. We also explored higher-level variance in these measures, between electoral wards. RESULTS: We found a consistent, replicable factor structure in both datasets. EFA results indicated a two-factor solution, and CFA demonstrated that this was superior to a one-factor model. These factors correspond to 'symptoms of mental disorder' and 'positive mental health'. Further analyses demonstrated independence of these factors in associations with age, gender, employment status, poor housing and household composition. Statistically significant ward-level variance was found for symptoms of mental disorder but not positive mental health. CONCLUSIONS: The GHQ-12 measures both positive and negative aspects of mental health, and although correlated, these dimensions have some independence. The GHQ-12 could be used to measure positive mental health in population-based research.