Spatial clustering of mental disorders and associated characteristics of the neighbourhood context in Malmö, Sweden, in 2001

Investigating the spatiotemporal patterns and clustering of attendances for mental health services to inform policy and resource allocation in Thailand

BACKGROUND

Mental illness poses a substantial global public health challenge, including in Thailand, where exploration of access to mental health services is limited. The spatial and temporal dimensions of mental illness in the country are not extensively studied, despite the recognized association between poor mental health and socioeconomic inequalities. Gaining insights into these dimensions is crucial for effective public health interventions and resource allocation.

METHODS

This retrospective study analyzed mental health service utilization data in Thailand from 2015 to 2023. Temporal trends in annual numbers of individuals visiting mental health services by diagnosis were examined, while spatial pattern analysis employed Moran's I statistics to assess autocorrelation, identify small-area clustering, and hotspots. The implications of our findings for mental health resource allocation and policy were discussed.

RESULTS

Between 2015 and 2023, mental health facilities documented a total of 13,793,884 visits. The study found anxiety, schizophrenia, and depression emerged as the top three illnesses for mental health visits, with an increase in patient attendance following the onset of the COVID-19 outbreak. Spatial analysis identified areas of significance for various disorders across different regions of Thailand. Positive correlations between certain disorder pairs were found in specific regions, suggesting shared risk factors or comorbidities.

CONCLUSIONS

This study highlights spatial and temporal variations in individuals visiting services for different mental disorders in Thailand, shedding light on service gaps and socioeconomic issues. Addressing these disparities requires increased attention to mental health, the development of appropriate interventions, and overcoming barriers to accessibility. The findings provide a baseline for policymakers and stakeholders to allocate resources and implement culturally responsive interventions to improve mental health outcomes.

Psychosis prevalence in London neighbourhoods; A case study in spatial confounding

Analysis of impacts of neighbourhood risk factors on mental health outcomes frequently adopts a disease mapping approach, with unknown neighbourhood influences summarised by random effects. However, such effects may show confounding with observed predictors, especially when such predictors have a clear spatial pattern. Here, the standard disease mapping model is compared to methods which account and adjust for spatial confounding in an analysis of psychosis prevalence in London neighbourhoods. Established area risk factors such as area deprivation, non-white ethnicity, greenspace access and social fragmentation are considered as influences on psychosis. The results show evidence of spatial confounding in the standard disease mapping model. Impacts expected on substantive grounds and available evidence are either nullified or reversed in direction. It is argued that the potential for spatial confounding to affect inferences about geographic disease patterns and risk factors should be routinely considered in ecological studies of health based on disease mapping.

Leading consumption patterns of psychoactive substances in Colombia: A deep neural network-based clustering-oriented embedding approach

The number of health-related incidents caused using illegal and legal psychoactive substances (PAS) has dramatically increased over two decades worldwide. In Colombia, the use of illicit substances has increased up to 10.3%, while the consumption alcohol and tobacco has increased to 84% and 12%, respectively. It is well-known that identifying drug consumption patterns in the general population is essential in reducing overall drug consumption. However, existing approaches do not incorporate Machine Learning and/or Deep Data Mining methods in combination with spatial techniques. To enhance our understanding of mental health issues related to PAS and assist in the development of national policies, here we present a novel Deep Neural Network-based Clustering-oriented Embedding Algorithm that incorporates an autoencoder and spatial techniques. The primary goal of our model is to identify general and spatial patterns of drug consumption and abuse, while also extracting relevant features from the input data and identifying clusters during the learning process. As a test case, we used the largest publicly available database of legal and illegal PAS consumption comprising 49,600 Colombian households. We estimated and geographically represented the prevalence of consumption and/or abuse of both PAS and non-PAS, while achieving statistically significant goodness-of-fit values. Our results indicate that region, sex, housing type, socioeconomic status, age, and variables related to household finances contribute to explaining the patterns of consumption and/or abuse of PAS. Additionally, we identified three distinct patterns of PAS consumption and/or abuse. At the spatial level, these patterns indicate concentrations of drug consumption in specific regions of the country, which are closely related to specific geographic locations and the prevailing social and environmental contexts. These findings can provide valuable insights to facilitate decision-making and develop national policies targeting specific groups given their cultural, geographic, and social conditions.

Opening the black box of the relationship between neighborhood socioeconomic status and mental health: Neighborhood social-interactive characteristics as contextual mechanisms

Previous studies have linked low neighborhood socioeconomic status (NSES) to mental health problems. However, few studies have investigated the mechanisms underlying this association and most focused on the association with negative indicators of mental health, such as symptoms of depression or anxiety. This paper investigated whether neighborhood social characteristics (social interaction, trust, safety, organization participation, and attachment) mediate the association between NSES and mental health. We combined Danish register data with survey data from the North Denmark Region Health Survey 2017. Mental health was assessed with the Rand 12-item Short-form Survey (SF-12). The sample consisted of 14,969 individuals nested in 1047 neighborhoods created with an automated redistricting algorithm. We fitted multilevel structural equation mediation models and used a Monte Carlo simulation method to estimate confidence intervals for the indirect effects. NSES was positively associated with mental health. Neighborhood trust significantly mediated this relationship, accounting for 34% of the association after controlling for other mediators. These results indicate that higher levels of mental health in more affluent neighborhoods are partially explained by higher levels of trust. Improving neighborhood trust could mitigate sociogeographic inequalities in mental health.

Neighborhood socioeconomic deprivation and psychiatric medication purchases. Different neighborhood delineations, different results? A nationwide register-based multilevel study

Previous studies of neighborhood socioeconomic deprivation and mental health treatment have shown mixed results. Multiple reviews have highlighted that the definition and measurement of neighborhoods can lead to different results, providing one explanation for these mixed findings. This study compares the use of micro-areas created using an automated redistricting algorithm and divided by physical barriers with the use of two administrative units, Danish parishes and postal codes. The geographical data are linked to Danish register data of the Danish population from age 16 in 2017, N = 4,347,001, to measure the association between the purchase of psychiatric medication and neighborhood socioeconomic deprivation using logistic multilevel models. Neighborhood socioeconomic deprivation is associated with a slightly increased probability of redeeming prescriptions for psychiatric medication after controlling for individual sociodemographic composition. However, this association was present only for micro-areas and not for parishes or postal codes. The results indicate that neighborhood effects on psychiatric medication purchases are affected by the neighborhood delineations used and that future studies should carefully consider how neighborhoods are defined and measured.

A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors

Introduction

The neighbourhood in which one lives affects health through complex pathways not yet fully understood. A way to move forward in assessing these pathways direction is to explore the spatial structure of health phenomena to generate hypotheses and examine whether the neighbourhood characteristics are able to explain this spatial structure. We compare the spatial structure of two cardiovascular disease risk factors in three European urban areas, thus assessing if a non-measured neighbourhood effect or spatial processes is present by either modelling the correlation structure at individual level or by estimating the intra-class correlation within administrative units.

Methods

Data from three independent studies (RECORD, DHS and BaBi), covering each a European urban area, are used. The characteristics of the spatial correlation structure of cardiovascular risk factors (BMI and systolic blood pressure) adjusted for age, sex, educational attainment and income are estimated by fitting an exponential model to the semi-variogram based on the geo-coordinates of places of residence. For comparison purposes, a random effect model is also fitted to estimate the intra-class correlation within administrative units. We then discuss the benefits of modelling the correlation structure to evaluate the presence of unmeasured spatial effects on health.

Results

BMI and blood pressure are consistently found to be spatially structured across the studies, the spatial correlation structures being stronger for BMI. Eight to 22% of the variability in BMI were spatially structured with radii ranging from 100 to 240 m (range). Only a small part of the correlation of residuals was explained by adjusting for the correlation within administrative units (from 0 to 4 percentage points).

Discussion

The individual spatial correlation approach provides much stronger evidence of spatial effects than the multilevel approach even for small administrative units. Spatial correlation structure offers new possibilities to assess the relevant spatial scale for health. Stronger correlation structure seen for BMI may be due to neighbourhood socioeconomic conditions and processes like social norms at work in the immediate neighbourhood.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11356-w.

The impact of neighbourhood crime on mental health: A systematic review and meta-analysis

BACKGROUND

Growing evidence indicates that the residential neighbourhood contributes to the complex aetiology of mental disorders. Although local crime and violence, key neighbourhood stressors, may be linked to mental health through direct and indirect pathways, studies are inconclusive. This systematic review and meta-analysis aimed to synthetize the evidence on the association between neighbourhood crime and individual-level mental health problems.

METHOD

We searched 11 electronic databases, grey literature and reference lists to identify relevant studies published before September 14, 2020. Studies were included if they reported confounder-adjusted associations between objective or perceived area-level crime and anxiety, depression, psychosis or psychological distress/internalising symptoms in non-clinical samples. Effect measures were first converted into Fisher's z-s, pooled with three-level random-effects meta-analyses, and then transformed into Pearson's correlation coefficients. Univariate and multivariate mixed-effects models were used to explore between-study heterogeneity.

RESULTS

We identified 63 studies reporting associations between neighbourhood crime and residents' mental health. Pooled associations were significant for depression (r = 0.04, 95% CI 0.03-0.06), psychological distress (r = 0.04, 95% CI 0.02-0.06), anxiety (r = 0.05, 95% CI 0.01-0.10), and psychosis (r = 0.04, 95% CI 0.01-0.07). Moderator analysis for depression and psychological distress identified stronger associations with perceived crime measurement and weaker in studies adjusted for area-level deprivation. Importantly, even after accounting for study characteristics, neighbourhood crime remained significantly linked to depression and psychological distress. Findings on anxiety and psychosis were limited due to low number of included studies.

CONCLUSIONS

Neighbourhood crime is an important contextual predictor of mental health with implications for prevention and policy. Area-based crime interventions targeting the determinants of crime, prevention and service allocation to high crime neighbourhoods may have public mental health benefits. Future research should investigate the causal pathways between crime exposure and mental health, identify vulnerably groups and explore policy opportunities for buffering against the detrimental effect of neighbourhood stressors.

Neighborhood Crime and Psychotropic Medications: A Longitudinal Data Linkage Study of 130,000 Scottish Adults

INTRODUCTION

Although neighborhood crime has been associated with mental health problems, longitudinal research utilizing objective measures of small-area crime and mental health service use is lacking. This study examines how local crime is associated with newly prescribed psychotropic medications in a large longitudinal sample of Scottish adults and explores whether the relationships vary between sociodemographic groups.

METHODS

Data from the Scottish Longitudinal Study, a 5.3% representative sample of the population, were linked with police-recorded crime in 2011 for residential locality and with psychotropic medications from 2009 to 2014, extracted from the prescription data set of National Health Service Scotland. Individuals receiving medication during the first 6 months of observation were excluded; the remaining sample was followed for 5.5 years. Covariate-adjusted, multilevel mixed-effects logistic models estimated associations between area crime and prescriptions for antidepressants, antipsychotics, and anxiolytics (analyzed in 2018-2019).

RESULTS

After adjustment for individual and neighborhood covariates, findings on 129,945 adults indicated elevated risk of antidepressant (OR=1.05, 95% CI=1.00, 1.10) and antipsychotic (OR=1.20, 95% CI=1.03, 1.39), but not anxiolytic (OR=0.99, 95% CI=0.93, 1.05) medication in high-crime areas. Crime showed stronger positive association with antidepressants among individuals (especially women) aged 24-53 years in 2009 and with antipsychotics among men aged 44-53 years in 2009. Skilled workers and people from lower nonmanual occupations had increased risk of medications in high-crime areas.

CONCLUSIONS

Local crime is an important predictor of mental health, independent of individual and other contextual risk factors. Place-based crime prevention and targeting vulnerable groups may have benefits for population mental health.

No man is an island: spatial clustering and access to primary care as possible targets for the development of new community mental health approaches

BACKGROUND

to understand if patients seen at Centro Hospitalar Psiquiátrico de Lisboa (CHPL) live in geographical clusters or randomly throughout the city, as well as determine their access to the psychiatric hospital and primary care facilities (PCF).

METHODS

spatial autocorrelation statistics were performed (queen criterion of contiguity), regarding all patients observed at CHPL in 2017 (at the census subsection level), and considering not only their overall number but also main diagnosis, and admission to the psychiatric ward - voluntary or compulsory. Distance to the hospital and to the closest PCF was measured (for each patient and the variables cited above), and the mean values were compared. Finally, the total number of patients around each PCF was counted, considering specified radius sizes of 656 and 1000 m.

RESULTS

All 5161 patients (509 psychiatric admissions) were geolocated, and statistical significance regarding patient clustering was found for the total number (p-0.0001) and specific group of disorders, namely Schizophrenia and related disorders (p-0.007) and depressive disorders (p-0.0002). Patients who were admitted in a psychiatric ward live farther away from the hospital (p-0.002), with the compulsory admissions (versus voluntary ones) living even farther (p-0.004). Furthermore, defining a radius of 1000 m for each PCF allowed the identification of two PCF with more than 1000 patients, and two others with more than 800.

CONCLUSIONS

as patients seem to live in geographical clusters (and considering PCFs with the highest number of them), possible locations for the development of programs regarding mental health treatment and prevention can now be identified.

Non-completion of secondary education and early disability in Norway: geographic patterns, individual and community risks

Background

School non-completion and early work disability is a great public health challenge in Norway, as in most western countries. This study aims to investigate how medically based disability pension (DP) among young adults varies geographically and how municipal socioeconomic conditions interact with non-completion of secondary education in determining DP risk.

Methods

The study includes a nationally representative sample of 30% of all Norwegians (N = 350,699) aged 21–40 in 2010 from Statistic Norway’s population registries. Multilevel models incorporating factors at the individual, neighbourhood and municipal levels were applied to estimate the neighbourhood and municipality general contextual effects in DP receipt, and detect possible differences in the impact of municipal socioeconomic conditions on DP risk between completers and non-completers of secondary education.

Results

A pattern of spatial clustering at the neighbourhood (ICC = 0.124) and municipality (ICC = 0.021) levels are clearly evident, indicating that the underlying causes of DP receipt have a systematic neighbourhood and municipality variation in Norway. Non-completion of secondary education is strongly correlated with DP receipt among those younger than 40. Socioeconomic characteristics of the municipality are also significantly correlated with DP risk, but these associations are conditioned by the completion of secondary education. Living in a socioeconomically advantageous municipality (i.e. high income, high education levels and low unemployment and social security payment rates) is associated with a higher risk of DP, but only among those who do not complete their secondary education. Although the proportion of DPs was equal in rural and urban areas, it is evident that young people living in urban settings are more at risk of early DP than their counterparts living in rural parts of the country when controlling for other risk factors.

Conclusion

The association between school non-completion and DP risk varies between municipalities and local socioeconomic environments. The interplay between personal characteristics and the local community is important in DP risk among young adults, implying that preventive measures should be directed not only at the individual level, but also include the educational system and the local community.

Depression hurts, depression costs: The medical spending attributable to depression and depressive symptoms in China

Due to its fast economic growth and lifestyle changes, China is experiencing a rapid epidemiological transition from communicable to noncommunicable diseases (NCDs). Mental disorder such as depression is an important yet often neglected NCD and is becoming a growing cause of disability, suicides, and disease burden. This paper provides the first nationally representative estimate of the medical cost attributable to depression and depressive symptoms among the adult population in China. On the basis of the 2012 China Family Panel Studies survey, our results indicate that these mental health conditions have significant impacts on the individual medical expenditure, and they jointly contribute to 14.7% of total personal expected medical spending in China, with depression and depressive symptoms accounting for 6.9% and 7.8%, respectively. Given that patients with mental illness face multiple psychological and institutional barriers in seeking appropriate treatment, the high depression-induced medical costs may be primarily driven by the cost-shifting effect from mental health care to general health care, as mental disorders often coexist with other NCDs such as diabetes and hypertension. As an implication, our study calls for an urgent reform of China's mental health and insurance systems to remove the policy-induced obstacles for the access to mental health care resources.

Does Walkability Contribute to Geographic Variation in Psychosocial Distress? A Spatial Analysis of 91,142 Members of the 45 and Up Study in Sydney, Australia

Walkability describes the capacity of the built environment to promote walking, and has been proposed as a potential focus for community-level mental health planning. We evaluated this possibility by examining the contribution of area-level walkability to variation in psychosocial distress in a population cohort at spatial scales comparable to those used for regional planning in Sydney, Australia. Data on psychosocial distress were analysed for 91,142 respondents to the 45 and Up Study baseline survey between January 2006 and April 2009. We fit conditional auto regression models at the postal area level to obtain smoothed “disease maps” for psychosocial distress, and assess its association with area-level walkability after adjusting for individual- and area-level factors. Prevalence of psychosocial distress was 7.8%; similar for low (7.9%), low-medium (7.9%), medium-high (8.0%), and high (7.4%) walkability areas; and decreased with reducing postal area socioeconomic disadvantage: 12.2% (most), 9.3%, 7.5%, 5.9%, and 4.7% (least). Unadjusted disease maps indicated strong geographic clustering of psychosocial distress with 99.0% of excess prevalence due to unobserved and spatially structured factors, which was reduced to 55.3% in fully adjusted maps. Spatial and unstructured variance decreased by 97.3% and 39.8% after adjusting for individual-level factors, and another 2.3% and 4.2% with the inclusions of area-level factors. Excess prevalence of psychosocial distress in postal areas was attenuated in adjusted models but remained spatially structured. Postal area prevalence of high psychosocial distress is geographically clustered in Sydney, but is unrelated to postal area walkability. Area-level socioeconomic disadvantage makes a small contribution to this spatial structure; however, community-level mental health planning will likely deliver greatest benefits by focusing on individual-level contributors to disease burden and inequality associated with psychosocial distress.

Health in the Neighborhood and Household Contexts Among Older Chinese Americans

OBJECTIVE

This study examined the associations of neighborhood characteristics and living arrangements with physical and mental health among older Chinese Americans.

METHOD

A sample of 3,159 community-dwelling Chinese older adults in the Greater Chicago area provided reports of health, socio-demographic characteristics, living arrangements, social cohesion, and neighborhood disorder. We used multinomial logistic, Poisson, and negative binominal regression analyses.

RESULTS

Neighborhood disorder was consistently associated with negative health indicators, including poor self-reported health, more chronic conditions, depressive symptoms, and anxiety symptoms. Findings about the relationships between social cohesion and health indicators were mixed. Social cohesion was more salient to mental health for those living with spouse, children, and/or grandchildren relative to those living with spouse only.

DISCUSSION

Policies and interventions are needed to improve the physical and social environments of neighborhoods and to promote healthy aging among Chinese older adults and in the general population as well.

Spatiotemporal meta-analysis: reviewing health psychology phenomena over space and time

Individual studies of health psychology are samples taken in particular places at particular times. The results of such studies manifest multiple processes, including those associated with individual, sample, intervention, and study design characteristics. Although extant meta-analyses of health phenomena have routinely considered these factors to explain heterogeneity, they have tended to neglect the environments where studies are conducted, which is ironic, as health phenomena cluster in space and times (e.g., epidemics). The settings in which study participants live, work, and recreate can be characterised by such environmental factors such as disease, weather, local and broad economic trends, the level of stigmatisation of minority groups, and allostatic load due to all causes. We introduce spatiotemporal meta-analysis, designed to address heterogeneity in study environments. We list potential challenges in developing spatiotemporal meta-analyses, and discuss future directions for this form of systematic reviewing methodology. Logically, to the extent that relevant spatiotemporal information on environmental conditions is available and varies widely, it can help to explain variability in study results that is not explained by individual, sample, study, or intervention features.

Socioeconomic position and outdoor nitrogen dioxide (NO2) exposure in Western Europe: A multi-city analysis

BACKGROUND

Inconsistent associations between socioeconomic position (SEP) and outdoor air pollution have been reported in Europe, but methodological differences prevent any direct between-study comparison.

OBJECTIVES

Assess and compare the association between SEP and outdoor nitrogen dioxide (NO₂) exposure as a marker of traffic exhaust, in 16 cities from eight Western European countries.

METHODS

Three SEP indicators, two defined at individual-level (education and occupation) and one at neighborhood-level (unemployment rate) were assessed in three European multicenter cohorts. NO₂ annual concentration exposure was estimated at participants' addresses with land use regression models developed within the European Study of Cohorts for Air Pollution Effects (ESCAPE; http://www.escapeproject.eu/). Pooled and city-specific linear regressions were used to analyze associations between each SEP indicator and NO₂. Heterogeneity across cities was assessed using the Higgins' I-squared test (I²).

RESULTS

The study population included 5692 participants. Pooled analysis showed that participants with lower individual-SEP were less exposed to NO₂. Conversely, participants living in neighborhoods with higher unemployment rate were more exposed. City-specific results exhibited strong heterogeneity (I²>76% for the three SEP indicators) resulting in variation of the individual- and neighborhood-SEP patterns of NO₂ exposure across cities. The coefficients from a model that included both individual- and neighborhood-SEP indicators were similar to the unadjusted coefficients, suggesting independent associations.

CONCLUSIONS

Our study showed for the first time using homogenized measures of outcome and exposure across 16 cities the important heterogeneity regarding the association between SEP and NO₂ in Western Europe. Importantly, our results showed that individual- and neighborhood-SEP indicators capture different aspects of the association between SEP and exposure to air pollution, stressing the importance of considering both in air pollution health effects studies.

Moving to opportunity and mental health: Exploring the spatial context of neighborhood effects

Studies of housing mobility and neighborhood effects on health often treat neighborhoods as if they were isolated islands. This paper argues that conceptualizing neighborhoods as part of the wider spatial context within which they are embedded may be key in advancing our understanding of the role of local context in the life of urban dwellers. Analyses are based on mental health and neighborhood context measurements taken on over 3000 low-income families who participated in the Moving to Opportunity for Fair Housing Demonstration Program (MTO), a large field experiment in five major U.S. cities. Results from analyses of two survey waves combined with Census data at different geographic scales indicate that assignment to MTO's experimental condition of neighborhood poverty <10% significantly decreased average exposure to immediate and surrounding neighborhood disadvantage by 97% and 59% of a standard deviation, respectively, relative to the control group. Escaping concentrated disadvantage in either the immediate neighborhood or the surrounding neighborhood, but not both, was insufficient to make a difference for mental health. Instead, the results suggest that improving both the immediate and surrounding neighborhoods significantly benefits mental health. Compared to remaining in concentrated disadvantage in the immediate and surrounding neighborhoods, escaping concentrated disadvantage in both the immediate and surrounding neighborhoods (on average over the study duration) as a result of the intervention predicts an increase of 25% of a standard deviation in the composite mental health scores.

Model-based testing for space-time interaction using point processes: An application to psychiatric hospital admissions in an urban area

Spatio-temporal interaction is inherent to cases of infectious diseases and occurrences of earthquakes, whereas the spread of other events, such as cancer or crime, is less evident. Statistical significance tests of space-time clustering usually assess the correlation between the spatial and temporal (transformed) distances of the events. Although appealing through simplicity, these classical tests do not adjust for the underlying population nor can they account for a distance decay of interaction. We propose to use the framework of an endemic-epidemic point process model to jointly estimate a background event rate explained by seasonal and areal characteristics, as well as a superposed epidemic component representing the hypothesis of interest. We illustrate this new model-based test for space-time interaction by analysing psychiatric inpatient admissions in Zurich, Switzerland (2007-2012). Several socio-economic factors were found to be associated with the admission rate, but there was no evidence of general clustering of the cases.

The socio-spatial context as a risk factor for hospitalization due to mental illness in the metropolitan areas of Portugal

Abstract This study’s aims are: (i) identifying spatial patterns for the risk of hospitalization due to mental illness and for the potential risk resulting from contextual factors with influence on mental health; and (ii) analyzing the spatial association between risk of hospitalization due to mental illness and potential risk resulting from contextual factors in the metropolitan areas of Lisbon and Porto, Portugal. A cross-sectional ecological study was conducted by applying statistical methods for assessing spatial dependency and heterogeneity. Results reveal a spatial association between risk of hospitalization due to mental illness and potential risk resulting from contextual factors with a statistical relevance of moderate intensity. 20% of the population under study lives in areas with a simultaneously high potential risk resulting from contextual factors and risk of hospitalization due to mental illness. Porto Metropolitan Area show the highest percentage of population living in parishes with a significantly high risk of hospitalization due to mental health, which puts forward the need for interventions on territory-adjusted contextual factors influencing mental health.

A small-area analysis of inequalities in chronic disease prevalence across urban and non-urban communities in the Province of Nova Scotia, Canada, 2007-2011

BACKGROUND

Small-area studies of health inequalities often have an urban focus, and may be limited in their translatability to non-urban settings. Using small-area units representing communities, this study assessed the influence of living in different settlement types (urban, town and rural) on the prevalence of four chronic diseases (heart disease, cancer, diabetes and stroke) and compared the degrees of associations with individual-level and community-level factors among the settlement types.

METHODS

The associations between community-level and individual-level characteristics and prevalence of the chronic diseases were assessed using logistic regression (multilevel and non-multilevel) models. Individual-level data were extracted from the Canadian Community Health Survey (2007-2011). Indices of material deprivation and social isolation and the settlement type classification were created using the Canadian Census.

RESULTS

Respondents living in towns were 21% more likely to report one of the diseases than respondents living in urban communities even after accounting for individual-level and community-level characteristics. Having dependent children appeared to have protective effects in towns, especially for males (OR: 0.49 (95% CI 0.27 to 0.90)). Unemployment had a strong association for all types of communities, but being unemployed appeared to be particularly damaging to health of males in urban communities (OR: 2.48 (95% CI 1.43 to 4.30)).

CONCLUSIONS

The study showed that those living in non-urban settings, particularly towns, experience extra challenges in maintaining health above and beyond the socioeconomic condition and social isolation of the communities, and individual demographic, behavioural and socioeconomic attributes. Our findings also suggest that health inequality studies based on urban-only settings may underestimate the risks by some factors. Ways to devise meaningful small-area units comparable in all settlement types are necessary to help plan effective provision of chronic disease-related health services and programmes on a regional scale.

The environmental correlates of overall and neighborhood based recreational walking (a cross-sectional analysis of the RECORD Study)

Background

Preliminary evidence suggests that recreational walking has different environmental determinants than utilitarian walking. However, previous studies are limited in their assessment of environmental exposures and recreational walking and in the applied modeling strategies. Accounting for individual sociodemographic profiles and weather over the walking assessment period, the study examined whether numerous street network-based neighborhood characteristics related to the sociodemographic, physical, service, social-interactional, and symbolic environments were associated with overall recreational walking and recreational walking in one’s residential neighborhood and could explain their spatial distribution.

Methods

Based on the RECORD Cohort Study (Paris region, France, n = 7105, 2007–2008 data), multilevel-spatial regression analyses were conducted to investigate environmental factors associated with recreational walking (evaluated by questionnaire at baseline). A risk score approach was applied to quantify the overall disparities in recreational walking that were predicted by the environmental determinants.

Results

Sixty-nine percent of the participants reported recreational walking over the past 7 days. Their mean reported recreational walking time was 3h31mn. After individual-level adjustment, a higher neighborhood education, a higher density of destinations, green and open spaces of quality, and the absence of exposure to air traffic were associated with higher odds of recreational walking and/or a higher recreational walking time in one’s residential neighborhood. As the overall disparities that were predicted by these environmental factors, the odds of reporting recreational walking and the odds of a higher recreational walking time in one’s neighborhood were, respectively, 1.59 [95% confidence interval (CI): 1.56, 1.62] times and 1.81 (95% CI: 1.73, 1.87) times higher in the most vs. the least supportive environments (based on the quartiles).

Conclusions

Providing green/open spaces of quality, building communities with services accessible from the residence, and addressing environmental nuisances such as those related to air traffic may foster recreational walking in one’s environment.

Spatio-temporal clustering of the incidence of schizophrenia in Quebec, Canada from 2004 to 2007

Exploring spatio-temporal patterns of disease incidence can help to identify areas of significantly elevated or decreased risk, providing potential etiologic clues. In this study, we present a spatio-temporal analysis of the incidence of schizophrenia in Quebec from 2004 to 2007 using administrative databases from the Régie de l'Assurance Maladie du Quebec and the hospital discharge database. We conducted purely spatial analyses for each age group adjusted by sex for the whole period using SatScan (version 9.1.1). Findings from the study indicated variations in the spatial clustering of schizophrenia according to sex and age. In term of incidence rate, there are high differences between urban and rural-remote areas, as well as between the two main metropolitan areas of the province of Quebec (Island of Montreal and Quebec-City).

Neighborhood Contexts, Health, and Behavior: Understanding the Role of Scale and Residential Sorting

Recent reviews in sociology, public health, and urban planning suggest small-scale geographic variations in urban environments are associated with an individual's health, behavior, and well-being. However, estimation of these ‘neighborhood effects' are complicated. One complicating factor is residential sorting: Individual characteristics such as race, age, and socioeconomic status are associated with behavior and health and these same individual-level factors are often geographically clustered within neighborhoods. This residential sorting leads to a correlation between individual and environmental determinants of behavior and health and poses problems for statistical inference. A second complicating factor is uncertainty about the geographic dimensions of a person's neighborhood. We explore these two potential confounders through a simulation experiment that generates synthetic cityscapes and synthetic behaviors for geolocated individuals. The simulation is used to develop a model of how residential sorting, urban structure, and the geographic definition of an individual's neighborhood affect our understanding of the association between the urban environment and behavior. We find that residential sorting does not systematically affect the magnitude of neighborhood effect estimates, however, the misrepresentation of the geographic dimensions of an individual's neighborhood leads to systematic bias in estimates of neighborhood effects. Unlike previous research on the modifiable areal unit problem we find a systematic relationship between the definition of geographic units of analysis and the magnitude of regression coefficients.

Neighborhood characteristics and depressive symptoms of older people: local spatial analyses

Depressive symptoms in community-dwelling older people significantly increase the risk of developing clinically diagnosable depressive disorders. Knowledge of the spatial distribution of depressive symptoms in the older population can add important information to studies of neighborhood contextual factors and mental health outcomes, but analysis of spatial patterns is rarely undertaken. This study uses spatial statistics to explore patterns of clustering in depressive symptoms using data from a statewide survey of community-dwelling older people in New Jersey from 2006 to 2008. A significant overall pattern of clustering in depressive symptoms was observed at the state level. In a subsequent local clustering analysis, places with high levels of depressive symptoms near to other places with high levels of depressive symptoms were identified. The relationships between the level of depressive symptoms in a place and poverty, residential stability and crime were analyzed using geographically weighted regression. Significant local parameter estimates for the three independent variables were observed. Local parameters for the poverty variable were positive and significant almost everywhere in the state. The significant local parameters for residential stability and crime varied in their association with depressive symptoms in different regions of the state. This study is among the first to examine spatial patterns in depressive symptoms among community-dwelling older people, and it demonstrates the importance of exploring spatial variations in the relationships between neighborhood contextual factors and health outcomes.

Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain)

Background

Spatial analysis is a relevant set of tools for studying the geographical distribution of diseases, although its methods and techniques for analysis may yield very different results. A new hybrid approach has been applied to the spatial analysis of treated prevalence of depression in Catalonia (Spain) according to the following descriptive hypotheses: 1) spatial clusters of treated prevalence of depression (hot and cold spots) exist and, 2) these clusters are related to the administrative divisions of mental health care (catchment areas) in this region.

Methods

In this ecological study, morbidity data per municipality have been extracted from the regional outpatient mental health database (CMBD-SMA) for the year 2009. The second level of analysis mapped small mental health catchment areas or groups of municipalities covered by a single mental health community centre. Spatial analysis has been performed using a Multi-Objective Evolutionary Algorithm (MOEA) which identified geographical clusters (hot spots and cold spots) of depression through the optimization of its treated prevalence. Catchment areas, where hot and cold spots are located, have been described by four domains: urbanicity, availability, accessibility and adequacy of provision of mental health care.

Results

MOEA has identified 6 hot spots and 4 cold spots of depression in Catalonia. Our results show a clear spatial pattern where one cold spot contributed to define the exact location, shape and borders of three hot spots. Analysing the corresponding domain values for the identified hot and cold spots no common pattern has been detected.

Conclusions

MOEA has effectively identified hot/cold spots of depression in Catalonia. However these hot/cold spots comprised municipalities from different catchment areas and we could not relate them to the administrative distribution of mental care in the region. By combining the analysis of hot/cold spots, a better statistical and operational-based visual representation of the geographical distribution is obtained. This technology may be incorporated into Decision Support Systems to enhance local evidence-informed policy in health system research.

Revealing mental health status in Iran's capital: putting equity and efficiency together

Information about urban health is often based on averages, while to better understand health status in urban areas, inequality should also be included. In this paper, we applied an achievement index approach in order to surmount this defect and to examine mental health status in Iran's capital, Tehran. The data we required for this study were taken from the Urban Health Equity Assessment and Response Tool (Urban HEART) survey which was conducted in Tehran in 2007, covering people aged 15 and above. The concentration index, which is a commonly used measure of socioeconomic inequalities in health, was extended to enable the combination of inequality and averages and the formation of a mental health achievement index. Values from the standard concentration indices showed that mental disorders are concentrated disproportionately among the poor in Tehran. An extension of the standard concentration indices revealed that, in most of Tehran's districts, the mental health of populations in the poorest quintile is much worse than that of other groups. In addition, when we computed the achievement index and ranked districts according to this index, the ranking was different from the ranking by averages. These findings imply that mental health varies significantly across the economic groups of the population in Tehran and that efficiency-oriented strategies which target average level of mental health alone are not sufficient to improve mental health of all people especially mental health of the poor. Equity-oriented strategies which target the mental health inequalities should be considered as well.

A review of spatial methods in epidemiology, 2000-2010

Understanding the impact of place on health is a key element of epidemiologic investigation, and numerous tools are being employed for analysis of spatial health-related data. This review documents the huge growth in spatial epidemiology, summarizes the tools that have been employed, and provides in-depth discussion of several methods. Relevant research articles for 2000-2010 from seven epidemiology journals were included if the study utilized a spatial analysis method in primary analysis (n = 207). Results summarized frequency of spatial methods and substantive focus; graphs explored trends over time. The most common spatial methods were distance calculations, spatial aggregation, clustering, spatial smoothing and interpolation, and spatial regression. Proximity measures were predominant and were applied primarily to air quality and climate science and resource access studies. The review concludes by noting emerging areas that are likely to be important to future spatial analysis in public health.

Are associations between neighborhood socioeconomic characteristics and body mass index or waist circumference based on model extrapolations?

BACKGROUND

We investigated whether neighborhood socioeconomic characteristics, measured within person-centered areas (ie, centered on individuals' residences) are associated with body mass index (BMI [kg/m²]) and waist circumference. We used propensity-score matching as a diagnostic and validation tool to examine whether socio-spatial segregation (and related structural confounding) allowed us to estimate neighborhood socioeconomic effects adjusted for individual socioeconomic characteristics without excessive model extrapolations.

METHODS

Using the RECORD (Residential Environment and CORonary heart Disease) Cohort Study, we conducted cross-sectional analyses of 7230 adults from the Paris region. We first estimated the relationships of 3 neighborhood socioeconomic indicators (education, income, real estate prices) with BMI and waist circumference using traditional multilevel regression models adjusted for individual covariates. Second, we examined whether these associations persisted when estimated among participants exchangeable based on their probability of living in low-socioeconomic-status neighborhoods (propensity-score matched samples).

RESULTS

After adjustment for covariates, BMI/waist circumference increased with decreasing neighborhood socioeconomic status, especially with neighborhood education measured within 500-m radius buffers around residences; associations were stronger for women. With propensity-score matching techniques, there was some overlap in the odds of exposure between exposed and unexposed populations. As a function of socio-spatial segregation and an indicator of whether the data support inferences, sample size decreased by 17%-59% from the initial to the propensity-score matched samples. Propensity-score matched models confirmed relationships obtained from models in the entire sample.

CONCLUSIONS

Overall, adjusted associations between neighborhood socioeconomic variables and BMI/waist circumference were empirically estimable in the French context, without excessive model extrapolations, despite the extent of socio-spatial segregation.

The texture of neighborhoods and disability among older adults

OBJECTIVES

To present and test an ecological multidimensional model of neighborhood characteristics and examine its relationship to older disability among older adults.

METHOD

Indicators of social vulnerability, wealth, violence, storefronts, residential stability, and the presence of physicians, supermarkets, and fast-food establishments for 1,644 of New Jersey's census tracts were derived from sources that include the U.S. Census 2000, Uniform Crime Report for New Jersey, New Jersey Department of Agriculture, Division of Marketing and Development, New Jersey Department of Law and Public Safety Division of Alcohol Beverage Control, and Health Resources and Services Administration Geospatial Data Warehouse. Confirmatory factor analyses were used to develop and test a measurement model of neighborhood texture. Structural equation modeling examined the relationships between neighborhood characteristics and disability of persons aged 65-69 years.

RESULTS

Analyses revealed that distinct dimensions of neighborhoods could be modeled with administrative data and that neighborhood contextual (supermarkets, physicians, storefronts, violence) and compositional (social vulnerability, wealth, residential stability) characteristics were related to the prevalence of disability.

DISCUSSION

The use of multiple indicators of neighborhood with good psychometric qualities is critical for advancing knowledge about the mechanisms by which neighborhood characteristics are associated with the health of older people.

Reliability of perceived neighbourhood conditions and the effects of measurement error on self-rated health across urban and rural neighbourhoods

BACKGROUND

Limited psychometric research has examined the reliability of self-reported measures of neighbourhood conditions, the effect of measurement error on associations between neighbourhood conditions and health, and potential differences in the reliabilities between neighbourhood strata (urban vs rural and low vs high poverty). We assessed overall and stratified reliability of self-reported perceived neighbourhood conditions using five scales (social and physical disorder, social control, social cohesion, fear) and four single items (multidimensional neighbouring). We also assessed measurement error-corrected associations of these conditions with self-rated health.

METHODS

Using random-digit dialling, 367 women without breast cancer (matched controls from a larger study) were interviewed twice, 2-3 weeks apart. Test-retest (intraclass correlation coefficients (ICC)/weighted κ) and internal consistency reliability (Cronbach's α) were assessed. Differences in reliability across neighbourhood strata were tested using bootstrap methods. Regression calibration corrected estimates for measurement error.

RESULTS

All measures demonstrated satisfactory internal consistency (α ≥ 0.70) and either moderate (ICC/κ=0.41-0.60) or substantial (ICC/κ=0.61-0.80) test-retest reliability in the full sample. Internal consistency did not differ by neighbourhood strata. Test-retest reliability was significantly lower among rural (vs urban) residents for two scales (social control, physical disorder) and two multidimensional neighbouring items; test-retest reliability was higher for physical disorder and lower for one multidimensional neighbouring item among the high (vs low) poverty strata. After measurement error correction, the magnitude of associations between neighbourhood conditions and self-rated health were larger, particularly in the rural population.

CONCLUSION

Research is needed to develop and test reliable measures of perceived neighbourhood conditions relevant to the health of rural populations.

Association of area socioeconomic status and breast, cervical, and colorectal cancer screening: a systematic review

BACKGROUND

Although numerous studies have examined the association of area socioeconomic status (SES) and cancer screening after controlling for individual SES, findings have been inconsistent. A systematic review of existing studies is timely to identify conceptual and methodologic limitations and to provide a basis for future research directions and policy.

OBJECTIVE

The objectives were to (a) describe the study designs, constructs, methods, and measures; (b) describe the independent association of area SES and cancer screening; and (c) identify neglected areas of research.

METHODS

We searched six electronic databases and manually searched cited and citing articles. Eligible studies were published before 2008 in peer-reviewed journals in English, represented primary data on individuals ages > or = 18 years from developed countries, and measured the association of area and individual SES with breast, cervical, or colorectal cancer screening.

RESULTS

Of 19 eligible studies, most measured breast cancer screening. Studies varied widely in research design, definitions, and measures of SES, cancer screening behaviors, and covariates. Eight employed multilevel logistic regression, whereas the remainder analyzed data with standard single-level logistic regression. The majority measured one or two indicators of area and individual SES; common indicators at both levels were poverty, income, and education. There was no consistent pattern in the association between area SES and cancer screening.

DISCUSSION

The gaps and conceptual and methodologic heterogeneity in the literature to date limit definitive conclusions about an underlying association between area SES and cancer screening. We identify five areas of research deserving greater attention in the literature.

Are obesity and physical activity clustered? A spatial analysis linked to residential density

The aim of this study was to examine spatial clustering of obesity and/or moderate physical activity and their relationship to a neighborhood's built environment. Data on levels of obesity and moderate physical activity were derived from the results of a telephone survey conducted in 2006, with 1,863 survey respondents in the study sample. This sample was spread across eight suburban neighborhoods in Metro Vancouver. These areas were selected to contrast residential density and income and do not constitute a random sample, but within each area, respondents were selected randomly. Obesity and moderate physical activity were mapped to determine levels of global and local spatial autocorrelation within the neighborhoods. Clustering was measured using Moran's I at the global level, Anselin's Local Moran's I at the local level, and geographically weighted regression (GWR). The global-level spatial analysis reveals no significant clustering for the attributes of obesity or moderate physical activity. Within individual neighborhoods, there is moderate clustering of obesity and/or physical activity but these clusters do not achieve statistical significance. In some neighborhoods, local clustering is restricted to a single pair of respondents with moderate physical activity. In other neighborhoods, any moderate local clustering is offset by negative local spatial autocorrelation. Importantly, there is no evidence of significant clustering for the attribute of obesity at either the global or local level of analysis. The GWR analysis fails to improve significantly upon the global model-thus reinforcing the negative results. Overall, the study indicates that the relationship between the urban environment and obesity is not direct.

Stress perception and commuting

This paper analyzes the determinants of the perceived stress level of workers with a special focus on the effects of commuting, while controlling for personal and work-related characteristics. Using ordered logistic regression we find that several dimensions of the commuting situation, such as impedance, control and predictability of commuting, significantly influence the perceived stress level. Therefore, stress and stress-related health problems should be taken into consideration when analyzing the economic costs of commuting.

Using tax parcels to select a location-based sample: an illustration that examines residents' awareness of sex offenders in neighborhoods

Social science research is increasingly considering place when examining social programs and policies with a spatial component. A specific research challenge involving spatial policies is how to select a sample of individuals based on their geographic locations. This article illustrates the use of geographic information systems, tax parcels, and mail surveys to target residents in varied geographic areas. A provided example demonstrates how researchers obtained a sample of respondents living within one tenth of a mile of multiple registered sex offenders. The challenges of using tax parcels to obtain addresses for apartments and mobile home parks are also explored.

Area deprivation and its association with health in a cross-sectional study: are the results biased by recent migration?

BACKGROUND

The association between area deprivation and health has mostly been examined in cross-sectional studies or prospective studies with short follow-up. These studies have rarely taken migration into account. This is a possible source of misclassification of exposure, i.e. an unknown number of study participants are attributed an exposure of area deprivation that they may have experienced too short for it to have any influence. The aim of this article was to examine to what extent associations between area deprivation and health outcomes were biased by recent migration.

METHODS

Based on data from the Oslo Health Study, a cross-sectional study conducted in 2000 in Oslo, Norway, we used six health outcomes (self rated health, mental health, coronary heart disease, chronic obstructive pulmonary disease, smoking and exercise) and considered migration nine years prior to the study conduct. Migration into Oslo, between the areas of Oslo, and the changes in area deprivation during the period were taken into account. Associations were investigated by multilevel logistic regression analyses.

RESULTS

After adjustment for individual socio-demographic variables we found significant associations between area deprivation and all health outcomes. Accounting for migration into Oslo and between areas of Oslo did not change these associations much. However, the people who migrated into Oslo were younger and had lower prevalences of unfavourable health outcomes than those who were already living in Oslo. But since they were evenly distributed across the area deprivation quintiles, they had little influence on the associations between area deprivation and health. Evidence of selective migration within Oslo was weak, as both moving up and down in the deprivation hierarchy was associated with significantly worse health than not moving.

CONCLUSION

We have documented significant associations between area deprivation and health outcomes in Oslo after adjustment for socio-demographic variables in a cross-sectional study. These associations were weakly biased by recent migration. From our results it still appears that migration prior to study conduct may be relevant to investigate even within a relatively short period of time, whereas changes in area deprivation during such a period is of limited interest.

Understanding and representing 'place' in health research: a relational approach

Epidemiology, sociology, and geography have been successful in re-establishing interest in the role of place in shaping health and health inequalities. However, some of the relevant empirical research has relied on rather conventional conceptions of space and place and focused on isolating the "independent" contribution of place-level and individual-level factors. This approach may have resulted in an underestimate of the contribution of 'place' to disease risk. In this paper we argue the case for extensive (quantitative) as well as intensive (qualitative) empirical, as well as theoretical, research on health variation that incorporates 'relational', views of space and place. Specifically, we argue that research in place and health should avoid the false dualism of context and composition by recognising that there is a mutually reinforcing and reciprocal relationship between people and place. We explore in the discussion how these theoretical perspectives are beginning to influence empirical research. We argue that these approaches to understanding how place relates to health are important in order to deliver effective, 'contextually sensitive' policy interventions.

The effect of adverse housing and neighborhood conditions on the development of diabetes mellitus among middle-aged African Americans

The authors examined the associations of observed neighborhood (block face) and housing conditions with the incidence of diabetes by using data from 644 subjects in the African-American Health Study (St. Louis area, Missouri). They also investigated five mediating pathways (health behavior, psychosocial, health status, access to medical care, and sociodemographic characteristics) if significant associations were identified. The external appearance of the block the subjects lived on and housing conditions were rated as excellent, good, fair, or poor. Subjects reported about neighborhood desirability. Self-reported diabetes was obtained at baseline and 3 years later. Of 644 subjects without self-reported diabetes, 10.3% reported having diabetes at the 3-year follow-up. Every housing condition rated as fair-poor was associated with an increased risk of diabetes, with odds ratios ranging from 2.53 (95% confidence interval: 1.47, 4.34 for physical condition inside the building) to 1.78 (95% confidence interval: 1.03, 3.07 for cleanliness inside the building) in unadjusted analyses. No association was found between any of the block face conditions or perceived neighborhood conditions and incident diabetes. The odds ratios for the five housing conditions were unaffected when adjusted for the mediating pathways. Poor housing conditions appear to be an independent contributor to the risk of incident diabetes in urban, middle-aged African Americans.

Traumatic events and posttraumatic stress in cross-cultural mission assignments

In addition to cross-cultural and environmental stressors, aid workers and missionaries are frequently exposed to trauma. We explored the frequency of traumatic events, their mental health impact, and factors associated with posttraumatic stress in two groups of missionaries, one representing a predominantly stable setting (Europe) and the other an unstable setting (West Africa). The 256 participants completed self-report measures assessing lifetime traumatic events, current posttraumatic stress, depressive and anxiety symptoms, resilience, and functioning. The rate of traumatic events was significantly higher in the unstable setting. More-frequent traumatic events were associated with higher posttraumatic stress. Factors associated with the severity of posttraumatic stress were depression, functional impairment, subjective severity and number of traumatic events, and the level of resilience.

The importance of social context: neighborhood stressors, stress-buffering mechanisms, and alcohol, drug, and mental health disorders

This study examines the relationship among neighborhood stressors, stress-buffering mechanisms, and likelihood of alcohol, drug, and mental health (ADM) disorders in adults from 60 US communities (n=12,716). Research shows that larger support structures may interact with individual support factors to affect mental health, but few studies have explored buffering effects of these neighborhood characteristics. We test a conceptual model that explores effects of neighborhood stressors and stress-buffering mechanisms on ADM disorders. Using Health Care for Communities with census and other data, we found a lower likelihood of disorders in neighborhoods with a greater presence of stress-buffering mechanisms. Higher neighborhood average household occupancy and churches per capita were associated with a lower likelihood of disorders. Cross-level interactions revealed that violence-exposed individuals in high crime neighborhoods are vulnerable to depressive/anxiety disorders. Likewise, individuals with low social support in neighborhoods with high social isolation (i.e., low-average household occupancy) had a higher likelihood of disorders. If replicated by future studies using longitudinal data, our results have implications for policies and programs targeting neighborhoods to reduce ADM disorders.

Geographic clustering of adequate diagnostic follow-up after abnormal screening results for breast cancer among low-income women in Missouri

PURPOSE

In an effort to examine a cluster of late-stage breast cancer, this study reports (1) the extent of geographic variation in adequacy of diagnostic follow-up (ADFU) after abnormal breast cancer screening results across Missouri's counties and census tracts, (2) whether various personal characteristics or area poverty account for any geographic clustering observed, and (3) the association between area poverty rate and ADFU.

METHODS

We used 1998-2002 Missouri Show Me Healthy Women breast and cervical cancer program data from 2580 low-income women aged 50-64 who had abnormal breast cancer screening results. ADFU was based on established guidelines. Poverty rate was from the 2000 census data. We used 3 complementary statistical approaches.

RESULTS

Overall, 26.9% of screening results were inadequately followed up. County-level geographic variation accounted for 6.7% of the total variance in ADFU, while the census-tract-level variation was negligible. Women's sociodemographic characteristics, symptoms reported at time of screening, and screening results accounted for 25% of the county-level variation in ADFU. Statistically significant geographic variation in ADFU remained that could not be explained. Beyond 70 miles from the women's residence, the likelihood of receiving ADFU was geographically uncorrelated. We identified one large geographic cluster extending beyond the borders of counties and census tracts where women were less likely to receive ADFU (relative risk = 0.64; p = 0.01).

CONCLUSIONS

Efforts to improve the likelihood of ADFU should be directed at examining the relative contributions of the healthcare and social environments and characteristics of the women in the area where women were less likely to receive ADFU especially in the cluster area of late-stage breast cancer rather than targeting efforts at the county or census-tract level.

Neighbourhood environment and the incidence of depressive symptoms among middle-aged African Americans

AIM

To investigate the association between attributes of subject location and incidence of clinically relevant levels of depressive symptoms (CRLDS), and to investigate whether an association remained after adjusting for individual-level factors using data from the population-based African American Health Study.

METHODS

An 11-item depression scale (Center for Epidemiologic Studies Depression scale) was obtained at baseline and 3 years later through in-home evaluations. Census tract and block group deprivation indices were obtained from the 2000 census. The external appearance of the block where the subject lived was rated during sample enumeration, and the interior and exterior of the subject's dwelling were observed during the initial in-home interview.

RESULTS

Of 998 subjects at baseline, 21.1% had CRLDS. Although 12.7% of the 672 people without CRLDS at baseline developed them by the 3-year follow-up, univariate and propensity-adjusted analyses revealed no association between the subject's location and the incidence of CRLDS. Sensitivity analyses confirmed the robustness of the findings.

CONCLUSION

Despite other studies showing independent effects of neighbourhood characteristics on the prevalence of CRLDS, attributes of subject location are not independent contributors to the incidence of CRLDS in middle-aged urban African Americans.

Measuring the neighbourhood using UK benefits data: a multilevel analysis of mental health status

BACKGROUND

Evidence from multilevel research investigating whether the places where people live influence their mental health remains inconclusive. The objectives of this study are to derive small area-level, or contextual, measures of the local social environment using benefits data from the Department of Work and Pensions (DWP) and to investigate whether (1) the mental health status of individuals is associated with contextual measures of low income, economic inactivity, and disability, after adjusting for personal risk factors for poor mental health, (2) the associations between mental health and context vary significantly between different population sub-groups, and (3) to compare the effect of the contextual benefits measures with the Townsend area deprivation score.

METHODS

Data from the Welsh Health Survey 1998 were analysed in Normal response multilevel models of 24,975 individuals aged 17 to 74 years living within 833 wards and 22 unitary authorities in Wales. The mental health outcome measure was the Mental Health Inventory (MHI-5) of the Short Form 36 health status questionnaire. The benefits data available were the means tested Income Support and Income-based Job Seekers Allowance, and the non-means tested Incapacity Benefit, Severe Disablement Allowance, Disability Living Allowance and Attendance Allowance. Indirectly age-standardised census ward ratios were calculated to model as the contextual measures.

RESULTS

Each contextual variable was significantly associated with individual mental health after adjusting for individual risk factors, so that living in a ward with high levels of claimants was associated with worse mental health. The non-means tested benefits that were proxy measures of economic inactivity from permanent sickness or disability showed stronger associations with individual mental health than the means tested benefits and the Townsend score. All contextual effects were significantly stronger in people who were economically inactive and unavailable for work.

CONCLUSION

This study provides evidence for substantive contextual effects on mental health, and in particular the importance of small-area levels of economic inactivity and disability. DWP benefits data offer a more specific measure of local neighbourhood than generic deprivation indices and offer a starting point to hypothesise possible causal pathways to individual mental health status.