The impact of area deprivation on differences in health: does the choice of the geographical classification matter?

Multilevel Social Determinants of Patient-Reported Outcomes in Young Survivors of Childhood Cancer

In this study, the social determinants of patient-reported outcomes (PROs) in young survivors of childhood cancer aged <18 years are researched. This cross-sectional study investigated social determinants associated with poor PROs among young childhood cancer survivors. We included 293 dyads of survivors receiving treatment at St. Jude Children's Research Hospital who were <18 years of age during follow-up from 2017 to 2018 and their primary caregivers. Social determinants included family factors (caregiver-reported PROs, family dynamics) and county-level deprivation (socioeconomic status, physical environment via the County Health Rankings & Roadmaps). PROMIS measures assessed survivors' and caregivers' PROs. General linear regression tested associations of social determinants with survivors' PROs. We found that caregivers' higher anxiety was significantly associated with survivors' poorer depression, stress, fatigue, sleep issues, and reduced positive affect (p < 0.05); caregivers' sleep disturbances were significantly associated with lower mobility in survivors (p < 0.05). Family conflicts were associated with survivors' sleep problems (p < 0.05). Residing in socioeconomically deprived areas was significantly associated with survivors' poorer sleep quality (p < 0.05), while higher physical environment deprivation was associated with survivors' higher psychological stress and fatigue and lower positive affect and mobility (p < 0.05). Parental, family, and neighborhood factors are critical influences on young survivors' quality of life and well-being and represent new intervention targets.

Mapping the prevalence of cancer risk factors at the small area level in Australia

BACKGROUND

Cancer is a significant health issue globally and it is well known that cancer risk varies geographically. However in many countries there are no small area-level data on cancer risk factors with high resolution and complete reach, which hinders the development of targeted prevention strategies.

METHODS

Using Australia as a case study, the 2017-2018 National Health Survey was used to generate prevalence estimates for 2221 small areas across Australia for eight cancer risk factor measures covering smoking, alcohol, physical activity, diet and weight. Utilising a recently developed Bayesian two-stage small area estimation methodology, the model incorporated survey-only covariates, spatial smoothing and hierarchical modelling techniques, along with a vast array of small area-level auxiliary data, including census, remoteness, and socioeconomic data. The models borrowed strength from previously published cancer risk estimates provided by the Social Health Atlases of Australia. Estimates were internally and externally validated.

RESULTS

We illustrated that in 2017-2018 health behaviours across Australia exhibited more spatial disparities than previously realised by improving the reach and resolution of formerly published cancer risk factors. The derived estimates revealed higher prevalence of unhealthy behaviours in more remote areas, and areas of lower socioeconomic status; a trend that aligned well with previous work.

CONCLUSIONS

Our study addresses the gaps in small area level cancer risk factor estimates in Australia. The new estimates provide improved spatial resolution and reach and will enable more targeted cancer prevention strategies at the small area level. Furthermore, by including the results in the next release of the Australian Cancer Atlas, which currently provides small area level estimates of cancer incidence and relative survival, this work will help to provide a more comprehensive picture of cancer in Australia by supporting policy makers, researchers, and the general public in understanding the spatial distribution of cancer risk factors. The methodology applied in this work is generalisable to other small area estimation applications and has been shown to perform well when the survey data are sparse.

People living in disadvantaged areas faced greater challenges in staying active and using recreational facilities during the COVID-19 pandemic

This study aimed to understand the perceived effects of the COVID-19 pandemic on physical activity, recreation walking, and use of recreational facilities; and if the COVID-19 pandemic amplified disparities in physical activity, recreational walking, and use of recreational facilities related to the levels of neighborhood disadvantage. Recreational walking and the use of neighborhood streets and green spaces significantly decreased in high deprivation areas but not in low deprivation areas during the pandemic. While COVID-19 has negatively affected overall recreational activities, the inequitable impact on recreational walking and use of outdoor recreational facilities has been more evident in disadvantaged neighborhoods with greater deprivation.

Neighbourhood Social Determinants of Health and Geographical Inequalities in Premature Mortality in Taiwan: A Spatiotemporal Approach

Geographical inequalities in premature mortality and the role of neighbourhood social determinants of health (SDOH) have been less explored. This study aims to assess the geographical inequalities in premature mortality in Taiwan and how neighbourhood SDOH contribute to them and to examine the place-specific associations between neighbourhood SDOH and premature mortality. We used township-level nationwide data for the years 2015 to 2019, including age-standardized premature mortality rates and three upstream SDOH (ethnicity, education, and income). Space-time scan statistics were used to assess the geographical inequality in premature mortality. A geographical and temporal weighted regression was applied to assess spatial heterogeneity and how neighbourhood SDOH contribute to geographic variation in premature mortality. We found geographical inequality in premature mortality to be clearly clustered around mountainous rural and indigenous areas. The association between neighbourhood SDOH and premature mortality was shown to be area-specific. Ethnicity and education could explain nearly 84% variation in premature mortality. After adjusting for neighbourhood SDOH, only a handful of hotspots for premature mortality remained, mainly consisting of rural and indigenous areas in the central-south region of Taiwan. These findings provide empirical evidence for developing locally tailored public health programs for geographical priority areas.

Association between community deprivation and practising health behaviours among South Korean adults: a survey-based cross-sectional study

OBJECTIVES

This study aimed to determine the association between community deprivation and poor health behaviours among South Korean adults.

DESIGN

This was a survey-based cross-sectional study.

SETTING AND PARTICIPANTS

Data of 224 552 participants from 244 communities were collected from the Korea Community Health Survey, conducted in 2015.

PRIMARY AND SECONDARY OUTCOME MEASURES

We defined health behaviours by combining three variables: not smoking, not high-risk drinking and walking frequently. Community deprivation was classified into social and economic deprivation.

RESULTS

Multilevel logistic analysis was conducted to determine the association of poor health behaviours through a hierarchical model (individual and community) for the 224 552 participants. Among them, 69.9% did not practice healthy behaviours. We found that a higher level of deprivation index was significantly associated with higher odds of not-practising healthy behaviours (Q3, OR: 1.15, 95% CI: 1.00 to 1.31; Q4 (highest), OR: 1.22, 95% CI: 1.06 to 1.39). Economic deprivation had a positive association with not-practising health behaviours while social deprivation had a negative association.

CONCLUSION

These findings imply that community deprivation levels may influence individual health behaviours. Accordingly, there is a need for enforcing the role of primary healthcare centres in encouraging a healthy lifestyle among the residents in their communities, developing national health policy guidelines for health equity and providing financial help to people experiencing community deprivation.

Health Inequalities During COVID-19 and Their Effects on Morbidity and Mortality

Inequalities in health have existed for many decades and have led to unjust consequences in morbidity and mortality. These have become even more apparent during the COVID-19 pandemic with individuals from black and minority ethnic groups, poorer socioeconomic backgrounds, urban and rurally deprived locations, and vulnerable groups of society suffering the full force of its effects. This review is highlighting the current disparities that exist within different societies, that subsequently demonstrate COVID-19, does in fact, discriminate against disadvantaged individuals. Also explored in detail are the measures that can and should be taken to improve equality and provide equitable distribution of healthcare resources amongst underprivileged communities.

Bayesian spatial modelling of early childhood development in Australian regions

Background

Children’s early development plays a vital role for maintaining healthy lives and influences future outcomes. It is also heavily affected by community factors which vary geographically. Direct methods do not provide a comprehensive picture of this variation, especially for areas with sparse populations and low data coverage. In the context of Australia, the Australian Early Development Census (AEDC) provides a measure of early child development upon school entry. There are two primary aims of this study: (i) provide improved prevalence estimates of children who are considered as developmentally vulnerable in regions across Australia; (ii) ascertain how social-economic disadvantage partly explains the spatial variation.

Methods

We used Bayesian spatial hierarchical models with the Socio-economic Indexes for Areas (SEIFA) as a covariate to provide improved estimates of all 335 SA3 regions in Australia. The study included 308,953 children involved in the 2018 AEDC where 21.7% of them were considered to be developmentally vulnerable in at least one domain. There are five domains of developmental vulnerability—physical health and wellbeing; social competence; emotional maturity; language and cognitive skills; and communication and general knowledge.

Results

There are significant improvements in estimation of the prevalence of developmental vulnerability through incorporating the socio-economic disadvantage in an area. These improvements persist in all five domains—the largest improvements occurred in the Language and Cognitive Skills domain. In addition, our results reveal that there is an important geographical dimension to developmental vulnerability in Australia.

Conclusion

Sparsely populated areas in sample surveys lead to unreliable direct estimates of the relatively small prevalence of child vulnerability. Bayesian spatial modelling can account for the spatial patterns in childhood vulnerability while including the impact of socio-economic disadvantage on geographic variation. Further investigation, using a broader range of covariates, could shed more light on explaining this spatial variation.

Neighbourhood greenspace influences on childhood obesity in Sheffield, UK

BACKGROUND

One cause of childhood obesity is a reduction in the amount of unstructured time spent outdoors, resulting in less physical activity. Greenspaces have the potential to increase children's physical activity levels, so it is desirable to understand how to create spaces that promote visitation and activity.

OBJECTIVES

We investigate the relationship between rates of obesity at ages 4 to 5 and 10 to 11 in small-area census geographies, and indicators of the neighbourhood greenspace environment, in the northern English city of Sheffield.

METHODS

To capture the environment at scales relevant to children, we test the importance of overall green cover; garden size; tree density around residential addresses; and accessibility within 300 m of any greenspace, greenspaces that meet quality criteria, and greenspaces with play facilities. We use a multimodel inference approach to improve robustness.

RESULTS

The density of trees around addresses is significant at both ages, indicating the importance of the greenspace environment in the immediate vicinity of houses. For 10 to 11 year olds, accessibility of greenspaces meeting quality criteria is also significant, highlighting that the wider environment becomes important with age and independence.

CONCLUSIONS

More attention should be given to children's requirements of greenspace when considering interventions to increase physical activity or planning new residential areas.

The role of individual, household, and area of residence factors on self-rated health in Colombian adults: A multilevel study

Introduction:

Self-rated health is strongly associated with morbidity and mortality. It is largely influenced by individual factors but also by individuals’ social surroundings and environment.

Objective:

To investigate individual, household, and locality factors associated with self- rated health in Colombian adults.

Materials and methods:

We conducted a cross-sectional multilevel study using data from national databases on 19 urban localities and 37,352 individuals nested within 15,788 households using a population-based survey. Given the natural hierarchical structure of the data, the estimates of self-rated health related to individual, household, and locality characteristics were obtained by fitting a three-level logistic regression.

Results:

The adjusted multilevel logistic models showed that at individual level, higher odds of poor self-rated health were found among older adults, persons from low socio-economic status, those living without a partner, with no regular physical activity, and reporting morbidities. At the household level, poor self-rated health was associated with households of low socioeconomic status located near noise sources and factories and in polluted and insecure areas. At the locality level, only poverty was associated with poor self-rated health after adjusting for individual and household variables.

Conclusions:

These results highlight the need for a more integrated framework when designing and implementing strategies and programs that aim to improve health conditions in urban populations in Latin America.

Income inequality and psychological distress at neighbourhood and municipality level: An analysis in the Netherlands

This study examines the associations between income inequality at neighbourhood and municipality level and psychological distress in a country with a relatively low income inequality, the Netherlands. Multilevel linear regression analyses were used to investigate associations between income inequality and mean income at the neighbourhood (n = 7803) and municipality (n = 406) level and psychological distress (scale range 10-50), in a country-wide sample of 343,327 individuals, adjusted for gender, age, ethnicity, marital status, education and household income. No significant association was found between neighbourhood income inequality and psychological distress after adjustment for individual and neighbourhood level confounding. However, a higher neighbourhood income inequality in neighbourhoods with the middle to highest mean neighbourhood incomes was associated with more psychological distress. Individuals living in municipalities with the highest income inequality reported 2.5% higher psychological distress compared to those living in municipalities with the lowest income inequality. Income inequality seems to matter more for mental health at the municipality than neighbourhood level.

The challenges of recruiting cancer patient/caregiver dyads: informing randomized controlled trials

Background

Family members are increasingly involved in the care of cancer patients, however many are not prepared for this challenging role. Intervention-based studies are valuable to inform the most appropriate and effective support for caregivers. Barriers in the recruitment of patient/caregiver dyads exist but the reasons for non-participation are less well understood. This analysis determined the factors associated with participation in a randomized controlled trial involving patient/caregiver dyads, reasons for non-participation and factors associated with these reasons.

Methods

Patients with any type of cancer (other than non-melanoma skin cancer), and their caregiver were recruited at four Australian health services. Eligible patients were invited to participate together with their caregiver (N = 737). Non-participation data were collected from non-participants. Bivariate and binary logistic regression analyses were conducted to examine factors associated with participation.

Results

Of the 737 eligible dyads, 521 (71%) declined participation. Dyad characteristics associated with participation were caregiver gender, patient treatment modality and hospital type. The odds for participating were almost two times greater for female than male caregivers (p = 0.005); 13 times greater for patients receiving chemoradiotherapy compared to radiotherapy alone (p < 0.001); and three times greater for dyads attending a private versus public hospital (p < 0.001). Reasons for non-participation were lack of interest (33%), lack of time (29%), not requiring support (23%), too burdensome (15%); factors significantly associated with these reasons were treatment modality, patient age, cancer type, and hospital type. Patients diagnosed with prostate cancer and receiving chemotherapy alone were less likely to decline due to a lack of interest. Patients more likely to decline due to lack of time were those aged 40–59 years and receiving chemotherapy alone. Patients who were more likely to decline because they felt participation was too burdensome were those attending a private hospital for treatment.

Conclusions

To optimize recruitment, it is recommended that special attention is given to different cancer types and treatment modalities, gender and age. Approaching dyads at varied time points when their need for support is high is recommended. This analysis provides important information for researchers undertaking randomized controlled trials involving people diagnosed with cancer and their caregivers.

Rural dwellers are less likely to survive cancer - An international review and meta-analysis

BACKGROUND

Existing research from several countries has suggested that rural-dwellers may have poorer cancer survival than urban-dwellers. However, to date, the global literature has not been systematically reviewed to determine whether a rural cancer survival disadvantage is a global phenomenon.

METHODS

Medline, CINAHL, and EMBASE were searched for studies comparing rural and urban cancer survival. At least two authors independently screened and selected studies. We included epidemiological studies comparing cancer survival between urban and rural residents (however defined) that also took socioeconomic status into account. A meta-analysis was conducted using 11 studies with binary rural:urban classifications to determine the magnitude and direction of the association between rurality and differences in cancer survival. The mechanisms for urban-rural cancer survival differences reported were narratively synthesised in all 39 studies.

FINDINGS

39 studies were included in this review. All were retrospective observational studies conducted in developed countries. Rural-dwellers were significantly more likely to die when they developed cancer compared to urban-dwellers (HR 1.05 (95% CI 1.02 - 1.07). Potential mechanisms were aggregated into an ecological model under the following themes: Patient Level Characteristics; Institutions; Community, Culture and Environment; Policy and Service Organization.

INTERPRETATION

Rural residents were 5% less likely to survive cancer. This effect was consistently observed across studies conducted in various geographical regions and using multiple definitions of rurality. High quality mixed-methods research is required to comprehensively evaluate the underlying factors. We have proposed an ecological model to provide a coherent framework for future explanatory research.

FUNDING

None.

The relationship of neighbourhood-level material and social deprivation with health-related quality of life

PURPOSE

To examine the relationship of neighbourhood-level material and social deprivation with health-related quality of life, measured by the EQ-5D-5L, in the general adult population.

METHODS

A sample of 11,835 adults living in Alberta, Canada was drawn from three combined annual Health Quality Council of Alberta Satisfaction and Experiences with Health Care Services surveys from 2012 to 2016. Neighbourhood-level material and social deprivation indices were derived using the Pampalon index and the 2006 Canadian census. The EQ-5D-5L dimensions, index and VAS scores were compared across the deprivation indices quintiles in the overall sample and by participants' sub-groups. Differences were tested using ANOVA or Chi-square test as appropriate. Multivariate linear regression models were conducted to examine the independent association of material and social deprivation with the EQ-5D-5L index and VAS scores, and multinomial logistic regression models with each of the EQ-5D-5L dimensions.

RESULTS

Respondents in higher material or social deprivation categories had lower EQ-5D-5L index and VAS scores than those in the least deprived categories. Additionally, respondents with higher material deprivation were more likely to report problems on mobility, usual activities, and pain/discomfort; those with higher social deprivation were more likely to report problems on mobility, self-care, usual activities, and anxiety/depression.

CONCLUSION

Higher neighbourhood-level material and social deprivation is significantly associated with lower health-related quality of life in the general adult population. Examining the factors leading to this inequity in health between individuals living in the least and most deprived neighbourhoods is imperative to mitigating these inequities.

Postnatal screening and care for non-medical risk factors by preventive child healthcare in deprived and non-deprived neighbourhoods

Background

Children born in families with non-medical risk factors, such as deprivation, have higher odds of preterm birth (< 37 weeks of gestation) or being born small for gestational age (birth weight < 10th percentile). In addition, growing up they are at risk for growth and developmental problems. Preventive Child Healthcare (PCHC) monitors growth and development of babies and children. Early identification of children at risk could result in early interventions to prevent growth and developmental problems in later life. Therefore, we aimed to assess current practices in postnatal risk screening and care for non-medical risk factors and the collaboration with other healthcare professionals, in both deprived and non-deprived neighbourhoods in the Netherlands.

Methods

Eight out of ten invited PCHC organisations, from different areas in the Netherlands, consented to participate in this study. A questionnaire was designed and digitally distributed to professionals working at these organisations, where 370 physicians and nurses were employed. Data was collected between June and September 2016. Descriptive statistics, chi square tests and t-tests were applied.

Results

Eighty-nine questionnaires were eligible for analyses. Twenty percent of the respondents were working in a deprived neighbourhood and 70.8% of the respondents were employed as nurse. Most of them performed screening for non-medical risk factors in at least 50% of their consultations. PCHC professionals working in deprived neighbourhoods encountered significantly more often families with non-medical risk factors and experienced significantly more communication problems than their colleagues working in non-deprived neighbourhoods. 48.2% of the respondents were satisfied with the current form of postnatal risk screening in their organisation, whereas 41.2% felt a need for a structured postnatal risk assessment. Intensified collaboration is preferred with district-teams, general practitioners and midwifes, concerning clients with non-medical risk factors.

Conclusion

This study shows that postnatal screening for non-medical risk factors is part of current PCHC practice, regardless the neighbourhood status they are deployed. PCHC professionals consider screening for non-medical risk factors as their responsibility. Consequently, they felt a need for a structured postnatal risk assessment and for an intensified collaboration with other healthcare professionals.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3243-2) contains supplementary material, which is available to authorized users.

Are area-level and individual-level socioeconomic factors associated with self-rated health in adult urban citizens? Evidence from Slovak and Dutch cities

Background

Evidence shows that living in disadvantaged areas is associated with poor health. This may be due to the socioeconomic (SE) characteristics of both these residents and the areas where they live. Evidence regarding this on Central European (CE) countries is scarce. Our aim was to assess whether the prevalence of poor self-rated health (SRH) was higher in deprived urban areas, whether this can be explained by individual SE status (SES) and whether this differed between Slovakia and the Netherlands per age group. We examined the association of urban-level data and individual-level SE factors from different urban areas in different countries (Slovakia, the Netherlands) using comparable urban health indicators and area indicators. We also obtained unique data from the EU-FP7 EURO-URHIS 2 project. Multilevel logistic regression showed that poor SRH was associated with area deprivation in both countries. Regarding age by country, poor SRH occurred more frequently in the more deprived areas for the younger age group (≤64) in the Netherlands but for the older age group (≥65 years) in Slovakia. Moreover, Slovak citizens reported poor SRH significantly more often than Dutch residents. Individual SES was significantly associated with poor SRH in both age groups and both countries for most area-level SE measures. Individual SES is associated with SRH more strongly than area deprivation. Therefore, it is important to account for relative deprivation at an individual level when considering health-enhancing activities. Moreover, the effect of urban-area deprivation seems to differ between CE and WE countries.

Spatial Variability of Geriatric Depression Risk in a High-Density City: A Data-Driven Socio-Environmental Vulnerability Mapping Approach

Previous studies found a relationship between geriatric depression and social deprivation. However, most studies did not include environmental factors in the statistical models, introducing a bias to estimate geriatric depression risk because the urban environment was found to have significant associations with mental health. We developed a cross-sectional study with a binomial logistic regression to examine the geriatric depression risk of a high-density city based on five social vulnerability factors and four environmental measures. We constructed a socio-environmental vulnerability index by including the significant variables to map the geriatric depression risk in Hong Kong, a high-density city characterized by compact urban environment and high-rise buildings. Crude and adjusted odds ratios (ORs) of the variables were significantly different, indicating that both social and environmental variables should be included as confounding factors. For the comprehensive model controlled by all confounding factors, older adults who were of lower education had the highest geriatric depression risks (OR: 1.60 (1.21, 2.12)). Higher percentage of residential area and greater variation in building height within the neighborhood also contributed to geriatric depression risk in Hong Kong, while average building height had negative association with geriatric depression risk. In addition, the socio-environmental vulnerability index showed that higher scores were associated with higher geriatric depression risk at neighborhood scale. The results of mapping and cross-section model suggested that geriatric depression risk was associated with a compact living environment with low socio-economic conditions in historical urban areas in Hong Kong. In conclusion, our study found a significant difference in geriatric depression risk between unadjusted and adjusted models, suggesting the importance of including environmental factors in estimating geriatric depression risk. We also developed a framework to map geriatric depression risk across a city, which can be used for identifying neighborhoods with higher risk for public health surveillance and sustainable urban planning.

Ethnic inequalities in psychological distress among urban residents in the Netherlands: A moderating role of neighborhood ethnic diversity?

The main purpose of this study was to investigate whether neighborhood ethnic diversity moderated the association between ethnicity and psychological distress in the four largest cities of Netherlands. Multilevel linear regression analysis was used to assess whether the association between ethnicity and psychological distress differed by levels of neighborhood ethnic diversity. Results showed that the Turkish and Moroccan residents reported significantly higher psychological distress than native Dutch and Surinamese residents. In high ethnic diverse neighborhoods Turkish residents reported significantly less psychological distress than in low ethnic diverse neighborhoods. Ethnic diversity amplifies the risk of depression for some but not all ethnic minorities.

Contacts of general practitioners with illegal immigrants

Aims: Violence and economic hardship cause many people to go to industrialized countries, often without obtaining a residence permit. The aim of this study is to gain insight into the factors that determine the occurrence of contacts in primary health care with such illegal immigrants. Methods: Data were analysed on contacts with illegal immigrants from a national survey among Dutch general practitioners (GPs) ( n= 1,148; response: 62%). Results: GPs reported that they have on average 0.74 patient contacts with an illegal immigrant per week (95% CI: 0.56-0.92) . This probably includes some over-reporting. Contacts are more likely in practices and communities that comprise more non-Dutch-born people and more (patients with) typically urban health problems. Working experience and demography of the GP are not independently associated with the occurrence of contacts. Conclusions: Contacts of Dutch GPs with illegal immigrants mostly occur in the deprived areas of the big cities.

Impact of geographic area level on measuring socioeconomic disparities in cancer survival in New South Wales, Australia: A period analysis

BACKGROUND

Area-based socioeconomic measures are widely used in health research. In theory, the larger the area used the more individual misclassification is introduced, thus biasing the association between such area level measures and health outcomes. In this study, we examined the socioeconomic disparities in cancer survival using two geographic area-based measures to see if the size of the area matters.

METHODS

We used population-based cancer registry data for patients diagnosed with one of 10 major cancers in New South Wales (NSW), Australia during 2004-2008. Patients were assigned index measures of socioeconomic status (SES) based on two area-level units, census Collection District (CD) and Local Government Area (LGA) of their address at diagnosis. Five-year relative survival was estimated using the period approach for patients alive during 2004-2008, for each socioeconomic quintile at each area-level for each cancer. Poisson-regression modelling was used to adjust for socioeconomic quintile, sex, age-group at diagnosis and disease stage at diagnosis. The relative excess risk of death (RER) by socioeconomic quintile derived from this modelling was compared between area-units.

RESULTS

We found extensive disagreement in SES classification between CD and LGA levels across all socioeconomic quintiles, particularly for more disadvantaged groups. In general, more disadvantaged patients had significantly lower survival than the least disadvantaged group for both CD and LGA classifications. The socioeconomic survival disparities detected by CD classification were larger than those detected by LGA. Adjusted RER estimates by SES were similar for most cancers when measured at both area levels.

CONCLUSIONS

We found that classifying patient SES by the widely used Australian geographic unit LGA results in underestimation of survival disparities for several cancers compared to when SES is classified at the geographically smaller CD level. Despite this, our RER of death estimates derived from these survival estimates were generally similar for both CD and LGA level analyses, suggesting that LGAs remain a valuable spatial unit for use in Australian health and social research, though the potential for misclassification must be considered when interpreting research. While data confidentiality concerns increase with the level of geographical precision, the use of smaller area-level health and census data in the future, with appropriate allowance for confidentiality.

Neighborhood deprivation and maternal psychological distress during pregnancy: a multilevel analysis

Maternal psychosocial distress is conceptualized as an important factor underlying the association between neighborhood deprivation and pregnancy outcomes. However, empirical studies to examine effects of neighborhood deprivation on psychosocial distress during pregnancy are scant. Based on a large multicenter cohort of pregnant women in Montreal, we examined (1) the extent to which psychosocial distress is clustered at the neighborhood-level, (2) the extent to which the clustering is explained by neighborhood material or social deprivation, and (3) whether associations between neighborhood deprivation and psychosocial distress persist after accounting for neighborhood composition (individual-level characteristics) using multilevel analyses. For 5,218 women residing in 740 neighborhoods, a prenatal interview at 24-26 gestational weeks measured both general and pregnancy-related psychological distress using well-validated scales: perceived stress, social support, depressive symptoms, optimism, commitment to the pregnancy, pregnancy-related anxiety, and maternal locus-of-control. Neighborhood deprivation indices were linked to study participants by their residential postal code. Neighborhood-level clustering (intraclass correlation) ranged from 1 to 2 % for perceived stress (lowest), optimism, pregnancy-related anxiety, and commitment to pregnancy to 4-6 % for perceived social support, depressive symptoms, and maternal locus of control (highest). Neighborhood material deprivation explained far more of the clustering (23-75 %) than did social deprivation (no more than 4 %). Although both material and social deprivation were associated with psychological distress in unadjusted analyses, the associations disappeared after accounting for individual-level socioeconomic characteristics. Our results highlight the importance of accounting for individual-level socioeconomic characteristics in studies of potential neighborhood effects on maternal mental health.

Scale effects in food environment research: Implications from assessing socioeconomic dimensions of supermarket accessibility in an eight-county region of South Carolina

Choice of neighborhood scale affects associations between environmental attributes and health-related outcomes. This phenomenon, a part of the modifiable areal unit problem, has been described fully in geography but not as it relates to food environment research. Using two administrative-based geographic boundaries (census tracts and block groups), supermarket geographic measures (density, cumulative opportunity and distance to nearest) were created to examine differences by scale and associations between three common U.S. Census-based socioeconomic status (SES) characteristics (median household income, percentage of population living below poverty and percentage of population with at least a high school education) and a summary neighborhood SES z-score in an eight-county region of South Carolina. General linear mixed-models were used. Overall, both supermarket density and cumulative opportunity were higher when using census tract boundaries compared to block groups. In analytic models, higher median household income was significantly associated with lower neighborhood supermarket density and lower cumulative opportunity using either the census tract or block group boundaries, and neighborhood poverty was positively associated with supermarket density and cumulative opportunity. Both median household income and percent high school education were positively associated with distance to nearest supermarket using either boundary definition, whereas neighborhood poverty had an inverse association. Findings from this study support the premise that supermarket measures can differ by choice of geographic scale and can influence associations between measures. Researchers should consider the most appropriate geographic scale carefully when conducting food environment studies.

Socioeconomic differentials in the immediate mortality effects of the national Irish smoking ban

BACKGROUND

Consistent evidence has demonstrated that smoking ban policies save lives, but impacts on health inequalities are uncertain as few studies have assessed post-ban effects by socioeconomic status (SES) and findings have been inconsistent. The aim of this study was to assess the effects of the national Irish smoking ban on ischemic heart disease (IHD), stroke, and chronic obstructive pulmonary disease (COPD) mortality by discrete and composite SES indicators to determine impacts on inequalities.

METHODS

Census data were used to assign frequencies of structural and material SES indicators to 34 local authorities across Ireland with a 2000-2010 study period. Discrete indicators were jointly analysed through principal component analysis to generate a composite index, with sensitivity analyses conducted by varying the included indicators. Poisson regression with interrupted time-series analysis was conducted to examine monthly age and gender-standardised mortality rates in the Irish population, ages ≥35 years, stratified by tertiles of SES indicators. All models were adjusted for time trend, season, influenza, and smoking prevalence.

RESULTS

Post-ban mortality reductions by structural SES indicators were concentrated in the most deprived tertile for all causes of death, while reductions by material SES indicators were more equitable across SES tertiles. The composite indices mirrored the results of the discrete indicators, demonstrating that post-ban mortality decreases were either greater or similar in the most deprived when compared to the least deprived for all causes of death.

CONCLUSIONS

Overall findings indicated that the national Irish smoking ban reduced inequalities in smoking-related mortality. Due to the higher rates of smoking-related mortality in the most deprived group, even equitable reductions across SES tertiles resulted in decreases in inequalities. The choice of SES indicator was influential in the measurement of effects, underscoring that a differentiated analytical approach aided in understanding the complexities in which structural and material factors influence mortality.

Health-risk behaviours in deprived urban neighbourhoods: a comparison between Slovak and Dutch cities

OBJECTIVES

International comparisons of the associations of area-level socioeconomic position (SEP) and health-risk behaviours (HRBs) are for the most part lacking. The aims of this study were to compare Slovakia and the Netherlands regarding differences in the prevalence of HRBs by neighbourhood and individual deprivation, and to determine whether area differences could be explained by the SEP of residents.

METHODS

We obtained data on residents aged 19-64 from Slovak and Dutch cities from the FP7 EURO-URHIS2 project and employed multilevel logistic regression.

RESULTS

The association between neighbourhood-level unemployment and HRBs differed between countries. In the Netherlands, the prevalence of almost all HRBs was higher in deprived areas, except for the consumption of fruits and vegetables. These area effects diminished after controlling for individual-level SEP. In Slovakia, no area effects were observed, although Slovak residents showed a higher risk for most HRBs. At the individual level, an inverse SE gradient was found for almost all HRBs in both countries.

CONCLUSIONS

Local analyses of small area health differences and health determinants are critical for efficient implementation of neighbourhood-based interventions.

The construction of a decision tool to analyse local demand and local supply for GP care using a synthetic estimation model

BACKGROUND

This study addresses the growing academic and policy interest in the appropriate provision of local healthcare services to the healthcare needs of local populations to increase health status and decrease healthcare costs. However, for most local areas information on the demand for primary care and supply is missing. The research goal is to examine the construction of a decision tool which enables healthcare planners to analyse local supply and demand in order to arrive at a better match.

METHODS

National sample-based medical record data of general practitioners (GPs) were used to predict the local demand for GP care based on local populations using a synthetic estimation technique. Next, the surplus or deficit in local GP supply were calculated using the national GP registry. Subsequently, a dynamic internet tool was built to present demand, supply and the confrontation between supply and demand regarding GP care for local areas and their surroundings in the Netherlands.

RESULTS

Regression analysis showed a significant relationship between sociodemographic predictors of postcode areas and GP consultation time (F [14, 269,467] = 2,852.24; P <0.001). The statistical model could estimate GP consultation time for every postcode area with >1,000 inhabitants in the Netherlands covering 97% of the total population. Confronting these estimated demand figures with the actual GP supply resulted in the average GP workload and the number of full-time equivalent (FTE) GP too much/too few for local areas to cover the demand for GP care. An estimated shortage of one FTE GP or more was prevalent in about 19% of the postcode areas with >1,000 inhabitants if the surrounding postcode areas were taken into consideration. Underserved areas were mainly found in rural regions.

CONCLUSIONS

The constructed decision tool is freely accessible on the Internet and can be used as a starting point in the discussion on primary care service provision in local communities and it can make a considerable contribution to a primary care system which provides care when and where people need it.

Assessing associations between socio-economic environment and self-reported health in Amsterdam using bespoke environments

Background

The study of the relationship between residential environment and health at micro area level has a long time been hampered by a lack of micro-scale data. Nowadays data is registered at a much more detailed scale. In combination with Geographic Information System (GIS)-techniques this creates opportunities to look at the relationship at different scales, including very local ones. The study illustrates the use of a ‘bespoke environment’ approach to assess the relationship between health and socio-economic environment.

Methods

We created these environments by buffer-operations and used micro-scale data on 6-digit postcode level to describe these individually tailored areas around survey respondents in an accurate way. To capture the full extent of area effects we maximized variation in socio-economic characteristics between areas. The area effect was assessed using logistic regression analysis.

Results

Although the contribution of the socio-economic environment in the explanation of health was not strong it tended to be stronger at a very local level. A positive association was observed only when these factors were measured in buffers smaller than 200 meters. Stronger associations were observed when restricting the analysis to socioeconomically homogeneous buffers. Scale effects proved to be highly important but potential boundary effects seemed not to play an important role. Administrative areas and buffers of comparable sizes came up with comparable area effects.

Conclusions

This study shows that socio-economic area effects reveal only on a very micro-scale. It underlines the importance of the availability of micro-scale data. Through scaling, bespoke environments add a new dimension to study environment and health.

How to choose geographical units in ecological studies: proposal and application to campylobacteriosis

In spatial epidemiology, the choice of an appropriate geographical unit of analysis is a key decision that will influence most aspects of the study. In this study, we proposed and applied a set of measurable criteria applicable for orienting the choice of geographical unit. Nine criteria were selected, covering many aspects such as biological relevance, communicability of results, ease of data access, distribution of exposure variables, cases and population, and shape of unit. These criteria were then applied to compare various geographical units derived from administrative, health services, and natural frameworks that could be used for the study of the spatial distribution of campylobacteriosis in the province of Quebec, Canada. In this study, municipality was the geographical unit that performed the best according to our assessment and given the specific objectives and time period of the study. Future research areas for optimizing the choice of geographical unit are discussed.

The effects of deprivation and relative deprivation on self-reported morbidity in England: an area-level ecological study

Background

Socioeconomic status gradients in health outcomes are well recognised and may operate in part through the psychological effect of observing disparities in affluence. At an area-level, we explored whether the deprivation differential between neighbouring areas influenced self-reported morbidity over and above the known effect of the deprivation of the area itself.

Methods

Deprivation differentials between small areas (population size approximately 1,500) and their immediate neighbours were derived (from the Index of Multiple Deprivation (IMD)) for Lower Super Output Area (LSOA) in the whole of England (n=32482). Outcome variables were self-reported from the 2001 UK Census: the proportion of the population suffering Limiting Long-Term Illness (LLTI) and ‘not good health’. Linear regression was used to identify the effect of the deprivation differential on morbidity in different segments of the population, controlling for the absolute deprivation. The population was segmented using IMD tertiles and P² People and Places geodemographic classification. P² is a commercial market segmentation tool, which classifies small areas according to the characteristics of the population. The classifications range in deprivation, with the most affluent type being ‘Mature Oaks’ and the least being ‘Urban Challenge’.

Results

Areas that were deprived compared to their immediate neighbours suffered higher rates of ‘not good health’ (β=0.312, p<0.001) and LLTI (β=0.278, p<0.001), after controlling for the deprivation of the area itself (‘not good health’—ß=0.655, p<0.001; LLTI—ß=0.548, p<0.001). The effect of the deprivation differential relative to the effect of deprivation was strongest in least deprived segments (e.g., for ‘not good health’, P² segments ‘Mature Oaks’—β=0.638; ‘Rooted Households’—β=0.555).

Conclusions

Living in an area that is surrounded by areas of greater affluence has a negative impact on health in England. A possible explanation for this phenomenon is that negative social comparisons between areas cause ill-health. This ‘psychosocial effect’ is greater still in least deprived segments of the population, supporting the notion that psychosocial effects become more important when material (absolute) deprivation is less relevant.

Socioeconomic characteristics of residential areas and risk of death: is variation in spatial units for analysis a source of heterogeneity in observed associations?

OBJECTIVES

Evidence on the association between the adverse socioeconomic characteristics of residential area and mortality is mixed. We examined whether the choice of spatial unit is critical in detecting this association.

DESIGN

Register-linkage study.

SETTING

Data were from the Finnish Public Sector study's register cohort.

PARTICIPANTS

The place of residence of 146 600 cohort participants was linked to map grids and administrative areas, and they were followed up for mortality from 2000 to 2011. Residential area socioeconomic deprivation and household crowding were aggregated into five alternative areas based on map grids (250×250 m, 1×1 km and 10×10 km squares), and administrative borders (zip-code area and town).

PRIMARY AND SECONDARY OUTCOME MEASURES

All-cause mortality.

RESULTS

For the 250×250 m area, mortality risk increased with increasing socioeconomic deprivation (HR for top vs bottom quintile 1.36, 95% CI 1.21 to 1.52). This association was either weaker or missing when broader spatial units were used. For household crowding, excess mortality was observed across all spatial units, the HRs ranging from 1.14 (95% CI 1.03 to 1.25) for zip code, and 1.21 (95% CI 1.11 to 1.31) for 250×250 m areas to 1.28 (95% CI 1.10 to 1.50) for 10×10 km areas.

CONCLUSIONS

Variation in spatial units for analysis is a source of heterogeneity in observed associations between residential area characteristics and risk of death.

Patients living in impoverished areas have more severe ischemic strokes

BACKGROUND AND PURPOSE

Initial stroke severity is one of the strongest predictors of eventual stroke outcome. However, predictors of initial stroke severity have not been well-described within a population. We hypothesized that poorer patients would have a higher initial stroke severity on presentation to medical attention.

METHODS

We identified all cases of hospital-ascertained ischemic stroke occurring in 2005 within a biracial population of 1.3 million. "Community" socioecomic status was determined for each patient based on the percentage below poverty in the census tract in which the patient resided. Linear regression was used to model the effect of socioeconomic status on stroke severity. Models were adjusted for race, gender, age, prestroke disability, and history of medical comorbidities.

RESULTS

There were 1895 ischemic stroke events detected in 2005 included in this analysis; 22% were black, 52% were female, and the mean age was 71 years (range, 19-104). The median National Institutes of Health Stroke Scale was 3 (range, 0-40). The poorest community socioeconomic status was associated with a significantly increased initial National Institutes of Health Stroke Scale by 1.5 points (95% confidence interval, 0.5-2.6; P<0.001) compared with the richest category in the univariate analysis, which increased to 2.2 points after adjustment for demographics and comorbidities.

CONCLUSIONS

We found that increasing community poverty was associated with worse stroke severity at presentation, independent of other known factors associated with stroke outcomes. Socioeconomic status may impact stroke severity via medication compliance, access to care, and cultural factors, or may be a proxy measure for undiagnosed disease states.

Geographic inequalities in all-cause mortality in Japan: compositional or contextual?

Background

A recent study from Japan suggested that geographic inequalities in all-cause premature adult mortality have increased since 1995 in both sexes even after adjusting for individual age and occupation in 47 prefectures. Such variations can arise from compositional effects as well as contextual effects. In this study, we sought to further examine the emerging geographic inequalities in all-cause mortality, by exploring the relative contribution of composition and context in each prefecture.

Methods

We used the 2005 vital statistics and census data among those aged 25 or older. The total number of decedents was 524,785 men and 455,863 women. We estimated gender-specific two-level logistic regression to model mortality risk as a function of age, occupation, and residence in 47 prefectures. Prefecture-level variance was used as an estimate of geographic inequalities in mortality, and prefectures were ranked by odds ratios (ORs), with the reference being the grand mean of all prefectures (value  = 1).

Results

Overall, the degree of geographic inequalities was more pronounced when we did not account for the composition (i.e., age and occupation) in each prefecture. Even after adjusting for the composition, however, substantial differences remained in mortality risk across prefectures with ORs ranging from 0.870 (Okinawa) to 1.190 (Aomori) for men and from 0.864 (Shimane) to 1.132 (Aichi) for women. In some prefectures (e.g., Aomori), adjustment for composition showed little change in ORs, while we observed substantial attenuation in ORs in other prefectures (e.g., Akita). We also observed qualitative changes in some prefectures (e.g., Tokyo). No clear associations were observed between prefecture-level socioeconomic status variables and the risk of mortality in either sex.

Conclusions

Geographic disparities in mortality across prefectures are quite substantial and cannot be fully explained by differences in population composition. The relative contribution of composition and context to health inequalities considerably vary across prefectures.

Social and geographic inequalities in premature adult mortality in Japan: a multilevel observational study from 1970 to 2005

OBJECTIVES

To examine trends in social and geographic inequalities in all-cause premature adult mortality in Japan.

DESIGN

Observational study of the vital statistics and the census data.

SETTING

Japan.

PARTICIPANTS

Entire population aged 25 years or older and less than 65 years in 1970, 1975, 1980, 1985, 1990, 1995, 2000 and 2005. The total number of decedents was 984 022 and 532 223 in men and women, respectively.

MAIN OUTCOME MEASURES

For each sex, ORs and 95% CIs for mortality were estimated by using multilevel logistic regression models with 'cells' (cross-tabulated by age and occupation) at level 1, 8 years at level 2 and 47 prefectures at level 3. The prefecture-level variance was used as an estimate of geographic inequalities of mortality.

RESULTS

Adjusting for age and time-trends, compared with production process and related workers, ORs ranged from 0.97 (95% CI 0.96 to 0.98) among administrative and managerial workers to 2.22 (95% CI 2.19 to 2.24) among service workers in men. By contrast, in women, the lowest odds for mortality was observed among production process and related workers (reference), while the highest OR was 12.22 (95% CI 11.40 to 13.10) among security workers. The degree of occupational inequality increased in both sexes. Higher occupational groups did not experience reductions in mortality throughout the period and was overtaken by lower occupational groups in the early 1990s, among men. Conditional on individual age and occupation, overall geographic inequalities of mortality were relatively small in both sexes; the ORs ranged from 0.87 (Okinawa) to 1.13 (Aomori) for men and from 0.84 (Kanagawa) to 1.11 (Kagoshima) for women, even though there is a suggestion of increasing inequalities across prefectures since 1995 in both sexes.

CONCLUSIONS

The present findings suggest that both social and geographic inequalities in all-cause mortality have increased in Japan during the last 3 decades.

Social economic inequalities and mental health II. Methodological aspects and literature review

Summary

Objective - This study provides a framework for mental health inequalities beginners. It describes the methods used to measure socio economic inequalities and the inter-relations with different aspects of mental health: residence, mental health services organisation and main diagnostic categories. Method - Literature electronic-search on Medline, Psyclit, Econlit, Social Science Index and SocioSearch usingand relating the key-words inequalities, deprivation, poverty, socio-economic status, social class, occupational class, mental health for the period 1965-2002 (June). The articles selected were integrated with manual search (publications of the same authors, cross-references, working documents and reports of international andregional organisations). Results - Inequality is not an absolute concept and, mainly, it has been changing during the last years. For example, the integration and re-definition of variables that capture, in simple indices, a complex reality; the accent on social more than on economic aspects; the geo-validity and time-reference of the inequality's indices. Moreover, the inequalities could be the result of individual preferences, in this case, the social selectionand social causation issues will raise the suitability for a public intervention. Conclusions - Up to now, research has been mainly concentrated in describing and measuring health inequalities. For designing effective interventions, policy makers need to ground decisions on health-socioeconomic inequalities explanatory models.

Declaration of Interest

this work was partly funded by the Department of the Public Health Sciences “G. Sanarelli” of the University of Rome “La Sapienza” and the Department of Medicine and Public Health of the University of Verona.

Associations between regional socioeconomic deprivation and cancer risk: Analysis of population-based Cancer Registry data from Bavaria, Germany

OBJECTIVE

Previous research from other countries shows a positive association between cancer risk and regional deprivation. This study explores this association for lung and colorectal cancers in Germany.

METHOD

Regional deprivation was assessed by the 'Bavarian Index of Multiple Deprivation'. Cancer data were provided by the Cancer Registry of Bavaria (2003-2006). The association between cancer risk and regional deprivation was evaluated by multilevel Poisson regression analysis.

RESULTS

Crude incidence and mortality rates (per 1000 people) in the least deprived areas were 1.46 and 0.92 for lung cancer, 2.82 and 0.69 for colorectal cancer. For lung cancer, the age-adjusted relative risk (RR) for incidence in the most deprived districts (compared with the least deprived) in men was 1.41 (95% CI: 1.28-1.54), for mortality 1.59 (95% CI: 1.40-1.80); in women, an elevated RR was seen for mortality (1.24, 95% CI: 1.06-1.46). For colorectal cancer, the RR for incidence (men: 1.31, 95% CI: 1.17-1.46; women: 1.25, 95% CI: 1.12-1.40) and mortality (men: 1.51, 95% CI: 1.28-1.80; women: 1.49, 95% CI: 1.26-1.77) was always highest in the most deprived districts.

CONCLUSION

At the district level in Bavaria, the risk for lung and colorectal cancers mostly increases with increasing regional deprivation.

Place effects for areas defined by administrative boundaries: a life course analysis of mortality and cause specific morbidity in Scania, Sweden

To understand the origin of disease risk in adulthood, factors in all stages of life and on different contextual levels should be considered. Therefore, the aim of this study was to investigate the relevance of a person's area of residence over their life course with regard to four outcomes: all-cause mortality; ischemic heart disease mortality and morbidity; cancer mortality and morbidity; and respiratory diseases and related mortality. We applied a cross-classified multilevel model for three age groups on a longitudinal data set spanning a 35 year period in Scania, Sweden. According to our analyses, the proportion of the total variance at the district level for all the outcomes studied was below 2% for the 65 to 84 age group, below 4.5% for those ages 50-64 years, and below 6.5% for those 30-49 years old. Our results suggest that the parish of residence, at four different time points during the individual life course, had little influence on individual all-cause mortality, or on mortality or morbidity from IHD, cancer, and respiratory diseases; i.e., knowing when and where an individual resided during their life course gives little indication of future mortality and morbidity. Such knowledge is essential in assisting decision makers determine the relevant geographical level of intervention (in our case whether to direct interventions toward the entire region of Scania or to specific parishes) needed. Valuable information for planning public health interventions might be obtained by considering measures of variance and clustering from specific contexts before implementing strategic programs.

Socio-economic inequalities in cancer incidence - the choice of deprivation measure matters

BACKGROUND

There is a well established relationship between cancer incidence and socio-economic deprivation. The strength of this relationship may be subject to the choice of deprivation index used.

METHODS

A range of possibilities for measuring area-based deprivation in Northern Ireland are investigated. The relationship between each measure and cancer incidence is described using standardised incidence ratios and age-standardised rates fitted with a log-linear model.

RESULTS

Standardised incidence ratios for lung cancer comparing the most to the least deprived deciles were greater using an income measure (371.1, 95%CI: 355.4-386.9) than an employment measure (321.1; 95%CI: 307.9-334.2). Income, employment and education measures gave similar results for breast, prostate and colorectal cancers. Standardised incidence ratios generated for all cancers (excluding non-melanoma skin) using income deciles based upon census output areas (142.4; 95%CI: 139.6-145.1) were larger than those generated using super output areas (133.0; 95%CI: 130.3-135.7) or electoral wards (130.4; 95%CI: 127.8-133.1).

CONCLUSION

While the choice of time period for measuring area-based deprivation makes little difference to relative inequalities, smaller geographic units and income based deprivation measures can produce a stronger relationship between deprivation and cancer incidence than other measures.

The socio-spatial neighborhood estimation method: an approach to operationalizing the neighborhood concept

The literature on neighborhoods and health highlights the difficulty of operationalizing "neighborhood" in a conceptually and empirically valid manner. Most studies, however, continue to define neighborhoods using less theoretically relevant boundaries, risking erroneous inferences from poor measurement. We review an innovative methodology to address this problem, called the socio-spatial neighborhood estimation method (SNEM). To estimate neighborhood boundaries, researchers used a theoretically informed combination of qualitative GIS and on-the-ground observations in Texas City, Texas. Using data from a large sample, we assessed the SNEM-generated neighborhood units by comparing intra-class correlation coefficients (ICCs) and multi-level model parameter estimates of SNEM-based measures against those for census block groups and regular grid cells. ICCs and criterion-related validity evidence using SF-36 outcome measures indicate that the SNEM approach to operationalization could improve inferences based on neighborhoods and health research.

Migration does not enlarge inequalities in health between rich and poor neighbourhoods in The Netherlands

We estimate to what extent migration contributes to inequalities in health between rich and poor neighbourhoods in The Netherlands. We used a sample from the survey WoonOnderzoek Nederland 2006. Using multilevel logistic regression analyses, we assessed the magnitude of health differences between poor vs. rich areas for the migrant and total population. Next, we compared the health of migrants to non-migrant populations and we assessed the role of sociodemographic characteristics. For most health indicators, area inequalities in health were much smaller in the migrant population than in the total population. The health of migrants was generally in-between the health of non-migrants who lived in areas of origin and destination. The differences in health with the population in the areas of origin were almost completely explained by sociodemographic characteristics. Health is related to risk of migration between poor and rich areas, mostly through sociodemographic selection instead of a direct effect of health. Despite the relationship with health, migration does not enlarge inequalities in health between poor and rich neighbourhoods but possibly attenuates the health differences.

[Development of composite deprivation index for Korea: the correlation with standardized mortality ratio]

OBJECTIVES

The aims of this paper were to develop the composite deprivation index (CDI) for the sub-district (Eup-Myen-Dong) levels based on the theory of social exclusion and to explore the relationship between the CDI and the standardized mortality ratio (SMR).

METHODS

The paper calculated the age adjusted SMR and we included five dimensions of social exclusion for CDI; unemployment, poverty, housing, labor and social network. The proxy variables of the five dimensions were the proportion of unemployed males, the percent of recipients receiving National Basic Livelihood Security Act benefits, the proportion of households under the minimum housing standard, the proportion of people with a low social class and the proportion of single-parent household. All the variables were standardized using geometric transformation and then we summed up them for a single index. The paper utilized the 2004-2006 National Death Registry data, the 2003-2006 national residents' registration data, the 2005 Population Census data and the 2005-2006 means-tested benefit recipients' data.

RESULTS

The figures were 115.6, 105.8 and 105.1 for the CDI of metropolitan areas (big cities), middle size cities and rural areas, respectively. The distributional variation of the CDI was the highest in metropolitan areas (8.9 - 353.7) and the lowest was in the rural areas (26.8 - 209.7). The extent and relative differences of deprivation increased with urbanization. Compared to the Townsend and Carstairs index, the CDI better represented the characteristics of rural deprivation. The correlation with the SMR was statistically significant and the direction of the CDI effects on the SMR was in accordance with that of the previous studies.

CONCLUSIONS

The study findings indicated mortality inequalities due to the difference in the CDI. Despite the attempt to improve deprivation measures, further research is warranted for the consensus development of a deprivation index.

Do differences in the administrative structure of populations confound comparisons of geographic health inequalities?

Background

Geographical health inequalities are naturally described by the variation in health outcomes between areas (e.g. mortality rates). However, comparisons made between countries are hampered by our lack of understanding of the effect of the size of administrative units, and in particular the modifiable areal unit problem. Our objective was to assess how differences in geographic and administrative units used for disseminating data affect the description of health inequalities.

Methods

Retrospective study of standard populations and deaths aggregated by administrative regions within 20 European countries, 1990-1991. Estimated populations and deaths in males aged 0-64 were in 5 year age bands. Poisson multilevel modelling was conducted of deaths as standardised mortality ratios. The variation between regions within countries was tested for relationships with the mean region population size and the unequal distribution of populations within each country measured using Gini coefficients.

Results

There is evidence that countries whose regions vary more in population size show greater variation and hence greater apparent inequalities in mortality counts. The Gini coefficient, measuring inequalities in population size, ranged from 0.1 to 0.5 between countries; an increase of 0.1 was accompanied by a 12-14% increase in the standard deviation of the mortality rates between regions within a country.

Conclusions

Apparently differing health inequalities between two countries may be due to differences in geographical structure per se, rather than having any underlying epidemiological cause. Inequalities may be inherently greater in countries whose regions are more unequally populated.

The effects of rurality on mental and physical health

The effects of rurality on physical and mental health are examined in analyses of a national dataset, the Community Tracking Survey, 2000-2001, that includes individual level observations from household interviews. We merge it with county level data reflecting community resources and use econometric methods to analyze this multi-level data. The statistical analysis of the impact of the choice of definition on outcomes and on the estimates and significance of explanatory variables in the model is presented using modern econometric methods, and differences in results for mental health and physical health are evaluated.

Area deprivation affects behavioral problems of young adolescents in mixed urban and rural areas: the TRAILS study

PURPOSE

Behavioral problems occur more frequently among adolescents in deprived areas, but most evidence concerns urbanized areas. Our aim was to assess the impact of area deprivation and urbanization on the occurrence and development of behavioral problems among adolescents in a mixed urban and rural area and to examine the contributory factors.

METHODS

We obtained data from the first two waves (n=2,230; mean ages, 11.5 and 13.5 years respectively; response at follow-up, 96.4%) of the TRacking Adolescents' Individual Lives Survey (TRAILS). TRAILS is a prospective study of adolescent mental health in a mixed urban and rural region of the Netherlands. We assessed adolescent behavioral problems using the parent-reported Child Behavior Checklist (CBCL), the adolescent-reported Youth Self-Report (YSR) and the Antisocial Behavior Scale (ABS). Living areas were categorized into tertiles of deprivation. We further collected data on child temperament, perceived rearing style, parental socioeconomic position (education, income and occupation), family composition, and parental mental health history.

RESULTS

At baseline, adolescents living in the most deprived tertile more frequently had elevated behavioral problem scores than those from the least deprived tertile on the CBCL (11.2% against 7.1%), YSR (11.9% against 6.9%), and ASB (11.5% against 7.4%) (all p < .05). Socioeconomic position explained half of the differences due to area deprivation. Other familial and parental characteristics did not significantly contribute to the explanation of observed area differences.

CONCLUSIONS

As in highly urbanized areas, behavioral problems occur more frequently among adolescents in deprived mixed rural and urban areas. Urbanization has little effect on these area differences.

Mortality effects of average education: a multilevel study of small neighbourhoods in rural and urban areas in Norway

Background

The intention was to find out whether there was an association between the socio-economic resources in a small neighbourhood ("basic statistical unit"; BSU) and individual mortality, net of individual resources, and whether this association differed between municipalities including a quite large city and others. The possibility of a rural-urban difference in the health effect of community resources has not been checked earlier.

Methods

Discrete-time hazard models for mortality at age 60-89 were estimated for 1990-1992 and 2000-2002, using register data that cover the entire Norwegian population. For each person, the educational level and the municipality and BSU of residence in 1990 and 2000 were known. Average education was computed by aggregating over the individual data. In total, there were about 200000 deaths in more than 13000 BSUs during 5 million person-years of observation.

Results

There was a significant relationship between average education in the BSU and individual mortality, but only in the medium-sized and largest municipalities. The sharpest relationship was seen in the latter, where for example OR per year of education was 0.908 (95% CI 0.887-0.929) in the 1990-92 period. The findings were robust to various alternative specifications.

Conclusion

These results from a large data set are consistent with the idea that neighbourhood socio-economic resources may affect individual mortality, but suggest that distinctions according to population size or density be made in future research and that one should be careful, if focusing on cities, to generalize beyond that setting. With these data, one can only speculate about the reasons for the rural-urban difference. A stronger higher-level spatial segregation in urban areas may be one explanation.

Social class, marginality and self-assessed health: a cross-sectional analysis of the health gradient in Mexico

Background

Examining the association between social inequality and health is not new. However, there is little empirical evidence of this association in the Latin American literature, much less from the Mexican scholars. Its research, including the one conducted in Mexico, has mostly followed a theoretical approach and has not been able to provide strong empirical evidence of their important theoretical and conceptual contributions, mainly because reliable, complete and valid data are unavailable.

Methods

To empirically examine the gradient effect of social class on self-rated health in Mexico, a secondary cross-sectional mixed-level analysis was designed. Using individual level data from the Second National Health Survey (ENSA II), social class categories were specified following a stratification approach according to the occupation and education indicators available from ENSA II. Two types of categories were made, one for t urban and one for the rural labor force. Two indicators of perceived health status were used as health outcomes: self-assessed health and reported morbidity. Furthermore, the marginality index, an indicator of relative deprivation was used to examine its contextual effect at the state and regional level. The analysis was conducted using logistic multivariate models.

Results

The cross-sectional analysis showed a gradient effect of social class for good assessed-health. Relative to the low urban class, the odds ratio (OR) for a good perception of health for individuals belonging to the high urban class was 2.9 (95% confidence interval: 2.1–3.9). The OR for the middle high class was 2.8 (95% confidence interval: 2.4–3.4), while the OR for the middle low class was 1.8 (95% confidence interval: 1.6–2.1). However, for the rural labour force an OR of 1.5 was only significant between the high class who considered their health as good relative to the low class (95% confidence interval: 1.02–2.2). At the aggregate level, the results also showed individuals living in deprived regions were less likely to report their health as good than individuals living in relatively less deprived ones, OR = 0.6 (95% confidence interval: 0.4–0.7).

Conclusion

Overall, the findings of this study provided empirical evidence that social inequality negatively influences health through a differential exposure and an unequal distribution of resources across the class spectrum: the lower the social class, the poorer the perception of health. The results also showed that living in more deprived regions had a further negative effect on health. From a policy perspective, the gradient effects of social class suggest that non-targeted policies should be designed to address both material conditions at the individual level as well as deprived living conditions at higher levels of aggregation to improve health across the social spectrum.

Ecological association between a deprivation index and mortality in France over the period 1997 - 2001: variations with spatial scale, degree of urbanicity, age, gender and cause of death

Background

Spatial health inequalities have often been analysed in terms of deprivation. The aim of this study was to create an ecological deprivation index and evaluate its association with mortality over the entire mainland France territory. More specifically, the variations with the degree of urbanicity, spatial scale, age, gender and cause of death, which influence the association between mortality and deprivation, have been described.

Methods

The deprivation index, 'FDep99', was developed at the 'commune'(smallest administrative unit in France) level as the first component of a principal component analysis of four socioeconomic variables.

Proxies of the Carstairs and Townsend indices were calculated for comparison.

The spatial association between FDep99 and mortality was studied using five different spatial scales, and by degree of urbanicity (five urban unit categories), age, gender and cause of death, over the period 1997–2001.

'Avoidable' causes of death were also considered for subjects aged less than 65 years. They were defined as causes related to risk behaviour and primary prevention (alcohol, smoking, accidents).

Results

The association between the FDep99 index and mortality was positive and quasi-log-linear, for all geographic scales. The standardized mortality ratio (SMR) was 24% higher for the communes of the most deprived quintile than for those of the least deprived quintile. The between-urban unit category and between-région heterogeneities of the log-linear associations were not statistically significant. The association was positive for all the categories studied and was significantly greater for subjects aged less than 65 years, for men, and for 'avoidable' mortality.

The amplitude and regularity of the associations between mortality and the Townsend and Carstairs indices were lower.

Conclusion

The deprivation index proposed reflects a major part of spatial socioeconomic heterogeneity, in a homogeneous manner over the whole country. The index may be routinely used by healthcare authorities to observe, analyse, and manage spatial health inequalities.