Do places matter? A multi-level analysis of regional variations in health-related behaviour in Britain

The complexities of suicide: a multilevel survival analysis examining individual, familial and neighbourhood determinants of suicide risk using Danish register-based data

BACKGROUND

Suicide risk is complex and nuanced, and how place impacts suicide risk when considered alongside detailed individual risk factors remains uncertain. We aimed to examine suicide risk in Denmark with both individual and neighbourhood level risk factors.

METHODS

We used Danish register-based data to identify individuals born in Denmark from 1972, with full parental information and psychiatric diagnosis history. We fitted a two-level survival model to estimate individual and neighbourhood determinants on suicide risk.

RESULTS

We identified 1723 cases of suicide in Denmark during the follow-up period from 1982 to 2015. Suicide risk was explained mainly by individual determinants. Parental comorbidities, particularly maternal schizophrenia [incidence rate ratio (IRR): 2.29, 95% CI 1.56-3.16] and paternal death (2.29, 95% CI 1.31-3.72) partly explained suicide risk when adjusted for all other determinants. The general contextual effect of suicide risk across neighbourhoods showed a median incidence rate ratio (MRR) of 1.13 (1.01-1.28), which was further reduced with full adjustment. Suicide risk increased in neighbourhoods with a higher proportion of manual workers (IRR: 1.08; 1.03-1.14), and decreased with a higher population density (IRR: 0.89; 0.83-0.96).

CONCLUSION

Suicide risk varies mainly between individuals, with parental comorbidities having the largest effect on suicide risk. Suicide risk was less impacted by neighbourhood, though, albeit to a lesser extent than individual determinants, some characteristics were associated with suicide risk. Suicide prevention policies might consider targeting interventions towards individuals more vulnerable due to particular parental comorbidities, whilst taking into account that some neighbourhood characteristics might exacerbate this risk further.

Housing Instability and Socioeconomic Disparities in Health: Evidence from the U.S. Economic Recession

While a number of studies have observed the effects of housing instability on health outcomes, fewer have emphasized pre-existing socioeconomic disparities in health and the influence of housing instability on subsequent health outcomes in the wake of the economic recession. Using national data on six adult health indictors and foreclosure data aggregated by census tract, this study examines the association between neighborhood housing insecurity and health outcomes, particularly focusing on various income levels and racial groups in about 200 U.S. metropolitan areas after the 2008 housing crisis. Results suggest that high levels of housing instability induced by high levels of foreclosed properties in certain neighborhoods were strongly associated with more health problems among residents, but the results varied according to the income level and the dominant racial group in these neighborhoods. With regard to income levels, adverse health conditions in lower income neighborhoods remained longer and became stronger than those in higher income neighborhoods. The findings also show variation among racial groups: While multiple health problems plagued all income levels in white tracts, more severe and worsening pre-existing health problems appeared in lower income minority tracts. In addition, neighborhood housing instability generated by mortgage foreclosures was strongly associated with heart-related diseases, particularly in middle-income White neighborhoods, and mental health problems, particularly in upper-income Hispanic tracts. Finally, among multiple health indicators, mental health problems were the most common health conditions during the U.S. economic recession. In light of the socioeconomic disparities in health, policy makers should establish effective policy tools that integrate health and urban and housing planning.

'When will the doctor be around so that I come by?!' Geo-socio effects on health care supply, access and utilisation: experiences from Kalangala Islands, Uganda

Background

The study set out to give an in-depth intersection of geo, eco-socio exposition of the factors relating to geography, healthcare supply and utilization in an island setting. This analysis is informed by what has emerged to be known as social epidemiology. We provide in-depth explanation of context to health care access, utilization and outcomes. We argue that health care delivery has multiple intersections that are experientially complex, multi-layered and multi-dimensional to the disadvantage of vulnerable population segments of society in the study area.

Methods

We used a cross-sectional qualitative exploratory design. Qualitative methods facilitated an in-depth exploration and understanding of this island dispersed and peripheral setting. Data sources included a review of relevant literature and an ethnographic exploration of the lived experiences of community members while seeking and accessing health care. Data collection methods included in-depth interviews (IDI) from selected respondents, observation, focus group discussions (FGDs) and key informant interviews (KII).

Results

We report based on the health care systems model which posits that, health care activities are diverse but interconnected in a complex way. The identified themes are; the role of geography, access (geographical and financial) to health services, demand and utilization, Supplies, staffing and logistical barriers and a permissive and transient society. When and how to travel for care was beyond a matter of having a health need/ being sick and need arising. A motivated workforce is as critical as health facilities themselves in determining healthcare outcomes.

Conclusion

Geography doesn’t work and affect health outcomes in isolation. Measures that target only individuals will not be adequate to tackle health inequalities because aspects of the collective social group and physical environment may also need to be changed in order to reduce health variations.

Area-level deprivation and geographic factors influencing utilisation of General Practitioner services

Inequities in access to General Practitioner (GP) services are a key policy concern given the role of GPs as gatekeepers to secondary care services. Geographic or area-level factors, including local deprivation and supply of healthcare providers, are important elements of access. In considering how area-level deprivation relates to GP utilisation, two potentially opposing factors may be important. The supply of healthcare services tends to be lower in areas of higher deprivation. However, poorer health status among individuals in deprived areas suggests greater need for healthcare. To explore the relationship of area-level deprivation to healthcare utilisation, we use data from the Healthy Ireland survey, which provided a sample of 6326 respondents to face-to-face interviews.

A u-shaped relationship between GP supply and area-level deprivation is observed in the data. Modelling reveals that residing in more deprived communities has a strong, statistically significant positive association with having seen a GP within the last four weeks, controlling for individual characteristics and GP supply. All else equal, residing in an area ranked in the most deprived quintile increases the odds of a respondent having visited the GP in four weeks by 1.43 (95% Confidence Interval: 1.15–1.78), compared to the least deprived quintile (p-value< 0.001). The findings indicate that the level of deprivation in an area may be relevant to decisions about how to allocate primary care resources.

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GP utilisation is higher amongst those in more deprived areas.

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GP supply is lower in middle income areas compared to deprived or affluent areas.

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Differences in GP supply and GP utilisation occur across deprivation quintiles.

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Other geographic factors are not found to be significant in determining GP utilisation.

Small area influences on the individual unhealthy lifestyle behaviors: A multilevel analysis of discriminatory accuracy

We estimated the discriminatory power of area of residence (census tract) on the prevalence of main risk factors for chronic diseases. Results, based on a sample of 21,007 participants from the 2011-2012 National Health Survey of Spain, show a differential influence of the geosocial environment on the four health risk factors. Accounting for census tracts substantially increases the discriminatory power regarding at-risk alcohol consumption, unbalanced diet, and leisure-time sedentarism but not tobacco consumption. However, the socioeconomic characteristics of the tracts played a minor role. Further research on the specific geosocial contextual variables explaining variability in these risk factors is necessary.

Cost-related unmet need for healthcare services in Kenya

Background

The assessment of unmet need is one way to gauge inequities in access to healthcare services. While there are multiple reasons for unmet need, financial barriers are a major reason particularly in low- and middle-income countries where healthcare systems do not offer financial protection. Moreover, accessibility and affordability are paramount in achieving universal health coverage. This study examines the extent of unmet need in Kenya due to financial barriers, the associated determinants, and the influence of regional variations.

Methods

We use data from the 2013 Kenya household health expenditure and utilization (KHHEUS) cross sectional survey. Self-reported unmet need due to lack of money and high costs of care is used to compute the outcome of interest. A multilevel regression model is employed to assess the determinants of cost-related unmet need, confounding for the effect of variations at the regional level.

Results

Cost-related barriers are the main cause of unmet need for outpatient and inpatient services, with wide variations across the counties. A positive association between county poverty rates and cost-related unmet is noted. Results reveal a higher intraclass correlation coefficient (ICC) of 0.359(35.9%) for inpatient services relative to 0.091(9.1%) for outpatient services. Overall, differences between counties accounted for 9.4% (ICC ~ 0.094) of the total variance in cost-related unmet need. Factors that positively influence cost-related unmet need include older household heads, inpatient services, and urban residence. Education of household head, good self-rated health, larger household size, insured households, and higher wealth quintiles are negatively associated with cost-related unmet need.

Conclusion

The findings underscore the important role of cost in enabling access to healthcare services. The county level is seen to have a significant influence on cost-related unmet need. The variations noted in cost-related unmet need across the counties signify the existence of wide disparities within and between counties. Scaling up of health financing mechanisms would fundamentally require a multi-layered approach with a focus on the relatively poor counties to address the variations in access. Further segmentation of the population for better targeting of health financing policies is paramount, to address equity in access for the most vulnerable and marginalized populations.

Drinking patterns at the sub-national level: What do they tell us about drinking cultures in European countries?

Aim:

A drinking pattern is not only a major drinking variable, but is also one indicator of a country’s drinking culture. In the present study, we examine drinking patterns within and across the neighbouring countries of Denmark and Germany. The aim of the research is to determine to what extent drinking patterns differ or are shared at the sub-national level in the two countries.

Method:

Data came from the German 2012 Epidemiological Survey of Substance Use (n = 9084) 18–64 years (response rate 54%), and the Centre for Alcohol and Drug Research’s 2011 Danish national survey (n = 5133) 15–79 years (response rate 64%), which was reduced to a common age range, producing a final n = 4016. The drinking pattern variable included abstention, moderate drinking, heavy drinking, risky single occasion drinking (RSOD), and was investigated with bivariate statistics and gender-specific hierarchical cluster analysis.

Results:

For men three clusters emerged: one highlighting abstention and RSOD, moderate/heavy drinking, RSOD and RSOD + heavy drinking. For women, two clusters appeared: one highlighting abstention and moderate/heavy drinking and the other highlighting RSOD and RSDO + heavy drinking. The clusters revealed different geographical patterning: for men, a west vs. east divide; for women, a north–south gradient.

Conclusions:

The analysis could identify for each gender clusters representing both separate and shared drinking patterns as well as distinctive geographical placements. This new knowledge can contribute to a new understanding of the dynamics of drinking cultures and could indicate new approaches to prevention efforts and policy initiatives.

Culling from the herd's perspective-Exploring herd-level management factors and culling rates in Québec dairy herds

The relationship between cows' health, reproductive performance or disorders and their longevity is well demonstrated in the literature. However these associations at the cow level might not hold true at the herd level, and herd-level variables can modify cow-level outcomes independently of the cows' characteristics. The interaction between cow-level and herd-level variables is a relevant issue for understanding the culling of dairy cows. However it requires the appropriate group-level variables to assess any contextual effect. Based on 10 years of health and production data, the objectives of this paper are:(a) to quantify the culling rates of dairy herds in Québec; (b) to determine the profiles of the herds based on herd-level factors, such as demographics, reproduction, production and health indicators, and whether these profiles can be related to herd culling rates for use as potential contextual variables in multilevel modelling of culling risk. A retrospective longitudinal study was conducted on data from dairy herds in Québec, Canada, by extracting health information events from the dairy herd health management software used by most Québec producers and their veterinarians. Data were extracted for all lactations taking place between January 1st, 2001 and December 31st, 2010. A total of 432,733 lactations from 156,409 cows out of 763 herds were available for analysis. Thirty cow-level variables were aggregated for each herd and years of follow-up, and their relationship was investigated by Multiple Factor Analysis (MFA). The overall annual culling rate was 32%, with a 95% confidence interval (CI) of [31.6%,32.5%]. The dairy sale rate by 60 days in milk (DIM) was 3.2% [2.8%,3.6%]. The annual culling rate within 60 DIM was 8.2% [7.9%,8.4%]. The explained variance for each axis from the MFA was very low: 14.8% for the first axis and 13.1% for the second. From the MFA results, we conclude there is no relationship between the groups of herd-level indicators, demonstrating the heterogeneity among herds for their demographics, reproduction and production performance, and health status. However, based on Principal Component Analysis (PCA), the profiles of herds could be determined according to specific, single, herd-level indicators independently. The relationships between culling rates and specific herd-level variables within factors were limited to livestock sales, proportion of first lactation cows, herd size, proportion of calvings occurring in the fall, longer calving intervals and reduced 21-day pregnancy rates, increased days to first service, average age at first calving, and reduced milk fever incidence. The indicators found could be considered as contextual variables in multilevel model-building strategies to investigate cow culling risk.

Contextual generalized trust and immunization against the 2009 A(H1N1) pandemic in the American states: A multilevel approach

The aim of the study was to investigate the association between contextual generalized trust and individual-level 2009 A(H1N1) pandemic immunization acceptance. A second aim was to investigate whether knowledge about the A(H1N1) pandemic mediated the association between contextual generalized trust and A(H1N1) immunization acceptance. Data from the National 2009 H1N1 Flu Survey was used. To capture contextual generalized trust, data comes from an aggregation of surveys measuring generalized trust in the American states. To investigate the association between contextual generalized trust and immunization acceptance, while taking potential individual-level confounders into account, multilevel logistic regression was used. The investigation showed contextual generalized trust to be significantly associated with immunization acceptance. However, controlling for knowledge about the A(H1N1) pandemic did not substantially affect the association between contextual generalized trust and immunization acceptance. In conclusion, contextual state-level generalized trust was associated with A(H1N1) immunization, but knowledge about A(H1N1) was not mediating this association.

Cumulative Effects of Growing Up in Separate and Unequal Neighborhoods on Racial Disparities in Self-rated Health in Early Adulthood

Evidence suggests that living in a socioeconomically deprived neighborhood is associated with worse health. Yet most research relies on cross-sectional data, which implicitly ignore variation in longer-term exposure that may be more consequential for health. Using data from the 1970 to 2011 waves of the Panel Study of Income Dynamics merged with census data on respondents' neighborhoods (N = 1,757), this study estimates a marginal structural model with inverse probability of treatment and censoring weights to examine: (1) whether cumulative exposure to neighborhood disadvantage from birth through age 17 affects self-rated health in early adulthood, and (2) the extent to which variation in such exposure helps to explain racial disparities therein. Findings reveal that prolonged exposure to neighborhood disadvantage throughout childhood and adolescence is strikingly more common among nonwhite versus white respondents and is associated with significantly greater odds of experiencing an incidence of fair or poor health in early adulthood.

The regional geography of alcohol consumption in England: Comparing drinking frequency and binge drinking

Alcohol consumption frequency and volume are known to be related to health problems among drinkers. Most of the existing literature that analyses regional variation in drinking behaviour uses measures of consumption that relate only to volume, such as 'binge drinking'. This study compares the regional association of alcohol consumption using measures of drinking frequency (daily drinking) and volume (binge drinking) using a nationally representative sample of residents using the Health Survey for England, 2011-2013. Results suggest the presence of two differentiated drinking patterns with relevant policy implications. We find that people in northern regions are more likely to binge drink, whereas people in southern regions are more likely to drink on most days. Regression analysis shows that regional variation in binge drinking remains strong when taking into account individual and neighbourhood level controls. The findings provide support for regional targeting of interventions that aim to reduce the frequency as well as volume of drinking.

Multilevel modelling and public health policy

Background: Multilevel modelling is a statistical technique that extends ordinary regression analysis to the situation where the data are hierarchical. Such data form an increasingly common evidence base for public health policy, and as such it is important that policy makers should be aware of this methodology. Method: This paper therefore lays out the a basic description of multilevel modelling, discusses the problems of alternative approaches, and details the relevance for public health policy before describing which levels are relevant and illustrating the different kinds of hypotheses that can be tested using multilevel modelling. A series of examples is used throughout the paper. These relate to regional variations in the incidence of heart disease, the allocation of health resources, the relationship between neighbourhood disorder and mental health, the demand-control model in occupational health, and a school intervention to prevent cardiovascular disease.

Smoking and associated factors among adolescents in Tallinn, Helsinki and Moscow: a multilevel analysis

Aims: To investigate variations in smoking and associated factors on individual and aggregate level among adolescents in Tallinn (Estonia), Helsinki (Finland) and Moscow (the Russian Federation). Methods: The data was collected in Tallinn (N=1268 in Estonian and N=901 in Russian schools), in Helsinki (N=1396) and in Moscow (N=618) from pupils aged 13 - 18 by self-administered questionnaire. Multilevel analysis was used to estimate the possible effects of background characteristics, of the proximity of other smokers and the school context on the tobacco use of pupils. Results: The prevalence rate of smoking among girls in Russian schools in Tallinn (34.6%), among girls in Helsinki (39.5%), and in Moscow (32.1%) was higher than that among girls in Estonian schools in Tallinn (17.6%). Smoking was slightly less prevalent among boys in Helsinki (27.5%), compared to boys in Estonian (33.6%) and Russian (35.6%) schools in Tallinn, and to boys in Moscow (32.8%). Smoking increased with age. Multilevel analysis showed that smoking differed by school among pupils. Individual determinants of smoking as study site, grade, friends', siblings' and parental smoking behaved differently depending upon school. Friends and siblings' smoking showed interaction with study site to the smoking among girls. Conclusions: Strategies aimed at influencing smoking behaviour need to be directed not only towards the individual, but also towards the influences within the child's school environment.

An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy: The Case of Neighbourhoods and Health

BACKGROUND AND AIM

Many multilevel logistic regression analyses of "neighbourhood and health" focus on interpreting measures of associations (e.g., odds ratio, OR). In contrast, multilevel analysis of variance is rarely considered. We propose an original stepwise analytical approach that distinguishes between "specific" (measures of association) and "general" (measures of variance) contextual effects. Performing two empirical examples we illustrate the methodology, interpret the results and discuss the implications of this kind of analysis in public health.

METHODS

We analyse 43,291 individuals residing in 218 neighbourhoods in the city of Malmö, Sweden in 2006. We study two individual outcomes (psychotropic drug use and choice of private vs. public general practitioner, GP) for which the relative importance of neighbourhood as a source of individual variation differs substantially. In Step 1 of the analysis, we evaluate the OR and the area under the receiver operating characteristic (AUC) curve for individual-level covariates (i.e., age, sex and individual low income). In Step 2, we assess general contextual effects using the AUC. Finally, in Step 3 the OR for a specific neighbourhood characteristic (i.e., neighbourhood income) is interpreted jointly with the proportional change in variance (i.e., PCV) and the proportion of ORs in the opposite direction (POOR) statistics.

RESULTS

For both outcomes, information on individual characteristics (Step 1) provide a low discriminatory accuracy (AUC = 0.616 for psychotropic drugs; = 0.600 for choosing a private GP). Accounting for neighbourhood of residence (Step 2) only improved the AUC for choosing a private GP (+0.295 units). High neighbourhood income (Step 3) was strongly associated to choosing a private GP (OR = 3.50) but the PCV was only 11% and the POOR 33%.

CONCLUSION

Applying an innovative stepwise multilevel analysis, we observed that, in Malmö, the neighbourhood context per se had a negligible influence on individual use of psychotropic drugs, but appears to strongly condition individual choice of a private GP. However, the latter was only modestly explained by the socioeconomic circumstances of the neighbourhoods. Our analyses are based on real data and provide useful information for understanding neighbourhood level influences in general and on individual use of psychotropic drugs and choice of GP in particular. However, our primary aim is to illustrate how to perform and interpret a multilevel analysis of individual heterogeneity in social epidemiology and public health. Our study shows that neighbourhood "effects" are not properly quantified by reporting differences between neighbourhood averages but rather by measuring the share of the individual heterogeneity that exists at the neighbourhood level.

MASS APPRAISAL OF RESIDENTIAL REAL ESTATE USING MULTILEVEL MODELLING

Mass appraisal, or the automatic valuation of a large number of real estate assets, has attracted the attention of many researchers, who have mainly approached this issue employing traditional econometric models such as Ordinary Least Squares (OLS). However, this method does not consider the hierarchical structure of the data and therefore assumes the unrealistic hypothesis of the independence of the individuals in the sample. This paper proposes the use of the Hierarchical Linear Model (HLM) to overcome this limitation. The HLM also gives valuable information on the percentage of the variance error caused by each level in the hierarchical model. In this study HLM was applied to a large dataset of 2,149 apartments, which included 17 variables belonging to two hierarchical levels: apartment and neighbourhood. The model obtained high goodness of fit and all the estimated variances of the parameters in HLM were lower than those calculated by OLS. It can be concluded as well that no further neighbourhood variables need be added to the model to improve the goodness of fit, since almost all the residual variance can be attributed to the first hierarchical level of the model, the apartment level.

Neighbourhood effects on body constitution-A case study of Hong Kong

Traditional Chinese Medicine (TCM) has long perceived environment as an integral part of the development of body constitution, which is a personal state of health closely related to disease presence. Despite of the ever-growing studies on the clinical effectiveness of TCM and the scientific linking between body constitution and diseases, the geographical influence on body constitution has yet remained an unexplored territory. This study sought to investigate whether the neighbourhood environment is relevant to the composition of body type of a population through statistical multilevel and Geographic Information Systems modelling. The analysis comprised 3277 participants who had completed their body type assessment between 2009 and 2012 inclusive. The multilevel analysis also took simultaneous accounts of both individual-level (gender, age, BMI, type of housing) and area-level (percent greenery, percent road surface, total road intersection, sky view factor, temperature, relative humidity, rainfall and social deprivation index) characteristics to explain geographical variation by body types. Significant random or place effects (p < 0.001) were identified in the multilevel models. The spatial variation of body constitution involved the dynamic interplay between individual and environmental factors. The findings amassed the first scientific indications to back the common belief that place does play a role in the development of body constitution and is worthy of further investigation. By considering spatial and personal attributes simultaneously, the study can yield valuable insights into the patterning of area variation in body constitution and disease presence.

HIV Infection Among People Who Inject Drugs in the United States: Geographically Explained Variance Across Racial and Ethnic Groups

OBJECTIVES

We explored how variance in HIV infection is distributed across multiple geographical scales among people who inject drugs (PWID) in the United States, overall and within racial/ethnic groups.

METHODS

People who inject drugs (n = 9077) were recruited via respondent-driven sampling from 19 metropolitan statistical areas (MSAs) for the Centers for Disease Control and Prevention's 2009 National HIV Behavioral Surveillance system. We used multilevel modeling to determine the percentage of variance in HIV infection explained by zip codes, counties, and MSAs where PWID lived, overall and for specific racial/ethnic groups.

RESULTS

Collectively, zip codes, counties, and MSAs explained 29% of variance in HIV infection. Within specific racial/ethnic groups, all 3 scales explained variance in HIV infection among non-Hispanic/Latino White PWID (4.3%, 0.2%, and 7.5%, respectively), MSAs explained variance among Hispanic/Latino PWID (10.1%), and counties explained variance among non-Hispanic/Latino Black PWID (6.9%).

CONCLUSIONS

Exposure to potential determinants of HIV infection at zip codes, counties, and MSAs may vary for different racial/ethnic groups of PWID, and may reveal opportunities to identify and ameliorate intraracial inequities in exposure to determinants of HIV infection at these geographical scales.

Graphic pathogeographies

This paper focuses on the graphic pathogeographies in David B.'s Epileptic and David Small's Stitches: A Memoir to highlight the significance of geographic concepts in graphic novels of health and disease. Despite its importance in such works, few scholars have examined the role of geography in their narrative and structure. I examine the role of place in Epileptic and Stitches to extend the academic discussion on graphic novels of health and disease and identify how such works bring attention to the role of geography in the individual's engagement with health, disease, and related settings.

Translating multilevel theory into multilevel research: challenges and opportunities for understanding the social determinants of psychiatric disorders

INTRODUCTION

The observation that features of the social environment, including family, school, and neighborhood characteristics, are associated with individual-level outcomes has spurred the development of dozens of multilevel or ecological theoretical frameworks in epidemiology, public health, psychology, and sociology, among other disciplines. Despite the widespread use of such theories in etiological, intervention, and policy studies, challenges remain in bridging multilevel theory and empirical research.

METHODS

This paper set out to synthesize these challenges and provide specific examples of methodological and analytical strategies researchers are using to gain a more nuanced understanding of the social determinants of psychiatric disorders, with a focus on children's mental health. To accomplish this goal, we begin by describing multilevel theories, defining their core elements, and discussing what these theories suggest is needed in empirical work. In the second part, we outline the main challenges researchers face in translating multilevel theory into research. These challenges are presented for each stage of the research process. In the third section, we describe two methods being used as alternatives to traditional multilevel modeling techniques to better bridge multilevel theory and multilevel research. These are (1) multilevel factor analysis and multilevel structural equation modeling; and (2) dynamic systems approaches.

CONCLUSIONS

Through its review of multilevel theory, assessment of existing strategies, and examination of emerging methodologies, this paper offers a framework to evaluate and guide empirical studies on the social determinants of child psychiatric disorders as well as health across the life course.

Accessibility and utilization patterns of a mobile medical clinic among vulnerable populations

We mapped mobile medical clinic (MMC) clients for spatial distribution of their self-reported locations and travel behaviors to better understand health-seeking and utilization patterns of medically vulnerable populations in Connecticut. Contrary to distance decay literature, we found that a small but significant proportion of clients was traveling substantial distances to receive repeat care at the MMC. Of 8404 total clients, 90.2% lived within 5 miles of a MMC site, yet mean utilization was highest (5.3 visits per client) among those living 11-20 miles of MMCs, primarily for those with substance use disorders. Of clients making >20 visits, 15.0% traveled >10 miles, suggesting that a significant minority of clients traveled to MMC sites because of their need-specific healthcare services, which are not only free but available at an acceptable and accommodating environment. The findings of this study contribute to the important research on healthcare utilization among vulnerable population by focusing on broader dimensions of accessibility in a setting where both mobile and fixed healthcare services coexist.

Welfare state regimes, gender, and depression: a multilevel analysis of middle and high income countries

Using the 2002 World Health Survey, we examine the association between welfare state regimes, gender and mental health among 26 countries classified into seven distinct regimes: Conservative, Southeast Asian, Eastern European, Latin American, Liberal, Southern/Ex-dictatorship, and Social Democratic. A two-level hierarchical model found that the odds of experiencing a brief depressive episode in the last 12 months was significantly higher for Southern/Ex- dictatorship countries than for Southeast Asian (odds ratio (OR) = 0.12, 95% confidence interval (CI) 0.05-0.27) and Eastern European (OR = 0.36, 95% CI 0.22-0.58) regimes after controlling for gender, age, education, marital status, and economic development. In adjusted interaction models, compared to Southern/Ex-dictatorship males (reference category), the odds ratios of depression were significantly lower among Southeast Asian males (OR = 0.16, 95% CI 0.08-0.34) and females (OR = 0.23, 95% CI 0.10-0.53) and Eastern European males (OR = 0.41, 95% CI 0.26-0.63) and significantly higher among females in Liberal (OR = 2.00, 95% CI 1.14-3.49) and Southern (OR = 2.42, 95% CI 1.86-3.15) regimes. Our results highlight the importance of incorporating middle-income countries into comparative welfare regime research and testing for interactions between welfare regimes and gender on mental health.

Within the boundary fence: an investigation into the perceptions of men's experience of depression in rural and remote areas of Australia

This is a study exploring perceptions of men's experience of depression in rural and remote areas of Australia. The purpose of this investigation was to generate 'new' information that can inform models of diagnosis and primary care for the treatment of depression in men in rural and remote areas. Men and women were recruited from two North Queensland sites to participate in semistructured interviews in both an individual and focus group format and completing a series of questionnaires. A combination of grounded theory and content analysis was adopted to analyse the qualitative data, and develop theory around men's experience of depression in rural and remote areas. The findings of this study suggest that men's experience of depression within a rural context is defined by a process of 'internal compound' whereupon emotional distress can represent itself in avoidant and dulling behaviours along with self-reliant attempts to 'fix' the situation. From this study a language has been provided to give explanation to the experience of depression in men in rural and remote areas. The findings of this study have implications for, and provide opportunity for reform in, how we approach the recognition, diagnosis and treatment of depression for men in rural and remote areas.

Socioeconomic and geographic patterning of smoking behaviour in Canada: a cross-sectional multilevel analysis

OBJECTIVE

To describe the socioeconomic and geographic distribution of smoking behaviour in Canada among 19,383 individuals (51% women) aged 15-85 years.

METHODS

Current smoking and quitting were modeled using standard and multilevel logistic regression. Markers of socioeconomic status (SES) were education and occupation. Geography was defined by Canadian Provinces.

RESULTS

The adjusted prevalence of current smoking was 20.2% (95% confidence interval [CI]: 18.8-21.7) and 63.7% (95% CI: 61.1-66.3) of ever smokers had quit. Current smoking decreased and quitting increased with increasing SES. The adjusted prevalence of current smoking was 32.8% (95% CI: 28.4-37.5) among the least educated compared to 11.0% (95% CI: 8.9-13.4) for the highest educated. Among the least educated, 53.0% (95% CI: 46.8-59.2) had quit, rising to 68.7% (95% CI: 62.7-74.1) for the most educated. There was substantial variation in current smoking and quitting at the provincial level; current smoking varied from 17.9% in British Columbia to 26.1% in Nova Scotia, and quitting varied from 57.4% in Nova Scotia to 67.8% in Prince Edward Island. Nationally, increasing education and occupation level were inversely associated with current smoking (odds ratio [OR] 0.64, 95% CI: 0.60-0.68 for education; OR 0.82, 95% CI: 0.77-0.87 for occupation) and positively associated with quitting (OR 1.27, 95% CI: 1.16-1.40 for education; OR 1.20, 95% CI: 1.12-1.27 for occupation). These associations were consistent in direction across provinces although with some variability in magnitude.

CONCLUSION

Our findings indicate that socioeconomic inequalities in smoking have persisted in Canada; current smoking was less likely and quitting was more likely among the better off groups and in certain provinces. Current prevention and cessation policies have not been successful in improving the situation for all areas and groups. Future efforts to reduce smoking uptake and increase cessation in Canada will need consideration of socioeconomic and geographic factors to be successful.

Neighbourhood social capital and individual self-rated health in Wales

Although neighbourhood social capital can be beneficial for individual health, supporting evidence in the UK is scant. We aim to find the net effect of neighbourhood social capital and deprivation on individual health beyond sociodemographic composition of neighbourhood. We propose a multilevel path analytic model of health to delineate complex pathways involving neighbourhoods (measured as local super output area) and individuals. Analysis of the most recent data containing independent measures of neighbourhood social capital shows that neighbourhood social capital appears to be associated with benefits in some aspects of individual health in the Welsh setting. The improvement stands beyond individual determinants and neighbourhood deprivation. Social scientists and public health officials have reason to continue focusing on the neighbourhoods as well as the individuals to improve the health of the population.

Revisiting causal neighborhood effects on individual ischemic heart disease risk: a quasi-experimental multilevel analysis among Swedish siblings

Neighborhood socioeconomic disadvantage is associated to increased individual risk of ischemic heart disease (IHD). However, the value of this association for causal inference is uncertain. Moreover, neighborhoods are often defined by available administrative boundaries without evaluating in which degree these boundaries embrace a relevant socio-geographical context that condition individual differences in IHD risk. Therefore, we performed an analysis of variance, and also compared the associations obtained by conventional multilevel analyses and by quasi-experimental family-based design that provides stronger evidence for causal inference. Linking the Swedish Multi-Generation Register to several other national registers, we analyzed 184,931 families embracing 415,540 full brothers 45-64 years old in 2004, and residing in 8408 small-area market statistics (SAMS) considered as "neighborhoods" in our study. We investigated the association between low neighborhood income (categorized in groups by deciles) and IHD risk in the next four years. We distinguished between family mean and intrafamilial-centered low neighborhood income, which allowed us to investigate both unrelated individuals from different families and full brothers within families. We applied multilevel logistic regression techniques to obtain odds ratios (OR), variance partition coefficients (VPC) and 95% credible intervals (CI). In unrelated individuals a decile unit increase of low neighborhood income increased individual IHD risk (OR = 1.04, 95% CI: 1.03-1.07). In the intrafamilial analysis this association was reduced (OR = 1.02, 95% CI: 1.02-1.04). Low neighborhood income seems associated with IHD risk in middle-aged men. However, despite the family-based design, we cannot exclude residual confounding by genetic and non-shared environmental factors. Besides, the low neighborhood level VPC = 1.5% suggest that the SAMS are a rather inappropriate construct of the socio-geographic context that conditions individual variance in IHD risk. In contrast the high family level VPC = 20.1% confirms the relevance of the family context for understanding IHD risk.

Bringing the individual back to small-area variation studies: a multilevel analysis of all-cause mortality in Andalusia, Spain

We performed a multilevel analysis (including individuals, households, census tracts, municipalities and provinces) on a 10% sample (N=230,978) from the Longitudinal Database of the Andalusian Population (LDAP). We aimed to investigate place effects on 8-year individual mortality risk. Moreover, besides calculating association (yielding odds ratios, ORs) between area socio-economic circumstances and individual risk, we wanted to estimate variance and clustering using the variance partition coefficient (VPC). We explicitly proclaim the relevance of considering general contextual effects (i.e. the degree to which the context, as a whole, affects individual variance in mortality risk) under at least two circumstances. The first of these concerns the interpretation of specific contextual effects (i.e. the association between a particular area characteristic and individual risk) obtained from multilevel regression analyses. The second involves the interpretation of geographical variance obtained from classic ecological spatial analyses. The so-called "ecological fallacy" apart, the lack of individual-level information renders geographical variance unrelated to the total individual variation and, therefore, difficult to interpret. Finally, we stress the importance of considering the familial household in multilevel analyses. We observed an association between percentage of people with a low educational level in the census tract and individual mortality risk (OR, highest v. lowest quintile=1.14; 95% confidence interval, CI 1.08-1.20). However, only a minor proportion of the total individual variance in the probability of dying was at the municipality (M) and census tract (CT) levels (VPC(M)=0.2% and VPC(CT)=0.3%). Conversely, the household (H) level appeared much more relevant (VPC(H)=18.6%) than the administrative geographical areas. Without considering general contextual effects, both multilevel analyses of specific contextual effects and ecological studies of small-area variation may provide a misleading picture that overstates the role of administrative areas as contextual determinants of individual differences in mortality.

Road traffic crashes and the protective effect of road curvature over small areas

Road bends are known to cause traffic crashes, but the hypothesis in this study was that small geographical areas with many road bends have less, not more, road casualties than comparable areas with fewer bends. Data on road crashes involving fatal, serious and slight casualties in 571 wards in Eastern England were examined against four measures of average road curvature (mean angle per bend, cumulative angle per km, number of bends per km and ratio of road distance to straight distance) using regression analysis. Taking account of other risk factors, measures of average road curvature in wards were negatively associated with crash numbers, especially for fatal crashes. The strongest associations were with the cumulative angle turned per km. The results add to evidence suggesting that road casualty risk effects vary with geographical scale. Although individual road bends might be hazardous, frequent bends have a protective effect over a few kilometres of road.

Distal and variably proximal causes: education, obesity, and health

Medical sociologists hold that social conditions generate disparities across a host of health conditions through exposure to a variety of more proximate risk factors. Though distal and proximal causes jointly influence disease, the nature of risk accumulation may differ appreciably by the link of a proximal cause to the outcome in question. This paper employs a representative sample of over 3000 American older adults to examine whether position in the educational gradient amplifies the effect of obesity on two health outcomes. Results indicate that educational inequalities amplify the effect of high body mass index on disability (unstandardized coefficients across education groups range from -.05 [ns] to .26 [p < .01] among overweight respondents yet reach .17 [ns] to .73 [p < .001] among severely obese adults), but fail to amplify the consequences of severe obesity in the case of C-reactive protein (CRP) levels. Instead, educational gradients in CRP are most pronounced at lower levels of body mass. Sex-specific analyses further clarify these patterns, as the connections between CRP and body mass are particularly strong among women. We conclude that risk accumulation processes differ based on the proximity of causes to the health outcome under examination.

Low socioeconomic status and body mass index as risk factors for inflammation in older adults: conjoint influence on C-reactive protein?

BACKGROUND

Low socioeconomic status and high levels of body mass are two risk factors for elevated C-reactive protein, a biomeasure signifying inflammation. Though past research identifies the additive effect of these particular risk factors, this study examines their interactive effects to uncover whether body mass index exacerbates or levels the detrimental consequences of occupying a disadvantaged social position.

METHODS

This study employs a representative survey of American adults, aged 57-84 years, using self-reported and laboratory measures. Additive and multiplicative linear regression models are used to analyze logged C-reactive protein levels (mg/l) drawn from assayed blood samples.

RESULTS

Significant negative interactions were observed between body mass index and two indicators of low socioeconomic status on C-reactive protein, reflecting a cross-over effect.

CONCLUSIONS

The results demonstrated the importance of a multiplicative model for studying risk factor accumulation and identify low socioeconomic status as an early and primary risk factor for elevated C-reactive protein.

Neighbourhood deprivation and regional inequalities in self-reported health among Canadians: are we equally at risk?

Individual-level data from the Canadian Community Health Survey was combined with area-level data from the 2001 Canada Census to explore the relationship between neighbourhood deprivation and regional inequalities in self-reported health (n=120,290). While neighbourhood deprivation was a significant predictor of fair/poor health in all geographic regions (OR=1.11; 95% CI: 1.08, 1.14), living on the Atlantic and Pacific coasts exacerbated the detrimental effects of neighbourhood deprivation on the perceived health of respondents (OR=1.21; 1.28). By failing to explore regional variations in risk, we could fail to identify areas where provincial policies may interact with neighbourhood factors to reinforce health inequalities amongst deprived communities.

Social inequalities in alcohol consumption in the Czech Republic: a multilevel analysis

Czech Republic traditionally ranks among the countries with the highest alcohol, consumption. This paper examines both risk and protective factors for frequent of alcohol, consumption in the Czech population using multilevel analysis. Risk factors were measured at the, individual level and at the area level. The individual-level data were obtained from a survey for a, sample of 3526 respondents aged 18-64 years. The area-level data were obtained from the Czech, Statistical Office. The group most inclinable to risk alcohol consumption and binge drinking are mainly, men, who live as single, with low education and also unemployed. Only the variable for divorce rate, showed statistical significance at both levels, thus the individual and the aggregated one. No cross-level interactions were found to be statistically significant.

Socio-geographic mobility and health status: a longitudinal analysis using the National Population Health Survey of Canada

The paper reviews arguments that associations between small area socio-economic conditions and individual health are likely to vary according to the type of health condition considered. We comment on the importance of longitudinal research to examine how far area conditions predict later health outcomes, and also how far area variations in health may result from selective migration processes predicted by health status. Using data for 1996 and 2002, from the National Population Health Survey of Canada, linked to small area data on social and on material deprivation in the area of residence for 6950 survey respondents at the two time points, we report on analyses to address these questions. The area measures of material and social deprivation were previously developed by Pampalon and colleagues at the Institut National de Santé Publique de Québec and related to the dissemination area matching the informant's postal code. The health outcomes considered were restriction of activity due to chronic conditions and psychological distress. Our findings suggest that individuals living in materially deprived areas in 2002 were more likely to be affected by health conditions resulting in restriction of activity. Prevalence of psychological distress was higher in areas with greater social deprivation in 2002. Most of these area differences were attenuated when adjustment was made for individual socio-demographic characteristics. Measures recorded in 1996 of individual characteristics and measures of deprivation for area of residence were used to predict change in health outcomes by 2002. Several individual factors (sex, age group, income, household composition) in 1996 were predictive of later health outcomes. After controlling for these individual characteristics the only significant association between health change and area deprivation was with development of restricted activity, which was more common among people who, in 1996, had lived in areas that ranked moderately high on material deprivation. We also report some evidence for selective migration effects, though these mainly seem to operate indirectly via socio-economic characteristics that predict both health outcomes and differential migration patterns. The clearest evidence on this point is for those in with psychological distress in 1996, who were particularly likely to move to an area which was more socially or materially deprived by 2002. This supports the idea that area differences in psychological distress are partly the result of selective migration effects.

Smoking in context - a multilevel approach to smoking among females in Helsinki

Background

Smoking is associated with disadvantage. As people with lower social status reside in less privileged areas, the extent of contextual influences for smoking remains unclear. The aims were to examine the spatial patterning of daily smoking within the city of Helsinki, to analyse whether contextual variation can be observed and which spatial factors associate with current daily smoking in the employed female population.

Methods

Data from a cross-sectional questionnaire were collected for municipal employees of Helsinki (aged 40–60 years). The response rate was 69%. As almost 4/5 of the employees are females, the analyses were restricted to women (n = 5028). Measures included smoking status, individual level socio-demographic characteristics (age, occupational social class, education, family type) and statistical data describing areas in terms of social structure (unemployment rate, proportion of manual workers) and social cohesion (proportions of single parents and single households). Logistic multilevel analysis was used to analyse data.

Results

After adjusting for the individual-level composition, smoking was significantly more prevalent according to all social structural and social cohesion indicators apart from the proportion of manual workers. For example, high unemployment in the area of domicile increased the risk of smoking by almost a half. The largest observed area difference in smoking – 8 percentage points – was found according to the proportion of single households.

Conclusion

The large variation in smoking rates between areas appears mainly to result from variation in the characteristics of residents within areas. Yet, living in an area with a high level of unemployment appears to be an additional risk for smoking that cannot be fully accounted for by individual level characteristics even in a cohort of female municipal employees.

Non-communicable disease and injury-related mortality in rural and urban places of residence: a comparison between Canada and Australia

BACKGROUND

Few published studies looking at cross-national comparisons of rural-urban health status are available. As a first step towards addressing the lack of information on how rural populations in Canada compare with rural populations elsewhere in the world, this paper examines and contrasts Canadian mortality risks of selected diseases in rural and urban areas with those of Australia.

METHODS

Age-standardized mortality ratios for selected causes of deaths were calculated at the national level and broken down into place of residence categories using country-specific definitions of rurality (Metropolitan Influence Zones in Canada and the Australian Standard Geographical Classification [ASGC] Remoteness in Australia).

RESULTS

Patterns of rural-urban mortality risk were mostly similar in both countries. However, depending on the causes of death examined, important differences were found. Mortality from motor vehicle accidents, suicide and a few cancer sites showed similar urban-rural gradients in both Canada and Australia. Notable differences were found for diabetes, all cancers combined, as well as lung and colorectal cancer. Rural Australians were at higher risk of dying from these diseases than their urban counterparts, whereas rural Canadians were at lower risk than urban Canadians.

DISCUSSION

Overall, the patterns that have emerged from this comparison of Canadian and Australian mortality risks suggest that health status disparities between rural and urban populations are not limited to a specific country or region of the world. However, there are also important differences between the two countries, as the geographic mortality patterns varied according to sex and according to disease category. This analysis is an initial step in promoting discussion of rural health in an international context.

Health inequalities and place: A theoretical conception of neighbourhood

In the past 10 years, interest in studying the relationship between area of residence and health has grown. During this period empirical relations between place and health have been observed at a variety of spatial scales, from census tracts to administrative units in metropolitan areas to whole regions, and for a variety of health outcomes. Despite the richness of the data, there are relatively few publications offering theoretical explanations for these observations, and a sound conception of place itself is still lacking. Using place as a relational space linked to where people live, work and play, this paper conceptualises the nature of neighbourhoods as they contribute to the local production of health inequalities in everyday life. In reference to Giddens' structuration theory, we propose that neighbourhoods essentially involve the availability of, and access to, health-relevant resources in a geographically defined area. Taking inspiration from the work of Godbout on informal reciprocity, we further propose that such availability and access are regulated according to four different sets of rules: proximity, prices, rights, and informal reciprocity. Our theoretical framework suggests that these rules give rise to five domains, the physical, economic, institutional, local sociability, and community organisation domains which cut across neighbourhood environments through which residents may acquire resources that shape their lifecourse trajectory in health and social functioning.

Geographical inequalities in health in New Zealand, 1980-2001: the gap widens

OBJECTIVE

To monitor geographical inequalities in health in New Zealand during the period 1980 to 2001, a time of rapid social and economic change in society.

METHODS

Age-standardised mortality rates were calculated using mortality records aggregated to a consistent set of geographical areas (the 2001 District Health Boards) for the periods 1980-82, 1985-87, 1990-92, 1995-97 and 1999-2001. In addition, the Relative Index of Inequality (RII) was calculated for each period to provide a robust measure of mortality rates over time.

RESULTS

Although overall mortality rates have declined through the period 1980 to 2001, the reduction has not been consistent for all areas of New Zealand. Indeed for a small number of DHBs, mortality rates have increased slightly. There has been an increase in the geographical inequalities in health as measured by the RII between each time period except for between 1986 and 1991, where there was a small reduction.

CONCLUSIONS

At the start of the 21st century, geographical inequalities in health in New Zealand have reached very high levels and continue to increase. The excess mortality for the worst areas in New Zealand increased from 15% in 1981 to 25% in 2000. If policy makers are committed to reducing health inequalities then more redistributive economic policies are required.

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.

Geographical variation in the prevalence of problematic substance use in Canada

OBJECTIVE

The prevalence of substance-related problems has been shown to vary between Canadian provinces, but little else is known about the pattern of geographical differences. In this study, we modelled these differences, using methods of spatial analysis, and attempted to determine whether they are explained by known risk factors.

METHODS

We used data from Cycle 1.2 of the Canadian Community Health Survey. We tested interprovincial differences, before and after adjustment for covariates, and also examined differences between urban areas. We then used interpolation techniques to model variation in prevalence without reference to administrative boundaries. Finally, we performed a spatial cluster scan for areas of heightened prevalence.

RESULTS

The prevalence of problematic substance use is lower in Ontario and Quebec than in the rest of the country. This pattern is due principally to low prevalence in Toronto, Montreal, and surrounding areas. Prevalence is higher in mid-sized cities than in larger ones or in rural areas. Problematic substance use shows a fairly high degree of spatial clustering, especially within major cities. Interprovincial differences and clustering are generally not explained by known risk factors.

CONCLUSIONS

The pattern of large-scale differences is consistent with existing research and is probably part of a larger disparity among regions of Canada. The persistence of variation after adjustment for covariates suggests the influence of unmeasured, geographically varying factors, of which there are several candidates, including latitude and immigrant settlement patterns.

Understanding the relative influence of neighborhood, family, and youth on adolescent drug use

In the United States, a variety of programs have been developed to prevent substance use among youth. These programs often target youth directly, and may also have components that address the relational influence of families, schools, and communities. We discuss clustering of youth marijuana use within and between households and neighborhoods. As often discussed in the literature, we consider analyzing "components of variance" in a hierarchical sample design with two or more levels. With a continuous outcome variable, the estimated relative size of variance components at each level can be interpreted as its relative "importance." We estimate variance components when the outcome is dichotomous, and find that for the use of marijuana in the past year, the role of the individual (individual adolescent vs. role of household vs. role of neighborhood) is quite prominent (79% of variation). A similar result is observed for the continuous scale variable of individual positive attitudes toward drug use (83%). For continuous constructs related to either household (parental monitoring) or neighborhood (neighborhood disorganization) the majority of variation still occurs at the individual level (67% and 51%, respectively), although they reveal significant percent variation (about 30%) at the corresponding family or neighborhood levels as well. We discuss the use of variance component methodology and the relevance for prevention programs.

A simultaneous analysis of neighbourhood and childhood socio-economic environment with self-assessed health and health-related behaviours

Childhood socio-economic environment and neighbourhood socio-economic environment later in life are closely related. However, few studies have considered their effects simultaneously. Using cross-sectional data of approximately 8000 respondents in 86 neighbourhoods in the city of Eindhoven, The Netherlands, we study associations of both determinants with self-assessed health, smoking, alcohol consumption and overweight. Growing up in a low socio-economic environment increased the probability to live a more deprived neighbourhood in adulthood. Controlling for individual socio-economic characteristics, both childhood and neighbourhood socio-economic environment were related to smoking and overweight, but not with excessive alcohol consumption. Associations between childhood socio-economic environment and smoking and overweight are still substantial after controlling for neighbourhood socio-economic environment. Similarly, neighbourhood inequalities in smoking and overweight remain substantial after controlling for childhood socio-economic environment.