Exceptions to the rule: Healthy deprived areas and unhealthy wealthy areas

Does better than expected life expectancy in areas of disadvantage indicate health resilience? Stakeholder perspectives and possible explanations

Some places have better than expected health trends despite being disadvantaged in other ways. Thematic analysis of qualitative data from stakeholders (N = 25) in two case studies of disadvantaged local authorities the North West and South East of England assessed explanations for the localities' apparent health resilience. Participants identified ways of working that might contribute to improved life expectancy, such as partnering with third sector, targeting and outcome driven action. Stakeholders were reluctant to assume credit for better-than-expected health outcomes. External factors such as population change, national politics and finances were considered crucial. Local public health stakeholders regard their work as important but unlikely to cause place-centred health resilience.

Conceptualizing multilevel research designs of resilience

Resilience is a broad concept allowing us to understand health and well-being as a multidimensional process that continually grapples with a multitude of stressors. Currently, there are efforts across disciplines and scales to develop this concept of resilience. Unfortunately, individual and community resilience efforts tend to only abstractly conceptualize macroscale dynamics while social-ecological efforts tend to treat individuals and communities as nonindependent components of these macroscale dynamics. Combining these efforts is needed to create a robust dialog around resilience. This paper reviews and synthesizes social-ecological, community, and individual resilience literature by proposing longitudinal, multilevel models of resilience. In developing these models, some of the issues that have prevented synthesizing these literatures are resolved, including generalizability issues, within system variation, and the operationalization of social and natural and micro- and macroscale factors. Three brief examples are presented to elaborate on the utility of the multilevel model of resilience.

Immigrant and ethnic neighbourhood concentration and reduced child developmental vulnerability: A Canadian cohort study

INTRODUCTION

Studies have consistently demonstrated a gradient between median neighbourhood income and child developmental outcomes. By investigating statistical outliers-neighbourhoods with children exhibiting less or more developmental vulnerability than that predicted by median neighbourhood income-there is an opportunity to identify other neighbourhood characteristics that may be enhancing or impeding early childhood development.

OBJECTIVE

Testing a variety of neighbourhood factors, including immigrant or ethnic concentration and characteristics of structural disadvantage (proportion of social assistance recipients, homes in need of major repair, residents with high school education only, lone parent families, and residents moving in the last year) we sought to identify factors associated with more or less developmental vulnerability than that predicted by median neighbourhood income, for young children.

METHODS

For this cross-sectional study we used validated Early Development Instrument (EDI) data (2003-2013) linked to demographic and socioeconomic Census and Tax Filer data for 98.3% of Canadian neighbourhoods (n=2,023). The purpose of the instrument is to report, at a population-level, children's school readiness. Children's developmental vulnerability was assessed in five domains (physical health and well-being, emotional maturity, social competence, language and cognitive development, and communication and general knowledge) in relation to the 10th percentile from a national normative sample. Levels of children's neighbourhood vulnerability were determined per domain, as percent of children vulnerable at a given domain. Neighbourhoods were grouped into three cohorts, those having lower than predicted, as predicted, or higher than predicted children's vulnerability according to neighbourhood median income. Using multivariable binary logistic regression we modelled the association between select neighbourhood characteristics and neighbourhoods with lower or higher than predicted vulnerability per domain, compared to neighbourhoods with predicted vulnerability. This allowed us to determine neighbourhood characteristics associated with better or worse child developmental outcomes, at a neighbourhood-level, than that predicted by income.

RESULTS

In neighbourhoods with less child developmental vulnerability than that predicted by income, high or low immigrant concentration and ethnic homogeneity was associated with less vulnerability in physical (adjusted odds ratio (aOR) 1.66, 95% CI: 1.43, 1.94), social (aOR 1.30, 95% CI: 1.11, 1.51), and communication domains (aOR 1.24, 95% CI: 1.03, 1.47) compared to neighbourhoods with vulnerability concordant with income. Neighbourhood ethnic homogeneity was consistently associated with less developmental vulnerability than predicted by income across all developmental domains. Neighbourhood-level structural disadvantage was strongly associated with child developmental vulnerability beyond that predicted by median neighbourhood income.

CONCLUSION

Canadian neighbourhoods demonstrating less child developmental vulnerability than that predicted by income have greater ethnic and ethnic-immigrant homogeneity than neighbourhoods with child developmental vulnerability concordant with income. Neighbourhood social cohesion and cultural identity may be contributing factors. Neighbourhood structural disadvantage is associated with poorer early childhood development, over and above that predicted by neighbourhood income. Neighbourhood-level policy and programming should address income and non-income related barriers to healthy child development.

Identification of Resilient and At-Risk Neighborhoods for Cardiovascular Disease Among Black Residents: the Morehouse-Emory Cardiovascular (MECA) Center for Health Equity Study

INTRODUCTION

Despite the growing interest in place as a determinant of health, areas that promote rather than reduce cardiovascular disease (CVD) in blacks are understudied. We performed an ecologic analysis to identify areas with high levels of CVD resilience and risk among blacks from a large southern, US metropolitan area.

METHODS

We obtained census tract-level rates of cardiovascular deaths, emergency department (ED) visits, and hospitalizations for black adults aged 35 to 64 from 2010 through 2014 for the Atlanta, Georgia, metropolitan area. Census tracts with substantially lower rates of cardiovascular events on the basis of neighborhood socioeconomic status were identified as resilient and those with higher rates were identified as at risk. Logistic regression was used to estimate the odds ratios (OR) and 95% confidence intervals (CIs) of being classified as an at-risk versus resilient tract for differences in census-derived measures.

RESULTS

We identified 106 resilient and 121 at-risk census tracts, which differed in the rates per 5,000 person years of cardiovascular outcomes (mortality, 8.13 vs 13.81; ED visits, 32.25 vs 146.3; hospitalizations, 26.69 vs 130.0), despite similarities in their median black income ($46,123 vs $45,306). Tracts with a higher percentage of residents aged 65 or older (odds ratio [OR], 2.29; 95% CI, 1.41-3.85 per 5% increment) and those with incomes less than 200% of the federal poverty level (OR, 1.19; 95% CI, 1.02-1.39 per 5% increment) and greater Gini index (OR, 1.56; 95% CI, 1.19- 2.07 per 0.05 increment) were more likely to be classified as at risk than resilient neighborhoods.

DISCUSSION

Despite matching on median income level, at-risk neighborhoods for CVD among black populations were associated with a higher prevalence of socioeconomic indicators of inequality than resilient neighborhoods.

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 variation in nitrogen dioxide concentrations and cardiopulmonary hospital admissions

BACKGROUND

Air pollution episodes are associated with increased cardiopulmonary hospital admissions. Cohort studies showed associations of spatial variation in traffic-related air pollution with respiratory and cardiovascular mortality. Much less is known in particular about associations with cardiovascular morbidity. We explored the relation between spatial variation in nitrogen dioxide (NO₂) concentrations and cardiopulmonary hospital admissions.

METHODS

This ecological study was based on hospital admissions data (2001-2004) from the National Medical Registration and general population data for the West of the Netherlands (population 4.04 million). At the 4-digit postcode area level (n=683) associations between modeled annual average outdoor NO₂ concentrations and hospital admissions for respiratory and cardiovascular causes were evaluated by linear regression with the log of the postcode-specific percentage of subjects that have been admitted at least once during the study period as the dependent variable. All analyses were adjusted for differences in composition of the population of the postcode areas (age, sex, income).

RESULTS

At the postcode level, positive associations were found between outdoor NO₂ concentrations and hospital admission rates for asthma, chronic obstructive pulmonary disease (COPD), all cardiovascular causes, ischemic heart disease and stroke (e.g. adjusted relative risk (95% confidence interval) for the second to fourth quartile relative to the first quartile of exposure were 1.87 (1.46-2.40), 2.34 (1.83-3.01) and 2.81 (2.16-3.65) for asthma; 1.44 (1.19-1.74), 1.50 (1.24-1.82) and 1.60 (1.31-1.96) for COPD). Associations remained after additional (indirect) adjustment for smoking (COPD admission rate) and degree of urbanization.

CONCLUSIONS

Our study suggests an increased risk of hospitalization for respiratory and cardiovascular causes in areas with higher levels of NO₂. Our findings add to the currently limited evidence of a long-term effect of air pollution on hospitalization. The ecological design of our study is a limitation and more studies with individual data are needed to confirm our findings.

Community Resilience throughout the Lifespan--The Potential Contribution of Healthy Elders

An increase in the exposure and predisposition of civilian populations to disasters has been recorded in the last decades. In major disasters, as demonstrated recently in Nepal (2015) and previously in Haiti (2010), external aid is vital, yet in the first hours after a disaster, communities must usually cope alone with the challenge of providing emergent lifesaving care. Communities therefore need to be prepared to handle emergency situations. Mapping the needs of the populations within their purview is a trying task for decision makers and community leaders. In this context, the elderly are traditionally treated as a susceptible population with special needs. The current study aimed to explore variations in the level of community resilience along the lifespan. The study was conducted in nine small to mid-size towns in Israel between August and November 2011 (N = 885). The Conjoint Community Resiliency Assessment Measure (CCRAM), a validated instrument for community resilience assessment, was used to examine the association between age and community resilience score. Statistical analysis included spline and logistic regression models that explored community resiliency over the lifespan in a way that allowed flexible modeling of the curve without prior constraints. This innovative statistical approach facilitated identification of the ages at which trend changes occurred. The study found a significant rise in community resiliency scores in the age groups of 61–75 years as compared with younger age bands, suggesting that older people in good health may contribute positively to building community resiliency for crisis. Rather than focusing on the growing medical needs and years of dependency associated with increased life expectancy and the resulting climb in the proportion of elders in the population, this paper proposes that active "young at heart" older people can be a valuable resource for their community.

Features of home and neighbourhood and the liveability of older South Africans

While older people live in developing countries, little is known about the relative importance of features of their communities in influencing their liveability. We examine components of home and neighbourhood among older South Africans. Linear regression analyses revealed that features of home (basic amenities, household composition, financial status and safety) and neighbourhood (ability to shop for groceries, participate in organizations and feel safe from crime) are significantly associated with life satisfaction. Approaches to liveability that are person-centred and also set within contexts beyond home and neighbourhood are needed to address boundaries between home and neighbourhood; incorporate personal resources into liveability models and import broader environmental contexts such as health and social policy.

Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset

For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

Individual and area-level socioeconomic status and their association with depression amongst community-dwelling elderly in Singapore

OBJECTIVES

Neighborhood socioeconomic status (SES) can be associated with depression. We aimed to assess prevalence of depression amongst community-dwelling elderly in a multiethnic, urban, low-SES, Asian neighborhood, comparing against a higher SES neighborhood.

METHOD

The study population involved all residents aged ≥60 years in two Singaporean housing estates comprising owner-occupied public housing (higher SES) and public rental housing (low SES) in 2012. Having lifetime prevalence of depression was defined as having a score ≥5 on the Geriatric Depression Scale-15 or a history of depression. Demographic/clinical details were collected via questionnaire. Those with depression were referred to local polyclinics. Multilevel multivariate logistic regression determined predictors of depression and depression screening.

RESULTS

Participation was 61.5% (559/909). In the low-SES community, 26.2% (104/397) had depression, compared with 14.8% (24/162) in the higher SES community. After adjusting for other sociodemographic variables, staying in a low-SES community (public rental housing) was independently a ssociated with depression [adjusted odds ratio (aOR) = 1.68, 95% confidence interval (CI) = 1.02-2.84]. Within the low-SES community, not being married (aOR = 2.27, CI = 1.35-3.70), falls (aOR = 2.72, CI = 1.59-4.67), visual impairment (aOR = 2.37, CI = 1.28-4.39), and poorer social network (aOR = 3.70, CI = 1.96-7.14) were associated with depression.

CONCLUSION

Residing in a low-SES community was independently associated with depression after controlling for individual SES.

Defying the odds: a mixed-methods study of health resilience in deprived areas of England

Previous studies have identified an area-level association between socio-economic deprivation and poorer population health. However, some recent studies have suggested that some areas exhibit better health outcomes than would be expected given their level of deprivation. This has been conceptualised in terms of 'health resilience'. This study is the first to explore area-level 'health resilience' at different geographical scales and by using mixed-methods. Regression Tree Classification was used to identify local areas (Local Authority Districts and Census Area Statistical Wards) in England that performed relatively well in terms of mortality (premature mortality 1998-2003) or morbidity (2001 Census measures of self-reported general and limiting long-term illness) despite experiencing long term deprivation (Townsend scores 1971-2001). Five Local Authority Districts (LADs) and 90 Census Area Statistical Wards (CASWARDS) exhibited 'health resilience' in terms of self-reported health, three LADs and 88 CASWARDS for limiting long-term illness, and three LADs and 62 CASWARDS for premature mortality. Potential mechanisms underpinning this resilience were explored using focus groups and in-depth interviews in one case study area in the North East of England. This suggested that for this case study area, place attachment, the natural environment and social capital may have played a role in mediating the detrimental health effects of long term deprivation. The study concludes by exploring the implications of these findings within the context of the study limitations and by outlining future avenues for research and policy.

Ethnic differences in the effect of environmental stressors on blood pressure and hypertension in the Netherlands

BACKGROUND

Evidence strongly suggests that the neighbourhood in which people live influences their health. Despite this, investigations of ethnic differences in cardiovascular risk factors have focused mainly on individual-level characteristics. The main purpose of this study was to investigate associations between neighbourhood-level environmental stressors (crime, housing density, nuisance from alcohol and drug misuse, quality of green space and social participation), and blood pressure (BP) and hypertension among different ethnic groups.

METHODS

Individual data from the Amsterdam Health Survey 2004 were linked to data on neighbourhood stressors creating a multilevel design for data analysis. The study sample consisted of 517 Dutch, 404 Turkish and 365 Moroccans living in 15 neighbourhoods in Amsterdam, the Netherlands.

RESULTS

Amongst Moroccans, high density housing and nuisance from drug misuse were associated with a higher systolic BP, while high quality of green space and social participation were associated with a lower systolic BP. High level of nuisance from drug misuse was associated with a higher diastolic BP. High quality of green space was associated with lower odds of hypertension. Amongst Turkish, high level of crime and nuisance from motor traffic were associated with a higher diastolic BP. Similar associations were observed among the Dutch group but none of the differences were statistically significant.

CONCLUSION

The study findings show that neighbourhood-level stressors are associated with BP in ethnic minority groups but were less evident in the Dutch group. These findings might imply that the higher BP levels found in some ethnic minority groups might be partly due to their greater susceptibility to the adverse neighbourhood environment in which many ethnic minority people live. Primary prevention measures targeting these neighbourhood stressors may have an impact in reducing high BP related morbidity and mortality among ethnic minority groups.