Disentangling contextual effects on cause-specific mortality in a longitudinal 23-year follow-up study: impact of population density or socioeconomic environment?

Urban densification in the Netherlands and its impact on mental health: An expert-based causal loop diagram

Urban densification is a key strategy to accommodate rapid urban population growth, but emerging evidence suggests serious risks of urban densification for individuals' mental health. To better understand the complex pathways from urban densification to mental health, we integrated interdisciplinary expert knowledge in a causal loop diagram via group model building techniques. Six subsystems were identified: five subsystems describing mechanisms on how changes in the urban system caused by urban densification may impact mental health, and one showing how changes in mental health may alter urban densification. The new insights can help to develop resilient, healthier cities for all.

Adverse childhood experiences and living in the socially deprived areas in adulthood: a cross-sectional study of the nationwide data in Japan

OBJECTIVES

This study aimed to examine whether having adverse childhood experiences (ACEs) was associated with living in a deprived area in adulthood.

METHODS

The cross-sectional study was conducted by using nation-wide data in 2022 of the Japan COVID-19 and Society Internet Survey (JACSIS). Participants were community dwelling people 18 years or older. ACEs were assessed by Japanese version of 15-items ACE measurement tool (ACE-J). Living condition was measured by Area Deprived Index (ADI) and Densely Inhabited District (DID) based on zip code. Multivariable logistic regression to analyze the associations between ADI and ACE 4 + was conducted, controlling for individual-level factors, such as age, sex, marital status, and education, as an additional analysis.

RESULTS

The total of 27,916 participants were included in the analysis. The prevalence of emotional neglect, childhood poverty, and school bullying were 38.2%, 26.5%, 20.8%, respectively. 75% of the population had one or more ACE(s). The number of ACEs was associated with significantly higher risk of living in deprived area in the adulthood (p = 0.001). ACEs were not associated with living in density area. The association between ADI and ACEs 4 + was non-significant after controlling the individual-level factors.

CONCLUSION

People with higher number of ACEs tend to live in deprived areas in adulthood. Policy makers in highly deprived areas can apply the trauma-informed approach for the community care and support, which is critical to mitigating deficit perspectives and facilitating comprehensive support for those with ACEs.

Regional inequalities of tumour size at diagnosis in Germany: An ecological study in eight federal states

There is growing recognition of the importance of the residential environment for early detection of cancer. However, few studies have investigated area socioeconomic deprivation, social capital, and rurality in combination. Therefore, we aimed to estimate mutually adjusted associations of these characteristics with tumour size at diagnosis in Germany. We included incident cases of female breast cancer, colorectal cancer, malignant melanoma, uterine cancer, and male bladder cancer, collected by the cancer registries of eight German federal states between 2010 and 2014. Using information on T status, we defined an advanced tumour size for each cancer type. Sex-specific mutually adjusted associations of area socioeconomic deprivation, social capital, and rurality with advanced tumour size and variance partition coefficients were estimated in multilevel logistic regression. Missing data of the outcome were addressed by multiple imputation. Overall, 386,223 cases were included in this analysis. High area socioeconomic deprivation was associated with advanced tumour size at diagnosis of colorectal cancer and malignant melanoma. For malignant melanoma, low social capital was associated with an advanced tumour size among females and males, while a rural settlement structure was associated with advanced tumour size among males only. Since meaningful general contextual effects were found for malignant melanoma, our results underscore that the context of an area is an important predictor of melanoma tumour size. Secondary prevention programs for this cancer type should target areas with high area socioeconomic deprivation, low social capital, and a rural settlement structure in order to reach those most vulnerable.

Urban-rural disparities in old-age mortality vary systematically with age: evidence from Germany and England & Wales

OBJECTIVES

Population aging - which tends to be more pronounced in rural than in urban areas - poses important challenges for facilitating equal opportunities for aging well and 'aging in place.' Unmet health care needs among the older rural population may result in poorer health and higher mortality, but the scientific evidence of a systematic rural mortality disadvantage at older ages is scarce. We argue that systematic urban-rural mortality differences by age may be found if the confounding effect of life expectancy is considered.

STUDY DESIGN

Nationwide population-based study.

METHODS

We draw on age- and sex-specific data for the population aged 60+ years in NUTS-3 regions in Germany (2016-2018) and LAU-1 regions in England & Wales (2017-2019). To account for the confounding effect of life expectancy, we compare age-specific mortality only across urban and rural regions with similar life expectancy levels. We quantify statistical uncertainty with bootstrapping.

RESULTS

The results show a remarkable shift from higher mortality in urban regions to higher mortality in rural regions with increasing age, when controlling for the confounding effect of life expectancy. That is, the urban mortality disadvantage is strongest for the population aged 60-79 years, whereas the pattern shifts toward a rural mortality disadvantage for the population aged 80 years and older. This pattern is present at all levels of life expectancy, for both sexes and in both countries.

CONCLUSION

The shift from urban to rural excess mortality over age suggests that regions may vary in their capability to respond to arising health issues across older ages. This systematic mortality disadvantage is of high public health relevance and should be considered in designing policies to reduce regional mortality disparities.

Assessing Trade-Offs and Optimal Ranges of Density for Life Expectancy and 12 Causes of Mortality in Metro Vancouver, Canada, 1990-2016

Background: Understanding and managing the impacts of population growth and densification are important steps for sustainable development. This study sought to evaluate the health trade-offs associated with increasing densification and to identify the optimal balance of neighbourhood densification for health. Methods: We linked population density with a 27-year mortality dataset in Metro Vancouver that includes census-tract levels of life expectancy (LE), cause-specific mortalities, and area-level deprivation. We applied two methods: (1) difference-in-differences (DID) models to study the impacts of densification changes from the early 1990s on changes in mortality over a 27-year period; and (2) smoothed cubic splines to identify thresholds of densification at which mortality rates accelerated. Results: At densities above ~9400 persons per km², LE began to decrease more rapidly. By cause, densification was linked to decreased mortality for major causes of mortality in the region, such as cardiovascular diseases, neoplasms, and diabetes. Greater inequality with increasing density was observed for causes such as human immunodeficiency virus and acquired immunodeficiency syndrome (HIV/AIDS), sexually transmitted infections, and self-harm and interpersonal violence. Conclusions: Areas with higher population densities generally have lower rates of mortality from the major causes, but these environments are also associated with higher relative inequality from largely preventable causes of death.

Is Population Density Associated with Non-Communicable Disease in Western Developed Countries? A Systematic Review

Over the last three decades, researchers have investigated population density and health outcomes at differing scale. There has not been a systematic review conducted in order to synthesise this evidence. Following the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, we systematically reviewed quantitative evidence published since 1990 on population density and non-communicable disease (NCD) within Westernised countries. Fifty-four studies met the inclusion criteria and were evaluated utilising a quality assessment tool for ecological studies. High population density appears to be associated with higher mortality rates of a range of cancers, cardiovascular disease and COPD, and a higher incidence of a range of cancers, asthma and club foot. In contrast, diabetes incidence was found to be associated with low population density. High and low population density are therefore risk markers for a range of NCDs, indicating that there are unidentified factors and mechanisms underlying aetiology. On closer examination, our synthesis revealed important and complex relationships between population density, the built environment, the nature of greenspace and man-made exposures. In light of increasing rates of morbidity and mortality, future research is required to investigate these associations in order to establish causative agents for each NCD.

An investigation of cancer survival inequalities associated with individual-level socio-economic status, area-level deprivation, and contextual effects, in a cancer patient cohort in England and Wales

BACKGROUND

People living in more deprived areas of high-income countries have lower cancer survival than those in less deprived areas. However, associations between individual-level socio-economic circumstances and cancer survival are relatively poorly understood. Moreover, few studies have addressed contextual effects, where associations between individual-level socio-economic status and cancer survival vary depending on area-based deprivation.

METHODS

Using 9276 individual-level observations from a longitudinal study in England and Wales, we examined the association with cancer survival of area-level deprivation and individual-level occupation, education, and income, for colorectal, prostate and breast cancer patients aged 20-99 at diagnosis. With flexible parametric excess hazard models, we estimated excess mortality across individual-level and area-level socio-economic variables and investigated contextual effects.

RESULTS

For colorectal cancers, we found evidence of an association between education and cancer survival in men with Excess Hazard Ratio (EHR) = 0.80, 95% Confidence Interval (CI) = 0.60;1.08 comparing "degree-level qualification and higher" to "no qualification" and EHR = 0.74 [0.56;0.97] comparing "apprenticeships and vocational qualification" to "no qualification", adjusted on occupation and income; and between occupation and cancer survival for women with EHR = 0.77 [0.54;1.10] comparing "managerial/professional occupations" to "manual/technical," and EHR = 0.81 [0.63;1.06] comparing "intermediate" to "manual/technical", adjusted on education and income. For breast cancer in women, we found evidence of an association with income (EHR = 0.52 [0.29;0.95] for the highest income quintile compared to the lowest, adjusted on education and occupation), while for prostate cancer, all three individual-level socio-economic variables were associated to some extent with cancer survival. We found contextual effects of area-level deprivation on survival inequalities between occupation types for breast and prostate cancers, suggesting wider individual-level inequalities in more deprived areas compared to least deprived areas. Individual-level income inequalities for breast cancer were more evident than an area-level differential, suggesting that area-level deprivation might not be the most effective measure of inequality for this cancer. For colorectal cancer in both sexes, we found evidence suggesting area- and individual-level inequalities, but no evidence of contextual effects.

CONCLUSIONS

Findings highlight that both individual and contextual effects contribute to inequalities in cancer outcomes. These insights provide potential avenues for more effective policy and practice.

Higher Neighborhood Population Density Is Associated with Lower Potassium Intake in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

Current U.S. dietary guidelines recommend a daily potassium intake of 3400 mg/day for men and 2600 mg/day for women. Sub-optimal access to nutrient-rich foods may limit potassium intake and increase cardiometabolic risk. We examined the association of neighborhood characteristics related to food availability with potassium intake in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). 13,835 participants completed a 24-h dietary recall assessment and had complete covariates. Self-reported potassium intake was calibrated with an objective 24-h urinary potassium biomarker, using equations developed in the SOL Nutrition & Physical Activity Assessment Study (SOLNAS, N = 440). Neighborhood population density, median household income, Hispanic/Latino diversity, and a retail food environment index by census tract were obtained. Linear regression assessed associations with 24-h potassium intake, adjusting for individual-level and neighborhood confounders. Mean 24-h potassium was 2629 mg/day based on the SOLNAS biomarker and 2702 mg/day using multiple imputation and HCHS/SOL biomarker calibration. Compared with the lowest quartile of neighborhood population density, living in the highest quartile was associated with a 26% lower potassium intake in SOLNAS (adjusted fold-change 0.74, 95% CI 0.59–0.94) and a 39% lower intake in HCHS/SOL (adjusted fold-change 0.61 95% CI 0.45–0.84). Results were only partially explained by the retail food environment. The mechanisms by which population density affects potassium intake should be further studied.

Associations of Household Income with Health-Related Quality of Life Following a Colorectal Cancer Diagnosis Varies With Neighborhood Socioeconomic Status

BACKGROUND

Existing evidence indicates household income as a predictor of health-related quality of life (HRQoL) following a colorectal cancer diagnosis. This association likely varies with neighborhood socioeconomic status (nSES), but evidence is limited.

METHODS

We included data from 1,355 colorectal cancer survivors participating in the population-based Puget Sound Colorectal Cancer Cohort (PSCCC). Survivors reported current annual household income; we measured HRQoL via the Functional Assessment of Cancer Therapy - Colorectal (FACT-C) tool. Using neighborhood data summarized within a 1-km radial buffer of Census block group centroids, we constructed a multidimensional nSES index measure. We employed survivors' geocoded residential addresses to append nSES score for Census block group of residence. With linear generalized estimating equations clustered on survivor location, we evaluated associations of household income with differences in FACT-C mean score, overall and stratified by nSES. We used separate models to explore relationships for wellbeing subscales.

RESULTS

We found lower household income to be associated with clinically meaningful differences in overall FACT-C scores [<$30K: -13.6; 95% confidence interval (CI): -16.8 to -10.4] and subscale wellbeing after a recent colorectal cancer diagnosis. Relationships were slightly greater in magnitude for survivors living in lower SES neighborhoods.

CONCLUSIONS

Our findings suggest that recently diagnosed lower income colorectal cancer survivors are likely to report lower HRQoL, and modestly more so in lower SES neighborhoods.

IMPACT

The findings from this work will aid future investigators' ability to further consider the contexts in which the income of survivors can be leveraged as a means of improving HRQoL.

The Role of Neighborhood Experiences in Psychological Distress among African American and White Smokers

Residential area characteristics and discrimination have been associated with psychological distress. Differences in these relationships across racial groups are not well understood. We examined the relative role of perceived discrimination, neighborhood problems and neighborhood cohesion/trust in explaining differences in psychological distress (indicated by anxiety and depressive symptoms) between 224 African American and 225 White smokers (income ≤ 400% federal poverty level) in a smoking cessation intervention study. Surveys were linked to US census-tract data. We conducted random intercept Poisson multi-level regression models and examined interactions between race and neighborhood experiences. African Americans had greater risk of anxiety and depressive symptoms and greater individual and neighborhood disadvantage than Whites. Controlling for objective neighborhood characteristics, when perceived discrimination and perceived neighborhood characteristics were added to the regression models the association between anxiety symptoms and race were no longer statistically significant; the association between depressive symptoms and race decreased but remained statistically significant. Lower neighborhood social cohesion/trust and greater neighborhood problems increased depressive symptoms for African Americans, but not for Whites. Perceived discrimination and neighborhood social cohesion/trust outweighed the importance of race in explaining anxiety symptoms. These findings underscore the need for multi-level interventions addressing social and environmental contexts.

Environmental correlates of chronic obstructive pulmonary disease in 96 779 participants from the UK Biobank: a cross-sectional, observational study

BACKGROUND

The role of environmental exposures in chronic obstructive pulmonary disease (COPD) remains inconclusive. We examined the association between environmental exposures (PM_2·5, greenness, and urbanicity) and COPD prevalence using the UK Biobank cohort data to identify key built environment correlates of COPD.

METHODS

In this cross-sectional, observational study we used baseline data for UK Biobank participants. Included participants were aged 39 years and older, white, had available spirometry data, and had complete data for phenotypes and exposures. COPD was defined by spirometry with the 2017 Global Initiative for Chronic Obstructive Lung Disease criteria. Environmental exposures were PM_2·5 derived from monitoring data and interpolated using land-use regression at the participants' geocoded residential addresses. Built environment metrics of residential greenness were modelled in terms of normalised difference vegetation index from remotely sensed colour infrared data within a 500 m residential catchment, and an urbanicity index derived from spatial analyses and measured with a 1 km buffer around each participant's residential address. Logistic regression models examined the associations between environmental exposures and COPD prevalence adjusting for a range of confounders. Subgroup analyses by urbanicity and effect modification by white blood cell count as an inflammatory marker were also done.

FINDINGS

We assessed 96 779 participants recruited between April 4, 2006, and Oct 1, 2010, of which 5391 participants had COPD with a prevalence of 5·6%. Each 10 μg/m³ increment in ambient PM_2·5 exposure at a participant's residential location was associated with higher odds of COPD (odds ratio 1·55, 95% CI 1·14-2·10). Among the built environment metrics, urbanicity was associated with higher odds of COPD (1·05, 1·01-1·08 per interquartile increment), whereas residential greenness was protective, being associated with lower odds of COPD (0·89, 0·84-0·93 for each interquartile increment in greenness). The results remained consistent in models of COPD defined as per lower limit of normal criteria. The highest quartile of white blood cell count was associated with lower lung function and higher COPD risk with a significant interaction between PM_2·5 and white blood cell count only in the model of lung function (p=0·0003).

INTERPRETATION

In this study of the built environment and COPD, to our knowledge the largest done in the UK, we found that exposure to ambient PM_2·5 and urbanicity were associated with a higher risk of COPD. Residing in greener areas, as measured by normalised difference vegetation index, was associated with lower odds of COPD, suggesting the potential value of urban planning and design in minimising or offsetting environmental risks for the prevention and management of COPD.

FUNDING

University of Hong Kong, UK Biobank, and UK Economic & Social Research Council.

Population Density in Hiroshima and Nagasaki Before the Bombings in 1945: Its Measurement and Impact on Radiation Risk Estimates in the Life Span Study of Atomic Bomb Survivors

In the Life Span Study cohort of atomic bomb survivors, differences in urbanicity between high-dose and low-dose survivors could confound the association between radiation dose and adverse outcomes. We obtained data on the population distribution in Hiroshima and Nagasaki before the 1945 bombings and quantified the impact of adjustment for population density on radiation risk estimates for mortality (1950-2003) and incident solid cancer (1958-2009). Population density ranged from 4,671 to 14,378 people/km2 in the urban region of Hiroshima and 5,748 to 19,149 people/km2 in the urban region of Nagasaki. Radiation risk estimates for solid cancer mortality were attenuated by 5.1% after adjustment for population density, but those for all-cause mortality and incident solid cancer were unchanged. There was no overall association between population density and adverse outcomes, but there was evidence that the association between density and mortality differed according to age at exposure. Among survivors who were 10-14 years of age in 1945, there was a positive association between population density and risk of all-cause mortality (per 5,000-people/km2 increase, relative risk = 1.053, 95% confidence interval: 1.027, 1.079) and solid cancer mortality (per 5,000-people/km2 increase, relative risk = 1.069, 95% confidence interval: 1.025, 1.115). Our results suggest that radiation risk estimates from the Life Span Study are not sensitive to unmeasured confounding by urban-rural differences.

Urban population density and mortality in a compact Dutch city: 23-year follow-up of the Dutch GLOBE study

We investigated the association and underlying pathways between urban population density and mortality in a compact mid-sized university city in the Netherlands. Baseline data from the GLOBE cohort study (N = 10,120 residents of Eindhoven) were linked to mortality after 23 years of follow up and analyzed in multilevel models. Higher population density was modestly related to increased mortality, independently of baseline socioeconomic position and health. Higher population density was related to more active transport, more perceived urban stress and smoking. Increased active transport suppressed the mortality-increasing impact of higher population density. Overall, in dense cities with good infrastructure for walking and cycling, high population density may negatively impact mortality.

Absolute rather than relative income is a better socioeconomic predictor of chronic obstructive pulmonary disease in Swedish adults

BACKGROUND

While psychosocial theory claims that socioeconomic status (SES), acting through social comparisons, has an important influence on susceptibility to disease, materialistic theory says that socioeconomic position (SEP) and related access to material resources matter more. However, the relative role of SEP versus SES in chronic obstructive pulmonary disease (COPD) risk has still not been examined.

METHOD

We investigated the association between SES/SEP and COPD risk among 667 094 older adults, aged 55 to 60, residing in Sweden between 2006 and 2011. Absolute income in five groups by population quintiles depicted SEP and relative income expressed as quintile groups within each absolute income group represented SES. We performed sex-stratified logistic regression models to estimate odds ratios and the area under the receiver operator curve (AUC) to compare the discriminatory accuracy of SES and SEP in relation to COPD.

RESULTS

Even though both absolute (SEP) and relative income (SES) were associated with COPD risk, only absolute income (SEP) presented a clear gradient, so the poorest had a three-fold higher COPD risk than the richest individuals. While the AUC for a model including only age was 0.54 and 0.55 when including relative income (SES), it increased to 0.65 when accounting for absolute income (SEP). SEP rather than SES demonstrated a consistent association with COPD.

CONCLUSIONS

Our study supports the materialistic theory. Access to material resources seems more relevant to COPD risk than the consequences of low relative income.

Regional Inequalities in Lung Cancer Mortality in Belgium at the Beginning of the 21st Century: The Contribution of Individual and Area-Level Socioeconomic Status and Industrial Exposure

Being a highly industrialized country with one of the highest male lung cancer mortality rates in Europe, Belgium is an interesting study area for lung cancer research. This study investigates geographical patterns in lung cancer mortality in Belgium. More specifically it probes into the contribution of individual as well as area-level characteristics to (sub-district patterns in) lung cancer mortality. Data from the 2001 census linked to register data from 2001-2011 are used, selecting all Belgian inhabitants aged 65+ at time of the census. Individual characteristics include education, housing status and home ownership. Urbanicity, unemployment rate, the percentage employed in mining and the percentage employed in other high-risk industries are included as sub-district characteristics. Regional variation in lung cancer mortality at sub-district level is estimated using directly age-standardized mortality rates. The association between lung cancer mortality and individual and area characteristics, and their impact on the variation of sub-district level is estimated using multilevel Poisson models. Significant sub-district variations in lung cancer mortality are observed. Individual characteristics explain a small share of this variation, while a large share is explained by sub-district characteristics. Individuals with a low socioeconomic status experience a higher lung cancer mortality risk. Among women, an association with lung cancer mortality is found for the sub-district characteristics urbanicity and unemployment rate, while for men lung cancer mortality was associated with the percentage employed in mining. Not just individual characteristics, but also area characteristics are thus important determinants of (regional differences in) lung cancer mortality.

(Un)Healthy in the City: Respiratory, Cardiometabolic and Mental Health Associated with Urbanity

BACKGROUND

Research has shown that health differences exist between urban and rural areas. Most studies conducted, however, have focused on single health outcomes and have not assessed to what extent the association of urbanity with health is explained by population composition or socioeconomic status of the area. Our aim is to investigate associations of urbanity with four different health outcomes (i.e. lung function, metabolic syndrome, depression and anxiety) and to assess whether these associations are independent of residents' characteristics and area socioeconomic status.

METHODS

Our study population consisted of 74,733 individuals (42% males, mean age 43.8) who were part of the baseline sample of the LifeLines Cohort Study. Health outcomes were objectively measured with spirometry, a physical examination, laboratory blood analyses, and a psychiatric interview. Using multilevel linear and logistic regression models, associations of urbanity with lung function, and prevalence of metabolic syndrome, major depressive disorder and generalized anxiety disorder were assessed. All models were sequentially adjusted for age, sex, highest education, household equivalent income, smoking, physical activity, and mean neighborhood income.

RESULTS

As compared with individuals living in rural areas, those in semi-urban or urban areas had a poorer lung function (β -1.62, 95% CI -2.07;-1.16), and higher prevalence of major depressive disorder (OR 1.65, 95% CI 1.35;2.00), and generalized anxiety disorder (OR 1.58, 95% CI 1.35;1.84). Prevalence of metabolic syndrome, however, was lower in urban areas (OR 0.51, 95% CI 0.44;0.59). These associations were only partly explained by differences in residents' demographic, socioeconomic and lifestyle characteristics and socioeconomic status of the areas.

CONCLUSIONS

Our results suggest a differential health impact of urbanity according to type of disease. Living in an urban environment appears to be beneficial for cardiometabolic health but to have a detrimental impact on respiratory function and mental health. Future research should investigate which underlying mechanisms explain the differential health impact of urbanity.

Cross-sectional associations between residential environmental exposures and cardiovascular diseases

BACKGROUND

Prior research examining neighbourhood effects on cardiovascular diseases (CVDs) has focused on the impact of neighbourhood socio-economic status or a few selected environmental variables. No studies of cardiovascular disease outcomes have investigated a broad range of urban planning related environmental factors. This is the first study to combine multiple neighbourhood influences in an integrated approach to understanding the association between the built and social environment and CVDs. By modeling multiple neighbourhood level social and environmental variables simultaneously, the study improved the estimation of effects by accounting for potential contextual confounders.

METHODS

Data were collected using a cross-sectional survey (n = 2411) across 87 census tracts (CT) in Toronto, Canada, and commercial and census data were accessed to characterize the residential environment. Multilevel regressions were used to estimate the associations of neighbourhood factors on the risk of CVD.

RESULTS

Exposure to violent crimes, environmental noise, and proximity to a major road were independently associated with increased odds of CVDs (p < 0.05) in the fully adjusted model. While reduced access to food stores, parks/recreation, and increased access to fast food restaurants were associated with increased odds of CVDs in partially adjusted models (p < 0.05), these associations were fully attenuated after adjusting for BMI and physical activity. Housing disrepair was not associated with CVD risk.

CONCLUSIONS

These findings illustrate the importance of measuring and modeling a broad range of neighborhood factors--exposure to violent crimes, environmental noise, and traffic, and access to food stores, fast food, parks/recreation areas--to identify specific stressors in relation to adverse health outcomes. Further research to investigate the temporal order of events is needed to better understand the direction of causation for the observed associations.

Estimating the change in life expectancy after a diagnosis of cancer among the Australian population

OBJECTIVES

Communication of relevant prognostic information is critical in helping patients understand the implications of their cancer diagnosis. We describe measures of prognosis to help communicate relevant prognostic information to improve patients' understanding of the implications of their cancer diagnosis.

SETTING

Australia-wide population-based cancer registry cohort.

PARTICIPANTS

870,878 patients aged 15-89 years diagnosed with invasive cancer between 1990 and 2007, with mortality follow-up information to December 2010.

PRIMARY AND SECONDARY OUTCOME MEASURES

Flexible parametric models were used to estimate loss of life expectancy (LOLE), remaining life expectancy (RLE) and 10-year cumulative probability of cancer-specific death (1-relative survival).

RESULTS

On average, Australians diagnosed with cancer at age 40 years faced losing an average of 11.2 years of life (95% CI 11.1 to 11.4) due to their cancer, while those diagnosed at 80 years faced losing less, an average of 3.9 years (3.9 to 4.0) because of higher competing mortality risks. In contrast, younger people had lower estimated cumulative probabilities of cancer-specific death within 10 years (40 years: 21.5%, 21.4% to 22.1%) compared with older people (80 years: 55.4%, 55.0% to 55.9%). The patterns for individual cancers varied widely, both by cancer type and by age within cancer type.

CONCLUSIONS

The LOLE and RLE measures provide complementary messages to standard relative survival estimates (expressed here in terms of cumulative probability of cancer-specific death). Importantly, relative survival per se underplays the greater absolute impact that a cancer diagnosis has at a younger age on LOLE. When presented in isolation for all cancers, it may provide a misleading impression of future mortality burden of cancer overall, and furthermore, it will obscure patterns of mortality by type and by age data within type. Alternative measures of LOLE, therefore, provide important communication about mortality risk to patients with cancer worldwide and should be incorporated into standard reporting and dissemination strategies.

The role of population change in the increased economic differences in mortality: a study of premature death from all causes and major groups of causes of death in Spain, 1980-2010

Background

An increase has been observed in differences in mortality between the richest and poorest areas of rich countries. This study assesses whether one of the proposed explanations, i.e., population change, might be responsible for this increase in Spain.

Methods

Observational study based on average income, population change and mortality at provincial level. The premature mortality rate (ages 0–74 years) was estimated for all causes and for cancer, cardiovascular disease and external causes across the period 1980–2010. In the years analysed, provinces were grouped into tertiles based on provincial income, with the mortality rate ratio (MMR) being estimated by taking the tertile of highest-income provinces as reference. Population change was then controlled for to ascertain whether it would modify the rate ratio.

Results

In all-cause mortality, the magnitude of the MRR for provinces in the poorest versus the richest tertile was 1.01 in 1980 and 1.12 in 2010; in cardiovascular mortality, the MMRs for these same years were 1.08 and 1.31 respectively; and in the case of cancer and external-cause mortality, MMR magnitude was similar in 1980 and 2010. The magnitude of the MMR remained unchanged in response to adjustment for population change, with the single exception of 1980, when it increased in all-cause and cardiovascular mortality.

Conclusion

The increase in the difference in premature mortality between the richest and poorest areas in Spain is due to the increased difference in cardiovascular mortality. This increase is not accounted for by population change. In rich countries, more empirical evidence is thus needed to test other alternative explanations for the increase in economic differences in mortality.

Sparse modeling of spatial environmental variables associated with asthma

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors.

Neighborhood influences on recreational physical activity and survival after breast cancer

PURPOSE

Higher levels of physical activity have been associated with improved survival after breast cancer diagnosis. However, no previous studies have considered the influence of the social and built environment on physical activity and survival among breast cancer patients.

METHODS

Our study included 4,345 women diagnosed with breast cancer (1995-2008) from two population-based studies conducted in the San Francisco Bay Area. We examined questionnaire-based moderate/strenuous recreational physical activity during the 3 years before diagnosis. Neighborhood characteristics were based on data from the 2000 US Census, business listings, parks, farmers' markets, and Department of Transportation. Survival was evaluated using multivariable Cox proportional hazards models, with follow-up through 2009.

RESULTS

Women residing in neighborhoods with no fast-food restaurants (vs. fewer fast-food restaurants) to other restaurants, high traffic density, and a high percentage of foreign-born residents were less likely to meet physical activity recommendations set by the American Cancer Society. Women who were not recreationally physically active had a 22% higher risk of death from any cause than women that were the most active. Poorer overall survival was associated with lower neighborhood socioeconomic status (SES) (p(trend) = 0.02), whereas better breast cancer-specific survival was associated with a lack of parks, especially among women in high-SES neighborhoods.

CONCLUSION

Certain aspects of the neighborhood have independent associations with recreational physical activity among breast cancer patients and their survival. Considering neighborhood factors may aide in the design of more effective, tailored physical activity programs for breast cancer survivors.

Neighborhood socioeconomic deprivation, tumor subtypes, and causes of death after non-metastatic invasive breast cancer diagnosis: a multilevel competing-risk analysis

The purpose of this study is to examine the associations of neighborhood socioeconomic deprivation and triple-negative breast cancer (TNBC) subtype with causes of death [breast cancer (BC)-specific and non-BC-specific] among non-metastatic invasive BC patients. We identified 3,312 patients younger than 75 years (mean age 53.5 years; 621 [18.8 %] TNBC) with first primary BC treated at an academic medical center from 1999 to 2010. We constructed a census-tract-level socioeconomic deprivation index using the 2000 U.S. Census data and performed a multilevel competing-risk analysis to estimate the hazard ratios (HR) and 95 % confidence intervals (CI) of BC-specific and non-BC-specific mortality associated with neighborhood socioeconomic deprivation and TNBC subtype. The adjusted models controlled for patient sociodemographics, health behaviors, tumor characteristics, comorbidity, and cancer treatment. With a median 62-month follow-up, 349 (10.5 %) patients died; 233 died from BC. In the multivariate models, neighborhood socioeconomic deprivation was independently associated with non-BC-specific mortality (the most- vs. the least-deprived quartile: HR = 2.98, 95 % CI = 1.33-6.66); in contrast, its association with BC-specific mortality was explained by the aforementioned patient-level covariates, particularly sociodemographic factors (HR = 1.15, 95 % CI = 0.71-1.87). TNBC subtype was independently associated with non-BC-specific mortality (HR = 2.15; 95 % CI = 1.20-3.84), while the association between TNBC and BC-specific mortality approached significance (HR = 1.42; 95 % CI = 0.99-2.03, P = 0.057). Non-metastatic invasive BC patients who lived in more socioeconomically deprived neighborhoods were more likely to die as a result of causes other than BC compared with those living in the least socioeconomically deprived neighborhoods. TNBC was associated with non-BC-specific mortality but not BC-specific mortality.

Associations of all-cause mortality with census-based neighbourhood deprivation and population density in Japan: a multilevel survival analysis

Background

Despite evidence that neighbourhood conditions affect residents' health, no prospective studies of the association between neighbourhood socio-demographic factors and all-cause mortality have been conducted in non-Western societies. Thus, we examined the effects of areal deprivation and population density on all-cause mortality in Japan.

Methods

We employed census and survival data from the Japan Public Health Center-based Prospective Study, Cohort I (n = 37,455), consisting of middle-aged residents (40 to 59 years at the baseline in 1990) living in four public health centre districts. Data spanned between 1990 and 2010. A multilevel parametric proportional-hazard regression model was applied to estimate the hazard ratios (HRs) of all-cause mortality by two census-based areal variables —areal deprivation index and population density—as well as individualistic variables such as socioeconomic status and various risk factors.

Results

We found that areal deprivation and population density had moderate associations with all-cause mortality at the neighbourhood level based on the survival data with 21 years of follow-ups. Even when controlling for individualistic socio-economic status and behavioural factors, the HRs of the two areal factors (using quartile categorical variables) significantly predicted mortality. Further, this analysis indicated an interaction effect of the two factors: areal deprivation prominently affects the health of residents in neighbourhoods with high population density.

Conclusions

We confirmed that neighbourhood socio-demographic factors are significant predictors of all-cause death in Japanese non-metropolitan settings. Although further study is needed to clarify the cause-effect relationship of this association, the present findings suggest that health promotion policies should consider health disparities between neighbourhoods and possibly direct interventions towards reducing mortality in densely populated and highly deprived neighbourhoods.

Area-level socioeconomic characteristics, prevalence and trajectories of cardiometabolic risk

This study examines the relationships between area-level socioeconomic position (SEP) and the prevalence and trajectories of metabolic syndrome (MetS) and the count of its constituents (i.e., disturbed glucose and insulin metabolism, abdominal obesity, dyslipidemia, and hypertension). A cohort of 4,056 men and women aged 18+ living in Adelaide, Australia was established in 2000–2003. MetS was ascertained at baseline, four and eight years via clinical examinations. Baseline area-level median household income, percentage of residents with a high school education, and unemployment rate were derived from the 2001 population Census. Three-level random-intercepts logistic and Poisson regression models were performed to estimate the standardized odds ratio (SOR), prevalence risk ratio (SRR), ratio of SORs/SRRs, and (95% confidence interval (CI)). Interaction between area- and individual-level SEP variables was also tested. The odds of having MetS and the count of its constituents increased over time. This increase did not vary according to baseline area-level SEP (ratios of SORs/SRRs ≈ 1; p ≥ 0.42). However, at baseline, after adjustment for individual SEP and health behaviours, median household income (inversely) and unemployment rate (positively) were significantly associated with MetS prevalence (SOR (95%CI) = 0.76 (0.63–0.90), and 1.48 (1.26–1.74), respectively), and the count of its constituents (SRR (95%CI) = 0.96 (0.93–0.99), and 1.06 (1.04–1.09), respectively). The inverse association with area-level education was statistically significant only in participants with less than post high school education (SOR (95%CI) = 0.58 (0.45–0.73), and SRR (95%CI) = 0.91 (0.88–0.94)). Area-level SEP does not predict an elevated trajectory to developing MetS or an elevated count of its constituents. However, at baseline, area-level SEP was inversely associated with prevalence of MetS and the count of its constituents, with the association of area-level education being modified by individual-level education. Population-level interventions for communities defined by area-level socioeconomic disadvantage are needed to reduce cardiometabolic risks.

Residential selection across the life course: adolescent contextual and individual determinants of neighborhood disadvantage in mid-adulthood

Background

Numerous cross-sectional studies have examined neighborhood effects on health. Residential selection in adulthood has been stressed as an important cause of selection bias but has received little empirical attention, particularly its determinants from the earlier life course. The present study aims to examine whether neighborhood, family, school, health behaviors and health in adolescence are related to socioeconomic disadvantage of one's neighborhood of residence in adulthood.

Methods

Based on the prospective Northern Swedish Cohort (analytical N = 971, 90.6% retention rate), information was collected at age 16 years concerning family circumstances, school adjustment, health behaviors and mental and physical health. Neighborhood register data was linked to the cohort and used to operationalize aggregated measures of neighborhood disadvantage (ND) at age 16 and 42. Data was analyzed with linear mixed models, with ND in adulthood regressed on adolescent predictors and neighborhood of residence in adolescence as the level-2 unit.

Results

Neighborhood disadvantage in adulthood was clustered by neighborhood of residence in adolescence (ICC = 8.6%). The clustering was completely explained by ND in adolescence. Of the adolescent predictors, ND (b = .14 (95% credible interval = .07–.22)), final school marks (b = −.18 (−.26–−.10)), socioeconomic disadvantage (b = .07 (.01–.14)), and, with borderline significance, school peer problems (b = .07 (−.00–.13)), were independently related to adulthood ND in the final adjusted model. In sex-stratified analyses, the most important predictors were school marks (b = −.21 (−.32–−.09)) in women, and neighborhood of residence (ICC = 15.5%) and ND (b = .20 (.09–.31)) in men.

Conclusions

These findings show that factors from adolescence – which also may impact on adult health – could influence the neighborhood context in which one will live in adulthood. This indicates that residential selection bias in neighborhood effects on health research may have its sources in early life.

Geographic remoteness, area-level socioeconomic disadvantage and inequalities in colorectal cancer survival in Queensland: a multilevel analysis

Background

To explore the impact of geographical remoteness and area-level socioeconomic disadvantage on colorectal cancer (CRC) survival.

Methods

Multilevel logistic regression and Markov chain Monte Carlo simulations were used to analyze geographical variations in five-year all-cause and CRC-specific survival across 478 regions in Queensland Australia for 22,727 CRC cases aged 20–84 years diagnosed from 1997–2007.

Results

Area-level disadvantage and geographic remoteness were independently associated with CRC survival. After full multivariate adjustment (both levels), patients from remote (odds Ratio [OR]: 1.24, 95%CrI: 1.07-1.42) and more disadvantaged quintiles (OR = 1.12, 1.15, 1.20, 1.23 for Quintiles 4, 3, 2 and 1 respectively) had lower CRC-specific survival than major cities and least disadvantaged areas. Similar associations were found for all-cause survival. Area disadvantage accounted for a substantial amount of the all-cause variation between areas.

Conclusions

We have demonstrated that the area-level inequalities in survival of colorectal cancer patients cannot be explained by the measured individual-level characteristics of the patients or their cancer and remain after adjusting for cancer stage. Further research is urgently needed to clarify the factors that underlie the survival differences, including the importance of geographical differences in clinical management of CRC.

Warm homes for older people: aims and methods of a randomised community-based trial for people with COPD

Background

Chronic Obstructive Pulmonary Disease (COPD) is of increasing importance with about one in four people estimated to be diagnosed with COPD during their lifetime. None of the existing medications for COPD has been shown to have much effect on the long-term decline in lung function and there have been few recent pharmacotherapeutic advances. Identifying preventive interventions that can reduce the frequency and severity of exacerbations could have important public health benefits. The Warm Homes for Elder New Zealanders study is a community-based trial, designed to test whether a NZ$500 electricity voucher paid into the electricity account of older people with COPD, with the expressed aim of enabling them to keep their homes warm, results in reduced exacerbations and hospitalisation rates. It will also examine whether these subsidies are cost-beneficial.

Methods

Participants had a clinician diagnosis of COPD and had either been hospitalised or taken steroids or antibiotics for COPD in the previous three years; their median age was 71 years. Participants were recruited from three communities between 2009 to early 2011. Where possible, participants’ houses were retrofitted with insulation. After baseline data were received, participants were randomised to either ‘early’ or ‘late’ intervention groups. The intervention was a voucher of $500 directly credited to the participants’ electricity company account. Early group participants received the voucher the first winter they were enrolled in the study, late participants during the second winter. Objective measures included spirometry and indoor temperatures and subjective measures included questions about participant health and wellbeing, heating, medication and visits to health professionals. Objective health care usage data included hospitalisation and primary care visits. Assessments of electricity use were obtained through electricity companies using unique customer numbers.

Discussion

This community trial has successfully enrolled 522 older people with COPD. Baseline data showed that, despite having a chronic respiratory illness, participants are frequently cold in their houses and economise on heating.

Trial Registration

The clinical trial registration is http://NCT01627418

Neighborhood context and racial/ethnic differences in young children's obesity: structural barriers to interventions

Numerous studies in the last ten years have investigated racial/ethnic disparities in obesity for young children. Increasing attention is paid to the influence of neighborhood environments - social and physical-on a variety of young children's health outcomes. This work identifies resource-based and community-based mechanisms that impede on the maintenance of healthy weights for young children in socioeconomically depressed areas, and shows consistently higher rates of obesity in more deprived areas. None of this work, however, has explored whether area deprivation or the race/nativity composition of neighborhoods contributes to racial/ethnic disparities in young children's obesity. Utilizing restricted geo-coded data from the Early Childhood Longitudinal Study (Kindergarten) (N = 17,540), we utilize multilevel logistic regression models to show that neighborhood level measures do little to explain racial and ethnic differences in childhood obesity. However, living in neighborhoods with higher levels of poverty, lower levels of education, and a higher proportion of black residents is associated with increased child obesity risk after considering a host of relevant individual level factors. In addition, living in neighborhoods with a higher proportion of foreign-born residents is associated with reduced child obesity risk. Although well-intentioned childhood obesity intervention programs aimed at changing individual-level behaviors are important, our results highlight the importance of considering neighborhood structural factors for child obesity prevention.

Do neighborhoods affect individual mortality? A systematic review and meta-analysis of multilevel studies

There has been increasing interest in investigating whether inhabitants in socially or physically deprived neighborhoods have higher mortality when individual socioeconomic status is adjusted for. Results so far appear ambiguous and the objective of this study was to conduct a systematic literature review of previous studies and to quantify the association between area-level socioeconomic status (ALSES) and all-cause mortality in a meta-analysis. Current guidelines for systematic reviews and meta-analyses were followed. Articles were retrieved from Medline, Embase, Social Sciences Citation Index and PsycInfo and individually evaluated by two researchers. Only peer-reviewed multilevel studies from high-income countries, which analyzed the influence of at least one area-level indicator and which controlled for individual SES, were included. The ALSES estimates in each study were first combined into a single estimate using weighted linear regression. In the meta-analysis we calculated combined estimates with random effects to account for heterogeneity between studies. Out of the 40 studies found eligible for the systematic review 18 studies were included in the meta-analysis. The systematic review suggests that there is an association between social cohesion and mortality but found no evidence for a clear association for area-level income inequality or for social capital. Studies including more than one area level suggest that characteristics on different area levels contribute to individual mortality. In the meta-analysis we found significantly higher mortality among inhabitants living in areas with low ALSES. Associations were stronger for men and younger age groups and in studies analyzing geographical units with fewer inhabitants.

Socioeconomic position, comorbidity, and mortality in aortic aneurysms: a 13-year prospective cohort study

BACKGROUND

To evaluate factors associated with incidence and 3-year all-cause mortality in patients with aortic aneurysm (AA). The design is sex and age-stratified (60-79 and 80-90 years) prospective cohort. By using the population register, we constituted a cohort of all men and women born between 1900 and 1930 and living in Scania by 1991, and followed them for 13 years. Identification of AA was based on hospital discharge diagnosis obtained from the Swedish Patient Register or from the information on death certificates from the Cause of Death Register.

METHODS

We applied stepwise Cox regression and investigated both AA incidence (1991-2003) as well as 3-year survival after the first hospitalization for AA.

RESULTS

We found an inverse relation between AA incidence and previous hospitalization by diabetes mellitus in women (hazard ratio [HR]: 0.41; 95% confidence interval [CI]: 0.19-0.88) and in men (HR: 0.38; 95% CI: 0.24-0.61) aged 60-79 years. Three-year all-cause mortality after diagnosis of AA was 58.6% in women, 50.2% in men, 72.9% in octogenarians, and 43.7% for nonoctogenarians. Low income, chronic respiratory diseases, cerebrovascular diseases, dementia, systemic connective tissue disorders, renal failure, and malignant neoplasms were independent factors for mortality in 60-79-year-old men with AA.

CONCLUSIONS

Inferior socioeconomic position is associated with increased 3-year all-cause mortality in 60-79-year-old men with AA.

Geographic variation in colorectal cancer survival and the role of small-area socioeconomic deprivation: a multilevel survival analysis of the NIH-AARP Diet and Health Study Cohort

Adverse socioeconomic conditions, at both the individual and the neighborhood level, increase the risk of colorectal cancer (CRC) death, but little is known regarding whether CRC survival varies geographically and the extent to which area-level socioeconomic deprivation affects this geographic variation. Using data from the National Institutes of Health (NIH)-AARP Diet and Health Study, the authors examined geographic variation and the role of area-level socioeconomic deprivation in CRC survival. CRC cases (n = 7,024), identified during 1995-2003, were followed for their CRC-specific vital status through 2005 and overall vital status through 2006. Bayesian multilevel survival models showed that there was significant geographic variation in overall (variance = 0.2, 95% confidence interval (CI): 0.1, 0.2) and CRC-specific (variance = 0.3, 95% CI: 0.1, 0.4) risk of death. More socioeconomically deprived neighborhoods had a higher overall risk of death (most deprived quartile vs. least deprived: hazard ratio = 1.2, 95% CI: 1.1, 1.4) and a higher CRC-specific risk of death (most deprived quartile vs. least deprived: hazard ratio = 1.2, 95% CI: 1.1, 1.5). However, neighborhood socioeconomic deprivation did not account for the geographic variation in overall and CRC-specific risks of death. In future studies, investigators should evaluate other neighborhood characteristics to help explain geographic heterogeneity in CRC survival. Such research could facilitate interventions for reducing geographic disparity in CRC survival.

Examining the Racial Crossover in Mortality between African American and White Older Adults: A Multilevel Survival Analysis of Race, Individual Socioeconomic Status, and Neighborhood Socioeconomic Context

We examine whether individual and neighborhood socioeconomic context contributes to black/white disparities in mortality among USA older adults. Using national longitudinal data from the Americans' Changing Lives study, along with census tract information for each respondent, we conduct multilevel survival analyses. Results show that black older adults are disadvantaged in mortality in younger old age, but older black adults have lower mortality risk than whites after about age 80. Both individual SES and neighborhood socioeconomic disadvantage contribute to the mortality risk of older adults but do not completely explain race differences in mortality. The racial mortality crossover persists even after controlling for multilevel SES, suggesting that black older adults experience selective survival at very old ages. Addressing the individual and neighborhood socioeconomic disadvantage of blacks is necessary to reduce mortality disparities that culminate in older adulthood.

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.

Deprivation and the development of obesity a multilevel, longitudinal study in England

BACKGROUND

Evidence indicates that the rising trend in overweight and obesity may be stronger for people from more socioeconomically advantaged backgrounds.

PURPOSE

This study used longitudinal, multilevel data to describe trajectories of BMI for people living in more- versus less-deprived neighborhoods.

METHODS

Data from 2501 women and 5650 men in the Whitehall II study who were followed for up to 13 years from 1991 to 2004 were analyzed in 2009. BMI was measured on up to three occasions by a trained nurse. The Townsend index of multiple deprivation at census-ward level from the 1991 U.K. census captured neighborhood deprivation. Growth curves summarized change in BMI for men and women according to level of neighborhood deprivation, adjusted for age, individual socioeconomic position (captured by civil service employment grade), smoking status, alcohol intake, and physical activity level.

RESULTS

Women who remained in the most-deprived neighborhoods between 1991 and 2004 had higher initial BMI and greater weight gain. Compared to those in the least-deprived neighborhoods, weight gain for a woman of average height in one of the most-deprived neighborhoods was 1.0 kg more over 10 years. Neither BMI nor change in BMI in men was associated with neighborhood deprivation.

CONCLUSIONS

Whitehall II provides longitudinal evidence of socioeconomic differences in weight gain among middle-aged women, indicating that the neighborhood environment makes a contribution to the development of overweight and obesity.

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.

Disentangling the relative influence of built and socioeconomic environments on walking: the contribution of areas homogenous along exposures of interest

The geography of small areas has important implications for studying the contextual determinants of health because of potential errors when measuring ecologic exposures and estimating their effects on health. In this paper, we present an approach for designing homogeneous zones optimising the spatial distribution of an area-level exposure, active living potential (ALP), based on data collected in Montreal, Canada. The objectives are to (1) assess and compare variation in walking behaviours between these purposefully designed zones and between standard administrative units, census tracts; and (2) disentangle the relative influence of ALP and area-level socioeconomic conditions on walking using the alternative geographies. Zones were designed by statistically classifying smallest census areas (disseminations areas) into seven categories of exposure similar along three indicators of ALP: population density, land use mix, and geographic accessibility to services. Mapping of categories resulted in the delineation of zones characterised by one of seven levels of ALP. A sample of 2716 adults aged >/=45 years was geocoded and cross-classified in 270 zones and 112 census tracts. Individuals reported on minutes and motives of walking and provided socioeconomic information. Data were analysed using cross-classified multilevel models. Variation in utilitarian walking was larger across the purposefully defined zones than across census tracts. Total walking varied significantly between census tracts only. Greater ALP was associated with more utilitarian walking but with less recreational walking. Higher socioeconomic position in census tracts was positively associated with total, utilitarian, and recreational walking. The soundness of standard administrative units for measuring ecologic exposure and their associations with health should be considered prior to conducting analyses. The added value of different approaches for understanding how place relates to health remains to be established and should be the focus of further investigations.

Geographic life environments and coronary heart disease: a literature review, theoretical contributions, methodological updates, and a research agenda

A growing literature investigates associations between neighborhood social environments and coronary heart disease (CHD). After reviewing the literature, we present a theoretical model of the mechanisms through which geographic life environments may influence CHD, focusing particularly on the social-interactional environment. We suggest that, in addition to the common notions of social cohesion or fragmentation and social disorder, eco-epidemiologists should consider neighborhood identities and stigmatization processes. We posit that neighborhood social interactions affect the wide set of affective, cognitive, and relational experiences individuals have in their neighborhoods, which in turn influence the psycho-cognitive antecedents of behavior and in the end shape health behavior. Finally, we discuss key methodological challenges relevant to the advent of a new generation of neighborhood studies, including the operational definition of neighborhoods, non-residential environments, ecometric measurement, model specification strategies, mediational models, selection processes and notions of empirical/structural confounding, and the relevance of observational versus interventional studies.

Establishing the soundness of administrative spatial units for operationalising the active living potential of residential environments: an exemplar for designing optimal zones

Background

In health and place research, definitions of areas, area characteristics, and health outcomes should ideally be coherent with one another. Yet current approaches for delimiting areas mostly rely on spatial units "of convenience" such as census tracts. These areas may be homogeneous along socioeconomic conditions but heterogeneous along other environmental characteristics. This heterogeneity can lead to biased measurement of environment characteristics and misestimation of area effects on health. The objective of this study was to assess the soundness of census tracts as units of analysis for measuring the active living potential of environments, hypothesised to be associated with walking.

Results

Starting with data at the smallest census area level available, zones homogeneous along three indicators of active living potential, i.e. population density, land use mix, and accessibility to services were designed. Delimitation of zones ensued from statistical clustering of the smallest areas into seven clusters or "types of environment". Mapping of clusters into a GIS led to the delineation of 898 zones characterised by one of seven types of environment, corresponding to different levels of active living potential. Homogeneity of census tracts along indicators of active living potential varied. A greater proportion (83%) of variation in accessibility to services was attributable to differences between census tracts suggesting within-tract homogeneity along this variable. However, census tracts were heterogeneous with respect to population density and land use mix where a greater proportion of the variation was attributable to within-tract differences. About 55% of tracts were characterised by a combination of three or more "types of environment" suggesting substantial within-tract heterogeneity in the active living potential of environments.

Conclusion

Soundness of census tracts for measuring active living potential may be limited. Measuring active living potential with error may lead to misestimation of associations with walking, therefore limiting the correctness of inference about area effects on walking. Future studies should aim to determine homogeneity of spatial units "of convenience" along environment characteristics of interest prior to examining their association with health. Further evidence is needed to assess the extent of this methodological issue with other indicators of environment context relevant to other health indicators.

The effects of migration on the relationship between area socioeconomic structure and mortality

We studied whether migration influences the relationship between area socioeconomic structure and mortality. We used data on Finns aged 25-64 that are linked to information on proportions of manual workers in 85 functional regions in 1987 and 1997, and on deaths in 1998-2004. Participants aged 25-44 moving to areas with a lower proportion of manual workers had lower mortality and those moving to areas with a higher proportion of manual workers had mortality similar to those residing in these areas at both time points. Among the 45-64-year-olds, all migrants between areas had increased mortality. However, because these mortality differences and the migratory flows were relatively small, their effects on area socioeconomic differences in mortality were also small.

Toward the next generation of research into small area effects on health: a synthesis of multilevel investigations published since July 1998

To map out area effects on health research, this study had the following aims: (1) to inventory multilevel investigations of area effects on self rated health, cardiovascular diseases and risk factors, and mortality among adults; (2) to describe and critically discuss methodological approaches employed and results observed; and (3) to formulate selected recommendations for advancing the study of area effects on health. Overall, 86 studies were inventoried. Although several innovative methodological approaches and analytical designs were found, small areas are most often operationalised using administrative and statistical spatial units. Most studies used indicators of area socioeconomic status derived from censuses, and few provided information on the validity and reliability of measures of exposures. A consistent finding was that a significant portion of the variation in health is associated with area context independently of individual characteristics. Area effects on health, although significant in most studies, often depend on the health outcome studied, the measure of area exposure used, and the spatial scale at which associations are examined.