The contribution of neighbourhood material and social deprivation to survival: a 22-year follow-up of more than 500,000 Canadians

The Dynamic Nature of the Socioeconomic Determinants of Cardiovascular Health: A Narrative Review

Despite decades of social epidemiologic research, health inequities remain pervasive and ubiquitous in Canada and elsewhere. One reason may be our use of socioeconomic measurement, which has often relied on single point-in-time exposures. To explore the extent to which researchers have incorporated dynamic socioeconomic measurement into cardiovascular health outcome evaluations, we performed a narrative review. We estimated the prevalence of socioeconomic longitudinal cardiovascular research studies that identified socioeconomic exposures at 2 or more points in time between the years of 2019 and 2023. We defined cardiovascular outcome studies as those that examined coronary artery disease, myocardial infarction, acute coronary syndrome, stroke, heart failure, cardiac arrhythmias, cardiac death, cardiometabolic factors, transient ischemic attacks, peripheral artery disease, or hypertension. Socioeconomic exposures included individual income, neighbourhood income, intergenerational social mobility, education, occupation, insurance status, and economic security. Seven percent of socioeconomic cardiovascular outcome studies have measured socioeconomic status at 2 or more points in time throughout the follow-up period, hypothesized mechanisms by which dynamic socioeconomic measures affected outcome focused on social mobility, accumulation, and critical period theories. Insights, implications, and future directions are discussed, in which we highlight ways in which postal code data can be better used methodologically as a dynamic socioeconomic measure. Future research must incorporate dynamic socioeconomic measurement to better inform root causes, interventions, and health-system designs if health equity is to be improved.

Distribution of legal retail cannabis stores in Canada by neighbourhood deprivation

OBJECTIVES

In legal cannabis markets, the distribution of retail stores has the potential to influence transitions from illegal to legal sources as well as consumer patterns of use. The current study examined the distribution of legal cannabis stores in Canada according to level of neighbourhood deprivation.

METHODS

Postal code data for all legal cannabis stores in Canada were collected from government websites from October 2018 to September 2021. This data was linked to the Institut National de Santé Publique du Québec measures for material and social neighbourhood deprivation. Descriptive data are reported, including differences across provinces with different retail systems.

RESULTS

At the national level, there were approximately 8.0 retail cannabis stores per 100,000 individuals age 15+ in September 2021. The distribution of stores was closely aligned with the expected distribution across levels of material deprivation: for example, 19.5% of stores were located in neighbourhoods with the lowest level of material deprivation versus 19.1% in the highest level. More cannabis stores were located in the 'most socially deprived' or 'socially deprived' neighbourhoods (37.2% and 22.1%, respectively), characterized by a higher proportion of residents who live alone, are unmarried, or in single-parent families. The distribution of stores in provinces and territories were generally consistent with national patterns with a few exceptions.

CONCLUSION

In the first 3 years following cannabis legalization in Canada, retail cannabis stores were evenly distributed across materially deprived neighbourhoods but were more common in socially deprived neighbourhoods. Future monitoring of retail store locations is required as the legal retail market evolves in Canada.

Impact of Neighborhood Deprivation on Aging Sexual Minority People's Depression: Results from the CANUE and CLSA data

As the aging population grows across the world, exploring the impact of social environment on minority populations' aging and well-being would be an essential step towards building an inclusive society. Using the Canadian Longitudinal Study on Aging (CLSA) and Canadian Urban Environmental Health Research Consortium (CANUE) data, the study investigated the relationship between deprivation and depression level in aging sexual minority people to examine how neighborhood level social and material deprivation influence mental health. 48,792 survey respondents were included in our analyses and the average age was 62.9. The study had 47,792 heterosexual, 760 gay/lesbian, and 240 bisexual individuals (23,977 men and 24,815 women). Regression analyses were conducted while controlling for age in each model. Results revealed that neighborhood material deprivation has a significant impact on mental health outcomes of aging lesbian women and bisexual men. The study provides an opportunity for intervention considerations for materially deprived neighborhoods to serve the aging sexual minority people residing in such areas.

Neighbourhood socioeconomic improvement, residential mobility and premature death: a population-based cohort study and inverse probability of treatment weighting analysis

BACKGROUND

Causal inference using area-level socioeconomic measures is challenging due to risks of residual confounding and imprecise specification of the neighbourhood-level social exposure. By using multi-linked longitudinal data to address these common limitations, our study aimed to identify protective effects of neighbourhood socioeconomic improvement on premature mortality risk.

METHODS

We used data from the Canadian Community Health Survey, linked to health administrative data, including longitudinal residential history. Individuals aged 25-69, living in low-socioeconomic status (SES) areas at survey date (n = 8335), were followed up for neighbourhood socioeconomic improvement within 5 years. We captured premature mortality (death before age 75) until 2016. We estimated protective effects of neighbourhood socioeconomic improvement exposures using Cox proportional hazards models. Stabilized inverse probability of treatment weights (IPTW) were used to account for confounding by baseline health, social and behavioural characteristics. Separate analyses were carried out for three exposure specifications: any improvement, improvement by residential mobility (i.e. movers) or improvement in place (non-movers).

RESULTS

Overall, 36.9% of the study cohort experienced neighbourhood socioeconomic improvement either by residential mobility or improvement in place. There were noted differences in baseline health status, demographics and individual SES between exposure groups. IPTW survival models showed a modest protective effect on premature mortality risk of socioeconomic improvement overall (HR = 0.86; 95% CI 0.63, 1.18). Effects were stronger for improvement in place (HR = 0.67; 95% CI 0.48, 0.93) than for improvement by residential mobility (HR = 1.07, 95% 0.67, 1.51).

CONCLUSIONS

Our study provides robust evidence that specific neighbourhood socioeconomic improvement exposures are important for determining mortality risks.

Association of neighbourhood disadvantage and individual socioeconomic position with all-cause mortality: a longitudinal multicohort analysis

BACKGROUND

Few studies have examined the interactions between individual socioeconomic position and neighbourhood deprivation and the findings so far are heterogeneous. Using a large sample of diverse cohorts, we investigated the interaction effect of neighbourhood socioeconomic deprivation and individual socioeconomic position, assessed using education, on mortality.

METHODS

We did a longitudinal multicohort analysis that included six cohort studies participating in the European LIFEPATH consortium: the CoLaus (Lausanne, Switzerland), E3N (France), EPIC-Turin (Turin, Italy), EPIPorto (Porto, Portugal), Melbourne Collaborative Cohort Study (Melbourne, VIC, Australia), and Whitehall II (London, UK) cohorts. All participants with data on mortality, educational attainment, and neighbourhood deprivation were included in the present study. The data sources were the databases of each cohort study. Poisson regression was used to estimate the mortality rates and associations (relative risk, 95% CIs) with neighbourhood deprivation (Q1 being least deprived to Q5 being the most deprived). Baseline educational attainment was used as an indicator of individual socioeconomic position. Estimates were combined using pooled analysis and the relative excess risk due to the interaction was computed to identify additive interactions.

FINDINGS

The cohorts comprised a total population of 168 801 individuals. The recruitment dates were 2003-06 for CoLaus, 1989-91 for E3N, 1992-98 for EPIC-Turin, 1999-2003 for EPIPorto, 1990-94 for MCCS, and 1991-94 for Whitehall II. We use baseline data only and mortality data obtained using record linkage. Age-adjusted mortality rates were higher among participants residing in more deprived neighbourhoods than those in the least deprived neighbourhoods (Q1 least deprived neighbourhoods, 369·7 per 100 000 person-years [95% CI 356·4-383·2] vs Q5-most deprived neighbourhoods 445·7 per 100 000 person-years [430·2-461·7]), but the magnitude of the association varied according to educational attainment (relative excess risk due to interaction=0·18, 95% CI 0·08-0·28). The relative risk for Q5 versus Q1 was 1·31 (1·23-1·40) among individuals with primary education or less, but less pronounced among those with secondary education (1·12; 1·04-1·21) and tertiary education (1·16; 1·07-1·27). Associations remained after adjustment for individual-level factors, such as smoking, physical activity, and alcohol intake, among others.

INTERPRETATION

Our study suggests that the detrimental health effect of living in disadvantaged neighbourhoods is more pronounced among individuals with low education attainment, amplifying social inequalities in health. This finding is relevant to policies aimed at reducing health inequalities, suggesting that these issues should be addressed at both the individual level and the community level.

FUNDING

The European Commission, European Regional Development Fund, the Portugese Foundation for Science and Technology.

How Should We Measure Social Deprivation in Orthopaedic Patients?

BACKGROUND

Social deprivation negatively affects a myriad of physical and behavioral health outcomes. Several measures of social deprivation exist, but it is unclear which measure is best suited to describe patients with orthopaedic conditions.

QUESTIONS/PURPOSES

(1) Which measure of social deprivation, defined as "limited access to society's resources due to poverty, discrimination, or other disadvantage," is most strongly and consistently correlated with patient-reported physical and behavioral health in patients with orthopaedic conditions? (2) Compared with the use of a single measure alone, how much more variability in patient-reported health does the simultaneous use of multiple social deprivation measures capture?

METHODS

Between 2015 and 2017, a total of 79,818 new patient evaluations occurred within the orthopaedic department of a single, large, urban, tertiary-care academic center. Over that period, standardized collection of patient-reported health measures (as described by the Patient-reported Outcomes Measurement Information System [PROMIS]) was implemented in a staged fashion throughout the department. We excluded the 25% (19,926) of patient encounters that did not have associated PROMIS measures reported, which left 75% (59,892) of patient encounters available for analysis in this cross-sectional study of existing medical records. Five markers of social deprivation were collected for each patient: national and state Area Deprivation Index, Medically Underserved Area Status, Rural-Urban Commuting Area code, and insurance classification (private, Medicare, Medicaid, or other). Patient-reported physical and behavioral health was measured via PROMIS computer adaptive test domains, which patients completed as part of standard care before being evaluated by a provider. Adults completed the PROMIS Physical Function version 1.2 or version 2.0, Pain Interference version 1.1, Anxiety version 1.0, and Depression version 1.0. Children ages 5 to 17 years completed the PROMIS Pediatric Mobility version 1.0 or version 2.0, Pain Interference version 1.0 or version 2.0, Upper Extremity version 1.0, and Peer Relationships version 1.0. Age-adjusted partial Pearson correlation coefficients were determined for each social deprivation measure and PROMIS domain. Coefficients of at least 0.1 were considered clinically meaningful for this purpose. Additionally, to determine the percentage of PROMIS score variability that could be attributed to each social deprivation measure, an age-adjusted hierarchical regression analysis was performed for each PROMIS domain, in which social deprivation measures were sequentially added as independent variables. The model coefficients of determination (r2) were compared as social deprivation measures were incrementally added. Improvement of the r2 by at least 10% was considered clinically meaningful.

RESULTS

Insurance classification was the social deprivation measure with the largest (absolute value) age-adjusted correlation coefficient for all adult and pediatric PROMIS physical and behavioral health domains (adults: correlation coefficient 0.40 to 0.43 [95% CI 0.39 to 0.44]; pediatrics: correlation coefficient 0.10 to 0.19 [95% CI 0.08 to 0.21]), followed by national Area Deprivation Index (adults: correlation coefficient 0.18 to 0.22 [95% CI 0.17 to 0.23]; pediatrics: correlation coefficient 0.08 to 0.15 [95% CI 0.06 to 0.17]), followed closely by state Area Deprivation Index. The Medically Underserved Area Status and Rural-Urban Commuting Area code each had correlation coefficients of 0.1 or larger for some PROMIS domains but neither had consistently stronger correlation coefficients than the other. Except for the PROMIS Pediatric Upper Extremity domain, consideration of insurance classification and the national Area Deprivation Index together explained more of the variation in age-adjusted PROMIS scores than the use of insurance classification alone (adults: r2 improvement 32% to 189% [95% CI 0.02 to 0.04]; pediatrics: r2 improvement 56% to 110% [95% CI 0.01 to 0.02]). The addition of the Medically Underserved Area Status, Rural-Urban Commuting Area code, and/or state Area Deprivation Index did not further improve the r2 for any of the PROMIS domains.

CONCLUSION

To capture the most variability due to social deprivation in orthopaedic patients' self-reported physical and behavioral health, insurance classification (categorized as private, Medicare, Medicaid, or other) and national Area Deprivation Index should be included in statistical analyses. If only one measure of social deprivation is preferred, insurance classification or national Area Deprivation Index are reasonable options. Insurance classification may be more readily available, but the national Area Deprivation Index stratifies patients across a wider distribution of values. When conducting clinical outcomes research with social deprivation as a relevant covariate, we encourage researchers to consider accounting for insurance classification and/or national Area Deprivation Index, both of which are freely available and can be obtained from data that are typically collected during routine clinical care.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Neighbourhood-level material deprivation and response to combination antiretroviral therapy in the Canadian Observational Cohort (CANOC): a longitudinal cohort study

BACKGROUND

Socioeconomic status has been associated with higher viral loads and lower CD4 cell counts among people living with HIV. The objective of this study was to evaluate the relation between neighbourhood-level material deprivation and immunologic and virologic response to combination antiretroviral therapy (ART) among people living with HIV in Canada.

METHODS

The Canadian Observational Cohort (CANOC) is a longitudinal cohort of people living with HIV, containing data from 2000-2016 from 5 Canadian provinces. We defined response to combination ART as positive if the CD4 cell count increased by 50 cells/mm³ (0.05 cells × 10⁹/L) or more (CD4+) and viral load decreased to 50 copies/mL or less (VL+) within 6 months of treatment initiation. We further categorized response to therapy as concordant positive (CD4+/VL+), concordant negative (CD4-/VL-) or discordant (CD4+/VL- or CD4-/VL+). We used adjusted multinomial logistic regression to quantify the relation between neighbourhood-level material deprivation and immunologic and virologic response.

RESULTS

This study included 8274 people living with HIV, of which 1754 (21.2%) lived in the most materially deprived neighbourhoods. Most individuals (62.2%) showed a concordant positive response to combination ART. After adjustment, living in the most materially deprived neighbourhoods was associated with a CD4-/VL+ discordant response (adjusted odds ratio [OR] 1.31, 95% confidence interval [CI] 1.06-1.62) and a concordant negative response (adjusted OR 1.45, 95% CI 1.13-1.86), using a concordant positive response as the reference. No other deprivation quartile was independently associated with a particular response.

INTERPRETATION

People living with HIV from the most materially deprived neighbourhoods had increased odds of poor immunologic or virologic response to combination ART. These results motivate further study of the specific socioeconomic factors that potentially affect response to combination ART among people living with HIV in Canada.

Association between the regional variation in premature mortality and immigration in Ontario, Canada

Objectives

Health region differences in immigration patterns and premature mortality rates exist in Ontario, Canada. This study used linked population-based databases to describe the regional proportion of immigrants in the context of provincial health region variation in premature mortality.

Methods

We analyzed all adult premature deaths in Ontario from 1992 to 2012 using linked population files, Canadian census, and death registry databases. Geographic boundaries were analyzed according to 14 health service regions, known as Local Health Integration Networks (LHINs). We assessed the role of immigrant status and regional proportion of immigrants in the context of these health region variations and assessed the contribution using sex-specific multilevel negative binomial models, accounting for age, individual- and area-level immigration, and area-level material deprivation.

Results

We observed significant premature mortality variation among health service regions in Ontario between 1992 and 2012. Average annual rates ranged across LHINs from 3.03 to 6.40 per 1000 among males and 2.04 to 3.98 per 1000 among females. The median rate ratio (RR) decreased for men from 1.14 (95% CI 1.06, 1.19) to 1.07 (95% CI 1.00, 1.11) after adjusting for year, age, area-based material deprivation, and individual- and area-level immigration, and among females reduced from 1.13 (95% CI 1.05, 1.18) to 1.04 (95% CI 1.00, 1.05). These adjustments explained 84.1% and 94.4% of the LHIN-level variation in males and females respectively. Reduced premature mortality rates were associated with immigrants compared with those for long-term residents in the fully adjusted models for both males 0.43 (95% CI 0.42, 0.44) and females 0.45 (0.44, 0.46).

Conclusion

The findings demonstrate that health region differences in premature mortality in Ontario are in part explained by individual-level effects associated with the health advantage of immigrants, as well as contextual area-level effects that are associated with regional differences in the immigrant population. These factors should be considered in addition to health system factors when looking at health region variation in premature deaths.

Electronic supplementary material

The online version of this article (10.17269/s41997-020-00330-5) contains supplementary material, which is available to authorized users.

Non-compensatory aggregation method to measure social and material deprivation in an urban area: relationship with premature mortality

Health inequalities exist between nations, regions, and even smaller units. In societies where social and economic structures change rapidly and continuously, analysis of health socioeconomic determinants plays a fundamental role to provide proper policy answers. This study aims to measure accurately two different conceptions of deprivation by developing two different indexes using non-compensatory among sub-indicators aggregation methods. The proposed indicators are compared with premature mortality to verify deprivation's effect on health status. The results show that materially deprived areas are not necessarily socially deprived and vice versa. Material deprivation has a positive statistical co-graduation with premature mortality, while social deprivation has no association with premature mortality.

Socioeconomic factors and mortality in patients with atrial fibrillation-a cohort study in Swedish primary care

Background

Preventing ischaemic stroke attracts significant focus in atrial fibrillation (AF) cases. Less is known on the association between socioeconomic factors and mortality and cardiovascular outcomes in patients with AF.

Methods

Our study population included adults (n=12 283) ≥45 years diagnosed with AF at 75 primary care centres in Sweden 2001-07. Cox regression was used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for the association between the exposures educational level, marital status, neighbourhood socioeconomic status and the outcomes all-cause mortality, after adjustment for age, and comorbid cardiovascular conditions.

Results

During a mean of 5.8 years (SD 2.4) of follow-up, 3954 (32.3%) patients had died; 1971 were women (35.0%) and 1983 were men (29.8%). Higher educational level was associated with a reduced mortality in fully adjusted models: HR 0.85 (95% CI 0.77-0.96) for secondary school in men, HR 0.73 (95% CI 0.60-0.88) for college/university in women, and HR 0.82 (95% CI 0.71-0.94) for college/university in men, compared to primary school. Unmarried men and divorced men had an increased risk of death, compared with married men: HR 1.25 (95% CI 1.05-1.50), and HR 1.23 (95% CI 1.07-1.42), respectively. College/university education level was also associated with lower risk of myocardial infarction in men and women, and lower risk of congestive heart failure in women.

Conclusion

More attention could be paid to individuals of lower levels of formal education, and unmarried men, in order to provide timely management for AF and prevent its debilitating complications.

Community Socioeconomic Disadvantage in Midlife Relates to Cortical Morphology via Neuroendocrine and Cardiometabolic Pathways

Residing in communities of socioeconomic disadvantage confers risk for chronic diseases and cognitive aging, as well as risk for biological factors that negatively affect brain morphology. The present study tested whether community disadvantage negatively associates with brain morphology via 2 biological factors encompassing cardiometabolic disease risk and neuroendocrine function. Participants were 448 midlife adults aged 30-54 years (236 women) who underwent structural neuroimaging to assess cortical and subcortical brain tissue morphology. Community disadvantage was indexed by US Census data geocoded to participants' residential addresses. Cardiometabolic risk was indexed by measurements of adiposity, blood pressure, glucose, insulin, and lipids. Neuroendocrine function was indexed from salivary cortisol measurements taken over 3 days, from which we computed the cortisol awakening response, area-under-the-curve, and diurnal cortisol decline. Community disadvantage was associated with reduced cortical tissue volume, cortical surface area, and cortical thickness, but not subcortical morphology. Moreover, increased cardiometabolic risk and a flatter (dysregulated) diurnal cortisol decline mediated the associations of community disadvantage and cortical gray matter volume. These effects were independent of age, sex, and individual-level socioeconomic position. The adverse risks of residing in a disadvantaged community may extend to the cerebral cortex via cardiometabolic and neuroendocrine pathways.

Associations between fine particulate matter and mortality in the 2001 Canadian Census Health and Environment Cohort

BACKGROUND

Large cohort studies have been used to characterise the association between long-term exposure to fine particulate matter (PM_2.5) air pollution with non-accidental, and cause-specific mortality. However, there has been no consensus as to the shape of the association between concentration and response.

METHODS

To examine the shape of this association, we developed a new cohort based on respondents to the 2001 Canadian census long-form. We applied new annual PM_2.5 concentration estimates based on remote sensing and ground measurements for Canada at a 1km spatial scale from 1998 to 2011. We followed 2.4 million respondents who were non-immigrants aged 25-90 years and did not reside in an institution over a 10 year period for mortality. Exposures were assigned as a 3-year mean prior to the follow-up year. Income tax files were used to account for residential mobility among respondents using postal codes, with probabilistic imputation used for missing postal codes in the tax data. We used Cox survival models to determine hazard ratios (HRs) for cause-specific mortality. We also estimated Shape Constrained Health Impact Functions (a concentration-response function) for selected causes of death.

RESULTS

In models stratified by age, sex, airshed, and population centre size, and adjusted for individual and neighbourhood socioeconomic variables, HR estimates for non-accidental mortality were HR = 1.18 (95% CI: 1.15-1.21) per 10μg/m³ increase in concentration. We observed higher HRs for cardiovascular disease (HR=1.25; 95% CI: 1.19-1.31), cardio-metabolic disease (HR = 1.27; 95% CI: 1.21-1.33), ischemic heart disease (HR = 1.36; 95% CI: 1.28-1.44) and chronic obstructive pulmonary disease (COPD) mortality (HR = 1.24; 95% CI: 1.11-1.39) compared to HR for all non-accidental causes of death. For non-accidental, cardio-metabolic, ischemic heart disease, respiratory and COPD mortality, the shape of the concentration-response curve was supra-linear, with larger differences in relative risk for lower concentrations. For both pneumonia and lung cancer, there was some suggestion that the curves were sub-linear.

CONCLUSIONS

Associations between ambient concentrations of fine particulate matter and several causes of death were non-linear for each cause of death examined.

Spatial associations between socioeconomic groups and NO2 air pollution exposure within three large Canadian cities

Previous studies of environmental justice in Canadian cities have linked lower socioeconomic status to greater air pollution exposures at coarse geographic scales, (i.e., Census Tracts). However, studies that examine these associations at finer scales are less common, as are comparisons among cities. To assess differences in exposure to air pollution among socioeconomic groups, we assigned estimates of exposure to ambient nitrogen dioxide (NO2), a marker for traffic-related pollution, from city-wide land use regression models to respondents of the 2006 Canadian census long-form questionnaire in Toronto, Montreal, and Vancouver. Data were aggregated at a finer scale than in most previous studies (i.e., by Dissemination Area (DA), which includes approximately 400-700 persons). We developed simultaneous autoregressive (SAR) models, which account for spatial autocorrelation, to identify associations between NO2 exposure and indicators of social and material deprivation. In Canada's three largest cities, DAs with greater proportions of tenants and residents who do not speak either English or French were characterised by greater exposures to ambient NO2. We also observed positive associations between NO2 concentrations and indicators of social deprivation, including the proportion of persons living alone (in Toronto), and the proportion of persons who were unmarried/not in a common-law relationship (in Vancouver). Other common measures of deprivation (e.g., lone-parent families, unemployment) were not associated with NO2 exposures. DAs characterised by selected indicators of deprivation were associated with higher concentrations of ambient NO2 air pollution in the three largest cities in Canada.

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

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

Risk estimates of mortality attributed to low concentrations of ambient fine particulate matter in the Canadian community health survey cohort

BACKGROUND

Understanding the shape of the relationship between long-term exposure to ambient fine particulate matter (PM2.5) concentrations and health risks is critical for health impact and risk assessment. Studies evaluating the health risks of exposure to low concentrations of PM2.5 are limited. Further, many existing studies lack individual-level information on potentially important behavioural confounding factors.

METHODS

A prospective cohort study was conducted among a subset of participants in a cohort that linked respondents of the Canadian Community Health Survey to mortality (n = 299,500) with satellite-derived ambient PM2.5 estimates. Participants enrolled between 2000 and 2008 were followed to date of death or December 31, 2011. Cox proportional hazards models were used to estimate hazard ratios (HRs) for mortality attributed to PM2.5 exposure, adjusted for individual-level and contextual covariates, including smoking behaviour and body mass index (BMI).

RESULTS

Approximately 26,300 non-accidental deaths, of which 32.5 % were due to circulatory disease and 9.1 % were due to respiratory disease, occurred during the follow-up period. Ambient PM2.5 exposures were relatively low (mean = 6.3 μg/m(3)), yet each 10 μg/m(3) increase in exposure was associated with increased risks of non-accidental (HR = 1.26; 95 % CI: 1.19-1.34), circulatory disease (HR = 1.19; 95 % CI: 1.07-1.31), and respiratory disease mortality (HR = 1.52; 95 % CI: 1.26-1.84) in fully adjusted models. Higher hazard ratios were observed for respiratory mortality among respondents who never smoked (HR = 1.97; 95 % CI: 1.24-3.13 vs. HR = 1.45; 95 % CI: 1.17-1.79 for ever smokers), and among obese (BMI ≥ 30) respondents (HR = 1.76; 95 % CI: 1.15-2.69 vs. HR = 1.41; 95 % CI: 1.04-1.91 for normal weight respondents), though differences between groups were not statistically significant. A threshold analysis for non-accidental mortality estimated a threshold concentration of 0 μg/m(3) (+95 % CI = 4.5 μg/m(3)).

CONCLUSIONS

Increased risks of non-accidental, circulatory, and respiratory mortality were observed even at very low concentrations of ambient PM2.5. HRs were generally greater than most literature values, and adjusting for behavioural covariates served to reduce HR estimates slightly.

Neighbourhood socio-economic status and all-cause mortality in adults with atrial fibrillation: A cohort study of patients treated in primary care in Sweden

OBJECTIVE

Our aim was to study the potential impact of neighbourhood socio-economic status (SES) on all-cause mortality in patients with atrial fibrillation (AF) treated in primary care.

METHODS

Study population included adults (n=12,283) of 45 years and older diagnosed with AF in 75 primary care centres in Sweden. Association between neighbourhood SES and all-cause mortality was explored using Cox regression analysis, with hazard ratios (HRs) and 95% confidence intervals (95% CIs), and by Laplace regression where years to death (95% CI) of the first 10% of the participants were used as an outcome. All models were conducted in both men and women and adjusted for age, educational level, marital status, change of neighbourhood status, cardiovascular co-morbidities, anticoagulant treatment and statin treatment. High- and low-neighbourhood SES were compared with middle SES as reference group.

RESULTS

After adjustments for potential confounders, higher relative risk of all-cause mortality (HR 1.49, 95% CI 1.13-1.96) was observed in men living in low SES neighbourhoods compared to those from middle SES neighbourhoods. The results were confirmed using Laplace regression; the time until the first 10% of the men in low SES neighbourhoods died was 1.45 (95% CI 0.48-2.42) years shorter than for the men in middle SES neighbourhoods.

CONCLUSIONS

Increased rates of heart disease and subsequent mortality among adults in deprived neighbourhoods raise important clinical and public health concerns. These findings could serve as an aid to policy-makers when allocating resources in primary health care settings as well as to clinicians who encounter patients in deprived neighbourhoods.

Socioeconomic modifiers of genetic and environmental influences on body mass index in adult twins

OBJECTIVE

Individual measures of socioeconomic status (SES) suppress genetic variance in body mass index (BMI). Our objective was to examine the influence of both individual-level (i.e., educational attainment, household income) and macrolevel (i.e., neighborhood socioeconomic advantage) SES indicators on genetic contributions to BMI.

METHOD

The study used education level data from 4,162 monozygotic (MZ) and 1,900 dizygotic (DZ) same-sex twin pairs (64% female), income level data from 3,498 MZ and 1,534 DZ pairs (65% female), and neighborhood-level socioeconomic deprivation data from 2,327 MZ and 948 DZ pairs (65% female). Covariates included age (M = 40.4 ± 17.5 years), sex, and ethnicity. The cotwin control model was used to evaluate the mechanisms through which SES influences BMI (e.g., through genetic vs. environmental pathways), and a gene-by-environment interaction model was used to test whether residual variance in BMI, after controlling for the main effects of SES, was moderated by socioeconomic measures.

RESULTS

SES significantly predicted BMI. The association was noncausal, however, and instead was driven primarily through a common underlying genetic background that tended to grow less influential as SES increased. After controlling for the main effect of SES, both genetic and nonshared environmental variance decreased with increasing SES.

CONCLUSIONS

The impact of individual and macrolevel SES on BMI extends beyond its main effects. The influence of genes on BMI is moderated by individual and macrolevel measures of SES, such that when SES is higher, genetic factors become less influential.

Neighbourhood immigrant concentration and hospitalization: a multilevel analysis of cardiovascular-related admissions in Ontario using linked data

OBJECTIVE

To assess the influence of neighbourhood immigrant concentration on cardiovascular-disease-related hospitalizations in Canada (CVDH), while adjusting for individual-level immigrant status and socio-economic indicators at individual and neighbourhood levels.

METHODS

Data were from the 2006 Canadian Census linked to the hospital Discharge Abstract Data (DAD) for the province of Ontario. Adults (n=1,459,950) aged ≥18 years at baseline and grouped by place of birth (Canada, China, South Asia, Europe, and other) were followed between Census Day May 16, 2006 and March 31, 2008. Information on CVDH was obtained from the DAD, while that on immigration and socio-economic indicators was obtained from the Census. The analysis used multilevel logistic regression.

RESULTS

Unadjusted results showed that CVDH was significantly lower among people living in neighbourhoods with medium and high immigrant concentration. Neighbourhood immigrant concentration tended to have no independent effect on CVDH after adjustment for individual-level immigrant status. Immigrants were less likely to experience CVDH irrespective of their country of birth. However, cross-level interaction showed that neighbourhood immigrant concentration provided additional protection to individual-level immigrant status against CVDH for most female immigrant groups, but only for South Asian males.

CONCLUSION

This study resulted from the first-ever linkage of census data to hospitalization data in Canada. It is also the first Canadian study to report on neighbourhood variation and the effect of immigrant concentration on CVDH. The study shows that understanding immigrant health requires both individual and neighbourhood approaches, and a consideration of country of origin.

Construction of an environmental quality index for public health research

BACKGROUND

A more comprehensive estimate of environmental quality would improve our understanding of the relationship between environmental conditions and human health. An environmental quality index (EQI) for all counties in the U.S. was developed.

METHODS

The EQI was developed in four parts: domain identification; data source acquisition; variable construction; and data reduction. Five environmental domains (air, water, land, built and sociodemographic) were recognized. Within each domain, data sources were identified; each was temporally (years 2000-2005) and geographically (county) restricted. Variables were constructed for each domain and assessed for missingness, collinearity, and normality. Domain-specific data reduction was accomplished using principal components analysis (PCA), resulting in domain-specific indices. Domain-specific indices were then combined into an overall EQI using PCA. In each PCA procedure, the first principal component was retained. Both domain-specific indices and overall EQI were stratified by four rural-urban continuum codes (RUCC). Higher values for each index were set to correspond to areas with poorer environmental quality.

RESULTS

Concentrations of included variables differed across rural-urban strata, as did within-domain variable loadings, and domain index loadings for the EQI. In general, higher values of the air and sociodemographic indices were found in the more metropolitan areas and the most thinly populated areas have the lowest values of each of the domain indices. The less-urbanized counties (RUCC 3) demonstrated the greatest heterogeneity and range of EQI scores (-4.76, 3.57) while the thinly populated strata (RUCC 4) contained counties with the most positive scores (EQI score ranges from -5.86, 2.52).

CONCLUSION

The EQI holds promise for improving our characterization of the overall environment for public health. The EQI describes the non-residential ambient county-level conditions to which residents are exposed and domain-specific EQI loadings indicate which of the environmental domains account for the largest portion of the variability in the EQI environment. The EQI was constructed for all counties in the United States, incorporating a variety of data to provide a broad picture of environmental conditions. We undertook a reproducible approach that primarily utilized publically-available data sources.

Construction of an environmental quality index for public health research

BACKGROUND

A more comprehensive estimate of environmental quality would improve our understanding of the relationship between environmental conditions and human health. An environmental quality index (EQI) for all counties in the U.S. was developed.

METHODS

The EQI was developed in four parts: domain identification; data source acquisition; variable construction; and data reduction. Five environmental domains (air, water, land, built and sociodemographic) were recognized. Within each domain, data sources were identified; each was temporally (years 2000-2005) and geographically (county) restricted. Variables were constructed for each domain and assessed for missingness, collinearity, and normality. Domain-specific data reduction was accomplished using principal components analysis (PCA), resulting in domain-specific indices. Domain-specific indices were then combined into an overall EQI using PCA. In each PCA procedure, the first principal component was retained. Both domain-specific indices and overall EQI were stratified by four rural-urban continuum codes (RUCC). Higher values for each index were set to correspond to areas with poorer environmental quality.

RESULTS

Concentrations of included variables differed across rural-urban strata, as did within-domain variable loadings, and domain index loadings for the EQI. In general, higher values of the air and sociodemographic indices were found in the more metropolitan areas and the most thinly populated areas have the lowest values of each of the domain indices. The less-urbanized counties (RUCC 3) demonstrated the greatest heterogeneity and range of EQI scores (-4.76, 3.57) while the thinly populated strata (RUCC 4) contained counties with the most positive scores (EQI score ranges from -5.86, 2.52).

CONCLUSION

The EQI holds promise for improving our characterization of the overall environment for public health. The EQI describes the non-residential ambient county-level conditions to which residents are exposed and domain-specific EQI loadings indicate which of the environmental domains account for the largest portion of the variability in the EQI environment. The EQI was constructed for all counties in the United States, incorporating a variety of data to provide a broad picture of environmental conditions. We undertook a reproducible approach that primarily utilized publically-available data sources.