Moving beyond the residential neighborhood to explore social inequalities in exposure to area-level disadvantage: Results from the Interdisciplinary Study on Inequalities in Smoking

The association between off- and on-premise alcohol outlet density and 100% alcohol-attributable emergency department visits by neighbourhood-level socioeconomic status in Ontario, Canada

Alcohol availability is positively associated with alcohol use and harms, but the influence of socioeconomic status (SES) on these associations is not well established. This population-based cross-sectional study examined neighbourhood-level associations between physical alcohol availability (measured as off- and on-premise alcohol outlet density) and 100% alcohol-attributable emergency department (ED) visits by neighbourhood SES in Ontario, Canada from 2017 to 2019 (n = 19,740). A Bayesian spatial modelling approach was used to assess associations and account for spatial autocorrelation, which produced risk ratios (RRs) and 95% credible intervals (95% CrI). Each additional off-premise alcohol outlet in a neighbourhood was associated with a 3% increased risk of alcohol-attributable ED visits in both men (RR = 1.03, 95%CrI: 1.02-1.04) and women (RR = 1.03, 95% CrI: 1.02-1.04). Positive associations were also observed between on-premise alcohol outlet density and alcohol-attributable ED visits, although effect sizes were small. A disproportionately greater association with ED visits was observed with increasing alcohol outlet density in the lowest compared to higher SES neighbourhoods. Reducing physical alcohol availability may be an important policy lever for reducing alcohol harm and alcohol-attributable health inequities.

Activity space during treatment with medication for opioid use disorder: Relationships with personality, mood, and drug use

INTRODUCTION

Activity space in people with substance use disorders (SUDs) has been assessed for theoretical reasons and for detection/prevention of relapse. In this observational study, we relate passively obtained activity space measures to mental states and behaviors relevant to the success of treatment for opioid use disorder. Our long-term goal is to use such data to assess risk in real time and to recognize when SUD patients might benefit from a just-in-time intervention.

METHODS

We used GPS data from 238 urban residents in the first 16 weeks of stabilization on medication for opioid use disorder to test preregistered hypotheses about activity space (distance traveled, number of locations, time spent moving, and psychosocial-hazard levels of neighborhoods where participants spent time) in relation to certain static variables (personality, mood propensities) and time-varying treatment-relevant behaviors such as craving and use of opioids and cocaine.

RESULTS

The most consistent findings were that 1) mobility decreased over the course of the study; 2) neuroticism was associated with overall lower mobility; 3) trait-like positive mood (averaged from momentary ratings) was associated with higher mobility; 4) participants who used cocaine more frequently had lower mobility; 5) early in treatment, participants spent less time moving (i.e., were more sedentary) on days when they were craving. Some of these findings were in the expected direction (i.e., the ones involving neuroticism and positive mood), and some were opposite to the expected direction (i.e., we expected cocaine use to be associated with higher mobility); others (e.g., changes in mobility over time or in relation to craving) involved nondirectional hypotheses.

CONCLUSIONS

Real-time information that patients actively provide is valuable for assessing their current state, but providing this information can be burdensome. The current results indicate that certain static or passively obtained data (personality variables and GPS-derived mobility information) are relevant to time-varying, treatment-relevant mental states and drug-related behavior, and therefore might be useful when incorporated into algorithms for detecting need for intervention in real time. Further research should assess how population-specific these relationships are, and how these passive measures can best be combined with low temporal-density, actively-provided data to obtain valid, reliable assessments with minimal burden.

The role of the perceived environment for recreational walking among adults in socioeconomically disadvantaged situations: A study using walk-along interviews

Background

Persons in socioeconomically disadvantaged situations (PSEDS) are generally less likely to engage in recreational walking (RW) compared to higher socioeconomic groups and are often more dependent on their local environment. Studies on RW have primarily focused on the role of the built environment for the general adult population and the older population in urban areas. The aim of this study is to qualitatively identify the perceived environmental factors affecting RW among PSEDS in peri-urban areas.

Methods

In two peri-urban municipalities in Belgium, walk-along interviews were conducted until data saturation with a purposeful convenience sampling of 38 PSEDS (25-65y/o) to identify local environmental factors affecting RW. A subsample of 22 participants joined a focus group (n = 4) to categorize the identified factors into environmental types (physical, sociocultural, political, and economic) of the Analysis Grid for Environments Linked to Obesity (ANGELO) framework. The interviews were transcribed and analyzed thematically using Maxqda 2022.0.

Results

The information environment (dissemination, retrieving and understanding of information) was added to the ANGELO framework, highlighting the importance of digital literacy. Availability and accessibility of well-maintained walking surfaces, toilets, street lighting and seating options (physical environment), social support, dog-ownership, stigmatization, social isolation, and a sense of belonging (sociocultural environment) and indirect costs (economic environment) were identified as important environmental factors in RW among PSEDS. The identified political and economic factors are intertwined with the other environments.

Conclusions

Perceived environmental factors affect RW among PSEDS and peri-urban settings offer specific challenges. Local governments should incorporate citizen perception into decision-making processes to create supportive environments that have the potential to promote RW among PSEDS in a peri-urban setting.

Neighborhood Physical and Social Environments and Social Inequalities in Health in Older Adolescents and Young Adults: A Scoping Review

Poor health and well-being are prevalent among young people. Neighborhoods may play a role in promoting good health. Little is known on if and how neighborhood characteristics affect health, and social inequalities therein, among young people. In this scoping review, we asked: (1) what features of the neighborhood physical and social environments have been studied in association with the physical and mental health and well-being of young people 15 to 30 years old; and (2) to what extent have social differentials in these associations been studied, and how? We identified peer-reviewed articles (2000 to 2023) through database and snowball searches. We summarized study characteristics, exposure(s), outcome(s) and main findings, with an eye on social inequalities in health. Out of the 69 articles reviewed, most were quantitative, cross-sectional, conducted among 18-year-olds and younger, and focused on the residential neighborhood. Neighborhood social capital and mental health were the most common exposure and outcome studied, respectively. Almost half of the studies examined social inequalities in health, mostly across sex/gender, socioeconomic status, and ethnicity. Evidence gaps remain, which include exploring settings other than residential neighborhoods, studying the older age stratum of young adulthood, and assessing a broader range of social inequalities. Addressing these gaps can support research and action on designing healthy and equitable neighborhoods for young people.

Air pollution and metabolic disorders: Dynamic versus static measures of exposure among Hispanics/Latinos and non-Hispanics

INTRODUCTION

Exposure to air pollution disproportionately affects racial/ethnic minorities that could contribute to health inequalities including metabolic disorders. However, most existing studies used a static assessment of air pollution exposure (mostly using the residential address) and do not account for activity space when modelling exposure to air pollution. The aim of this study is to understand how exposure to air pollution impacts metabolic disorders biomarkers, how this effect differs according to ethnicity, and for the first time compare these findings with two methods of exposure assessment: dynamic and static measures.

METHODS

Among the Community of Mine study, a cross-sectional study conducted in San Diego County, insulin resistance, diabetes, hypertension, obesity, dyslipidemia, and metabolic syndrome (MetS) were assessed. Exposure to air pollution (PM_2.5, NO₂, traffic) was calculated using static measures around the home, and dynamic measures of mobility derived from Global Positioning Systems (GPS) traces using kernel density estimators to account for exposure variability across space and time. Associations of air pollution with metabolic disorders were quantified using generalized estimating equation models to account for the clustered nature of the data.

RESULTS

Among 552 participants (mean age 58.7 years, 42% Hispanic/Latino), Hispanics/Latinos had a higher exposure to PM_2.5 compared to non-Hispanics using static measures. In contrast, Hispanics/Latinos had less exposure to PM_2.5 using dynamic measures. For all participants, higher dynamic exposure to PM_2.5 and NO₂ was associated with increased insulin resistance and cholesterol levels, and increased risk of obesity, dyslipidemia and MetS (RR 1.17, 95% CI: 1.07-1.28; RR 1.21, 95% CI: 1.12-1.30, respectively). The association between dynamic PM_2.5 exposure and MetS differed by Hispanic/Latino ethnicity.

CONCLUSION

These results highlight the importance of considering people's daily mobility in assessing the impact of air pollution on health.

Aggravated social segregation during the COVID-19 pandemic: Evidence from crowdsourced mobility data in twelve most populated U.S. metropolitan areas

The notion of social segregation refers to the degrees of separation between socially different population groups. Many studies have examined spatial and residential separations among different socioeconomic or racial populations. However, with the advancement of transportation and communication technologies, people's activities and social interactions are no longer limited to their residential areas. Therefore, there is a growing necessity to investigate social segregation from a mobility perspective by analyzing people's mobility patterns. Taking advantage of crowdsourced mobility data derived from 45 million mobile devices, we innovatively quantify social segregation for the twelve most populated U.S. metropolitan statistical areas (MSAs). We analyze the mobility patterns between different communities within each MSA to assess their separations for two years. Meanwhile, we particularly explore the dynamics of social segregation impacted by the COVID-19 pandemic. The results demonstrate that New York and Washington D.C. are the most and least segregated MSA respectively among the twelve MSAs. Since the COVID-19 began, six of the twelve MSAs experienced a statistically significant increase in segregation. This study also shows that, within each MSA, the most and least vulnerable groups of communities are prone to interacting with their similar communities, indicating a higher degree of social segregation.

Perceived neighbourhood characteristics and depressive symptoms: Potential mediators and the moderating role of employment status

Multiple neighbourhood characteristics have been linked to depressive symptoms. However, few studies have simultaneously considered multiple mechanisms that explain this relationship, and how they might interact. Further, most studies regard exposure to the residential environment as constant, and therefore disregard variation in exposure by individual factors. This study investigates whether and to what extent stress and physical activity mediate the association between neighbourhood characteristics and depression, and also to what extent employment status moderates this relationship. A population-representative survey of n = 11,505 people in the Netherlands was conducted. Depressive symptoms were measured using the Patient Health Questionnaire (PHQ-9). Neighbourhood characteristics were perceived green and blue space, pleasantness, environmental disturbance, social cohesion and safety. Employment status was combined with place of work to establish two groups: those who were non-working or who worked from home ('at home'), and those who worked somewhere outside of the home ('working'). Multi-group structural equation modelling was employed to understand the theorised relationships for both groups. Perceived environmental disturbance, social cohesion and safety were significantly indirectly related to depressive symptoms via stress, with larger effect sizes in the 'at home' group. Pleasantness was also significantly indirectly related to depressive symptoms via stress, in the 'at home' group only. There was no evidence for physical activity as a mediator. Our findings suggest that neighbourhood social characteristics may have a greater influence on depressive symptoms than physical characteristics. Stress appears to be a key mediator of this relationship. In addition, the neighbourhood appears to exert a greater influence on those who spend more time in their neighbourhood. Interventions to promote mental health should focus on the social environment, and in particular pay attention to those who are spatially confined in poorer quality neighbourhoods.

Is Smoking Cessation in Young Adults Associated With Tobacco Retailer Availability in Their Activity Space?

INTRODUCTION

The presence of tobacco retailers in residential neighborhoods has been inversely associated with residents' likelihood of quitting smoking. Few studies have yet explored whether this association holds when accounting for tobacco retailers found in the multiple environments where people conduct their daily activities, that is, their activity space.

METHODS

We analyzed cross-sectional data from 921 young adults (18- to 25-years old) participating in the Interdisciplinary Study of Inequalities in Smoking (Montreal, Canada). Respondents self-reported sociodemographic, smoking, and activity location data. Log-binomial regression was used to estimate prevalence ratios (PRs) for the association between smoking cessation and (1) the number of tobacco retailers (counts), and (2) the distance to the closest retailer (proximity) in participants' residential neighborhood and activity space.

RESULTS

Smoking cessation was positively associated with low and intermediate tertile levels of tobacco retailer counts in both the residential neighborhood and activity space, and with the furthest distance level in the activity space [PR (95% CI) = 1.21 (1.02 to 1.43)].

CONCLUSIONS

Individuals encounter resources in the course of their regular daily activities that may hamper smoking cessation. This study highlights the relevance of considering the tobacco retail environment of both individuals' residential neighborhood and activity space to understand its association with smoking cessation.

IMPLICATIONS

This article contributes to the literature on the association between the tobacco retail environment and smoking cessation in young adults by moving beyond the residential neighborhood to also assess individuals' access to tobacco retailers in the multiple areas where they regularly spend time, that is, their activity space. Findings suggest that lower numbers of tobacco retailers in both the residential neighborhood and activity space, and further distance to tobacco retailers in the activity space are associated with increased smoking cessation.

Risk of late cervical cancer screening in the Paris region according to social deprivation and medical densities in daily visited neighborhoods

Background

Social and physical characteristics of the daily visited neighborhoods have gained an extensive interest in analyzing socio-territorial inequalities in health and healthcare. The objective of the present paper is to estimate and discuss the role of individual and contextual factors on participation in preventive health-care activities (smear screening) in the Greater Paris area focusing on the characteristics of daily visited neighborhoods in terms of medical densities and social deprivation.

Methods

The study included 1817 women involved in the SIRS survey carried out in 2010. Participants could report three neighborhoods they regularly visit (residence, work/study, and the next most regularly visited). Two “cumulative exposure scores” have been computed from household income and medical densities (general practitioners and gynecologists) in these neighborhoods. Multilevel logistic regression models were used to measure association between late cervical screening (> 3 years) and characteristics of daily visited neighborhoods (residential, work or study, visit).

Results

One-quarter of the women reported that they had not had a smear test in the previous 3 years. Late smear test was found to be more frequent among younger and older women, among women being single, foreigners and among women having a low-level of education and a limited activity space. After adjustment on individual characteristics, a significant association between the cumulative exposure scores and the risk of a delayed smear test was found: women who were exposed to low social deprivation and to low medical densities in the neighborhoods they daily visit had a significantly higher risk of late cervical cancer screening than their counterparts.

Conclusions

For a better understanding of social and territorial inequalities in healthcare, there is a need for considering multiple daily visited neighborhoods. Cumulative exposure scores may be an innovative approach for analyzing contextual effects of daily visited neighborhoods rather than focusing on the sole residential neighborhood.

Examining Ethnic Exposure through the Perspective of the Neighborhood Effect Averaging Problem: A Case Study of Xining, China

An increasing number of studies have observed that ignoring individual exposures to non-residential environments in people's daily life may result in misleading findings in research on environmental exposure. This issue was recognized as the neighborhood effect averaging problem (NEAP). This study examines ethnic segregation and exposure through the perspective of NEAP. Focusing on Xining, China, it compares the Hui ethnic minorities and the Han majorities. Using 2010 census data and activity diary data collected in 2013, the study found that NEAP exists when examining ethnic exposure. Respondents who live in highly mixed neighborhoods (with high exposures to the other ethnic group) experience lower activity-space exposures because they tend to conduct their daily activities in ethnically less mixed areas outside their home neighborhoods (which are more segregated). By contrast, respondents who live in highly segregated neighborhoods (with low exposures to the other ethnic group) tend to have higher exposures in their activity locations outside their home neighborhoods (which are less segregated). Therefore, taking into account individuals' daily activities in non-residential contexts in the assessment of environmental exposure will likely lead to an overall tendency towards the mean exposure. Using Tobit models, we further found that specific types of activity places, especially workplaces and parks, contribute to NEAP. Ignoring individual exposures in people's activity places will most likely result in misleading findings in the measurement of environmental exposure, including ethnic exposure.

Stability of activity space footprint, size, and environmental features over six months

As activity space measures are increasingly used to estimate exposure to environmental determinants of health, little is known about the stability of these measures over time. To test the stability of GPS-derived measures of activity-space footprint, size, and environmental features over time, we compared 14-day measures at baseline and six months later for 35 adults in a large city. Activity-space measures were based on convex hulls and 500 m route buffers, and included the geographic footprint (i.e. location of the activity space), size (i.e., area in square miles; (Cummins, 2007)), and environmental features including supermarket, fast-food restaurant, and parkland density. The proportion of the participants' smaller geographic footprint covered by the larger was, on average, 0.64 (SD 0.17) for the 500 m route buffer and 0.84 (SD 0.18) for the convex hull. Mean percent change in activity space size ranged from 36.3% (mean daily 500 m route buffer) to 221.3% (cumulative convex hull). Mean percent change in the density of environmental features ranged from 28.8 to 66.5%. Forty-one percent to 92.4% of the variance at one timepoint was predicted by environmental features measured within approximately six months. Activity-space size and environmental features were moderately to highly stable over six months, although there was considerable variation in stability between measures. Strategies for addressing measurement error in studies of activity space-health associations are discussed.

The association of county-level socioeconomic factors with individual tobacco and alcohol use: a longitudinal study of U.S. adults

Background

Place-based factors have been implicated as root causes of socioeconomic disparities in risky health behaviors such as tobacco and alcohol use. Yet few studies examine the effects of county-level socioeconomic characteristics, despite the fact that social and public health policies are often implemented at the county level. In this study, we tested the hypothesis that county-level socioeconomic disadvantage was associated with individual tobacco and alcohol use.

Methods

The sample included a panel of participants from the National Longitudinal Survey of Youth (N = 9302). The primary predictors were three time-varying measures of socioeconomic disadvantage in an individual’s county of residence: educational attainment, percent unemployment, and per capita income. We first conducted traditional ordinary least squares (OLS) models, both unadjusted and adjusted for individual-level covariates. We then conducted fixed effects (FE) models to adjust for confounding by unmeasured time-invariant individual-level factors.

Results

OLS and FE models yielded contrasting results: higher county-level per capita income was associated with decreased drinking in OLS models and increased drinking in FE models, while decreased county-level educational attainment was associated with decreased smoking in OLS models and more cigarettes per day in FE models. The findings from FE models suggest that OLS models were confounded by unobserved time-invariant characteristics. Notably, the point estimates for the county-level measures were small, and in many cases they may not represent a clinically meaningful effect except at the population level.

Conclusions

These results suggest that county-level socioeconomic characteristics may modestly influence tobacco and alcohol use. Future work should examine the effects of specific county policies that might explain these findings.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6700-x) contains supplementary material, which is available to authorized users.

How many days of global positioning system (GPS) monitoring do you need to measure activity space environments in health research?

This study examined the number of days of global positioning system (GPS) monitoring needed to measure attributes of an individual's routine activity space. Multiple alternative activity space representations (cumulative, mean daily), measures (kernel density, route buffer, convex hull), and attributes (area size, supermarkets, fast food restaurants, parks) were examined. Results suggested wide variability in required GPS days to obtain valid estimates of activity space attributes (1-23 days). In general, fewer days were needed for mean daily activity space representations, kernel density measures, and densities of environmental exposures (vs. counts). While kernel density measures reliably estimated between-person differences in attributes after just a few days, most variability in environmental attributes for convex hull and route buffer measures was within-person. Based on these results, a minimum of 14 days of valid GPS data is recommended to measure activity spaces.

Convergent validity of an activity-space survey for use in health research

We explored the validity of a survey measuring activity spaces for use in health research in a racially/ethnically diverse adult sample (n = 86) living in four Chicago neighborhoods. Participants reported on the location and visit frequency of 64 activities and wore a GPS data logger. We assessed the spatial congruence of survey- and GPS-derived convex hull measures and the number of GPS points within 100 m and 1000 m of survey locations. The survey-derived convex hull measures captured a small percentage (median = 35.9%) of the GPS-derived convex hull area. However, most GPS points were located within 100 m or 1000 m of home or reported survey locations (median = 73.4% and 92.6%, respectively).

Collecting Mobility Data with GPS Methods to Understand the HIV Environmental Riskscape Among Young Black Men Who Have Sex with Men: A Multi-city Feasibility Study in the Deep South

While research increasingly studies how neighborhood contexts influence HIV among gay, bisexual and other men who have sex with men (MSM) populations, to date, no research has used global positioning system (GPS) devices, an innovative method to study spatial mobility through neighborhood contexts, i.e., the environmental riskscape, among a sample of Black MSM. The purpose of this study was to examine the feasibility of collecting two-week GPS data (as measured by a pre- and post-surveys as well as objectively measured adherence to GPS protocol) among a geographically-diverse sample of Black MSM in the Deep South: Gulfport, MS, Jackson, MS, and New Orleans LA (n = 75). GPS feasibility was demonstrated including from survey items, e.g. Black MSM reported high ratings of pre-protocol acceptability, ease of use, and low levels of wear-related concerns. Findings from this study demonstrate that using GPS methods is acceptable and feasible among Black MSM in the Deep South.

The "Residential" Effect Fallacy in Neighborhood and Health Studies: Formal Definition, Empirical Identification, and Correction

BACKGROUND

Because of confounding from the urban/rural and socioeconomic organizations of territories and resulting correlation between residential and nonresidential exposures, classically estimated residential neighborhood-outcome associations capture nonresidential environment effects, overestimating residential intervention effects. Our study diagnosed and corrected this "residential" effect fallacy bias applicable to a large fraction of neighborhood and health studies.

METHODS

Our empirical application investigated the effect that hypothetical interventions raising the residential number of services would have on the probability that a trip is walked. Using global positioning systems tracking and mobility surveys over 7 days (227 participants and 7440 trips), we employed a multilevel linear probability model to estimate the trip-level association between residential number of services and walking to derive a naïve intervention effect estimate and a corrected model accounting for numbers of services at the residence, trip origin, and trip destination to determine a corrected intervention effect estimate (true effect conditional on assumptions).

RESULTS

There was a strong correlation in service densities between the residential neighborhood and nonresidential places. From the naïve model, hypothetical interventions raising the residential number of services to 200, 500, and 1000 were associated with an increase by 0.020, 0.055, and 0.109 of the probability of walking in the intervention groups. Corrected estimates were of 0.007, 0.019, and 0.039. Thus, naïve estimates were overestimated by multiplicative factors of 3.0, 2.9, and 2.8.

CONCLUSIONS

Commonly estimated residential intervention-outcome associations substantially overestimate true effects. Our somewhat paradoxical conclusion is that to estimate residential effects, investigators critically need information on nonresidential places visited.

An Innovative Context-Based Crystal-Growth Activity Space Method for Environmental Exposure Assessment: A Study Using GIS and GPS Trajectory Data Collected in Chicago

Scholars in the fields of health geography, urban planning, and transportation studies have long attempted to understand the relationships among human movement, environmental context, and accessibility. One fundamental question for this research area is how to measure individual activity space, which is an indicator of where and how people have contact with their social and physical environments. Conventionally, standard deviational ellipses, road network buffers, minimum convex polygons, and kernel density surfaces have been used to represent people’s activity space, but they all have shortcomings. Inconsistent findings of the effects of environmental exposures on health behaviors/outcomes suggest that the reliability of existing studies may be affected by the uncertain geographic context problem (UGCoP). This paper proposes the context-based crystal-growth activity space as an innovative method for generating individual activity space based on both GPS trajectories and the environmental context. This method not only considers people’s actual daily activity patterns based on GPS tracks but also takes into account the environmental context which either constrains or encourages people’s daily activity. Using GPS trajectory data collected in Chicago, the results indicate that the proposed new method generates more reasonable activity space when compared to other existing methods. This can help mitigate the UGCoP in environmental health studies.

Using Individual GPS Trajectories to Explore Foodscape Exposure: A Case Study in Beijing Metropolitan Area

With the growing interest in studying the characteristics of people’s access to the food environment and its influence upon individual health, there has been a focus on assessing individual food exposure based on GPS trajectories. However, existing studies have largely focused on the overall activity space using short-period trajectories, which ignores the complexity of human movements and the heterogeneity of the spaces that are experienced by the individual over daily life schedules. In this study, we propose a novel framework to extract the exposure areas consisting of the localized activity spaces around daily life centers and non-motorized commuting routes from long-term GPS trajectories. The newly proposed framework is individual-specific and can incorporate the internal heterogeneity of individual activities (spatial extent, stay duration, and timing) in different places as well as the dynamics of the context. A pilot study of the GeoLife dataset suggests that there are significant variations in the magnitude as well as the composition of the food environment in different parts of the individual exposure area, and residential environment is not representative of the overall foodscape exposure.

Standardized cancer incidence disparities in Upper Manhattan New York City neighborhoods: the role of race/ethnicity, socioeconomic status, and known risk factors

We examined the effects of race/ethnicity and neighborhood, a proxy of socioeconomic status, on cancer incidence in New York City neighborhoods: East Harlem (EH), Central Harlem (CH), and Upper East Side (UES). In this ecological study, Community Health Survey data (2002-2006) and New York State Cancer Registry incidence data (2007-2011) were stratified by sex, age, race/ethnicity, and neighborhood. Logistic regression models were fitted to each cancer incidence rate with race/ethnicity, neighborhood, and Community Health Survey-derived risk factors as predictor variables. Neighborhood was significantly associated with all cancers and 14 out of 25 major cancers. EH and CH residence conferred a higher risk of all cancers compared with UES (OR=1.34, 95% CI 1.07-1.68; and OR=1.39, 95% CI 1.12-1.72, respectively). The prevalence of diabetes and tobacco smoking were the largest contributors toward high cancer rates. Despite juxtaposition and similar proximity to medical centers, cancer incidence disparities persist among EH, CH, and UES neighborhoods. Targeted, neighborhood-specific outreach may aid in reducing cancer incidence rates.

Integrating activity spaces in health research: Comparing the VERITAS activity space questionnaire with 7-day GPS tracking and prompted recall

BACKGROUND

Accounting for daily mobility allows assessment of multiple exposure to environments. This study compares spatial data obtained (i) from an interactive map-based questionnaire on regular activity locations (VERITAS) and (ii) from GPS tracking.

METHODS

234 participants of the RECORD GPS Study completed the VERITAS questionnaire and wore a GPS tracker for 7 days. Analyses illustrate the spatial match between both datasets.

RESULTS

For half of the sample, 85.5% of GPS data fell within 500 m of a VERITAS location. The median minimum distance between a VERITAS location and a GPS coordinate ranged from 0.4 m for home to slightly over 100 m for a recreational destination.

CONCLUSIONS

There is a spatial correspondence between destinations collected through VERITAS and 7-day GPS tracking. Both collection methods offer complementary ways to assess daily mobilities, useful to study environmental determinants of health and health inequities.

Multi-Contextual Segregation and Environmental Justice Research: Toward Fine-Scale Spatiotemporal Approaches

Many environmental justice studies have sought to examine the effect of residential segregation on unequal exposure to environmental factors among different social groups, but little is known about how segregation in non-residential contexts affects such disparity. Based on a review of the relevant literature, this paper discusses the limitations of traditional residence-based approaches in examining the association between socioeconomic or racial/ethnic segregation and unequal environmental exposure in environmental justice research. It emphasizes that future research needs to go beyond residential segregation by considering the full spectrum of segregation experienced by people in various geographic and temporal contexts of everyday life. Along with this comprehensive understanding of segregation, the paper also highlights the importance of assessing environmental exposure at a high spatiotemporal resolution in environmental justice research. The successful integration of a comprehensive concept of segregation, high-resolution data and fine-grained spatiotemporal approaches to assessing segregation and environmental exposure would provide more nuanced and robust findings on the associations between segregation and disparities in environmental exposure and their health impacts. Moreover, it would also contribute to significantly expanding the scope of environmental justice research.

The daycourse of place

The present paper aims to contribute to the debate about the temporal relationships between place and health. It explores the notion of 'daycourse of place' echoing the discussion which recently occurred in this journal about the 'lifecourse of place' (Andrews, 2017; Lekkas et al., 2017a, b). When highlighting the importance of time in shaping health within places, most of studies focus either on the trajectories of places over a matter of years or the daily trajectories of people in link with their activity space. However, daily trajectories of places remain a poor cousin in place and health literature. This paper is intended to overcome 'jetlag', which places suffer when they are labelled with frozen attributes over a 24-h period. It explores the values and feasibility of exploring daily trajectories of places to investigate place effects on health or to design area-based interventions for public health action. More than just a metaphor, the 'daycourse of place' appears to be an inspiring framework to elaborate the importance of daily temporal relationalities for research and action in place-based health inequalities.

Enhancement of urban heat load through social inequalities on an example of a fictional city King's Landing

The numerical model MUKLIMO_3 is used to simulate the urban climate of an imaginary city as an illustrative example to demonstrate that the residential areas with deprived socio-economic conditions can exhibit an enhanced heat load at night, and thus more disadvantageous environmental conditions, compared with the areas of higher socio-economic status. The urban climate modelling simulations differentiate between orographic, natural landscape, building and social effects, where social differences are introduced by selection of location, building type and amount of vegetation. The model results show that the increase of heat load can be found in the areas inhabited by the poor population as a combined effect of natural and anthropogenic factors. The unfavourable location in the city and the building type, consisting of high density, low housing with high fraction of pavement and small amount of vegetation contribute to the formation of excessive heat load. This abstract example shows that the enhancement of urban heat load can be linked to the concept of a socially stratified city and is independent of the historical development of any specific city.

Differential Effects of Neighborhood Type on Adolescent Alcohol Use in New Zealand

Identifying neighborhood typologies associated with adolescent alcohol use can inform the development of harm reduction strategies. Utilizing data from a nationally representative youth survey (n = 4267) in New Zealand, latent class analysis was used to categorize neighborhood types (defined by 10 demographic, social and environmental indicators) to investigate their association with alcohol consumption and related harm. Three neighborhood types were distinguished: (1) "high outlet density and economic deprivation" (30 % of all neighborhoods); (2) "high deprivation, social disorganization, and unsafe" (38 %); and (3) "higher income, safe, and socially organized" (32 %). Significant ethnic variation was evident between neighborhood types. There was an age-group interaction in the main effects with significant associations between neighborhood type and drinking measures and harm most apparent among younger adolescents (<16 years), as described next. Compared to students residing in "higher income, safe, and socially organized" neighborhoods, the frequency of binge drinking and high typical consumption was significantly higher in students residing in "high outlet density and economic deprivation" and "high deprivation, social disorganization, and unsafe", with students residing in "high outlet density and economic deprivation" also experiencing higher levels of alcohol-related harm. The findings that neighborhoods characterized by high deprivation and alcohol outlet density and low social organization and perceptions of safety were associated with risky drinking patterns and harm, specifically among young adolescents, underscores the importance of adopting a developmental approach to the study of contextual effects on adolescents.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Accounting for the daily locations visited in the study of the built environment correlates of recreational walking (the RECORD Cohort Study)

BACKGROUND

Understanding how built environment characteristics influence recreational walking is of the utmost importance to develop population-level strategies to increase levels of physical activity in a sustainable manner.

PURPOSE

This study analyzes the residential and non-residential environmental correlates of recreational walking, using precisely geocoded activity space data.

METHODS

The point-based locations regularly visited by 4365 participants of the RECORD Cohort Study (Residential Environment and CORonary heart Disease) were collected between 2011 and 2013 in the Paris region using the VERITAS software (Visualization and Evaluation of Regular Individual Travel destinations and Activity Spaces). Zero-inflated negative binomial regressions were used to investigate associations between both residential and non-residential environmental exposure and overall self-reported recreational walking over 7 days.

RESULTS

Density of destinations, presence of a lake or waterway, and neighborhood education were associated with an increase in the odds of reporting any recreational walking time. Only the density of destinations was associated with an increase in time spent walking for recreational purpose. Considering the recreational locations visited (i.e., sports and cultural destinations) in addition to the residential neighborhood in the calculation of exposure improved the model fit and increased the environment-walking associations, compared to a model accounting only for the residential space (Akaike Information Criterion equal to 52797 compared to 52815).

CONCLUSIONS

Creating an environment supportive to walking around recreational locations may particularly stimulate recreational walking among people willing to use these facilities.

Does the effect of walkable built environments vary by neighborhood socioeconomic status?

OBJECTIVE

To examine socioeconomic status as a moderator of the relationship between the built environment and active transportation such as walking or cycling using measures of built environment exposure derived from individuals transport trips.

METHODS

The 2008 Montreal Origin-destination (OD) survey provided origin-destination coordinates for a sample of 156,700 participants. We selected participants from this survey that had traveled within the census metropolitan area of Montreal the day preceding the interview, and that were between 18-65 years of age. Measures of connectivity, land-use mix, and density of business and services were collected using 400-m buffers of the trip routes. Logistic regression was used to model the relationship between built environment variables and active transportation.

RESULTS

Trip routes in the 2nd, 3rd, and 4th quartile of density of business and services or connectivity translated into greater odds of taking AT (compared to a trip in the lowest quartile). Trip routes in the 2nd, 3rd, and 4th quartile of land-use mix translated into lower odds of taking AT. Trips in the highest quartiles of connectivity and density of business and services were found to have a weaker association with active transportation if the individual undergoing the trip was from a low SES neighborhood.

CONCLUSION

Our results suggest that previous studies finding no effect modification may have been due to the limitation of measurements of exposures to the residential neighborhood.

Is There a Relationship Between the Concentration of Same-Sex Couples and Tobacco Retailer Density?

BACKGROUND

Tobacco use is markedly higher among lesbian, gay, and bisexual populations than heterosexuals. Higher density of tobacco retailers is found in neighborhoods with lower income and more racial/ethnic minorities. Same-sex couples tend to live in similar neighborhoods, but the association of this demographic with tobacco retailer density has not been examined.

METHODS

For a national sample of 97 US counties, we calculated the number of tobacco retailers per 1000 persons and rates of same-sex couples per 1000 households in each census tract (n = 17 941). Using spatial regression, we examined the association of these variables in sex-stratified models, including neighborhood demographics and other environmental characteristics to examine confounding.

RESULTS

Results from spatial regression show that higher rates of both female and male same-sex couples were associated with a higher density of tobacco retailers. However the magnitude of this association was small. For female couples, the association was not significant after controlling for area-level characteristics, such as percent black, percent Hispanic, median household income, the presence of interstate highways, and urbanicity, which are neighborhood correlates of higher tobacco retailer density. For male couples, the association persisted after control for these characteristics.

CONCLUSION

Same-sex couples reside in areas with higher tobacco retailer density, and for men, this association was not explained by neighborhood confounders, such as racial/ethnic composition and income. While lesbian, gay, and bisexual disparities in tobacco use may be influenced by neighborhood environment, the magnitude of the association suggests other explanations of these disparities remain important areas of research.

Canada Post community mailboxes: implications for health research

This article discusses the implications for health research of Canada Post's transition from door-to-door postal delivery to community mailboxes. We argue that using postal code data to geocode participants based on community mailboxes will result in positional and linkage errors. Positional errors involve misplacing people's residential location. Linkage errors result from incorrectly linking residential location from community mailboxes to census or health administrative data. The article discusses examples of how the transition to community mailboxes could have important implications for health research. We encourage research examining the extent of positional and linkage errors on the 11 pilot communities transitioning to community mailboxes in the fall of 2014.