The role of daily mobility in mental health inequalities: the interactive influence of activity space and neighbourhood of residence on depression

Open-source data pipeline for street-view images: A case study on community mobility during COVID-19 pandemic

Street View Images (SVI) are a common source of valuable data for researchers. Researchers have used SVI data for estimating pedestrian volumes, demographic surveillance, and to better understand built and natural environments in cityscapes. However, the most common source of publicly available SVI data is Google Street View. Google Street View images are collected infrequently, making temporal analysis challenging, especially in low population density areas. Our main contribution is the development of an open-source data pipeline for processing 360-degree video recorded from a car-mounted camera. The video data is used to generate SVIs, which then can be used as an input for longitudinal analysis. We demonstrate the use of the pipeline by collecting an SVI dataset over a 38-month longitudinal survey of Seattle, WA, USA during the COVID-19 pandemic. The output of our pipeline is validated through statistical analyses of pedestrian traffic in the images. We confirm known results in the literature and provide new insights into outdoor pedestrian traffic patterns. This study demonstrates the feasibility and value of collecting and using SVI for research purposes beyond what is possible with currently available SVI data. Our methods and dataset represent a first of its kind longitudinal collection and application of SVI data for research purposes. Limitations and future improvements to the data pipeline and case study are also discussed.

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.

Residential mobility restrictions and adverse mental health outcomes during the COVID-19 pandemic in the UK

During the COVID-19 pandemic, several governments tried to contain the spread of SARS-CoV-2, the virus that causes COVID-19, with lockdowns that prohibited leaving one's residence unless carrying out a few essential services. We investigate the relationship between limitations to mobility and mental health in the UK during the first year and a half of the pandemic using a unique combination of high-frequency mobility data from Google and monthly longitudinal data collected through the Understanding Society survey. We find a strong and statistically robust correlation between mobility data and mental health survey data and show that increased residential stationarity is associated with the deterioration of mental wellbeing even when regional COVID-19 prevalence and lockdown stringency are controlled for. The relationship is heterogeneous, as higher levels of distress are seen in young, healthy people living alone; and in women, especially if they have young children.

How is the COVID-19 pandemic impacting our life, mental health, and well-being? Design and preliminary findings of the pan-Canadian longitudinal COHESION study

BACKGROUND

With the advent of the COVID-19 pandemic, in-person social interactions and opportunities for accessing resources that sustain health and well-being have drastically reduced. We therefore designed the pan-Canadian prospective COVID-19: HEalth and Social Inequities across Neighbourhoods (COHESION) cohort to provide a deeper understanding of how the COVID-19 pandemic context affects mental health and well-being, key determinants of health, and health inequities.

METHODS

This paper presents the design of the two-phase COHESION Study, and descriptive results from the first phase conducted between May 2020 and September 2021. During that period, the COHESION research platform collected monthly data linked to COVID-19 such as infection and vaccination status, perceptions and attitudes regarding pandemic-related measures, and information on participants' physical and mental health, well-being, sleep, loneliness, resilience, substances use, living conditions, social interactions, activities, and mobility.

RESULTS

The 1,268 people enrolled in the Phase 1 COHESION Study are for the most part from Ontario (47%) and Quebec (33%), aged 48 ± 16 years [mean ± standard deviation (SD)], and mainly women (78%), White (85%), with a university degree (63%), and living in large urban centers (70%). According to the 298 ± 68 (mean ± SD) prospective questionnaires completed each month on average, the first year of follow-up reveals significant temporal variations in standardized indexes of well-being, loneliness, anxiety, depression, and psychological distress.

CONCLUSIONS

The COHESION Study will allow identifying trajectories of mental health and well-being while investigating their determinants and how these may vary by subgroup, over time, and across different provinces in Canada, in varying context including the pandemic recovery period. Our findings will contribute valuable insights to the urban health field and inform future public health interventions.

Place-Based Developmental Research: Conceptual and Methodological Advances in Studying Youth Development in Context

Scientists have, for some time, recognized that development unfolds in numerous settings, including families, schools, neighborhoods, and organized and unorganized activity settings. Since the turn of the 20th century, the body of mainstream neighborhood effects scholarship draws heavily from the early 20th century Chicago School of Sociology frameworks and have been situating development in neighborhood contexts and working to identify the structures and processes via which neighborhoods matter for a range of developmental outcomes, especially achievement, behavioral and emotional problems, and sexual activity. From this body of work, two new areas of developmental scholarship are emerging. Both areas are promising for advancing an understanding of child development in context. First, cultural-developmental neighborhood researchers are advancing neighborhood effects research that explicitly recognizes the ways that racial, ethnic, cultural, and immigrant social positions matter for neighborhood environments and for youths' developmental demands, affordances, experiences, and competencies. This body of work substantially expands the range of developmental outcomes examined in neighborhood effects scholarship to recognize normative physical, emotional, cognitive, behavioral, social, and cultural competencies that have largely been overlooked in neighborhood effects scholarship that espoused a more color-blind developmental approach. Second, activity space neighborhood researchers are recognizing that residential neighborhoods have important implications for broader activity spaces-or the set of locations and settings to which youth are regularly exposed, including, for example, schools, work, organized activities, and hang-outs. They are using newer technologies and geographic frameworks to assess exposure to residential neighborhood and extra-neighborhood environments. These perspectives recognize that time (i.e., from microtime to mesotime) and place are critically bound and that exposures can be operationalized at numerous levels of the ecological system (i.e., from microsystems to macrosystems). These frameworks address important limitations of prior development in context scholarship by addressing selection and exposure. Addressing selection involves recognizing that families have some degree of choice when selecting into settings and variables that predict families' choices (e.g., income) also predict development. Considering exposure involves recognizing that different participants or residents experience different amounts of shared and nonshared exposures, resulting in both under-and over-estimation of contextual effects. Activity space scholars incorporate exposure to the residential neighborhood environments, but also to other locations and settings to which youth are regularly exposed, like schools, after-school settings, work, and hang-outs. Unfortunately, the cultural-development and activity space streams, which have both emerged from early 20th century work on neighborhood effects on development, have been advancing largely independently. Thus, the overarching aim of this monograph is to integrate scholarship on residential neighborhoods, cultural development, and activity spaces to advance a framework that can support a better understanding of development in context for diverse groups. In Chapters I and II we present the historical context of the three streams of theoretical, conceptual, and methodological research. We also advance a comprehensive cultural-developmental activity space framework for studying development in context among children, youth, and families that are ethnically, racially, and culturally heterogeneous. This framework actively recognized diversity in ethnic, racial, immigrant, and socioeconomic social positions. In Chapters III-V we advance specific features of the framework, focusing on: (1) the different levels of nested and nonnested ecological systems that can be captured and operationalized with activity space methods, (2) the different dimensions of time and exposures or experiences that can be captured and operationalized by activity space methods, and (3) the importance of settings structures and social processes for identifying underlying mechanisms of contextual effects on development. Structures are setting features related to the composition and spatial arrangement of people and institutions (e.g., socioeconomic disadvantage, ethnic/racial compositions). Social processes represent the collective social dynamics that take place in settings, like social interactions, group activities, experiences with local institutions, mechanisms of social control, or shared beliefs. In Chapter VI, we highlight a range of methodological and empirical exemplars from the United States that are informed by our comprehensive cultural-developmental activity space framework. These exemplars feature both quantitative and qualitative methods, including method mixing. These exemplars feature both quantitative and qualitative methods, including method mixing. The exemplars also highlight the application of the framework across four different samples from populations that vary in terms of race, ethnicity, gender, age, socioeconomic status (SES), geographic region, and urbanicity. They capture activity space characteristics and features in a variety of ways, in addition to incorporating family shared and nonshared activity space exposures. Finally, in Chapter VII we summarize the contributions of the framework for advancing a more comprehensive science of development in context, one that better realizes major developmental theories emphasizing persons, processes, contexts, and time. Additionally, we offer a place-based, culturally informed developmental research agenda to meet the needs of an increasingly diverse population.

Micro urban spaces and mental well-being: Measuring the exposure to urban landscapes along daily mobility paths and their effects on momentary depressive symptomatology among older population

The urban environment plays an important role for the mental health of residents. Researchers mainly focus on residential neighbourhoods as exposure context, leaving aside the effects of non-residential environments. In order to consider the daily experience of urban spaces, a people-based approach focused on mobility paths is needed. Applying this approach, (1) this study investigated whether individuals' momentary mental well-being is related to the exposure to micro-urban spaces along the daily mobility paths within the two previous hours; (2) it explored whether these associations differ when environmental exposures are defined considering all location points or only outdoor location points; and (3) it examined the associations between the types of activity and mobility and momentary depressive symptomatology. Using a geographically-explicit ecological momentary assessment approach (GEMA), momentary depressive symptomatology of 216 older adults living in the Ile-de-France region was assessed using smartphone surveys, while participants were tracked with a GPS receiver and an accelerometer for seven days. Exposure to multiple elements of the streetscape was computed within a street network buffer of 25 m of each GPS point over the two hours prior to the questionnaire. Mobility and activity type were documented from a GPS-based mobility survey. We estimated Bayesian generalized mixed effect models with random effects at the individual and day levels and took into account time autocorrelation. We also estimated fixed effects. A better momentary mental wellbeing was observed when residents performed leisure activities or were involved in active mobility and when they were exposed to walkable areas (pedestrian dedicated paths, open spaces, parks and green areas), water elements, and commerce, leisure and cultural attractors over the previous two hours. These relationships were stronger when exposures were defined based only on outdoor location points rather than all location points, and when we considered within-individual differences compared to between-individual differences.

Urban-Rural Differences in the Prevalence of Depressive Symptoms in Korean Adults

This study aimed to investigate the prevalence of depression among Koreans living in urban and rural areas, stratified by socioeconomic status. The study included 216,765 participants from the 2017 Korean Community Health Survey. Depressive symptoms were assessed using the PHQ-9, with a score of 10 or higher indicating depressive symptoms. Residences with the words Eup and Myeon in their addresses were categorized as rural areas, and residences with Dong in their addresses as urban areas. Socioeconomic status was evaluated by household income and education level. A Poisson regression analysis with sampling weights was conducted and adjusted for demographic, lifestyle, socioeconomic status, and comorbidity. The adjusted prevalence rate of depressive symptoms was 3.33% (95% CI, 3.21-3.45) in urban areas and 2.59% (95% CI, 2.43-2.74) in rural areas. The prevalence of depressive symptoms in urban areas was 1.29 times (95% CI, 1.20-1.38) higher than in rural areas. The prevalence rate ratio for depressive symptoms in urban areas compared to rural areas sorted by monthly incomes was 1.39 (95% CI, 1.28-1.51) for less than 2 million won, 1.22 (95% CI, 1.06-1.41) for 2 to 3.99 million won, and 1.09 (95% CI, 0.90-1.32) for more than 4 million won, and the urban-rural difference was more evident in lower household income subjects (p for interaction=0.033). However, urban-rural differences did not differ according to sex, age, or education level. In conclusion, we found urban-rural differences in depressive symptoms in a representative sample of Koreans, and revealed that these differences may vary according to income level. These results suggest that mental health policy must consider the health disparities according to residence and income.

Egalitarian Attitudes and Activity Spaces in Chitwan, Nepal

Connections between individuals' sociodemographic characteristics and their social attitudes have been widely studied, but there has been less research on how individuals' spatial patterns are related to attitudes. Studies that do incorporate space have focused on residential locations, neglecting spatial experience outside residential neighborhoods. To fill this gap, we test hypotheses relating multiple measures of activity space (AS) to social attitudes, using innovative spatial data from Nepal. First, we hypothesize that the gender and caste attitudes of a focal individual will be positively associated with the gender and caste attitudes of others in the focal individual's AS, including spaces beyond the residential neighborhood. Second, we hypothesize that privileged individuals (i.e., males and those of the Chhetri/Brahmin caste) with greater potential exposure to females and those of lower castes in their AS will have more egalitarian attitudes about gender and caste than those with less exposure in their AS. Linear regression models provide support for both hypotheses.

The ILHBN: challenges, opportunities, and solutions from harmonizing data under heterogeneous study designs, target populations, and measurement protocols

The ILHBN is funded by the National Institutes of Health to collaboratively study the interactive dynamics of behavior, health, and the environment using Intensive Longitudinal Data (ILD) to (a) understand and intervene on behavior and health and (b) develop new analytic methods to innovate behavioral theories and interventions. The heterogenous study designs, populations, and measurement protocols adopted by the seven studies within the ILHBN created practical challenges, but also unprecedented opportunities to capitalize on data harmonization to provide comparable views of data from different studies, enhance the quality and utility of expensive and hard-won ILD, and amplify scientific yield. The purpose of this article is to provide a brief report of the challenges, opportunities, and solutions from some of the ILHBN's cross-study data harmonization efforts. We review the process through which harmonization challenges and opportunities motivated the development of tools and collection of metadata within the ILHBN. A variety of strategies have been adopted within the ILHBN to facilitate harmonization of ecological momentary assessment, location, accelerometer, and participant engagement data while preserving theory-driven heterogeneity and data privacy considerations. Several tools have been developed by the ILHBN to resolve challenges in integrating ILD across multiple data streams and time scales both within and across studies. Harmonization of distinct longitudinal measures, measurement tools, and sampling rates across studies is challenging, but also opens up new opportunities to address cross-cutting scientific themes of interest.

An Observational Pilot Study using a Digital Phenotyping Approach in Patients with Major Depressive Disorder Treated with Trazodone

This 8-week study was designed to explore any correlation between a passive data collection approach using a wearable device (i.e., digital phenotyping), active data collection (patient's questionnaires), and a traditional clinical evaluation [Montgomery-Åsberg Depression Rating Scale (MADRS)] in patients with major depressive disorder (MDD) treated with trazodone once a day (OAD). Overall, 11 out of 30 planned patients were enrolled. Passive parameters measured by the wearable device included number of steps, distance walked, calories burned, and sleep quality. A relationship between the sleep score (derived from passively measured data) and MADRS score was observed, as was a relationship between data collected actively (assessing depression, sleep, anxiety, and warning signs) and MADRS score. Despite the limited sample size, the efficacy and safety results were consistent with those previously reported for trazodone. The small population in this study limits the conclusions that can be drawn about the correlation between the digital phenotyping approach and traditional clinical evaluation; however, the positive trends observed suggest the need to increase synergies among clinicians, patients, and researchers to overcome the cultural barriers toward implementation of digital tools in the clinical setting. This study is a step toward the use of digital data in monitoring symptoms of depression, and the preliminary data obtained encourage further investigations of a larger population of patients monitored over a longer period of time.

Social and cultural conditions affecting the mental health of Syrian, Lebanese and Palestinian adolescents living in and around Bar Elias, Lebanon

An estimated 1.5 million displaced Syrians live in Lebanon, sharing neighbourhoods and communal spaces with longer-term Lebanese and Palestinian residents. The Syrian Civil War has lasted over one decade. Protracted mass displacement means that many young people are growing up in neighbourhoods, towns and cities which include comparable numbers of recently displaced and longer-term residents. In this study, we explore adolescent mental health and the intersections between Syrians, Lebanese and Palestinians in the town of Bar Elias, where comparable numbers of displaced people and citizens live. We conducted semi-structured interviews with 30 adolescents in April 2019. We found that Palestinian, Syrian and Lebanese adolescents in Bar Elias identified the same shared conditions as affecting their mental health, although with different impacts on each individual. Sometimes, this difference accords with nationality, but it is also determined by gender and different physical and cognitive abilities. We conclude that recently displaced and host community adolescents can be seen to be affected by shared conditions, and that intersectional identities affect how adolescent mental health is affected by these conditions. We argue that investments in shared infrastructures can support the improvement of mental health for all adolescents.

Environmental Factors in the Rehabilitation Framework: Role of the One Health Approach to Improve the Complex Management of Disability

Environment factors play a crucial implication in human health, with strong evidence suggesting that several biological, chemical, physical and social factors could be possible targets to implement effective strategies for human health promotion. On the other hand, a large gap of knowledge still exists about the implications of environmental factors in terms of functional impairment and disability, while the integration of an environmental-based approach in the therapeutic care of patients affected by disabilities remains still challenging. In this scenario, the One Health approach has been recently introduced in clinical care and aims to optimize health outcomes by recognizing the interconnection between people and the environment. Concurrently, the "Rehabilitation 2030 Initiative" proposed in 2017 by the WHO emphasized the need to integrate environmental-based strategies to promote rehabilitation across different health systems and different nations. However, no previous study underlined the potential implications of the One Health approach in the rehabilitation setting, nor the role of a comprehensive rehabilitation approach focused on environmental factors. Therefore, the aim of this narrative review was to present a comprehensive overview of the data currently available assessing the close relationship between rehabilitation and the environment to provide a different perspective on the comprehensive care of patients affected by disability.

Transportation and other social needs as markers of mental health conditions

Objective

The study sought to determine whether reporting a history of depression, anxiety, PTSD, bipolar disorder, drug or alcohol use disorder, ADHD, schizophrenia, or current depressive symptoms was associated with requesting help for any of 12 social needs.

Methods

A community-based sample of 1,944 low-income adult smokers in Missouri who had called a telephone helpline for social needs were recruited between June 1, 2017 and November 15, 2020. Helpline data on callers' requests for assistance with utilities, housing, food, household goods, healthcare, transportation, adult care, financial assistance, employment, legal assistance, personal safety and childcare were merged with self-reported mental health data collected in a subsequent phone survey with the same callers. Using binary logistic regression, we examined which mental health conditions were associated with each social need.

Results

Reporting mental health conditions were associated with greater odds of requests for assistance with transportation, food, healthcare and personal safety. Of these, the strongest and most consistent associations were with transportation needs. In post-hoc analyses, most associations between transportation needs and mental health remained significant after adjusting for possible confounders.

Conclusions

Compared to participants who did not report histories of mental health conditions, those who reported mental health conditions were more likely to call 2-1-1 seeking transportation assistance. Community-based agencies providing transportation or mental health services could partner to provide linkages between services and increase capacity to address transportation and mental health needs.

Developing a mental health index using a machine learning approach: Assessing the impact of mobility and lockdown during the COVID-19 pandemic

Governments worldwide have implemented stringent restrictions to curtail the spread of the COVID-19 pandemic. Although beneficial to physical health, these preventive measures could have a profound detrimental effect on the mental health of the population. This study focuses on the impact of lockdowns and mobility restrictions on mental health during the COVID-19 pandemic. We first develop a novel mental health index based on the analysis of data from over three million global tweets using the Microsoft Azure machine learning approach. The computed mental health index scores are then regressed with the lockdown strictness index and Google mobility index using fixed-effects ordinary least squares (OLS) regression. The results reveal that the reduction in workplace mobility, reduction in retail and recreational mobility, and increase in residential mobility (confinement to the residence) have harmed mental health. However, restrictions on mobility to parks, grocery stores, and pharmacy outlets were found to have no significant impact. The proposed mental health index provides a path for theoretical and empirical mental health studies using social media.

Sex and Gender Differences in Environmental Influences on Dementia Incidence in Germany, 2014-2019: An Observational Cohort Study Based on Health Claims Data

BACKGROUND

There is an ongoing debate about whether environmental characteristics influence dementia risk like individual traits do, and whether these differ by sex and gender.

OBJECTIVE

This study examines the influence of regional characteristics on the incidence of dementia and explores sex and gender differences using individual-level health information and regional characteristics.

METHODS

Using a random sample of 250,000 people aged 70 + insured through Germany's largest German public health agency, we analyzed quarterly data about diagnoses and place of residence from 2014 to 2019. Using five-digit postal codes, we added data on various dimensions of regional characteristics offered by the INKAR database and the 2011 Census database. We used multilevel survival regressions to tease out regional incidence differences while accounting for spatial clustering.

RESULTS

After adjusting for multi-morbidity and relocation-related selection bias, we saw that people living in regions with the highest tertile of income (HR = 0.87, p <  0.001), and who had the highest tertile of remaining life expectancy at age 60 (HR = 0.93, p = 0.012) had lower dementia risks. There was no gender difference in the regional income effect, but the effect of education (HR = 0.91, p = 0.015) was significant only for men and remaining life-expectancy was significant only for women (HR = 0.93, p = 0.026).

CONCLUSION

Environmental characteristics related to wealth and health resources of a region influence the risk of dementia among the elderly in Germany. This effect is independent of the health profiles of the individuals and differs between the two genders. Health policies need to acknowledge these modifiable risk factors and consider how they affect men and women differently.

GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data

Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behavioral patterns. However, raw GPS data consisting of densely sampled time series of latitude and longitude coordinate pairs do not readily convey meaningful information concerning intra-individual dynamics and inter-individual differences; substantial data processing is required. Raw GPS data need to be integrated into a Geographic Information System (GIS) and analyzed, from which the mobility and activity patterns of individuals can be derived, a process that is unfamiliar to many behavioral scientists. In this tutorial article, we introduced GPS2space, a free and open-source Python library that we developed to facilitate the processing of GPS data, integration with GIS to derive distances from landmarks of interest, as well as extraction of two spatial features: activity space of individuals and shared space between individuals, such as members of the same family. We demonstrated functions available in the library using data from the Colorado Online Twin Study to explore seasonal and age-related changes in individuals' activity space and twin siblings' shared space, as well as gender, zygosity and baseline age-related differences in their initial levels and/or changes over time. We concluded with discussions of other potential usages, caveats, and future developments of GPS2space.

GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data

Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behavioral patterns. However, raw GPS data consisting of densely sampled time series of latitude and longitude coordinate pairs do not readily convey meaningful information concerning intra-individual dynamics and inter-individual differences; substantial data processing is required. Raw GPS data need to be integrated into a Geographic Information System (GIS) and analyzed, from which the mobility and activity patterns of individuals can be derived, a process that is unfamiliar to many behavioral scientists. In this tutorial article, we introduced GPS2space, a free and open-source Python library that we developed to facilitate the processing of GPS data, integration with GIS to derive distances from landmarks of interest, as well as extraction of two spatial features: activity space of individuals and shared space between individuals, such as members of the same family. We demonstrated functions available in the library using data from the Colorado Online Twin Study to explore seasonal and age-related changes in individuals' activity space and twin siblings' shared space, as well as gender, zygosity and baseline age-related differences in their initial levels and/or changes over time. We concluded with discussions of other potential usages, caveats, and future developments of GPS2space.

The Influence of Emotional Health on the Activity Characteristics of the Elderly and the Selection of Environmental Quality Factors in Residential Areas

The environment in urban residential areas is the main field of daily activity for the elderly. Environmental renewal has played a significant role in improving residents' quality of life and promoting physical and mental health. However, there is a general tendency that more attention has been focused on the environment during environmental renewal but not the residents. There is a continued lack of discussion on the emotional status of the elderly and its impact on outdoor activities. Based on the investigation of four types of typical residential environments in the Dalian residential area, a hierarchical linear model (HLM) has been constructed to reveal the influence of the emotional status of elderly persons on their activity characteristics and the selection of environmental quality factors. The results show that the distribution of older people with different emotional statuses varies among different residential types. The proportion of positive emotion is relatively high in the flat land in rows category, and the activity characteristics are significantly different under different emotional statuses. Among the four kinds of residential environments, which are (flat land in rows, flat land enclosed, slope, and mountainous) the environmental quality factors that have the highest impact on the emotional status of the elderly are greening quality (0.395), acoustic environment (0.167), environmental cleanliness (0.269), and greening quality (0.230), respectively. In the mountainous type, the impact of environmental quality factors on the emotional status of the elderly is the highest (39.7%), and the impact contributions of the other three environmental types are 23.3%, 8.9% and 20.1%, respectively. These research results provide helpful guidance for the scientific community about practical implementation of residential environmental renewal for the elderly.

Time trend analysis of social inequalities in psychological distress among young adults before and during the pandemic: evidence from the UK Household Longitudinal Study COVID-19 waves

BACKGROUND

Despite concerns about mental health problems among those aged 16-24 in England, which social groups have been most at risk, both over the past decade and during the COVID-19 pandemic, remains unclear.

METHODS

We examined trends in psychological distress among young adults 16-24 years old in England using data from the UK Household Longitudinal Study. Using longitudinal data as repeated cross-sectional waves, we examined differences over time in mean General Health Questionnaire (GHQ) scores from wave 1 (2009-2010) to wave 10 (2018-2019) and six COVID-19 waves collected between April and November 2020, by economic activity, cohabitation with parents, parental education, area deprivation, ethnicity, age and sex.

RESULTS

Compared with 2009-2010, increases in GHQ scores in 2018-2019 were higher in women than men (2.1 vs 1.3), those aged 16-18 than aged 22-24 (2.6 vs 0.9), those from white UK group versus other ethnic minorities, and those out of the labour force (3.6) or employed part time (2.2) than those employed full time (0.8). Compared with 2018-2019, psychological distress in 2020 also further increased among young adults residing in the most deprived areas (4.1 vs 1.2 in the least deprived areas). In 2020, losing one's job or most of one's work hours was associated with higher psychological distress and attenuated the differences between deprivation quartiles by 17%.

CONCLUSION

In England, inequalities in psychological distress among young adults may have changed and increased during the COVID-19 pandemic. Investing in opportunities for young adults, particularly in more deprived areas, may be key to improve population levels of mental health.

From Comparative and Statistical Assessments of Liveability and Health Conditions of Districts in Hong Kong towards Future City Development

Liveability is an indispensable component in future city planning and is practically linked with the health status of individuals and communities. However, there was nor comprehensive and universal district-level framework for assessing liveability due to geospatial and social discrepancies among different countries. In this study, using Hong Kong, a highly dense and international city as an example, the Liveability and Health Index (LHI-HK) consisting of 30 indicators was established, with 21 of them related to education, economy, housing, walkability/transport, environment, and health facilities aspects, while the health conditions of citizens in individual districts were examined by other 9 indicators. Respective scoring allocation was determined by statistical reasoning, and was applied to quantify the connections between liveability and health among the 18 districts of Hong Kong in both 2016 and 2019. Temporal changes of spatial features could be traced by this quantitative framework, and obvious correlations between liveability and health were attained, with R values of 0.496 and 0.518 in 2016 and 2019, and corresponding slopes of 0.80 and 0.88, respectively. Based on the statistical results, it was found that Sai Kung and Kwun Tong are the most and the least liveable district of Hong Kong in 2019. The LHI-HK index was well-validated by renowned AARP liveability index and The California Healthy Places Index (HPI), with R values of 0.90 and 0.70, and the potential uncertainties due to data projection were less than 2.5% for all districts, which implicates its relevancy and appropriateness in conducting similar spatial assessments in international cities. Further, both favorable and unfavorable spatial arrangements of each of the 3 district types in Hong Kong were identified, namely residential, commercial, and industrial districts. This opens new windows in enhancing liveability and health status within communities, with the aim of promoting the sustainability of cities in the long run.

Perceiving Residents’ Festival Activities Based on Social Media Data: A Case Study in Beijing, China

Social media data contains real-time expressed information, including text and geographical location. As a new data source for crowd behavior research in the era of big data, it can reflect some aspects of the behavior of residents. In this study, a text classification model based on the BERT and Transformers framework was constructed, which was used to classify and extract more than 210,000 residents’ festival activities based on the 1.13 million Sina Weibo (Chinese “Twitter”) data collected from Beijing in 2019 data. On this basis, word frequency statistics, part-of-speech analysis, topic model, sentiment analysis and other methods were used to perceive different types of festival activities and quantitatively analyze the spatial differences of different types of festivals. The results show that traditional culture significantly influences residents’ festivals, reflecting residents’ motivation to participate in festivals and how residents participate in festivals and express their emotions. There are apparent spatial differences among residents in participating in festival activities. The main festival activities are distributed in the central area within the Fifth Ring Road in Beijing. In contrast, expressing feelings during the festival is mainly distributed outside the Fifth Ring Road in Beijing. The research integrates natural language processing technology, topic model analysis, spatial statistical analysis, and other technologies. It can also broaden the application field of social media data, especially text data, which provides a new research paradigm for studying residents’ festival activities and adds residents’ perception of the festival. The research results provide a basis for the design and management of the Chinese festival system.

Exploring the Spatiotemporal Patterns of Residents’ Daily Activities Using Text-Based Social Media Data: A Case Study of Beijing, China

The use of social media data provided powerful data support to reveal the spatiotemporal characteristics and mechanisms of human activity, as it integrated rich spatiotemporal and textual semantic information. However, previous research has not fully utilized its semantic and spatiotemporal information, due to its technical and algorithmic limitations. The efficiency of the deep mining of textual semantic resources was also low. In this research, a multi-classification of text model, based on natural language processing technology and the Bidirectional Encoder Representations from Transformers (BERT) framework is constructed. The residents’ activities in Beijing were then classified using the Sina Weibo data in 2019. The results showed that the accuracy of the classifications was more than 90%. The types and distribution of residents’ activities were closely related to the characteristics of the activities and holiday arrangements. From the perspective of a short timescale, the activity rhythm on weekends was delayed by one hour as compared to that on weekdays. There was a significant agglomeration of residents’ activities that presented a spatial co-location cluster pattern, but the proportion of balanced co-location cluster areas was small. The research demonstrated that location conditions, especially the microlocation condition (the distance to the nearest subway station), were the driving factors that affected the resident activity cluster patterns. In this research, the proposed framework integrates textual semantic analysis, statistical method, and spatial techniques, broadens the application areas of social media data, especially text data, and provides a new paradigm for the research of residents’ activities and spatiotemporal behavior.

Mobility impact and well-being in later life: A multidisciplinary systematic review

In modern societies, the understanding of how active mobility affects the elderly's psycho-physical well-being is crucial to design ageing-friendly transport measures. From a multidisciplinary perspective, this systematic review points out the mobility impact on three elements of the EU Active Ageing Index: health, independence and social connectedness. By scanning four databases (Scopus, Web of Science, PubMed, and TRID), 3727 peer-reviewed papers published in the last decade were found, of which 57 met the inclusion criteria. The screening process was conducted following the PRISMA protocol and registered to the database PROSPERO, while the quality assessment was done using the Mixed Methods Appraisal Tool. More than 80% of the papers showed that an active mobility prevents psycho-physical harms, while only few papers study the relation of mobility with independence and social inclusion, to reduce the need for assistance and the related public expenditures. The findings of this review give important information both to transportation researchers and policymakers and companies, underlining the need for further research as well as investments in targeted age-friendly transport systems. The Covid-19 emergency has further underlined the importance of this issue, being the elderly one of the more disadvantaged and frailer social group.

Identifying the Daily Activity Spaces of Older Adults Living in a High-Density Urban Area: A Study Using the Smartphone-Based Global Positioning System Trajectory in Shanghai

The characteristics of the built environment and the configuration of public facilities can affect the health and well-being of older adults. Recognizing the range of daily activities and understanding the utilization of public facilities among older adults has become essential in planning age-friendly communities. However, traditional methods are unable to provide large-scale objective measures of older adults’ travel behaviors. To address this issue, we used the smartphone-based global positioning system (GPS) trajectory to explore the activity spaces of 76 older adults in a high-density urban community in Shanghai for 102 consecutive days. We found that activity spaces are centered around older adults’ living communities, with 46.3% within a 1.5 km distance. The older adults’ daily activities are within a 15 min walking distance, and accessibility is the most important factor when making a travel choice to parks and public facilities. We also found that the travel range and spatial distribution of points of interest are different between age and gender groups. In addition, we found that using a concave hull with Alpha shape algorithm is more applicable and robust than the traditional convex hull algorithm. This is a unique case study in a high-density urban area with objective measures for assessing the activity spaces of older adults, thus providing empirical evidence for promoting healthy aging in cities.

Health-Related Quality of Life Among Refugees and Asylum Seekers in Northern Greece

We aimed at assessing the health-related quality-of-life (HRQoL) of refugees and asylum seekers in Northern Greece. The SF-36 Health Survey was used to assess participants' HRQoL. Participants were contacted in person. Correlation and dependence tests were employed to examine the association of participants' demographic, residence-related and medical-related characteristics with the two SF-36 component (physical-PCS/mental-MCS) scales. Regressions were conducted to investigate the effect of these characteristics on component scales. Refugees and asylum seekers (n = 161) living in urban apartments and camps in Northern Greece participated in the study reporting poor HRQoL (PCS = 43.9, MCS = 39.5). Age, gender, duration of stay, benefits offered by Non-Governmental Organisations (NGOs), type of accommodation, suffering from a serious health problem and receipt of medication were associated with HRQoL. This study constitutes the first research assessing HRQoL of refugees and asylum seekers in Northern Greece.

Applying Environmental Context to Rehabilitation Research Using Geographic Information Systems and Global Positioning Systems Geospatial Technologies

Background

The International Classification of Functioning, Disability, and Health includes important considerations of environmental context in understanding disability, but the environmental impact is often difficult to measure.

Purpose

Demonstrates the use of Geographic Information Systems (GIS) and Global Positioning Systems (GPS) in rehabilitation research in assessing accessibility and participation; describes how to use these methods, and presents several considerations in using GIS and GPS in research.

Method

Using methods from public health and medical geography, this article describes how to apply GIS and GPS technologies to rehabilitation research to measure community participation and accessibility to resources.

Findings

Directions for using ArcGIS functions and case examples joining these mapping technologies with rehabilitation measures are provided.

Conclusions

Together with traditional measures, these technologies may provide rehabilitation researchers a more comprehensive approach to assessing accessibility and participation.

The spatiotemporal movement of patients in and out of a psychiatric hospital: an observational GPS study

BACKGROUND

Movement is a basic component of health. Little is known about the spatiotemporal movement of patients with mental disorders. The aim of this study was to determine how spatiotemporal movement of patients related to their symptoms and wellbeing.

METHOD

A total of 106 patients (inpatients (n = 69) and outpatients (n = 37)) treated for a wide range of mental disorders (transdiagnostic sample) carried a GPS-enabled smartphone for one week at the beginning of treatment. Algorithms were applied to establish spatiotemporal clusters and subsequently related to known characteristics of these groups (i.e., at the hospital, at home). Symptomatology, Wellbeing, and Psychological flexibility were also assessed.

RESULTS

Spatiotemporal patterns of inpatients and outpatients showed differences consistent with predictions (e.g., outpatients showed higher active areas). These patterns were largely unassociated with symptoms (except for agoraphobic symptoms). Greater movement and variety of movement were more predictive of wellbeing, however, in both inpatients and outpatients.

CONCLUSION

Measuring spatiotemporal patterns is feasible, predictive of wellbeing, and may be a marker of patient functioning. Ethical issues of collecting GPS data are discussed.

Bringing the "Place" to Life-Space in Gerontology Research

Understanding older adults' relationships with their environments and the way this relationship evolves over time have been increasingly acknowledged in gerontological research. This relationship is often measured in terms of life-space, defined as the spatial area through which a person moves within a specific period of time. Life-space is traditionally reported using questionnaires or travel diaries and is, thus, subject to inaccuracies. More recently, studies are using a global positioning system to accurately measure life-space. Although life-space provides useful insights into older adults' relationships with their environment, it does not capture the inherent complexities of environmental exposures. In the fields of travel behaviour and health geography, a substantial amount of research has looked at people's spatial behaviour using the notion of "Activity Space," allowing for increasing sophistication in understanding older adults' experience of their environment. This manuscript discusses developments and directions for extending the life-space framework in environmental gerontology by drawing on the advancements in the activity space framework.

Neighborhood physical disorder and common mental disorders in adolescence

OBJECTIVE

The aim of this study is to estimate the association between observed indicators of neighborhood physical disorder and common mental disorders in adolescents.

METHODS

The study population included 2506 adolescents from three Brazilian state capitals (Rio de Janeiro, Porto Alegre, and Fortaleza) who participated in the Cardiovascular Risk Study in Adolescents (ERICA), a cross-sectional school-based study conducted in 2013-2014. Common mental disorders were assessed using the 12-item General Health Questionnaire. Measures of neighborhood physical disorder were based on the 2010 Brazilian census data and were derived using principal component analysis.

RESULTS

Although associations were found between some exposure components and CMD, there were no clear or consistent trends across exposure quartiles.

CONCLUSION

Overall, there was no evidence of an association between observed indicators of neighborhood physical disorder and common mental disorders. Future studies should explore alternative tools for measuring neighborhood physical disorder to minimize the likelihood of exposure misclassification.

Urban and Rural Differences in Trajectories of Depressive Symptoms in Later Life in the United States

OBJECTIVE

This research has two primary goals: to examine the relationship between urban residence and trajectories of depressive symptoms and to investigate whether this relationship differs by social isolation and loneliness.

METHOD

Data are from 2006, 2008, 2010, 2012, 2014, and 2016 waves of the Health and Retirement Study (HRS), a nationally representative sample of U.S. adults aged 51+ (n = 3,346 females and 2,441 males). We conduct latent growth curve analysis to predict both baseline and trajectories of depression based on urban or rural residency.

RESULTS

Residing in urban or rural areas is neither significantly associated with baseline nor the development of late-life depressive symptoms. For females, the relationship between urban residence and baseline depressive symptoms is explained by socioeconomic factors.

DISCUSSION

Findings of this study serve to better understand how social and geographic contexts shape long-term well-being of older adults.

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.

Linking physical and social environments with mental health in old age: a multisensor approach for continuous real-life ecological and emotional assessment

Background

Urban stress is mentioned as a plausible mechanism leading to chronic stress, which is a risk factor of depression. Yet, an accurate assessment of urban stressors in environmental epidemiology requires new methods. This article discusses methods for the sensor-based continuous assesment of geographic environments, stress and depressive symptoms in older age. We report protocols of the promoting mental well-being and healthy ageing in cities (MINDMAP) and Healthy Aging and Networks in Cities (HANC) studies nested in the RECORD Cohort as a background for a broad discussion about the theoretical foundation and monitoring tools of mobile sensing research in older age. Specifically, these studies allow one to compare how older people with and without depression perceive, navigate and use their environment; and how the built environments, networks of social contacts, and spatial mobility patterns influence the mental health of older people.

Methods

Our research protocol combines (1) Global Positioning System (GPS) and accelerometer tracking and a GPS-based mobility survey to assess participants’ mobility patterns, activity patterns and environmental exposures; (2) proximity detection to assess whether household members are close to each other; (3) ecological momentary assessment to track momentary mood and stress and environmental perceptions; and (4) electrodermal activity for the tentative prediction of stress. Data will be compared within individuals (at different times) and between persons with and without depressive symptoms.

Conclusion

The development of mobile sensing and survey technologies opens an avenue to improve understanding of the role of momentary stressors and resourcing features of residential and non-residential environments for older populations’ mental health. However, validation, privacy and ethical aspects are important issues to consider.

The mediating effect of self-esteem on the relationship of living environment, anxiety, and depression of underprivileged children: A path analysis in Chinese context

This study aimed to explore the relationships of living environment, self-esteem, anxiety, and depression of children in poverty. A sample of 1314 children (grades 4–9) was collected by a school-based survey in Xiushui city, Mainland China. Structural equation modeling was adopted to analyze the data and verify the hypothesized model. Results showed that living environment was negatively correlated with poor children’s anxiety and depression levels, and self-esteem had a mediating effect on the relationship between living environment and the mental health of underprivileged children. Based on these findings, we proposed relevant theoretical and practical implications.

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.

Influence of Individual and Contextual Perceptions and of Multiple Neighborhoods on Depression

The risk of depression is related to multiple various determinants. The consideration of multiple neighborhoods daily frequented by individuals has led to increased interest in analyzing socio-territorial inequalities in health. In this context, the main objective of this study was (i) to describe and analyze the spatial distribution of depression and (ii) to investigate the role of the perception of the different frequented spaces in the risk of depression in the overall population and in the population stratified by gender. Data were extracted from the 2010 SIRS (a French acronym for "health, inequalities and social ruptures") cohort survey. In addition to the classic individual characteristics, the participants reported their residential neighborhoods, their workplace neighborhoods and a third one: a daily frequented neighborhood. A new approach was developed to simultaneously consider the three reported neighborhoods to better quantify the level of neighborhood socioeconomic deprivation. Multiple simple and cross-classified multilevel logistic regression models were used to analyze the data. Depression was reported more frequently in low-income (OR = 1.89; CI = [1.07-3.35]) or middle-income (OR = 1.91; CI = [1.09-3.36]) neighborhoods and those with cumulative poverty (OR = 1.64; CI = [1.10-2.45]). In conclusion, a cumulative exposure score, such as the one presented here, may be an appropriate innovative approach to analyzing their effects in the investigation of socio-territorial inequalities in health.

Integrating Urban Adolescent Mental Health Into Urban Sustainability Collective Action: An Application of Shiffman & Smith's Framework for Global Health Prioritization

The majority (55%) of the world's population lives in urban environments. Of relevance to global mental health, the rapid growth in urban populations around the world and the attendant risks coincide with the presence of the largest population of adolescents the global community has seen to date. Recent reviews on the effects of the urban environment on mental health report a greater risk of depression, anxiety, and some psychotic disorders among urban dwellers. Increased risk for mental disorders is associated with concentrated poverty, low social capital, social segregation, and other social and environmental adversities that occur more frequently in cities. To address these problems, urban adolescent mental health requires attention from decision makers as well as advocates who seek to establish sustainable cities. We examine opportunities to increase the prominence of urban adolescent mental health on the global health and development agenda using Shiffman and Smith's framework for policy priorities, and we explore approaches to increasing its relevance for urban health and development policy communities. We conclude with suggestions for expanding the community of actors who guide the field and bridging the fields of mental health and urban development to meet urban adolescent mental health needs.

Beyond Activity Space: Detecting Communities in Ecological Networks

Emerging research suggests that the extent to which activity spaces - the collection of an individual's routine activity locations - overlap provides important information about the functioning of a city and its neighborhoods. To study patterns of overlapping activity spaces, we draw on the notion of an ecological network, a type of two-mode network with the two modes being individuals and the geographic locations where individuals perform routine activities. We describe a method for detecting "ecological communities" within these networks based on shared activity locations among individuals. Specifically, we identify latent activity pattern profiles, which, for each community, summarize its members' probability distribution of going to each location, and community assignment vectors, which, for each individual, summarize his/her probability distribution of belonging to each community. Using data from the Adolescent Health and Development in Context (AHDC) Study, we employ latent Dirichlet allocation (LDA) to identify activity pattern profiles and communities. We then explore differences across neighborhoods in the strength, and within-neighborhood consistency of community assignment. We hypothesize that these aspects of the neighborhood structure of ecological community membership capture meaningful dimensions of neighborhood functioning likely to co-vary with economic and racial composition. We discuss the implications of a focus on ecological communities for the conduct of "neighborhood effects" research more broadly.

Tick Bite Risk as a Socio-Spatial Representation—An Exploratory Study in Massif Central, France

Ticks are responsible for the largest number of transmissions of vector-borne diseases in the northern hemisphere, which makes the risk from tick bites a serious public health problem. Biological scientific research and prevention studies are important, but they have not focused on the population’s perception of tick bite risk, especially at a spatial level. This exploratory article sets out to study this point through an innovative methodology involving the collection of 133 mental maps associated with a semi-structured interview and a socio-demographic questionnaire collected in the Massif Central region, France. The results show a strong link between the representation of the tick bite risk and the representation of particular landscapes. Forests appear as dangerous for the population, especially in the traditional activities of family walking or hiking. This calls into question overly anxiogenic prevention approaches that neglect the impact on practices in risk-prone spaces. It accentuates the need for localized education measure to improve knowledge about tick biology and avoid stereotypical and unnecessary negative representations associated with the environment.

Influence of activity space on the association between neighborhood characteristics and dementia risk: results from the 3-City study cohort

Background

Socioeconomic level of residential environment was found to influence cognitive performance. However, individuals from the same place of residence may be affected differently. We aim to investigate for the first time the influence of individual activity space on the association between neighborhood socioeconomic status (NSES) and the risk of dementia.

Methods

In the frame of the Three-City cohort, a French population-based study, we followed longitudinally (12 years) 7009 participants aged over 65. The activity space (i.e., the spatial area through which a person moves daily) was defined using two questions from Lawton’s Instrumental Activities of Daily Living scale (“Goes shopping independently”,“Travels alone”), and one question about mobility restriction. The survival analysis was performed using a Cox marginal model that takes into account intra-neighborhood correlations and includes a large number of potential confounders.

Results

Among people with a limited activity space (n = 772, 11%), risk of dementia is increased in subjects living in a deprived area (characterized by high GINI index or low median income) compared to those living in more favored.

Conclusion

This study shows that the individual activity space modifies the association between NSES and the risk of dementia providing a more complete picture of residential inequalities. If confirmed in different populations, these findings suggest that people with limited activity space and living in a deprived neighborhood are particularly at risk and should be targeted for prevention.

Using Geospatial Research Methods to Examine Resource Accessibility and Availability as it Relates to Community Participation of Individuals with Serious Mental Illnesses

Greater community participation among individuals with serious mental illnesses is associated with better psychosocial and health outcomes. Typically, studies examining community participation have utilized self-report measures and been conducted in limited settings. The introduction of methodological advances to examining community participation of individuals with serious mental illnesses has the potential to advance the science of community mental health research and invigorate the work of community psychologists in this area. This study employed an innovative geospatial approach to examine the relationship between community participation and resource accessibility (i.e., proximity) and availability (i.e., concentration) among 294 individuals utilizing community mental health services throughout the United States. Findings suggest small but significant associations between community participation and the accessibility and availability of resources needed for participation. Furthermore, findings demonstrate the importance of car access for individuals residing in both urban and non-urban settings. The methods and results presented in this study have implications for community mental health research and services and provide an illustration of ways that geospatial methodologies can be used to investigate environmental factors that impact community inclusion and participation of individuals with serious mental illnesses.

Movement patterns in women at risk for perinatal depression: use of a mood-monitoring mobile application in pregnancy

Objectives

To examine, using a smartphone application, whether mood is related to daily movement patterns in pregnant women at risk for perinatal depression.

Materials and Methods

Thirty-six women with elevated depression symptoms (PHQ-9 ≥ 5) in pregnancy used the application for 8 weeks. Mood was reported using application-administered surveys daily (2 questions) and weekly (PHQ-9 and GAD-7). The application measured daily mobility (distance travelled on foot) and travel radius. Generalized linear mixed-effects regression models estimated the association between mood and movement.

Results

Women with milder depression symptoms had a larger daily radius of travel (2.7 miles) than women with more severe symptoms (1.9 miles), P  = .04. There was no difference in mobility. A worsening of mood from the prior day was associated with a contracted radius of travel, as was being in the group with more severe symptoms. No significant relationships were found between anxiety and either mobility or radius.

Discussion

We found that the association of mood with radius of travel was more pronounced than its association with mobility. Our study also demonstrated that a change in mood from the prior day was significantly associated with radius but not mood on the same day that mobility and radius were measured.

Conclusion

This study lays the groundwork for future research on how smartphone mood-monitoring applications can combine actively and passively collected data to better understand the relationship between the symptoms of perinatal depression and physical activity that could lead to improved monitoring and novel interventions.

Living environment and its relationship to depressive mood: A systematic review

BACKGROUND AND AIMS

The notion that environment affects mental health has a long history; in this systematic review, we aimed to study whether the living environment is related to depressive mood.

METHODS

We searched databases of PubMed, Scopus and Web of Science for population-based original studies prior to October 2016. We included studies that measured depressive symptoms or depression and had measures of urbanization, population density, aesthetics of living environment, house/built environment, green areas, walkability, noise, air pollution or services.

RESULTS

Out of 1,578 articles found, 44 studies met our inclusion criteria. Manual searches of the references yielded 13 articles, resulting in 57 articles being included in the systematic review. Most of the studies showed statistically significant associations with at least one of the characteristics of living environment and depressive mood. House and built environment with, for example, poor housing quality and non-functioning, lack of green areas, noise and air pollution were more clearly related to depressive mood even after adjustment for different individual characteristics. On the contrary, the results in relation to population density, aesthetics and walkability of living environment, and availability of services and depressive mood were more inconsistent.

CONCLUSION

Adverse house/built environment, including poor housing quality and non-functioning, lack of green spaces, noise and air pollution are related to depressive mood and should be taken into account during planning in order to prevent depressive mood.

User acceptance of location-tracking technologies in health research: Implications for study design and data quality

Research regarding place and health has undergone a revolution due to the availability of consumer-focused location-tracking devices that reveal fine-grained details of human mobility. Such research requires that participants accept such devices enough to use them in their daily lives. There is a need for a theoretically grounded understanding of acceptance of different location-tracking technology options, and its research implications. Guided by an extended Unified Theory of Acceptance and Use of Technology (UTAUT), we conducted a 28-day field study comparing 21 chronically ill people's acceptance of two leading, consumer-focused location-tracking technologies deployed for research purposes: (1) a location-enabled smartphone, and (2) a GPS watch/activity tracker. Participants used both, and completed two surveys and qualitative interviews. Findings revealed that all participants exerted effort to facilitate data capture, such as by incorporating devices into daily routines and developing workarounds to keep devices functioning. Nevertheless, the smartphone was perceived to be significantly easier and posed fewer usability challenges for participants than the watch. Older participants found the watch significantly more difficult to use. For both devices, effort expectancy was significantly associated with future willingness to participate in research although prosocial motivations overcame some concerns. Social influence, performance expectancy and use behavior were significantly associated with intentions to use the devices in participants' personal lives. Data gathered via the smartphone was significantly more complete than data gathered via the watch, primarily due to usability challenges. To make longer-term participation in location tracking research a reality, and to achieve complete data capture, researchers must minimize the effort involved in participation; this requires usable devices. For long-term location-tracking studies using similar devices, findings indicate that only smartphone-based tracking is up to the challenge.

The mediating effect of self-esteem on the relationship of living environment, anxiety, and depression of underprivileged children: A path analysis in Chinese context

This study aimed to explore the relationships of living environment, self-esteem, anxiety, and depression of children in poverty. A sample of 1314 children (grades 4-9) was collected by a school-based survey in Xiushui city, Mainland China. Structural equation modeling was adopted to analyze the data and verify the hypothesized model. Results showed that living environment was negatively correlated with poor children's anxiety and depression levels, and self-esteem had a mediating effect on the relationship between living environment and the mental health of underprivileged children. Based on these findings, we proposed relevant theoretical and practical implications.

Sex-specific association between neighborhood characteristics and dementia: The Three-City cohort

INTRODUCTION

The living environment affects general health and may influence cognitive aging; however, the relationships between neighborhood characteristics and dementia are still poorly understood.

METHODS

We used data from a French population-based prospective study (the Three-City cohort) that included 7016 participants aged 65 years and older with a 12-year follow-up. We used principal components analysis of neighborhood composition indicators to construct the Three-City deprivation score. To study its impact on dementia incidence, we performed survival analyses using a marginal Cox model to take into account intraneighborhood correlations. As interaction with sex was significant, analyses were stratified by sex.

RESULTS

Even after controlling on individual factors, women living in deprived neighborhoods were at higher risk of dementia (hazard ratio = 1.29, 95% confidence interval 1.00-1.67) and Alzheimer's disease (hazard ratio = 1.42, 95% confidence interval 1.09-1.84). No association was found for men.

DISCUSSION

Living in a deprived neighborhood is associated with higher risk of dementia in women.

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.

An intervention strategy for improving residential environment and positive mental health among public housing tenants: rationale, design and methods of Flash on my neighborhood!

BACKGROUND

In Canada, public housing programs are an important part of governmental strategies to fight poverty and public exclusion. The Flash on my neighborhood! project is a four-year multiphase community-based participatory action research strategy currently implemented in six public housing developments (n = 1009 households) across the province of Québec, Canada. The goal is to reduce the mental health disparities faced by these public housing tenants compared to the general population, while identifying which environmental and policy changes are needed to turn public housing settings into healthier environments.

METHODS

The protocol involves three successive, interconnected phases: 1) Strengths and needs assessment, including community outreach and recruitment of tenants to collaborate as peer researchers, an exploratory qualitative component (photovoice), a systematic neighborhood observation, and a household survey; 2) Action plan development, including a community forum and interactive capacity-building and discussion sessions; 3) Action plan implementation and monitoring. The entire intervention is evaluated using a mixed-method design, framed within a multiple case study perspective. Throughout the project and particularly in the evaluation phase, data will be collected to record a) contextual factors (tenants' previous experience of participation, history of public housing development, etc.); b) activities that took place and elements from the action plan that were implemented; and c) short- and medium-term outcomes (objective and perceived improvements in the quality of the residential setting, both physically and in terms of mental health and social capital).

DISCUSSION

The study will provide unprecedented evidence-based information on the key ingredients of a collective intervention process associated with the increased collective empowerment and positive mental health of public housing tenants.

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.