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

STROBE-GEMA: a STROBE extension for reporting of geographically explicit ecological momentary assessment studies

CONTEXT

While a growing body of research has been demonstrating how exposure to social and built environments relate to various health outcomes, specific pathways generally remain poorly understood. But recent technological advancements have enabled new study designs through continuous monitoring using mobile sensors and repeated questionnaires. Such geographically explicit momentary assessments (GEMA) make it possible to link momentary subjective states, behaviors, and physiological parameters to momentary environmental conditions, and can help uncover the pathways linking place to health. Despite its potential, there is currently no review of GEMA studies detailing how location data is used to measure environmental exposure, and how this in turn is linked to momentary outcomes of interest. Moreover, a lack of standard reporting of such studies hampers comparability and reproducibility.

AIMS

The objectives of this research were twofold: 1) conduct a systematic review of GEMA studies that link momentary measurement with environmental data obtained from geolocation data, and 2) develop a STROBE extension guideline for GEMA studies.

METHOD

The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Inclusion criteria consisted of a combination of repeated momentary measurements of a health state or behavior with GPS coordinate collection, and use of these location data to derive momentary environmental exposures. To develop the guideline, the variables extracted for the systematic review were compared to elements of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and CREMAS (CRedibility of Evidence from Multiple Analyses of the Same data) checklists, to provide a new guideline for GEMA studies. An international panel of experts participated in a consultation procedure to collectively develop the proposed checklist items. RESULTS AND DEVELOPED TOOLS: A total of 20 original GEMA studies were included in the review. Overall, several key pieces of information regarding the GEMA methods were either missing or reported heterogeneously. Our guideline provides a total of 27 categories (plus 4 subcategories), combining a total of 70 items. The 22 categories and 32 items from the original STROBE guideline have been integrated in our GEMA guideline. Eight categories and 6 items from the CREMAS guideline have been included to our guideline. We created one new category (namely "Consent") and added 32 new items specific to GEMA studies.

CONCLUSIONS AND RECOMMENDATIONS

This study offers a systematic review and a STROBE extension guideline for the reporting of GEMA studies. The latter will serve to standardize the reporting of GEMA studies, as well as facilitate the interpretation of results and their generalizability. In short, this work will help researchers and public health professionals to make the most of this method to advance our understanding of how environments influence health.

The influence of neighborhood safety and built environment on childhood obesity: isolated and combined effect of contextual factors

This study aims to analyze the isolated and combined effect of objective measures concerning neighborhood safety, food, and physical activity environments on students' obesity. This is a cross-sectional study conducted with 9- and 10-year-old children enrolled in the municipal education network of a Brazilian metropolis. Environment objective measures comprised neighborhood unsafety (annual criminality and road traffic accident rates), availability of public parks and spaces for physical activity practicing, and index of establishments that predominantly sell ultra-processed food. Euclidean buffers of 1,000m around the children's house were used as eligible geographic units. This study adopted the Principal Component Analysis and Generalized Estimation Equation models. Stratified analyses were conducted based on neighborhood unsafety and on child's family income. In total, 717 students were assessed, 12.2% of them were children with obesity. The latent variable of the obesogenic environment (deduced by environment unsafety rates and the index of establishments that predominantly sell ultra-processed food) was a risk factor for obesity in children with lower socioeconomic levels (OR = 2.37; 95%CI: 1.06-5.19). Public parks and spaces for physical activity practicing were protective factors against childhood obesity only in locations recording the lowest environment unsafety rates (OR = 0.30; 95%CI: 0.09-0.94). Based on our findings, social conditions change the effect of the environment on childhood obesity, reinforcing the relevance of inter-sectoral policies and strategies against this condition.

Spatial variation of cardiovascular mortality in Cali, Colombia, between 2010 and 2017

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of mortality worldwide and in Colombia. The analysis of CVD mortality has been mainly relied on individual factors and rates, but occurrence is also related to contextual conditions. Understanding the distribution of CVD in a region will contribute to implement more focused-preventive and care interventions.

METHODS

Using the national mortality register established by the Department of National Statistics, standardized rates and spatial distribution of CVD mortality were estimated for Cali, Colombia, between 2010-2017. Global and local spatial aggregation was assessed using the Geary's C test and for each district standardized mortality ratios smoothed by the Bayesian empirical were estimated.

RESULTS

Over the period, CVD was the main cause of mortality with 28,804 deaths accounting for 23,8% of total deaths. The global CVD mortality rate varied from 235.9 to 257.4 per 100.000 habitants, with an average increase of 9.1% in the percentage change. The main cause of mortality were hypertensive diseases following by ischemic heart diseases and stroke. The standardized mortality ratios smoothed by the Bayesian empirical method showed that the districts 7, 13, 14, 15 and 16 located at the eastern area with the lowest socio-economic strata and the district 22 at the south of the city with the highest socio-economic strata had the high risks of CVD mortality. All these areas were at the boundary of the city. The the lowest risk was observed in districts 1 and 2 at the northwest area with the upper socio-economic strata. Over the study period, a spatial autocorrelation was found in the districts 1,9 10, 11, 12, 13, 14, 15, 19, and 21 by using the Geary's C test. The highest significant spatial association was found in the districts 1 and 21.

CONCLUSION

Of 22 districts in Cali, the highest risk of CVD mortality was found in three at the lowest and one in the upper socio-economic strata between 2013 and 2017. Over the period a global spatial aggregation was identified due mainly to districts peripherical located suggesting that there could be contextual conditions influencing the risk. Therefore, there is a need for considering local conditions to prevent CVD mortality.

Census-Tract-Level Median Household Income and Median Family Income Estimates: A Unidimensional Measure of Neighborhood Socioeconomic Status?

Previous studies suggested either census-tract-level median household income (MHI) or median family income (MFI) estimates may be used as a unidimensional measure of neighborhood socioeconomic status (SES) in the United States (US). To better understand its general use, the purpose of this study was to assess the usefulness of MHI and MFI in a wide range of geographic areas. Area-based socioeconomic data at the census tract level were obtained from the 2000 Census as well as the 2005-2009, 2010-2014, and 2015-2019 American Community Survey. MHI and MFI were used as two simple measures of neighborhood SES. Based on the five area-based indexes developed in the US, several census-tract-level socioeconomic indicators were used to derive five composite measures of neighborhood SES. Then, a series of correlation analyses was conducted to assess the relationships between these seven measures in the State of California and its seven Metropolitan Statistical Areas. Two simple measures were very strongly and positively correlated with one another, and were also strongly or very strongly correlated, either positively or negatively, with five composite measures. Hence, the results of this study support an analytical thinking that simple measures and composite measures may capture the same dimension of neighborhood SES in different geographic areas.

Associations of neighborhood walkability with moderate to vigorous physical activity: an application of compositional data analysis comparing compositional and non-compositional approaches

BACKGROUND

We compared the relation between neighborhood features and moderate to vigorous physical activity (MVPA) using linear regression analysis and the more novel compositional data analysis (CoDA). Compositional data analysis allows us to take the time children allocate to different movement behaviours during a 24-hour time period into account.

METHODOLOGY

Data from youth participants (n = 409) in the QUALITY (QUebec Adipose and Lifestyle InvesTigation in Youth) cohort were included. Time spent in MVPA, light physical activity, sedentary behavior, and sleep ("24-hour movement behaviours") was measured using accelerometers. Neighborhood data were collected using a geographic information system and through direct observation. In CoDA models, we used orthogonal logratio coordinates, which allows for the association of neighbourhood walkability with MVPA to be estimated with respect to the average composition of all other behaviours within a 24-hour time frame. In baseline linear regression models, MVPA was regressed cross-sectionally on neighborhood walkability. All models were stratified by sex, and controlled for BMI z-scores, pubertal development, seasonal variation, parental education, and neighbourhood safety.

RESULTS

Based on CoDA, girls who lived in more walkable neighborhoods had 10% higher daily MVPA (95% CI: 2%, 19%), taking into account all other movement behaviours. Based on linear regression, girls who resided in more walkable neighborhoods engaged in 4.2 (95% confidence interval [CI]: 1.2, 6.6) more minutes of MVPA per day on average than girls residing in less walkable neighborhoods.

CONCLUSIONS

Unlike with traditional linear models, all movement behaviours were included in a single model using CoDA, allowing for a more complete picture of the strength and direction of the association between neighbourhood Walkability and MVPA. Application of CoDA to investigate determinants of physical activity provides additional insight into potential mechanisms and the ways in which people allocate their time.

Interpreting a standardized and normalized measure of neighborhood socioeconomic status for a better understanding of health differences

BACKGROUND

Standardization and normalization of continuous covariates are used to ease the interpretation of regression coefficients. Although these scaling techniques serve different purposes, they are sometimes used interchangeably or confused for one another. Therefore, the objective of this study is to demonstrate how these scaling techniques lead to different interpretations of the regression coefficient in multilevel logistic regression analyses.

METHODS

Area-based socioeconomic data at the census tract level were obtained from the 2015-2019 American Community Survey for creating two measures of neighborhood socioeconomic status (SES), and a hypothetical data on health condition (favorable versus unfavorable) was constructed to represent 3000 individuals living across 300 census tracts (i.e., neighborhoods). Two measures of neighborhood SES were standardized by subtracting its mean and dividing by its standard deviation (SD) or by dividing by its interquartile range (IQR), and were normalized into a range between 0 and 1. Then, four separate multilevel logistic regression analyses were conducted to assess the association between neighborhood SES and health condition.

RESULTS

Based on standardized measures, the odds of having unfavorable health condition was roughly 1.34 times higher for a one-SD change or a one-IQR change in neighborhood SES; these reflect a health difference of individuals living in relatively high SES (relatively affluent) neighborhoods and those living in relatively low SES (relatively deprived) neighborhoods. On the other hand, when these standardized measures were replaced by its respective normalized measures, the odds of having unfavorable health condition was roughly 3.48 times higher for a full unit change in neighborhood SES; these reflect a health difference of individuals living in highest SES (most affluent) neighborhoods and those living in lowest SES (most deprived) neighborhoods.

CONCLUSION

Multilevel logistic regression analyses using standardized and normalized measures of neighborhood SES lead to different interpretations of the effect of neighborhood SES on health. Since both measures are valuable in their own right, interpreting a standardized and normalized measure of neighborhood SES will allow us to gain a more rounded view of the health differences of individuals along the gradient of neighborhood SES in a certain geographic location as well as across different geographic locations.

Cortisol activity partially accounts for a relationship between community socioeconomic position and atherosclerosis

Compared to others, individuals living in communities of socioeconomic disadvantage experience more atherosclerotic cardiovascular disease (CVD) and a greater extent of preclinical atherosclerosis. Although the mechanisms underlying these associations remain unclear, it is widely hypothesized that alterations in normative cortisol release from the Hypothalamic Pituitary Adrenal (HPA) axis may play a role in linking lower community socioeconomic position (C-SEP) to CVD risk. The current study examined this hypothesis in relation to a marker of preclinical atherosclerosis among 488 healthy midlife adults (30-54 years, Mean age= 43, 52% Female, 81% White). All participants were employed and without clinical CVD. C-SEP was estimated from census tract data, and atherosclerosis was measured as intima-medial thickness of the carotid arteries (cIMT) by duplex ultrasonography. Four indicators of HPA activity [cortisol at awakening and the cortisol awakening response (CAR), rate of diurnal decline in cortisol (diurnal slope), and total output expressed as area under the curve (AUC)] were derived from salivary cortisol measurements obtained from 5 samples on each of 3 working days. Path analyses were used to examine associations of C-SEP with cIMT and HPA activity and to test whether individual differences in HPA activity could account for any association of C-SEP with cIMT using bootstrapping (5000 iterations). All models were adjusted for age, sex, race, and composite measures of both individual-level socioeconomic position (income, education, occupation), and cardiometabolic risk (systolic and diastolic blood pressure, waist circumference, fasting lipids and glucose). Lower C-SEP was related to both greater cIMT (b = -0.004, p = .021) and a flatter diurnal slope of cortisol (b = -0.001, p = .039). An indirect effect showed attenuated diurnal slope to partially mediate the relationship between C-SEP and cIMT (95% CI = -0.0018 to -0.0001), and a residual direct effect of C-SEP on cIMT remained significant (95% CI = -0.0097 to -0.004). These results suggest that low C-SEP associations with preclinical atherosclerosis may be due in part to correlated variation in adrenocortical activity.

The health potential of neighborhoods: A population-wide study in the Netherlands

BACKGROUND

While differences in population health across neighborhoods with different socioeconomic characteristics are well documented, health disparities across neighborhoods with similar socioeconomic characteristics are less well understood. We aimed to estimate population health inequalities, both within and between neighborhoods with similar socioeconomic status, and assessed the association of neighborhood characteristics and socioeconomic spillover effects from adjacent neighborhoods.

METHODS

Based on Dutch whole-population data we determined the percentage of inhabitants with good or very good self-assessed health (SAH) and the percentage of inhabitants with at least one chronic disease (CD) in 11,504 neighborhoods. Neighborhoods were classified by quintiles of a composite neighborhoods socioeconomic status score (NSES). A set of spatial models was estimated accounting for spatial effects in the dependent, independent, and error components of the model.

RESULTS

Substantial population health disparities in SAH and CD both within and between neighborhoods NSES quintiles were observed, with the largest SAH variance in the lowest NSES group. Neighborhoods adjacent to higher SES neighborhoods showed a higher SAH and a lower prevalence of CD. Projected impacts from the spatial regressions indicate how modest changes in NSES among the lowest socioeconomic neighborhoods can contribute to population health in both low- and high-SES neighborhoods.

CONCLUSION

Population health differs substantially among neighborhoods with similar socioeconomic characteristics, which can partially be explained by a spatial socio-economic spillover effect.

An Integrated Individual Environmental Exposure Assessment System for Real-Time Mobile Sensing in Environmental Health Studies

The effects of environmental exposure on human health have been widely explored by scholars in health geography for decades. However, recent advances in geospatial technologies, especially the development of mobile approaches to collecting real-time and high-resolution individual data, have enabled sophisticated methods for assessing people’s environmental exposure. This study proposes an individual environmental exposure assessment system (IEEAS) that integrates objective real-time monitoring devices and subjective sensing tools to provide a composite way for individual-based environmental exposure data collection. With field test data collected in Chicago and Beijing, we illustrate and discuss the advantages of the proposed IEEAS and the composite analysis that could be applied. Data collected with the proposed IEEAS yield relatively accurate measurements of individual exposure in a composite way, and offer new opportunities for developing more sophisticated ways to measure individual environmental exposure. With the capability to consider both the variations in environmental risks and human mobility in high spatial and temporal resolutions, the IEEAS also helps mitigate some uncertainties in environmental exposure assessment and thus enables a better understanding of the relationship between individual environmental exposure and health outcomes.

An ego-centred approach for the evaluation of spatial effects on health in urban areas based on parametric semi-variogram models: concept and validation

Background

Neighbourhood is a complex structure but of high relevance for health. Its operationalisation remains however a challenge.The aim of this work is to present a new application of the use of semi-variograms as an approach for the evaluation of spatial effects on health. For this, we propose to estimate two parameters providing a measure of an average neighbourhood or spatial effect at city level without having to predefine any notion of physical neighbourhood.

Methods

We present the statistical method to estimate the parameters of this correlation neighbourhood by fitting an exponential model to the empirical semi-variogram at short distances. With a simulation study, we show for which sample size and sampling density the method performs well and illustrate how to use the method with data from a birth cohort using the outcome birthweight.

Results

For small sample sizes (500) the method provides reliable estimates if the density of observations is high. For larger sample sizes other parameters influencing the quality of estimates are the maximal distance at which the semi-variograms are estimated.

Conclusions

Given the complexity of spatial scales relative to neighbourhood spatial processes, our approach offers the possibility to incorporate existing approaches to the operationalisation of neighbourhood in quantitative analyses while providing a measure of the part of health inequalities which could be possibly due to unmeasured spatial exposure as well as a measure of their spatial scale.

Oxidative Stress in Ischemic Heart Disease

One of the novel interesting topics in the study of cardiovascular disease is the role of the oxidation system, since inflammation and oxidative stress are known to lead to cardiovascular diseases, their progression and complications. During decades of research, many complex interactions between agents of oxidative stress, oxidation, and antioxidant systems have been elucidated, and numerous important pathophysiological links to na number of disorders and diseases have been established. This review article will present the most relevant knowledge linking oxidative stress to vascular dysfunction and disease. The review will focus on the role of oxidative stress in endotheleial dysfunction, atherosclerosis, and other pathogenetic processes and mechanisms that contribute to the development of ischemic heart disease.

Neighborhood social environments, healthy resources, and adult diabetes: Accounting for activity space exposures

This study broadens contextual environments to include adults' activity spaces-inside and outside the residential neighborhood-to examine how contextual exposures shape type 2 diabetes risk. We use novel longitudinal data from the Los Angeles Family and Neighborhood Survey, construct time-weighted exposure measures of adults' social-structural and healthy resource environments, and execute random effects logistic models predicting the probability of being diabetic. Results indicate that residential and activity space exposures are independently associated with adult diabetes, and that residential and activity space healthy resources combine to influence diabetes risk in synergistic ways. Living in more socioeconomically advantaged neighborhoods reduces diabetes risk, particularly when spending time in activity spaces with greater access to recreational facilities. Moreover, healthier activity space environments may compensate for living in neighborhoods devoid of healthy food options to lessen diabetes risk. Adopting an activity space framework can inform multilevel interventions aimed at alleviating type 2 diabetes and other chronic ailments.

An activity space approach to understanding how food access is associated with dietary intake and BMI among urban, low-income African American women

Inconclusive evidence for how food environments affect health may result from an emphasis on residential neighborhood-based measures of exposure. We used an activity space approach to examine whether 1) measures of food access and 2) associations with diet and BMI differ between residential and activity space food environments among low-income African American women in Atlanta, Georgia (n = 199). Although residential and activity space environments differed across all dimensions of food access, being located farther away from 'unhealthy' outlets was associated with lower BMI in both environments. Future research should move beyond asking whether residential and activity space environments differ, toward examining if, how, and under what conditions these differences impact the estimation of health effects.

Contextualising lifestyles: how socially contrasting places in Fife, Scotland influence lay understandings of lifestyle and health behaviours in relation to coronary heart disease

Coronary heart disease (CHD) is a significant public health issue showing persistent geographical health inequalities. However, little attention has focussed on lay perspectives of how contrasting social contexts influence lifestyles and health behaviour in relation to CHD. The aim of this qualitative study is to explore lay perspectives of lifestyle and behaviour in socioeconomically contrasting places, with women and men who had survived a heart attack in Fife, Scotland. This study contributes to knowledge on CHD health inequalities and health promotion, particularly cardiac rehabilitation, emphasising the importance of situating experiences and understandings of health, geographically.

My neighborhood has a good reputation: Associations between spatial stigma and health

Health researchers increasingly recognize the influence of spatial stigma, or negative reputation of place, as a social determinant of health. Drawing from a New Haven-based cohort study (n = 251), we assessed the relationships between spatial stigma, self-rated health, and psychological distress using generalized estimating equation models. Adjusting for neighborhood-level poverty and racial composition, those who perceived living in spatially stigmatized neighborhoods were significantly more likely to report severe psychological distress compared to those that did not perceive their neighborhoods to be stigmatized (B = 1.09, CI: 0.31, 1.87). Our findings contribute to a growing body of literature that suggests that socially constructed meanings of place may influence health.

Understanding the Interplay Between Health Disparities and Epigenomics

Social epigenomics has emerged as an integrative field of research focused on identification of socio-environmental factors, their influence on human biology through epigenomic modifications, and how they contribute to current health disparities. Several health disparities studies have been published using genetic-based approaches; however, increasing accessibility and affordability of molecular technologies have allowed for an in-depth investigation of the influence of external factors on epigenetic modifications (e.g., DNA methylation, micro-RNA expression). Currently, research is focused on epigenetic changes in response to environment, as well as targeted epigenetic therapies and environmental/social strategies for potentially minimizing certain health disparities. Here, we will review recent findings in this field pertaining to conditions and diseases over life span encompassing prenatal to adult stages.

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.

Embedding Mobile Health Technology into the Nurses' Health Study 3 to Study Behavioral Risk Factors for Cancer

BACKGROUND

Physical activity and sleep are behavioral risk factors for cancer that may be influenced by environmental exposures, including built and natural environments. However, many studies in this area are limited by residence-based exposure assessment and/or self-reported, time-aggregated measures of behavior.

METHODS

The Nurses' Health Study 3 (NHS3) Mobile Health Substudy is a pilot study of 500 participants in the prospective NHS3 cohort who use a smartphone application and a Fitbit for seven-day periods, four times over a year, to measure minute-level location, physical activity, heart rate, and sleep.

RESULTS

We have collected data on 435 participants, comprising over 6 million participant-minutes of heart rate, step, sleep, and location. Over 90% of participants had five days of ≥600 minutes of Fitbit wear-time in their first sampling week, and this percentage dropped to 70% for weeks 2 to 4. Over 819 sampling weeks, we observed an average of 7,581 minutes of heart rate and step data [interquartile range (IQR): 6,651-9,645] per participant-week, and >2 million minutes of sleep in over 5,700 sleep bouts. We have recorded location data for 5,237 unique participant-days, averaging 104 location observations per participant-day (IQR: 103-107).

CONCLUSIONS

This study describes a protocol to incorporate mobile health technology into a nationwide prospective cohort to measure high-resolution objective data on environment and behavior.

IMPACT

This project could provide translational insights into interventions for urban planning to optimize opportunities for physical activity and healthy sleep patterns to reduce cancer risk.See all articles in this CEBP Focus section, "Modernizing Population Science."

Neighbourhood community life and health: A systematic review of reviews

Neighbourhood community life has been widely recognized as an important determinant of population health. This systematic review of reviews provides an overview of the evidence for the ecological correlation between neighbourhood community life and population health. Nine databases were searched from 2008 to 2018 in order to identify systematic reviews of studies examining the association between neighbourhood community life and population health in urban neighbourhoods within the Organisation for Economic Co-operation and Development countries. Two reviewers completed selection and data extraction, then assessed the methodological quality of reviews using the Measurement Tool to Assess Systematic Reviews. We identified three high quality reviews and five of moderate quality. The reviews vary in quality of methodology, concepts, and measures. Most of the reviews examined the influence of social cohesion, social capital, and social interactions on health. Reviews found evidence supporting a consistently favourable correlation between social cohesion and physical activity, as well as a favourable trend in the relationship between social cohesion and healthy weight. They also found evidence of a favourable trend in the correlation between social capital and healthy weight. Reviews identified studies supporting a consistently favourable correlation between social interaction and depression. We identify evidence of a positive association between neighbourhood community life and several population health outcomes. Future research should define and conceptualize neighbourhood community life factors and health indicators to improve the comparison between studies and the process of evidence synthesis. This will also enable policy makers to take appropriate decisions.

Asthma status moderates the relationship between neighbourhood disadvantage and obesity in African American adolescent females

INTRODUCTION

Significant health disparities exist in asthma and obesity for African American youths. Successful interventions present an opportunity to address these disparities but require detailed study in order to ensure generalizability. This study investigated the intersection of obesity, neighbourhood disadvantage, and asthma.

METHODS

Data were extracted from 129 African American females ages 13 to 19 years (mean = 15.6 years [SD = 1.9]). Obesity was measured via body mass index (BMI). Asthma status was based on clinical diagnosis and/or results of the International Study of Asthma and Allergies during Childhood (ISAAC) questionnaire. The concentrated disadvantage index (CDI) assessed neighbourhood disadvantage.

RESULTS

Findings showed that 21.5% (n = 28) of participants were clinically defined as having asthma, 76.2% (n = 99) had obesity, and 24.9% (n = 31) were classified without obesity. The mean BMI was 35.1 (SD = 9.1) and the mean CDI was 1.0 (SD = 0.9). CDI and obesity were significantly associated in participants without asthma, but not in those with asthma. Multivariable linear regression results showed a significant interaction between CDI and asthma (t value = 2.2, P = .03).

CONCLUSION

In sum, results from this study found that asthma moderated the relationship between neighbourhood disadvantage and obesity.

Built environment and health: a systematic review of studies in Germany

Objectives

Empirical research on the relationship between the built environment and health is increasing at a tremendous pace. However, findings from Anglo-American countries may not apply to the European context. Therefore, we systematically reviewed the existing evidence on the role of the built environment for leading risk factors and health behavior in Germany.

Methods

Through an extensive search via PubMed and Web of Science, using predefined selection criteria, two independent reviewers identified 25 empirical studies. We described the main study variables (year of publication, study design, data source, sample characteristics), classified the studies according to their respective operationalization of environmental features and health outcomes, and qualitatively summarized the main results.

Results

The majority of the studies focused on anthropometric measures and physical activity. Access to respective destinations was associated with sports-related physical activity but not with body composition. Also, people living in urban structures tended to show more health-adverse behaviors such as smoking and drinking. Some evidence indicated that higher levels of noise and air pollution were related to higher blood pressure levels. No association was observed between green spaces or street design and health.

Conclusions

Future research should investigate relationships using a sound theoretical basis and research designs that better account for the complex relationship between the built environment and health.

Understanding the role of service providers, land use, and resident characteristics on the occurrence of mental health crisis calls to the police

Similar to concentrations of crime, mental health calls have been found to concentrate at a small number of places, but few have considered the context of places where mental health calls occur. The current study examines the influence of the physical and social context of street segments, particularly the role of service providers, land use features of the street and nearby area, and characteristics of residents on the likelihood of a mental health crisis call to the police occurring on the street. The findings demonstrate that the social context, such as offending and drug use among residents, levels of social cohesion and community involvement, and drug and violent crime influenced the occurrence of mental health crisis calls. Findings from this study make theoretical and practical contributions to a number of disciplines by improving our understanding of where mental health crisis calls occur and why they are found at specific places.

Assessing the spatial scale of context effects: The example of neighbourhoods' educational composition and its relevance for individual aspirations

The neighbourhood environment has repeatedly proven to be a relevant context for central aspects of individuals' lives, such as educational attainment. The conventional approach of measuring neighbourhood characteristics within disjunct geographical units fixed at a particular scale is less suitable for representing the characteristics of individual action spaces in everyday activities and for detecting scale-dependent relationships. We, therefore, adapted an ego-centred context approach by aggregating contextual characteristics within (approximately) circular areas around individual respondents' places of residence (ego-hoods). We also used an analytical framework that considers the quality of hierarchical context effects. This allowed us to derive conclusions about the spatial reference of micro-level mechanisms from the scale of context effects observed as a macro-micro relationship. We linked contextual indicators to individual-level data from the German Socio-Economic Panel. Comparing ego-hoods of different ranges, we confirmed the expectation of distance decay in the relevance of neighbours for individual educational aspirations.

Activity spaces in studies of the environment and physical activity: A review and synthesis of implications for causality

Activity spaces are increasingly used to understand how people interact with their environment and engage in activity but their use may raise challenges regarding causal inference. We conducted a systematic review of findings and the methodological, analytical and conceptual issues relevant to causal inference. Studies were included if they comprised a spatial summary of locations visited, assessed any part of the causal pathway between the environment, physical activity and health, and used quantitative or qualitative methods. We searched seven electronic databases in January 2018 and screened 11910 articles for eligibility. Forty-seven studies were included for review. Studies answered research questions about features of or environmental features within activity spaces using a range of spatial and temporal summary techniques. The conceptual challenge of using activity spaces to strengthen causal inference was rarely considered, although some studies discussed circularity, temporality, and plausibility. Future studies should use longitudinal and experimental designs and consider the potential and actual use of spaces for physical activity, and their relationship with total levels of activity.

Acute myocardial infarction: Does survival depend on geographical location and social background?

AIMS

This study described the interplay between geographical and social inequalities in survival after incident acute myocardial infarction (AMI) and examined whether geographical variation in survival exists when accounting for sociodemographic characteristics of the patients and their neighbourhood.

METHODS

Ringmap visualization and generalized linear models were performed to study post-AMI mortality. Three individual-level analyses were conducted: immediate case fatality, mortality between days 1 and 28 after admission and 365-day survival among patients who survived 28 days after admission.

RESULTS

In total, 99,013 incident AMI cases were registered between 2005 and 2014 in Denmark. Survival after AMI tended to correlate with sociodemographic indicators at the municipality level. In individual-level models, geographical inequality in immediate case fatality was observed with high mortality in northern parts of Jutland after accounting for sociodemographic characteristics. In contrast, no geographical variation in survival was observed among patients who survived 28 days. In all three analyses, odds and rates of mortality were higher among patients with low educational level (odds ratio (OR) (95% credible intervals) of 1.20 (1.12-1.29), OR of 1.12 (1.01-1.24) and mortality rate ratio of 1.45 (1.30-1.61)) and low income (OR of 1.24 (1.15-1.33), OR of 1.33 (1.20-1.48) and mortality rate ratio of 1.25 (1.13-1.38)).

CONCLUSION

Marked geographical inequality was observed in immediate case fatality. However, no geographically unequal distribution of survival was found among patients who survived 28 days after AMI. Results additionally showed social inequality in survival following AMI.

Assessing Individuals' Exposure to Environmental Conditions Using Residence-based Measures, Activity Location-based Measures, and Activity Path-based Measures

BACKGROUND

Many approaches are available to researchers who wish to measure individuals' exposure to environmental conditions. Different approaches may yield different estimates of associations with health outcomes. Taking adolescents' exposure to alcohol outlets as an example, we aimed to (1) compare exposure measures and (2) assess whether exposure measures were differentially associated with alcohol consumption.

METHODS

We tracked 231 adolescents 14-16 years of age from the San Francisco Bay Area for 4 weeks in 2015/2016 using global positioning systems (GPS). Participants were texted ecologic momentary assessment surveys six times per week, including assessment of alcohol consumption. We used GPS data to calculate exposure to alcohol outlets using three approach types: residence-based (e.g., within the home census tract), activity location-based (e.g., within buffer distances of frequently attended places), and activity path-based (e.g., average outlets per hour within buffer distances of GPS route lines). Spearman correlations compared exposure measures, and separate Tobit models assessed associations with the proportion of ecologic momentary assessment responses positive for alcohol consumption.

RESULTS

Measures were mostly strongly correlated within approach types (ρ ≥ 0.7), but weakly (ρ < 0.3) to moderately (0.3 ≤ ρ < 0.7) correlated between approach types. Associations with alcohol consumption were mostly inconsistent within and between approach types. Some of the residence-based measures (e.g., census tract: β = 8.3, 95% CI = 2.8, 13.8), none of the activity location-based approaches, and most of the activity path-based approaches (e.g., outlet-hours per hour, 100 m buffer: β = 8.3, 95% CI = 3.3, 13.3) were associated with alcohol consumption.

CONCLUSIONS

Methodologic decisions regarding measurement of exposure to environmental conditions may affect study results.

Hot Spots of Crime are Not Just Hot Spots of Crime: Examining Health Outcomes at Street Segments

In this paper we seek to identify whether the relationship between health disparities and crime occurs at a micro geographic level. Do hot spot streets evidence much higher levels of mental and physical illness than streets with little crime? Are residents of crime hot spots more likely to have health problems that interfere with their normal daily activities? To answer these questions, we draw upon a large National Institutes of Health study of a sample of hot spots and non-hot spots in Baltimore, Maryland. This is the first study we know of to report on this relationship, and accordingly we present unique descriptive data. Our findings show that both physical and mental health problems are much more likely to be found on hot spot streets than streets with little crime. This suggests that crime hot spots are not simply places with high levels of crime, but also places that evidence more general disadvantage. We argue that these findings have important policy implications for the targeting of health services and for developing proactive prevention programs.

Geographical inequalities in acute myocardial infarction beyond neighbourhood-level and individual-level sociodemographic characteristics: a Danish 10-year nationwide population-based cohort study

OBJECTIVE

This study examined whether geographical patterns in incident acute myocardial infarction (AMI) were explained by neighbourhood-level and individual-level sociodemographic characteristics.

DESIGN

An open cohort study design of AMI-free adults (age ≥30 years) with a residential location in Denmark in 2005-2014 was used based on nationwide administrative population and health register data linked by the unique personal identification number. Poisson regression of AMI incidence rates (IRs) with a geographical random effect component was performed using a Bayesian approach. The analysis included neighbourhood-level variables on income, ethnic composition, population density and population turnover and accounted for individual-level age, sex, calendar year, cohabitation status, income and education.

SETTING

Residents in Denmark (2005-2014).

PARTICIPANTS

The study population included 4 128 079 persons (33 907 796 person-years at risk) out of whom 98 265 experienced an incident AMI.

OUTCOME MEASURE

Incident AMI registered in the National Patient Register or the Register of Causes of Death.

RESULTS

Including individual and neighbourhood sociodemographic characteristics in the model decreased the variation in IRs of AMI. However, living in certain areas was associated with up to 40% increased IRs of AMI in the adjusted model and accounting for sociodemographic characteristics only moderately changed the geographical disease patterns.

CONCLUSIONS

Differences in sociodemographic characteristics of the neighbourhood and individuals explained part, but not all of the geographical inequalities in incident AMI. Prevention strategies should address the confirmed social inequalities in incident AMI, but also target the areas with a heavy disease burden to enable efficient allocation of prevention resources.

The Hispanic Community Health Study/Study of Latinos Community and Surrounding Areas Study: sample, design, and procedures

PURPOSE

We describe the sample, design, and procedures for the Community and Surrounding Areas Study (CASAS), an ancillary to the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). The aim of SOL CASAS was to test an ecological model of macro- and micro-neighborhood environment factors, intermediate behavioral (physical activity) and psychosocial (e.g., depression and stress) mechanisms, and changes in cardiometabolic health in Hispanics/Latinos.

METHODS

Between 2015 and 2017, approximately 6 years after the HCHS/SOL baseline (2008-2011), 1776 San Diego HCHS/SOL participants enrolled in SOL CASAS and completed a repeat physical activity assessment. Participants' residential addresses were geoprocessed, and macroenvironmental features of the home were derived from publicly available data concurrent with the HCHS/SOL baseline and Visit 2 (2014-2017). Microscale environmental attributes were coded for 943 unique routes for 1684 participants, with a validated observational tool, concurrent with Visit 2, for SOL CASAS participants only.

RESULTS

Of 2520 HCHS/SOL participants approached, 70.5% enrolled (mean age 55.3 years; 94% Mexican; 67.5% female). Accelerometer adherence (three or more days with at least 10 hours wear time) was outstanding (94%).

CONCLUSIONS

With its more comprehensive ecological model and well-characterized Hispanic/Latino population, SOL CASAS will advance the science concerning the contribution of neighborhood factors to cardiometabolic health.

Evaluation of data accuracies within a comprehensive geospatial-health data surveillance platform: SOMAARTH Demographic Development and Environmental Surveillance Site, Palwal, Haryana, India

Evidence exists of an increasing prevalence of chronic conditions within developed and developing nations, notably for priority population groups. The need for the collection of geospatial data to monitor the health impact of rapid social-environmental and economic changes occurring in these countries is being increasingly recognized. Rigorous accuracy assessment of such geospatial data is required to enable error estimation, and ultimately, data utility for exploring population health. This research outlines findings from a field-based evaluation exercise of the SOMAARTH DDESS geospatial-health platform. Participatory-based mixed methods have been employed within Palwal-India to capture villager perspectives on built infrastructure across 51 villages. This study, conducted in 2013, included an assessment of data element position and attribute accuracy undertaken in six villages, documenting mapping errors and land parcel changes. Descriptive analyses of 5.1% (n = 455) of land parcels highlighted some discrepancies in position (6.4%) and attribute (4.2%) accuracy, and land parcel changes (17.4%). Furthermore, the evaluation led to a refinement of the existing geospatial health platform incorporating ground-truthed reflections from the participatory field exercise. The evaluation of geospatial data accuracies contributes to understandings on global public health surveillance systems, outlining the need to systematically consider assessment of environmental features in relation to lifestyle-related diseases.

Geographic and area-level socioeconomic variation in cardiometabolic risk factor distribution: a systematic review of the literature

INTRODUCTION

A growing number of publications report variation in the distribution of cardiometabolic risk factors (CMRFs) at different geographic scales. A review of these variations may help inform policy and health service organisation.

AIM

To review studies reporting variation in the geographic distribution of CMRFs and its association with various proxy measures of area-level socioeconomic disadvantage (ASED) among the adult ( ≥ 18 years) population across the world.

METHODS

A systematic search for published articles was conducted in four databases (MEDLINE (Ovid), PubMed, Scopus and Web of Science) considering the interdisciplinary nature of the review question. Population-based cross-sectional and cohort studies on geographic variations of one or more biological proxies of CMRFs with/without an analysed contextual association with ASED were included. Two independent reviewers screened the studies and PRISMA guidelines were followed in the study selection and reporting.

RESULT

A total of 265 studies were retrieved and screened, resulting in 24 eligible studies. The review revealed reports of variation in the distribution of CMRFs, at varying geographic scales, in multiple countries. In addition, consistent associations between ASED and higher prevalence of CMRFs were demonstrated. The reports were mainly from industrialised nations and small area geographic units were frequently used.

CONCLUSION

Geographic variation in cardiometabolic risk exists across multiple spatial scales and is positively associated with ASED. This association is independent of individual-level factors and provides an imperative for area-based approaches to informing policy and health service organisation. The study protocol is registered in International prospective register of systematic reviews (Register No: CRD42018115294) PROSPERO 2018.

Community Social Characteristics and Health at Older Ages: Evidence From 156 Religious Communities

Objectives

Previous studies have found that individuals' health is associated with the social characteristics of their communities. However, interpreting the causality of the relationships is difficult due to a number of potential confounders on both the individual- and community-levels as well as potential selection effects. In the current article, we analyze data on health and community characteristics from Catholic order members aged 50+ living together in religious communities. We argue that the potential for confounders and selection effects is reduced in our sample.

Method

We use multilevel group actor-partner interdependence models and cross-sectional questionnaire data (N = 1,041, k = 156 communities) to test whether individuals' self-rated health was associated with the level of social conflict and connectedness of their community separate from their own involvement in conflict and feelings of connectedness.

Results

We find that living in communities with higher levels of conflict is associated with worse health, especially at older ages. We also find that (a) the relationship between health and own feelings of connectedness is stronger for men and (b) women report better health than men in more connected communities.

Discussion

Our results offer further evidence that at least some social characteristics of the community have a causal impact on health.

Residential and GPS-Defined Activity Space Neighborhood Noise Complaints, Body Mass Index and Blood Pressure Among Low-Income Housing Residents in New York City

Little is known about how neighborhood noise influences cardiovascular disease (CVD) risk among low-income populations. The aim of this study was to investigate associations between neighborhood noise complaints and body mass index (BMI) and blood pressure (BP) among low-income housing residents in New York City (NYC), including the use of global positioning system (GPS) data. Data came from the NYC Low-Income Housing, Neighborhoods and Health Study in 2014, including objectively measured BMI and BP data (N = 102, Black = 69%), and 1 week of GPS data. Noise reports from "NYC 311" were used to create a noise complaints density (unit: 1000 reports/km²) around participants' home and GPS-defined activity space neighborhoods. In fully-adjusted models, we examined associations of noise complaints density with BMI (kg/m²), and systolic and diastolic BP (mmHg), controlling for individual- and neighborhood-level socio-demographics. We found inverse relationships between home noise density and BMI (B = -2.7 [kg/m²], p = 0.009), and systolic BP (B = -5.3 mmHg, p = 0.008) in the fully-adjusted models, and diastolic BP (B = -3.9 mmHg, p = 0.013) in age-adjusted models. Using GPS-defined activity space neighborhoods, we observed inverse associations between noise density and systolic BP (B = -10.3 mmHg, p = 0.019) in fully-adjusted models and diastolic BP (B = -7.5 mmHg, p = 0.016) in age-adjusted model, but not with BMI. The inverse associations between neighborhood noise and CVD risk factors were unexpected. Further investigation is needed to determine if these results are affected by unobserved confounding (e.g., variations in walkability). Examining how noise could be related to CVD risk could inform effective neighborhood intervention programs for CVD risk reduction.

An Analytical Framework for Integrating the Spatiotemporal Dynamics of Environmental Context and Individual Mobility in Exposure Assessment: A Study on the Relationship between Food Environment Exposures and Body Weight

In past studies, individual environmental exposures were largely measured in a static manner. In this study, we develop and implement an analytical framework that dynamically represents environmental context (the environmental context cube) and effectively integrates individual daily movement (individual space-time tunnel) for accurately deriving individual environmental exposures (the environmental context exposure index). The framework is applied to examine the relationship between food environment exposures and the overweight status of 46 participants using data collected with global positioning systems (GPS) in Columbus, Ohio, and binary logistic regression models. The results indicate that the proposed framework generates more reliable measurements of individual food environment exposures when compared to other widely used methods. Taking into account the complex spatial and temporal dynamics of individual environmental exposures, the proposed framework also helps to mitigate the uncertain geographic context problem (UGCoP). It can be used in other environmental health studies concerning environmental influences on a wide range of health behaviors and outcomes.

Comparing the Data Quality of Global Positioning System Devices and Mobile Phones for Assessing Relationships Between Place, Mobility, and Health: Field Study

Background

Mobile devices are increasingly used to collect location-based information from individuals about their physical activities, dietary intake, environmental exposures, and mental well-being. Such research, which typically uses wearable devices or mobile phones to track location, benefits from the growing availability of fine-grained data regarding human mobility. However, little is known about the comparative geospatial accuracy of such devices.

Objective

In this study, we compared the data quality of location information collected from two mobile devices that determine location in different ways—a global positioning system (GPS) watch and a mobile phone with Google’s Location History feature enabled.

Methods

A total of 21 chronically ill participants carried both devices, which generated digital traces of locations, for 28 days. A mobile phone–based brief ecological momentary assessment (EMA) survey asked participants to manually report their location at 4 random times throughout each day. Participants also took part in qualitative interviews and completed surveys twice during the study period in which they reviewed recent mobile phone and watch trace data to compare the devices’ trace data with their memory of their activities on those days. Trace data from the devices were compared on the basis of (1) missing data days, (2) reasons for missing data, (3) distance between the route data collected for matching day and the associated EMA survey locations, and (4) activity space total area and density surfaces.

Results

The watch resulted in a much higher proportion of missing data days (P<.001), with missing data explained by technical differences between the devices as well as participant behaviors. The mobile phone was significantly more accurate in detecting home locations (P=.004) and marginally more accurate (P=.07) for all types of locations combined. The watch data resulted in a smaller activity space area and more accurately recorded outdoor travel and recreation.

Conclusions

The most suitable mobile device for location-based health research depends on the particular study objectives. Furthermore, data generated from mobile devices, such as GPS phones and smartwatches, require careful analysis to ensure quality and completeness. Studies that seek precise measurement of outdoor activity and travel, such as measuring outdoor physical activity or exposure to localized environmental hazards, would benefit from the use of GPS devices. Conversely, studies that aim to account for time within buildings at home or work, or those that document visits to particular places (such as supermarkets, medical facilities, or fast food restaurants), would benefit from the greater precision demonstrated by the mobile phone in recording indoor activities.

Capturing exposure in environmental health research: challenges and opportunities of different activity space models

Background

The built environment health promotion has attracted notable attention across a wide spectrum of health-related research over the past decade. However, the results about the contextual effects on health and PA are highly heterogeneous. The discrepancies between the results can potentially be partly explained by the diverse use of different spatial units of analysis in assessing individuals’ exposure to various environment characteristics. This study investigated whether different residential and activity space units of analysis yield distinct results regarding the association between the built environment and health. In addition, this study examines the challenges and opportunities of the different spatial units of analysis for environmental health-related research.

Methods

Two common residential units of analysis and two novel activity space models were used to examine older adults’ wellbeing in relation to the built environment features in the Helsinki Metropolitan Area, Finland. An administrative unit, 500 m residential buffer, home range model and individualized residential exposure model were used to assess the associations between the built environment and wellbeing of respondent’s (n = 844).

Results

All four different spatial units of analysis yield distinct results regarding the associations between the built environment characteristics and wellbeing. A positive association between green space and health was found only when exposure was assessed with individualized residential exposure model. Walkability index and the length of pedestrian and bicycle roads were found to positively correlate with perceived wellbeing measures only with a home range model. Additionally, all units of analysis differed from each other in terms of size, shape, and how they capture different contextual measures.

Conclusions

The results show that different spatial units of analysis result in considerably different measurements of built environment. In turn, the differences derived from the use of different spatial units seem to considerably affect the associations between environment characteristics and wellbeing measures. Although it is not easy to argue about the correctness of these measurements, what is evident is that they can reveal different wellbeing outcomes. While some methods are especially usable to determine the availability of environmental opportunities that promote active travel and the related health outcomes, others can provide us with insight into the mechanisms how the actual exposure to green structure can enhance wellbeing.

Exploring spatial patterns of cardiovascular disease in Sweden between 2000 and 2010

AIMS

Cardiovascular disease (CVD) is one of the leading causes of mortality and morbidity worldwide, including in Sweden. The main aim of this study was to explore the temporal trends and spatial patterns of CVD in Sweden using spatial autocorrelation analyses.

METHODS

The CVD admission rates between 2000 and 2010 throughout Sweden were entered as the input disease data for the analytic processes performed for the Swedish capital, Stockholm, and also for the whole of Sweden. Age-adjusted admission rates were calculated using a direct standardisation approach for men and women, and temporal trends analysis were performed on the standardised rates. Global Moran's I was used to explore the structure of patterns and Anselin's local Moran's I, together with Kulldorff's scan statistic were applied to explore the geographical patterns of admission rates.

RESULTS

The rates followed a spatially clustered pattern in Sweden with differences occurring between sexes. Accordingly, hot spots were identified in northern Sweden, with higher intensity identified for men, together with clusters in central Sweden. Cold spots were identified in the adjacency of the three major Swedish cities of Stockholm, Gothenburg and Malmö.

CONCLUSIONS

The findings of this study can serve as a basis for distribution of health-care resources, preventive measures and exploration of aetiological factors.

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.

A prospective investigation of neighborhood socioeconomic deprivation and physical activity and sedentary behavior in older adults

Neighborhood conditions may have an important impact on physical activity and sedentary behaviors in the older population. Most previous studies in this area are cross-sectional and report mixed findings regarding the effects of neighborhood environment on different types of physical activity. Moreover, little is known about the prospective relationship between neighborhood environment and sedentary behaviors. Our analysis included 136,526 participants from the NIH-AARP Diet and Health Study (age 51-70). Neighborhood socioeconomic deprivation was measured with an index based on census variables and developed using principal component analysis. Physical activity and sedentary behaviors were measured both at baseline (1995-1996) and follow-up (2004-2006). Multiple regression analyses were conducted to examine the prospective relationship between neighborhood deprivation and exercise, non-exercise physical activity, and sedentary behaviors, adjusting for baseline physical activity and sedentary behaviors as well as potential confounders. We found that more severe neighborhood socioeconomic deprivation was prospectively associated with reduced time for exercise (β _Q5 vs _Q1 (95% confidence interval), hour, -0.85 (-0.95, -0.75)) but increased time spent in non-exercise physical activities (1.16 (0.97, 1.34)), such as household activities, outdoor chores, and walking for transportation. Moreover, people from more deprived neighborhoods were also more likely to engage in prolonged (≥5 h/day) TV viewing (Odds ratio _Q5 vs _Q1 (95% confidence interval), 1.21 (1.15, 1.27)). In conclusion, neighborhood socioeconomic deprivation is associated with physical activity and sedentary behavior in the older population. These associations may differ for different types of physical activities.

Defining the Human Envirome: An Omics Approach for Assessing the Environmental Risk of Cardiovascular Disease

Both genetic and environmental factors contribute to the development of cardiovascular disease, but in comparison with genetics, environmental factors have received less attention. Evaluation of environmental determinants of cardiovascular disease is limited by the lack of comprehensive omics approaches for integrating multiple environmental exposures. Hence, to understand the effects of the environment as a whole (envirome), it is important to delineate specific domains of the environment and to assess how, individually and collectively; these domains affect cardiovascular health. In this review, we present a hierarchical model of the envirome; defined by 3 consecutively nested domains, consisting of natural, social, and personal environments. Extensive evidence suggests that features of the natural environment such as sunlight, altitude, diurnal rhythms, vegetation, and biodiversity affect cardiovascular health. However, the effects of the natural environment are moderated by the social environment comprised of built environments, agricultural and industrial activities, pollutants and contaminants, as well as culture, economic activities, and social networks that affect health by influencing access to healthcare, social cohesion, and socioeconomic status. From resources available within society, individuals create personal environments, characterized by private income, wealth and education, and populated by behavioral and lifestyle choices relating to nutrition, physical activity, sleep, the use of recreational drugs, and smoking. An understanding of the interactions between different domains of the envirome and their integrated effects on cardiovascular health could lead to the development of new prevention strategies and deeper insights into etiologic processes that contribute to cardiovascular disease risk and susceptibility.

The Uncertain Geographic Context Problem in the Analysis of the Relationships between Obesity and the Built Environment in Guangzhou

Traditionally, static units of analysis such as administrative units are used when studying obesity. However, using these fixed contextual units ignores environmental influences experienced by individuals in areas beyond their residential neighborhood and may render the results unreliable. This problem has been articulated as the uncertain geographic context problem (UGCoP). This study investigates the UGCoP through exploring the relationships between the built environment and obesity based on individuals’ activity space. First, a survey was conducted to collect individuals’ daily activity and weight information in Guangzhou in January 2016. Then, the data were used to calculate and compare the values of several built environment variables based on seven activity space delineations, including home buffers, workplace buffers (WPB), fitness place buffers (FPB), the standard deviational ellipse at two standard deviations (SDE2), the weighted standard deviational ellipse at two standard deviations (WSDE2), the minimum convex polygon (MCP), and road network buffers (RNB). Lastly, we conducted comparative analysis and regression analysis based on different activity space measures. The results indicate that significant differences exist between variables obtained with different activity space delineations. Further, regression analyses show that the activity space delineations used in the analysis have a significant influence on the results concerning the relationships between the built environment and obesity. The study sheds light on the UGCoP in analyzing the relationships between obesity and the built environment.

Are Perceived and Objective Distances to Fresh Food and Physical Activity Resources Associated with Cardiometabolic Risk?

Perceived and objective measures of neighbourhood features have shown limited correspondence. Few studies have examined whether discordance between objective measures and individual perceptions of neighbourhood environments relates to individual health. Individuals with mismatched perceptions may benefit from initiatives to improve understandings of resource availability. This study utilised data from n = 1491 adult participants in a biomedical cohort to evaluate cross-sectional associations between measures of access (perceived, objective, and perceived-objective mismatch) to fruit and vegetable retailers (FVR) and public open space (POS), and clinically-measured metabolic syndrome and its component risk factors: central obesity, dyslipidaemia, hypertension and pre-diabetes/diabetes. Access measures included perceived distances from home to the nearest FVR and POS, corresponding objectively-assessed road network distances, and the discordance between perceived and objective distances (overestimated (i.e., mismatched) distances versus matched perceived-objective distances). Individual and neighbourhood measures were spatially joined using a geographic information system. Associations were evaluated using multilevel logistic regression, accounting for individual and area-level covariates. Hypertension was positively associated with perceived distances to FVR (odds ratio (OR) = 1.14, 95% confidence interval (CI) = 1.02, 1.28) and POS (OR = 1.19, 95% CI = 1.05, 1.34), after accounting for covariates and objective distances. Hypertension was positively associated with overestimating distances to FVR (OR = 1.36, 95% CI = 1.02, 1.80). Overestimating distances to POS was positively associated with both hypertension (OR = 1.42, 95% CI = 1.11, 1.83) and dyslipidaemia (OR = 1.25, 95% CI = 1.00, 1.57). Results provide new evidence for specific associations between perceived and overestimated distances from home to nearby resources and cardiometabolic risk factors.

Causal nature of neighborhood deprivation on individual risk of coronary heart disease or ischemic stroke: A prospective national Swedish co-relative control study in men and women

We studied the association between neighborhood socioeconomic status (SES) and incidence of coronary heart disease (CHD) or ischemic stroke in the total population and in full- and half-siblings to determine whether these associations are causal or a result from familial confounding. Data were retrieved from nationwide Swedish registers containing individual clinical data linked to neighborhood of residence. After adjustment for individual SES, the association between neighborhood SES and CHD showed no decrease with increasing genetic resemblance, particularly in women. This indicates that the association between neighborhood SES and CHD incidence is partially causal among women, which represents a novel finding.

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.