Dataset Information

Associations Between the Built Environment and Objective Measures of Sleep: The Multi-Ethnic Study of Atherosclerosis.

ABSTRACT: Although dense neighborhood built environments support increased physical activity and lower obesity, these features may also disturb sleep. Therefore, we sought to understand the association between the built environment and objectively measured sleep. From 2010 to 2013, we analyzed data from examination 5 of the Multi-Ethnic Study of Atherosclerosis, a diverse population from 6 US cities. We fit multilevel models that assessed the association between the built environment (Street Smart Walk Score, social engagement destinations, street intersections, and population density) and sleep duration or efficiency from 1-week wrist actigraphy in 1,889 individuals. After adjustment for covariates, a 1-standard-deviation increase in Street Smart Walk Score was associated with 23% higher odds of short sleep duration (?6 hours; odds ratio = 1.2, 95% confidence interval: 1.0, 1.4), as well as shorter average sleep duration (mean difference = -8.1 minutes, 95% confidence interval: -12.1, -4.2). Results were consistent across other built environment measures. Associations were attenuated after adjustment for survey-based measure of neighborhood noise. Dense neighborhood development may have multiple health consequence. In promoting denser neighborhoods to increase walkability, it is important to also implement strategies that reduce the adverse impacts of this development on sleep, such as noise reductions efforts.

SUBMITTER: Johnson DA

PROVIDER: S-EPMC5928457 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Associations Between the Built Environment and Objective Measures of Sleep: The Multi-Ethnic Study of Atherosclerosis.

Johnson Dayna A DA Hirsch Jana A JA Moore Kari A KA Redline Susan S Diez Roux Ana V AV

American journal of epidemiology 20180501 5

Although dense neighborhood built environments support increased physical activity and lower obesity, these features may also disturb sleep. Therefore, we sought to understand the association between the built environment and objectively measured sleep. From 2010 to 2013, we analyzed data from examination 5 of the Multi-Ethnic Study of Atherosclerosis, a diverse population from 6 US cities. We fit multilevel models that assessed the association between the built environment (Street Smart Walk Sc ...[more]

PMID: 29547912

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Project description:BackgroundTransport walking has drawn growing interest due to its potential to increase levels of physical activities and reduce reliance on vehicles. While existing studies have compared built environment-health associations between Euclidean buffers and network buffers, no studies have systematically quantified the extent of bias in health effect estimates when exposures are measured in different buffers. Further, prior studies have done the comparisons focusing on only one or two geographic regions, limiting generalizability and restricting ability to test whether direction or magnitude of bias are different by context. This study aimed to quantify the degree of bias in associations between built environment exposures and transport walking when exposures were operationalized using Euclidean buffers rather than network buffers in diverse contexts.MethodsWe performed a simulations study to systematically evaluate the degree of bias in associations between built environment exposures in Euclidean buffers and network buffers and transport walking, assuming network buffers more accurately captured true exposures. Additionally, we used empirical data from a multi-ethnic, multi-site cohort to compare associations between built environment amenities and walking for transport where built environment exposures were derived using Euclidean buffers versus network buffers.ResultsSimulation results found that the bias induced by using Euclidean buffer models was consistently negative across the six study sites (ranging from -80% to -20%), suggesting built environment exposures measured using Euclidean buffers underestimate health effects on transport walking. Percent bias was uniformly smaller for the larger 5 km scale than the 1 km and 0.25 km spatial scales, independent of site or built environment categories. Empirical findings aligned with the simulation results: built environment-health associations were stronger for built environment exposures operationalized using network buffers than using Euclidean buffers.ConclusionThis study is the first to quantify the extent of bias in the magnitude of the associations between built environment exposures and transport walking when the former are measured in Euclidean buffers vs. network buffers, informing future research to carefully conceptualize appropriate distance-based buffer metrics in order to better approximate real geographic contexts. It also helps contextualize existing research in the field that used Euclidean buffers when that were the only option. Further, this study provides an example of the uncertain geographic context problem.

Project description:IntroductionMounting evidence documents the importance of urban form for active travel, but international studies could strengthen the evidence. The aim of the study was to document the strength, shape, and generalizability of relations of objectively measured built environment variables with transport-related walking and cycling.MethodsThis cross-sectional study maximized variation of environments and demographics by including multiple countries and by selecting adult participants living in neighborhoods based on higher and lower classifications of objectively measured walkability and socioeconomic status. Analyses were conducted on 12,181 adults aged 18-66 years, drawn from 14 cities across 10 countries worldwide. Frequency of transport-related walking and cycling over the last seven days was assessed by questionnaire and four objectively measured built environment variables were calculated. Associations of built environment variables with transport-related walking and cycling variables were estimated using generalized additive mixed models, and were tested for curvilinearity and study site moderation.ResultsWe found positive associations of walking for transport with all the environmental attributes, but also found that the relationships was only linear for land use mix, but not for residential density, intersection density, and the number of parks. Our findings suggest that there may be optimum values in these attributes, beyond which higher densities or number of parks could have minor or even negative impact. Cycling for transport was associated linearly with residential density, intersection density (only for any cycling), and land use mix, but not with the number of parks.ConclusionAcross 14 diverse cities and countries, living in more densely populated areas, having a well-connected street network, more diverse land uses, and having more parks were positively associated with transport-related walking and/or cycling. Except for land-use-mix, all built environment variables had curvilinear relationships with walking, with a plateau in the relationship at higher levels of the scales.

Project description:BackgroundCortisol is often used as a biological marker for stress. When measured in urine or serum, representing a short-term measurement of the hormone, it has been associated with unfavorable sleep characteristics and both low and high physical activity levels. However, cortisol in hair represents a long-term stress measure and has been suggested as a promising new marker for chronic stress. Therefore, we aimed to examine the association between objectively measured sleep, physical activity and hair cortisol levels in preschool children.MethodsIn order to obtain objective measures of physical activity and sleep habits, 54 children aged 2-6 years wore an ActiGraph for 5 consecutive days and nights. For chronic stress measurements of each child, hair was cut from the back of the head close to the scalp for analysis of cortisol levels. Associations between measured sleep quality and quantity and level of physical activity and hair cortisol levels were estimated using linear regression analysis, presented as β. Results were adjusted for sex, age and BMI z-score.ResultsWe found no significant association between log-transformed cortisol (pg/mg) and sleep duration (hours) (β = - 0.0016, p = 0.99), sleep efficiency (β = - 3.1, p = 0.18), sleep latency (β = 0.015, p = 0.16) or physical activity level (100 counts per min) (β = 0.014, p = 0.22). However, sleep latency (min) was directly associated with physical activity (counts per min) levels (β = 35.2, p = 0.02), while sleep duration (hours) (β = - 142.1, p = 0.55) and sleep efficiency (%) (β = - 4087, p = 0.26) showed no significant associations.ConclusionsIn our study, a high physical activity level was associated with poorer sleep habits. Neither sleep quality nor physical activity were related to long term cortisol exposure. These results are among the first to study associations between objectively measured sleep, physical activity and chronic cortisol levels among preschool children. More and larger studies are therefore needed.

Dataset Information

Associations Between the Built Environment and Objective Measures of Sleep: The Multi-Ethnic Study of Atherosclerosis.

Publications

Associations Between the Built Environment and Objective Measures of Sleep: The Multi-Ethnic Study of Atherosclerosis.

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