15132891
Assessing opportunities for physical activity in the built environment of children: interrelation between kernel density and neighborhood scale
Background Built environment studies provide broad evidence that urban characteristics influence physical activity (PA). However, findings are still difficult to compare, due to inconsistent measures assessing urban point characteristics and varying definitions of spatial scale. Both were found to influence the strength of the association between the built environment and PA.MethodsWe simultaneously evaluated the effect of kernel approaches and network-distances to investigate the association between urban characteristics and physical activity depending on spatial scale and intensity measure. We assessed urban measures of point characteristics such as intersections, public transit stations, and public open spaces in ego-centered network-dependent neighborhoods based on geographical data of one German study region of the IDEFICS study. We calculated point intensities using the simple intensity and kernel approaches based on fixed bandwidths, cross-validated bandwidths including isotropic and anisotropic kernel functions and considering adaptive bandwidths that adjust for residential density. We distinguished six network-distances from 500 m up to 2 km to calculate each intensity measure. A log-gamma regression model was used to investigate the effect of each urban measure on moderate-to-vigorous physical activity (MVPA) of 400 2- to 9.9-year old children who participated in the IDEFICS study. Models were stratified by sex and age groups, i.e. pre-school children (2 to $${<}6$$<6  years) and school children (6–9.9 years), and were adjusted for age, body mass index (BMI), education and safety concerns of parents, season and valid weartime of accelerometers.Results Association between intensity measures and MVPA strongly differed by network-distance, with stronger effects found for larger network-distances. Simple intensity revealed smaller effect estimates and smaller goodness-of-fit compared to kernel approaches. Smallest variation in effect estimates over network-distances was found for kernel intensity measures based on isotropic and anisotropic cross-validated bandwidth selection.Conclusion We found a strong variation in the association between the built environment and PA of children based on the choice of intensity measure and network-distance. Kernel intensity measures provided stable results over various scales and improved the assessment compared to the simple intensity measure. Considering different spatial scales and kernel intensity methods might reduce methodological limitations in assessing opportunities for PA in the built environment.
6688446
The influence of geographic life environments on cardiometabolic risk factors: a systematic review, a methodological assessment and a research agenda
Recent environmental changes play a role in the dramatic increase in the prevalence of cardiometabolic risk factors (CMRFs) such as obesity, hypertension, type 2 diabetes, dyslipidemias and the metabolic syndrome in industrialized countries. Therefore, identifying environmental characteristics that are associated with risk factors is critical to develop more effective public health interventions. We conducted a systematic review of the literature investigating relationships between characteristics of geographic life environments and CMRFs (131 articles). Most studies were published after 2006, relied on cross‐sectional designs, and examined whether sociodemographic and physical environmental characteristics, and more recently service environment characteristics, were associated with obesity or, to a lesser extent, hypertension. Only 14 longitudinal studies were retrieved; diabetes, dyslipidemias and the metabolic syndrome were rarely analysed; and aspects of social interactions in the neighbourhood were critically underinvestigated. Environmental characteristics that were consistently associated with either obesity or hypertension include low area socioeconomic position; low urbanization degree; low street intersection, service availability and residential density; high noise pollution; low accessibility to supermarkets and high density of convenience stores; and low social cohesion. Intermediate mechanisms between environmental characteristics and CMRFs have received little attention. We propose a research agenda based on the assessment of underinvestigated areas of research and methodological limitations of current literature.
1097400
In search of causality: a systematic review of the relationship between the built environment and physical activity among adults
BackgroundEmpirical evidence suggests that an association between the built environment and physical activity exists. This evidence is mostly derived from cross-sectional studies that do not account for other causal explanations such as neighborhood self-selection. Experimental and quasi-experimental designs can be used to isolate the effect of the built environment on physical activity, but in their absence, statistical techniques that adjust for neighborhood self-selection can be used with cross-sectional data. Previous reviews examining the built environment-physical activity relationship have not differentiated among findings based on study design. To deal with self-selection, we synthesized evidence regarding the relationship between objective measures of the built environment and physical activity by including in our review: 1) cross-sectional studies that adjust for neighborhood self-selection and 2) quasi-experiments.MethodIn September 2010, we searched for English-language studies on built environments and physical activity from all available years in health, leisure, transportation, social sciences, and geographical databases. Twenty cross-sectional and 13 quasi-experimental studies published between 1996 and 2010 were included in the review.ResultsMost associations between the built environment and physical activity were in the expected direction or null. Land use mix, connectivity and population density and overall neighborhood design were however, important determinants of physical activity. The built environment was more likely to be associated with transportation walking compared with other types of physical activity including recreational walking. Three studies found an attenuation in associations between built environment characteristics and physical activity after accounting for neighborhood self-selection.ConclusionMore quasi-experiments that examine a broader range of environmental attributes in relation to context-specific physical activity and that measure changes in the built environment, neighborhood preferences and their effect on physical activity are needed.
1951215
The built environment and obesity: a systematic review of the epidemiologic evidence.
We completed a systematic search of the epidemiologic literature on built environment and obesity and identified 63 relevant papers, which were then evaluated for the quality of between-study evidence. We were able to classify studies into one of two primary approaches for defining place and corresponding geographic areas of influence: those based on contextual effects derived from shared pre-determined administrative units and those based on individually unique geographic buffers. The 22 contextual papers evaluated 80 relations, 38 of which did not achieve statistical significance. The 15 buffer papers evaluated 40 relations, 24 of which did not achieve statistical significance. There was very little between-study similarity in methods in both types of approaches, which prevented estimation of pooled effects. The great heterogeneity across studies limits what can be learned from this body of evidence.
3884361
Measuring the built environment for physical activity: state of the science.
Physical inactivity is one of the most important public health issues in the U.S. and internationally. Increasingly, links are being identified between various elements of the physical-or built-environment and physical activity. To understand the impact of the built environment on physical activity, the development of high-quality measures is essential. Three categories of built environment data are being used: (1) perceived measures obtained by telephone interview or self-administered questionnaires; (2) observational measures obtained using systematic observational methods (audits); and (3) archival data sets that are often layered and analyzed with GIS. This review provides a critical assessment of these three types of built-environment measures relevant to the study of physical activity. Among perceived measures, 19 questionnaires were reviewed, ranging in length from 7 to 68 questions. Twenty audit tools were reviewed that cover community environments (i.e., neighborhoods, cities), parks, and trails. For GIS-derived measures, more than 50 studies were reviewed. A large degree of variability was found in the operationalization of common GIS measures, which include population density, land-use mix, access to recreational facilities, and street pattern. This first comprehensive examination of built-environment measures demonstrates considerable progress over the past decade, showing diverse environmental variables available that use multiple modes of assessment. Most can be considered first-generation measures, so further development is needed. In particular, further research is needed to improve the technical quality of measures, understand the relevance to various population groups, and understand the utility of measures for science and public health.
17972809
Neighborhoods and health
Features of neighborhoods or residential environments may affect health and contribute to social and race/ethnic inequalities in health. The study of neighborhood health effects has grown exponentially over the past 15 years. This chapter summarizes key work in this area with a particular focus on chronic disease outcomes (specifically obesity and related risk factors) and mental health (specifically depression and depressive symptoms). Empirical work is classified into two main eras: studies that use census proxies and studies that directly measure neighborhood attributes using a variety of approaches. Key conceptual and methodological challenges in studying neighborhood health effects are reviewed. Existing gaps in knowledge and promising new directions in the field are highlighted.
2383437
The development of a walkability index: application to the Neighborhood Quality of Life Study
Emerging evidence supports a link between neighbourhood built environment and physical activity. Systematic methodologies for characterising neighbourhood built environment are needed that take advantage of available population information such as census-level demographics. Based on transportation and urban planning literatures, an integrated index for operationalising walkability using parcel-level information is proposed. Validity of the walkability index is examined through travel surveys among areas examined in the Neighborhood Quality of Life Study (NQLS), a study investigating built environment correlates of adults' physical activity.
22167278
Neighborhood Walkability and Active Travel (Walking and Cycling) in New York City
Urban planners have suggested that built environment characteristics can support active travel (walking and cycling) and reduce sedentary behavior. This study assessed whether engagement in active travel is associated with neighborhood walkability measured for zip codes in New York City. Data were analyzed on engagement in active travel and the frequency of walking or biking ten blocks or more in the past month, from 8,064 respondents to the New York City 2003 Community Health Survey (CHS). A neighborhood walkability scale that measures: residential, intersection, and subway stop density; land use mix; and the ratio of retail building floor area to retail land area was calculated for each zip code. Data were analyzed using zero-inflated negative binomial regression incorporating survey sample weights and adjusting for respondents’ sociodemographic characteristics. Overall, 44 % of respondents reported no episodes of active travel and among those who reported any episode, the mean number was 43.2 episodes per month. Comparing the 75th to the 25th percentile of zip code walkability, the odds ratio for reporting zero episodes of active travel was 0.71 (95 % CI 0.61, 0.83) and the exponentiated beta coefficient for the count of episodes of active travel was 1.13 (95 % CI 1.06, 1.21). Associations between lower walkability and reporting zero episodes of active travel were significantly stronger for non-Hispanic Whites as compared to non-Hispanic Blacks and to Hispanics and for those living in higher income zip codes. The results suggest that neighborhood walkability is associated with higher engagement in active travel.
154721929
The ‘constant size neighbourhood trap’ in accessibility and health studies
In literature on neighbourhood effects and resources accessibility, the number of neighbourhood resources to which residents may have access are often estimated from spatial units whose constant size fails to account for unique ways residents experience their neighbourhoods. To investigate this ‘constant size neighbourhood trap’, we compared numbers of healthcare resources included in Constant Size Buffers (CSBs) and in Perceived Neighbourhood Polygons (PNPs) from cognitive neighbourhood data collected among 653 residents of the Paris metropolitan area. We observed that residents of deprived and peripheral areas had smaller PNPs than their counterparts. Studying residents assessments of the quantity of neighbourhood practitioners, we then assessed the validity of using PNPs rather than CSBs to estimate number of neighbourhood resources. Lastly, resource inequalities across the Paris metropolitan area were found to be far wider when considering PNPs rather than CSBs. Using constant neighbourhood delineation can lead to inaccurately measured individual accessibility to neighbourhood resources and to downplay the extent of inequalities in urban resources.
6319985
Effects of buffer size and shape on associations between the built environment and energy balance.
Uncertainty in the relevant spatial context may drive heterogeneity in findings on the built environment and energy balance. To estimate the effect of this uncertainty, we conducted a sensitivity analysis defining intersection and business densities and counts within different buffer sizes and shapes on associations with self-reported walking and body mass index. Linear regression results indicated that the scale and shape of buffers influenced study results and may partly explain the inconsistent findings in the built environment and energy balance literature.
205206590
The spatial dimensions of neighborhood effects.
In the decade or so of renewed interest in neighborhood contexts and health, significant progress has been made conceptualizing the relationships between the urban environment and public health. Applied research on the link between the environment and health remains limited by the way spatial concepts, such as "the neighborhood" or "the built environment" are operationalized. In this paper we argue that representations of these spatial concepts in statistical models should be based upon the individuals, the place, and the problem under study. Through a series of simulation experiments we describe the sensitivity of estimates of the association between neighborhoods and health to the operationalization of spatial concepts. We explore the practice of conducting the same analysis at multiple scales and find that using model fit to "discover" the spatial dimension is problematic. In sum, there is a gap between our understanding of how the environment influences health and spatial statistical modeling techniques. For quantitative spatial inquiry into the relationship between the neighborhood environment and health to be effective this gap must be closed.
1614021
The complexities of measuring access to parks and physical activity sites in New York City: a quantitative and qualitative approach
BackgroundProximity to parks and physical activity sites has been linked to an increase in active behaviors, and positive impacts on health outcomes such as lower rates of cardiovascular disease, diabetes, and obesity. Since populations with a low socio-economic status as well as racial and ethnic minorities tend to experience worse health outcomes in the USA, access to parks and physical activity sites may be an environmental justice issue. Geographic Information systems were used to conduct quantitative and qualitative analyses of park accessibility in New York City, which included kernel density estimation, ordinary least squares (global) regression, geographically weighted (local) regression, and longitudinal case studies, consisting of field work and archival research. Accessibility was measured by both density of park acreage and density of physical activity sites. Independent variables included percent non-Hispanic black, percent Hispanic, percent below poverty, percent of adults without high school diploma, percent with limited English-speaking ability, and population density.ResultsThe ordinary least squares linear regression found weak relationships in both the park acreage density and the physical activity site density models (Ra2 = .11 and .23, respectively; AIC = 7162 and 3529, respectively). Geographically weighted regression, however, suggested spatial non-stationarity in both models, indicating disparities in accessibility that vary over space with respect to magnitude and directionality of the relationships (AIC = 2014 and -1241, respectively). The qualitative analysis supported the findings of the local regression, confirming that although there is a geographically inequitable distribution of park space and physical activity sites, it is not globally predicted by race, ethnicity, or socio-economic status.ConclusionThe combination of quantitative and qualitative analyses demonstrated the complexity of the issues around racial and ethnic disparities in park access. They revealed trends that may not have been otherwise detectable, such as the spatially inconsistent relationship between physical activity site density and socio-demographics. In order to establish a more stable global model, a number of additional factors, variables, and methods might be used to quantify park accessibility, such as network analysis of proximity, perception of accessibility and usability, and additional park quality characteristics. Accurate measurement of park accessibility can therefore be important in showing the links between opportunities for active behavior and beneficial health outcomes.
35067737
Linking objectively measured physical activity with objectively measured urban form: findings from SMARTRAQ.
BACKGROUND
To date, nearly all research on physical activity and the built environment is based on self-reported physical activity and perceived assessment of the built environment.


OBJECTIVE
To assess how objectively measured levels of physical activity are related with objectively measured aspects of the physical environment around each participant's home while controlling for sociodemographic covariates.


METHODS
Objective measures of the built environment unique to each household's physical location were developed within a geographic information system to assess land-use mix, residential density, and street connectivity. These measures were then combined into a walkability index. Accelerometers were deployed over a 2-day period to capture objective levels of physical activity in 357 adults.


RESULTS
Measures of land-use mix, residential density, and intersection density were positively related with number of minutes of moderate physical activity per day. A combined walkability index of these urban form factors was significant (p =0.002) and explained additional variation in the number of minutes of moderate activity per day over sociodemographic covariates. Thirty-seven percent of individuals in the highest walkability index quartile met the > or =30 minutes of physical activity recommended, compared to only 18% of individuals in the lowest walkability quartile. Individuals in the highest walkability quartile were 2.4 times more likely (confidence interval=1.18-4.88) than individuals in the lowest walkability quartile to meet the recommended > or =30 minutes of moderate physical activity per day.


CONCLUSIONS
This research supports the hypothesis that community design is significantly associated with moderate levels of physical activity. These results support the rationale for the development of policy that promotes increased levels of land-use mix, street connectivity, and residential density as interventions that can have lasting public health benefits.
20708178
Neighborhood environment and physical activity among youth a review.
CONTEXT
Research examining the association between environmental attributes and physical activity among youth is growing. An updated review of literature is needed to summarize the current evidence base, and to inform policies and environmental interventions to promote active lifestyles among young people.


EVIDENCE ACQUISITION
A literature search was conducted using the Active Living Research (ALR) literature database, an online database that codes study characteristics and results of published papers on built/social environment and physical activity/obesity/sedentary behavior. Papers in the ALR database were identified through PubMed, Web of Science, and SPORTDiscus using systematically developed and expert-validated search protocols. For the current review, additional inclusion criteria were used to select observational, quantitative studies among youth aged 3-18 years.


EVIDENCE SYNTHESIS
Papers were categorized by design features, sample characteristics, and measurement mode. Relevant results were summarized, stratified by age (children or adolescents) and mode of measurement (objective or perceived) for environmental attributes and physical activity. Percentage of significant results was calculated.


CONCLUSIONS
Mode of measurement greatly influenced the consistency of associations between environmental attributes and youth physical activity. For both children and adolescents, the most consistent associations involved objectively measured environmental attributes and reported physical activity. The most supported correlates for children were walkability, traffic speed/volume, access/proximity to recreation facilities, land-use mix, and residential density. The most supported correlates for adolescents were land-use mix and residential density. These findings support several recommendations for policy and environmental change from such groups as the IOM and National Physical Activity Plan.
7500841
Development and application of a moveability index to quantify possibilities for physical activity in the built environment of children.
Several studies show that urban forms are environmental correlates of physical activity. Most of these studies used data based on questionnaires while only a few used geographic information systems (GIS) to objectively assess urban forms. Based on GIS data, we applied a kernel density method to measure urban forms and combined these measures to a moveability index to assess the opportunities for physical activity in the German intervention region of the IDEFICS study. In this proof-of-principal analysis, we linked the moveability index with physical activity data obtained from the baseline survey of the IDEFICS study. Regression analyses revealed a modest but significant impact of the built environment on the physical activity of 596 school children in the study region, supporting the potential application of the moveability index.
118582840
Statistical Analysis of Spatial and Spatio-Temporal Point Patterns
Introduction Spatial point patterns Sampling Edge-effects Complete spatial randomness Objectives of statistical analysis The Dirichlet tessellation Monte Carlo tests Software Preliminary Testing Tests of complete spatial randomness Inter-event distances Nearest neighbor distances Point to nearest event distances Quadrat counts Scales of pattern Recommendations Methods for Sparsely Sampled Patterns General remarks Quadrat counts Distance measurements Tests of independence Recommendations Spatial Point Processes Processes and summary descriptions Second-order properties Higher order moments and nearest neighbor distributions The homogeneous Poisson process Independence and random labeling Estimation of second-order properties Displaced amacrine cells in the retina of a rabbit Estimation of nearest neighbor distributions Concluding remarks Nonparametric Methods Estimating weighted integrals of the second-order intensity Nonparametric estimation of a spatially varying intensity Analyzing replicated spatial point patterns Parametric or nonparametric methods? Models Contagious distributions Poisson cluster processes Inhomogeneous Poisson processes Cox processes Trans-Gaussian Cox processes Simple inhibition processes Markov point processes Other constructions Multivariate models Model-Fitting Using Summary Descriptions Parameter estimation using the K-function Goodness-of-fit assessment using nearest neighbor distributions Examples Parameter estimation via goodness-of-fit testing Model-Fitting Using Likelihood-Based Methods Likelihood inference for inhomogeneous Poisson processes Likelihood inference for Markov point processes Likelihood inference for Cox processes Additional reading Point Process Methods in Spatial Epidemiology Spatial clustering Spatial variation in risk Point source models Stratification and matching Disentangling heterogeneity and clustering Spatio-Temporal Point Processes Motivating examples A classification of spatio-temporal point patterns and processes Second-order properties Conditioning on the past Empirical and mechanistic models Exploratory Analysis Animation Marginal and conditional summaries Second-order properties Empirical Models and Methods Poisson processes Cox processes Log-Gaussian Cox processes Inference Gastro-intestinal illness in Hampshire, UK Concluding remarks: point processes and geostatistics Mechanistic Models and Methods Conditional intensity and likelihood Partial likelihood The 2001 foot-and-mouth epidemic in Cumbria, UK Nesting patterns of Arctic terns References
28545171
Objective Measures of the Built Environment and Physical Activity in Children: From Walkability to Moveability
Features of the built environment that may influence physical activity (PA) levels are commonly captured using a so-called walkability index. Since such indices typically describe opportunities for walking in everyday life of adults, they might not be applicable to assess urban opportunities for PA in children. Particularly, the spatial availability of recreational facilities may have an impact on PA in children and should be additionally considered. We linked individual data of 400 2- to 9-year-old children recruited in the European IDEFICS study to geographic data of one German study region, based on individual network-dependent neighborhoods. Environmental features of the walkability concept and the availability of recreational facilities, i.e. playgrounds, green spaces, and parks, were measured. Relevant features were combined to a moveability index that should capture urban opportunities for PA in children. A gamma log-regression model was used to model linear and non-linear effects of individual variables on accelerometer-based moderate-to-vigorous physical activity (MVPA) stratified by pre-school children (<6 years) and school children (≥6 years). Single environmental features and the resulting indices were separately included into the model to investigate the effect of each variable on MVPA. In school children, commonly used features such as residential density β^=0.5⋅10−4,p=0.02$$ \left(\widehat{\beta}=0.5\cdot {10}^{-4},p=0.02\right) $$, intersection density β^=0.003,p=0.04$$ \left(\widehat{\beta}=0.003,p=0.04\right) $$, and public transit density β^=0.037,p=0.01$$ \left(\widehat{\beta}=0.037,p=0.01\right) $$ showed a positive effect on MVPA, while land use mix revealed a negative effect on MVPA β^=−0.173,p=0.13$$ \left(\widehat{\beta}=-0.173,p=0.13\right) $$. In particular, playground density β^=0.048,p=0.01$$ \left(\widehat{\beta}=0.048,p=0.01\right) $$ and density of public open spaces, i.e., playgrounds and parks combined β^=0.040,p=0.01$$ \left(\widehat{\beta}=0.040,p=0.01\right) $$, showed positive effects on MVPA. However, availability of green spaces showed no effect on MVPA. Different moveability indices were constructed based on the walkability index accounting for the negative impact of land use mix. Moveability indices showed also strong effects on MVPA in school children for both components, expanded by playground density β^=0.014,p=0.008$$ \left(\widehat{\beta}=0.014,p=0.008\right) $$ or by public open space density β^=0.014,p=0.007$$ \left(\widehat{\beta}=0.014,p=0.007\right) $$, but no effects of urban measures and moveability indices were found in pre-school children. The final moveability indices capture relevant opportunities for PA in school children. Particularly, availability of public open spaces seems to be a strong predictor of MVPA. Future studies involving children should consider quantitative assessment of public recreational facilities in larger cities or urban sprawls in order to investigate the influence of the moveability on childhood PA in a broader sample.
12652579
Modern statistics for spatial point processes ∗ April 1 , 2006
We summarize and discuss the current state of spatial point process theory and directions for future research, making an analogy with generalized linear models and random effect models, and illustrating the theory with various examples of applications. In particular, we consider Poisson, Gibbs, and Cox process models, diagnostic tools and model checking, Markov chain Monte Carlo algorithms, computational methods for likelihood-based inference, and quick non-likelihood approaches to inference.
7964971
Density estimation and adaptive bandwidths: A primer for public health practitioners
BackgroundGeographic information systems have advanced the ability to both visualize and analyze point data. While point-based maps can be aggregated to differing areal units and examined at varying resolutions, two problems arise 1) the modifiable areal unit problem and 2) any corresponding data must be available both at the scale of analysis and in the same geographic units. Kernel density estimation (KDE) produces a smooth, continuous surface where each location in the study area is assigned a density value irrespective of arbitrary administrative boundaries. We review KDE, and introduce the technique of utilizing an adaptive bandwidth to address the underlying heterogeneous population distributions common in public health research.ResultsThe density of occurrences should not be interpreted without knowledge of the underlying population distribution. When the effect of the background population is successfully accounted for, differences in point patterns in similar population areas are more discernible; it is generally these variations that are of most interest. A static bandwidth KDE does not distinguish the spatial extents of interesting areas, nor does it expose patterns above and beyond those due to geographic variations in the density of the underlying population. An adaptive bandwidth method uses background population data to calculate a kernel of varying size for each individual case. This limits the influence of a single case to a small spatial extent where the population density is high as the bandwidth is small. If the primary concern is distance, a static bandwidth is preferable because it may be better to define the "neighborhood" or exposure risk based on distance. If the primary concern is differences in exposure across the population, a bandwidth adapting to the population is preferred.ConclusionsKernel density estimation is a useful way to consider exposure at any point within a spatial frame, irrespective of administrative boundaries. Utilization of an adaptive bandwidth may be particularly useful in comparing two similarly populated areas when studying health disparities or other issues comparing populations in public health.
33197885
Selection of bandwidth type and adjustment side in kernel density estimation over inhomogeneous backgrounds
This article identifies and compares four different methods for dealing with inhomogeneous backgrounds in kernel density estimation. The four methods result from combinations of two bandwidth types (fixed vs. adaptive) and two adjustment sides (site side vs. case side). The fixed and adaptive bandwidths employ different uniform bases in density calculation (spatial extent vs. population support). The adaptive bandwidth's strength lies in identifying spatial extents of density variation. It also produces values that are more comparable between locations and more stable statistically. When making adjustments to address the background, the site-side method makes the adjustment at each site for which the density value is to be estimated, and the case-side method makes the adjustment at each case location. Within a disease-mapping context, the former measures population at risk around each site and the latter measures around each disease case. The case-side adjustment is more justifiable in an application like disease mapping. It is also less sensitive to spatial details of the background (a favorable feature) and considerably more computationally efficient. Lung cancer data from Merrimack County, New Hampshire, USA, are used to demonstrate and compare the results from the four methods, leading to the conclusion that the case-side-adaptive-bandwidth method is most advantageous.
10169205
Objectively measured physical activity in European children: the IDEFICS study
Objectives:To provide sex- and age-specific percentile values for levels of physical activity (PA) and sedentary time of European children aged 2.0–10.9 years from eight European countries (Sweden, Germany, Hungary, Italy, Cyprus, Spain, Belgium and Estonia).Methods:Free-living PA and sedentary time were objectively assessed using ActiGraph GT1M or ActiTrainer activity monitors in all children who had at least 3 days' worth of valid accelerometer data, with at least 8 h of valid recording time each day. The General Additive Model for Location Scale and Shape was used for calculating percentile curves.Results:Reference values for PA and sedentary time in the European children according to sex and age are displayed using smoothed percentile curves for 7684 children (3842 boys and 3842 girls). The figures show similar trends in boys and girls. The percentage of children complying with recommendations regarding moderate-to-vigorous physical activity (MVPA) is also presented and varied considerably between sexes and country. For example, the percentage of study participants who were physically active (as assessed by MVPA) for 60 or more minutes per day ranged from 2.0% (Cyprus) to 14.7% (Sweden) in girls and from 9.5% (Italy) to 34.1% (Belgium) in boys.Conclusion:This study provides the most up-to-date sex- and age-specific reference data on PA in young children in Europe. The percentage compliance to MVPA recommendations for these European children varied considerably between sexes and country and was generally low. These results may have important implications for public health policy and PA counselling.
6872665
Extended international (IOTF) body mass index cut‐offs for thinness, overweight and obesity
The international (International Obesity Task Force; IOTF) body mass index (BMI) cut‐offs are widely used to assess the prevalence of child overweight, obesity and thinness. Based on data from six countries fitted by the LMS method, they link BMI values at 18 years (16, 17, 18.5, 25 and 30 kg m−2) to child centiles, which are averaged across the countries. Unlike other BMI references, e.g. the World Health Organization (WHO) standard, these cut‐offs cannot be expressed as centiles (e.g. 85th).
156341230
The International Standard Classification of Education 2011
The International Standard Classification of Education (ISCED) is a tool for harmonising education-related information. It covers almost all countries in the world and is centrally maintained and documented by UNESCO Institute for Statistics. ISCED is commonly used in official statistics and surveys (e.g. by OECD and Eurostat), but it is also increasingly used for the measurement of educational attainment in academic cross-national surveys. ISCED has been revised between 2008 and 2011, and the new version was adopted by the UNESCO General Conference in November 2011. This research note describes ISCED 2011 and the most important changes as compared to the previous version, ISCED 1997, with a special focus on educational attainment. A brief discussion of strengths and weaknesses of the classification as well as future challenges conclude the note.
15863916
spatstat: An R Package for Analyzing Spatial Point Patterns
spatstat is a package for analyzing spatial point pattern data. Its functionality includes exploratory data analysis, model-fitting, and simulation. It is designed to handle realistic datasets, including inhomogeneous point patterns, spatial sampling regions of arbitrary shape, extra covariate data, and "marks" attached to the points of the point pattern. A unique feature of spatstat is its generic algorithm for fitting point process models to point pattern data. The interface to this algorithm is a function ppm that is strongly analogous to lm and glm. This paper is a general description of spatstat and an introduction for new users.
67073029
Density Estimation for Statistics and Data Analysis.
Suppose, now, that we have a set of observed data points assumed to be a sample from an unknown probability density function. Density estimation, as discussed in this book, is the construction of an estimate of the density function from the observed data. The two main aims of the book are to explain how to estimate a density from a given data set and to explore how density estimates can be used, both in their own right and as an ingredient of other statistical procedures.
122318576
Geostatistics: Modeling Spatial Uncertainty
Preliminaries. Structural Analysis. Kriging. Intrinsic Model of Order k. Multivariate Methods. Nonlinear Methods. Conditional Simulations. Scale Effects and Inverse Problems. Appendix. References. Index.
120367913
An alternative method of cross-validation for the smoothing of density estimates
Cross-validation with Kullback-Leibler loss function has been applied to the choice of a smoothing parameter in the kernel method of density estimation. A framework for this problem is constructed and used to derive an alternative method of cross-validation, based on integrated squared error, recently also proposed by Rudemo (1982). Hall (1983) has established the consistency and asymptotic optimality of the new method. For small and moderate sized samples, the performances of the two methods of cross-validation are compared on simulated data and specific examples.
3584495
Examination of how neighborhood definition influences measurements of youths' access to tobacco retailers: a methodological note on spatial misclassification.
Measurements of neighborhood exposures likely vary depending on the definition of "neighborhood" selected. This study examined the extent to which neighborhood definition influences findings regarding spatial accessibility to tobacco retailers among youth. We defined spatial accessibility to tobacco retailers (i.e., tobacco retail density, closest tobacco retailer, and average distance to the closest 5 tobacco retailers) on the basis of circular and network buffers of 400 m and 800 m, census block groups, and census tracts by using residential addresses from the 2008 Boston Youth Survey Geospatial Dataset (n = 1,292). Friedman tests (to compare overall differences in neighborhood definitions) were applied. There were differences in measurements of youths' access to tobacco retailers according to the selected neighborhood definitions, and these were marked for the 2 spatial proximity measures (both P < 0.01 for all differences). For example, the median average distance to the closest 5 tobacco retailers was 381.50 m when using specific home addresses, 414.00 m when using census block groups, and 482.50 m when using census tracts, illustrating how neighborhood definition influences the measurement of spatial accessibility to tobacco retailers. These analyses suggest that, whenever possible, egocentric neighborhood definitions should be used. The use of larger administrative neighborhood definitions can bias exposure estimates for proximity measures.
31779435
A Framework for Using GPS Data in Physical Activity and Sedentary Behavior Studies
Global Positioning Systems (GPS) are applied increasingly in activity studies, yet significant theoretical and methodological challenges remain. This article presents a framework for integrating GPS data with other technologies to create dynamic representations of behaviors in context. Using more accurate and sensitive measures to link behavior and environmental exposures allows for new research questions and methods to be developed.
22788313
When cities move children: development of a new methodology to assess context-specific physical activity behaviour among children and adolescents using accelerometers and GPS.
This study presents a novel method to assess context-specific physical activity patterns using accelerometer and GPS. The method efficiency is investigated by providing descriptive results on the use of domains and subdomains, and assessing how much of children's and adolescents' daily activity time can be classified by these domains and subdomains. Four domains and 11 subdomains were defined as important contexts for child and adolescent behaviour. During weekdays (n=367) and weekend days (n=178) the majority of children and adolescents spent time in active transport, urban green space, clubs and sports facilities. Satisfactory method efficiency was found during weekdays. Natural experiments combined with objective assessment of context-specific behaviours hold the potential to create evidence on the effects of changes to the built environment on behaviour.
38624951
Home versus nonhome neighborhood: quantifying differences in exposure to the built environment.
BACKGROUND
Built environment and health research have focused on characteristics of home neighborhoods, whereas overall environmental exposures occur over larger spatial ranges.


PURPOSE
Differences in built environment characteristics were analyzed for home and nonhome locations using GPS data.


METHODS
GPS data collected in 2007-2008 were analyzed for 41 subjects in the Seattle area in 2010. Environmental characteristics for 3.8 million locations were measured using novel GIS data sets called SmartMaps, representing spatially continuous values of local built environment variables in the domains of neighborhood composition, utilitarian destinations, transportation infrastructure, and traffic conditions. Using bootstrap sampling, CIs were estimated for differences in built environment values for home (<833 m of home address) and nonhome (>1666 m) GPS locations.


RESULTS
Home and nonhome built environment values were significantly different for more than 90% of variables across subjects (p<0.001). Only 51% of subjects had higher counts of supermarkets near than away from home. Different measures of neighborhood parks yielded varying results.


CONCLUSIONS
SmartMaps helped measure local built environment characteristics for a large set of GPS locations. Most subjects had significantly different home and nonhome built environment exposures. Considering the full range of individuals' environmental exposures may improve understanding of effects of the built environment on behavior and health outcomes.
24889107
Association between neighborhood walkability and GPS-measured walking, bicycling and vehicle time in adolescents.
OBJECTIVES
To investigate relations of walking, bicycling and vehicle time to neighborhood walkability and total physical activity in youth.


METHODS
Participants (N=690) were from 380 census block groups of high/low walkability and income in two US regions. Home neighborhood residential density, intersection density, retail density, entertainment density and walkability were derived using GIS. Minutes/day of walking, bicycling and vehicle time were derived from processing algorithms applied to GPS. Accelerometers estimated total daily moderate-to-vigorous physical activity (MVPA). Models were adjusted for nesting of days (N=2987) within participants within block groups.


RESULTS
Walking occurred on 33%, active travel on 43%, and vehicle time on 91% of the days observed. Intersection density and neighborhood walkability were positively related to walking and bicycling and negatively related to vehicle time. Residential density was positively related to walking.


CONCLUSIONS
Increasing walking in youth could be effective in increasing total physical activity. Built environment findings suggest potential for increasing walking in youth through improving neighborhood walkability.
27749509
Conceptualization and measurement of environmental exposure in epidemiology: accounting for activity space related to daily mobility.
A considerable body of literature has investigated how environmental exposures affect health through various pathways. These studies have generally adopted a common approach to define environmental exposures, focusing on the local residential environment, using census tracts or postcodes to delimit exposures. However, use of such administrative units may not be appropriate to evaluate contextual effets on health because they are generally not a 'true' representation of the environments to which individuals are exposed. Recent work has suggested that advances may be made if an activity-space approach is adopted. The present paper investigates how various disciplines may contribute to the refinement of the concept of activity space for use in health research. In particular we draw on seminal work in time geography, which provides a framework to describe individual behavior in space and time, and can help the conceptualization of activity space. In addition we review work in environmental psychology and social networks research, which provides insights on how people and places interact and offers new theories for improving the spatial definition of contextual exposures.
14366540
Emerging Technologies for Assessing Physical Activity Behaviors in Space and Time
Precise measurement of physical activity is important for health research, providing a better understanding of activity location, type, duration, and intensity. This article describes a novel suite of tools to measure and analyze physical activity behaviors in spatial epidemiology research. We use individual-level, high-resolution, objective data collected in a space-time framework to investigate built and social environment influences on activity. First, we collect data with accelerometers, global positioning system units, and smartphone-based digital travel and photo diaries to overcome many limitations inherent in self-reported data. Behaviors are measured continuously over the full spectrum of environmental exposures in daily life, instead of focusing exclusively on the home neighborhood. Second, data streams are integrated using common timestamps into a single data structure, the “LifeLog.” A graphic interface tool, “LifeLog View,” enables simultaneous visualization of all LifeLog data streams. Finally, we use geographic information system SmartMap rasters to measure spatially continuous environmental variables to capture exposures at the same spatial and temporal scale as in the LifeLog. These technologies enable precise measurement of behaviors in their spatial and temporal settings but also generate very large datasets; we discuss current limitations and promising methods for processing and analyzing such large datasets. Finally, we provide applications of these methods in spatially oriented research, including a natural experiment to evaluate the effects of new transportation infrastructure on activity levels, and a study of neighborhood environmental effects on activity using twins as quasi-causal controls to overcome self-selection and reverse causation problems. In summary, the integrative characteristics of large datasets contained in LifeLogs and SmartMaps hold great promise for advancing spatial epidemiologic research to promote healthy behaviors.
43798538
Variations in active transport behavior among different neighborhoods and across adult lifestages.
OBJECTIVE
Built environment characteristics are closely related to transport behavior, but observed variations could be due to residents own choice of neighborhood called residential self-selection. The aim of this study was to investigate differences in neighborhood walkability and residential self-selection across life stages in relation to active transport behavior.


METHODS
The IPEN walkability index, which consists of four built environment characteristics, was used to define 16 high and low walkable neighborhoods in Aarhus, Denmark (250.000 inhabitants). Transport behavior was assessed using the IPAQ questionnaire. Life stages were categorized in three groups according to age and parental status. A factor analysis was conducted to investigate patterns of self-selection. Multivariable logistic regression analyses were carried out to evaluate the association between walkability and transport behavior i.e. walking, cycling and motorized transport adjusted for residential self-selection and life stages.


RESULTS
A total of 642 adults aged 20-65 years completed the questionnaire. The highest rated self-selection preference across all groups was a safe and secure neighborhood followed by getting around easily on foot and by bicycle. Three self-selection factors were detected, and varied across the life stages. In the multivariable models high neighborhood walkability was associated with less motorized transport (OR 0.33 95%CI 0.18-0.58), more walking (OR 1.65 95%CI 1.03-2.65) and cycling (OR 1.50 95% CI 1.01-2.23). Self-selection and life stage were also associated with transport behavior, and attenuated the association with walkability.


CONCLUSION
This study supports the hypothesis that some variation in transport behavior can be explained by life stages and self-selection, but the association between living in a more walkable neighborhood and active transport is still significant after adjusting for these factors. Life stage significantly moderated the association between neighborhood walkability and cycling for transport, and household income significantly moderated the association between neighborhood walkability and walking for transport. Getting around easily by bicycle and on foot was the highest rated self-selection factor second only to perceived neighborhood safety.
7194713
Patterns of neighborhood environment attributes related to physical activity across 11 countries: a latent class analysis
BackgroundNeighborhood environment studies of physical activity (PA) have been mainly single-country focused. The International Prevalence Study (IPS) presented a rare opportunity to examine neighborhood features across countries. The purpose of this analysis was to: 1) detect international neighborhood typologies based on participants’ response patterns to an environment survey and 2) to estimate associations between neighborhood environment patterns and PA.MethodsA Latent Class Analysis (LCA) was conducted on pooled IPS adults (N=11,541) aged 18 to 64 years old (mean=37.5 ±12.8 yrs; 55.6% women) from 11 countries including Belgium, Brazil, Canada, Colombia, Hong Kong, Japan, Lithuania, New Zealand, Norway, Sweden, and the U.S. This subset used the Physical Activity Neighborhood Environment Survey (PANES) that briefly assessed 7 attributes within 10–15 minutes walk of participants’ residences, including residential density, access to shops/services, recreational facilities, public transit facilities, presence of sidewalks and bike paths, and personal safety. LCA derived meaningful subgroups from participants’ response patterns to PANES items, and participants were assigned to neighborhood types. The validated short-form International Physical Activity Questionnaire (IPAQ) measured likelihood of meeting the 150 minutes/week PA guideline. To validate derived classes, meeting the guideline either by walking or total PA was regressed on neighborhood types using a weighted generalized linear regression model, adjusting for gender, age and country.ResultsA 5-subgroup solution fitted the dataset and was interpretable. Neighborhood types were labeled, “Overall Activity Supportive (52% of sample)”, “High Walkable and Unsafe with Few Recreation Facilities (16%)”, “Safe with Active Transport Facilities (12%)”, “Transit and Shops Dense with Few Amenities (15%)”, and “Safe but Activity Unsupportive (5%)”. Country representation differed by type (e.g., U.S. disproportionally represented “Safe but Activity Unsupportive”). Compared to the Safe but Activity Unsupportive, two types showed greater odds of meeting PA guideline for walking outcome (High Walkable and Unsafe with Few Recreation Facilities, OR= 2.26 (95% CI 1.18-4.31); Overall Activity Supportive, OR= 1.90 (95% CI 1.13-3.21). Significant but smaller odds ratios were also found for total PA.ConclusionsMeaningful neighborhood patterns generalized across countries and explained practical differences in PA. These observational results support WHO/UN recommendations for programs and policies targeted to improve features of the neighborhood environment for PA.