Does the built environment influence location- and trip-based sedentary behaviors? Evidence from a GPS-based activity space approach of neighborhood effects on older adults.

OBJECTIVE: Evidence on the influence of built environments on sedentary behaviors remains unclear and is often contradictory. The main limitations encompass the use of self-reported proxies of sedentary time (ST), the scarce consideration of the plurality of sedentary behaviors, and environmental exposures limited to the residential neighborhood. We investigated the relationships between GPS-based activity space measures of environmental exposures and accelerometer-based ST measured in total, at the place of residence, at all locations, and during trips. METHODS: This study is part of the CURHA project, based on 471 older adults residing in Luxembourg, who wore a GPS receiver and a tri-axial accelerometer during 7 days. Daily ST was computed in total, at the residence, at all locations and during trips. Environmental exposures included exposure to green spaces, walking, biking, and motorized transportation infrastructures. Associations between environments and ST were examined using linear and negative binomial mixed models, adjusted for demographics, self-rated health, residential self-selection, weather conditions and wear time. RESULTS: Participants accumulated, on average, 8 h and 14 min of ST per day excluding sleep time. ST spent at locations accounted for 83 % of the total ST. ST spent at the residence accounted for 87 % of the location-based ST and 71 % of the total ST. Trip-based ST represents 13 % of total ST, and 4 % remained unclassified. Higher street connectivity was negatively associated with total ST, while the density of parking areas correlated positively with total and location-based ST. Stronger associations were observed for sedentary bouts (uninterrupted ST over 20 and 30 min). CONCLUSION: Improving street connectivity and controlling the construction of new parking, while avoiding the spatial segregation of populations with limited access to public transport, may contribute to limit ST. Such urban planning interventions may be especially efficient in limiting the harmful uninterrupted bouts of ST among older adults.

Physical activity and sedentary behaviour related to transport activity assessed with multiple body-worn accelerometers: the RECORD MultiSensor Study.

OBJECTIVES: The study explored the physical activity and sedentary behaviours related to transport activity. The aim was to provide evidence to support public health and transport policies encouraging people to reach daily recommendations of physical activity. STUDY DESIGN: The study design of this study is a cross-sectional study design. METHODS: Between 2013 and 2015, the RECORD MultiSensor Study collected data from 155 participants using two accelerometers worn on the thigh and trunk. In addition, data were collected from Global Positioning System (GPS) receivers and a GPS-based mobility survey. Relationships between transport modes and the durations and partition patterns of physical behaviours were established at the trip stage (n = 7692) and trip levels (n = 4683) using multilevel linear models with a random effect at the individual level and taking into account temporal autocorrelation. RESULTS: Participants travelled for a median of 1 h 45 min per day. Trip stages and trips involving walking, other active modes or public transport were associated with a lower sitting duration and a higher moderate-to-vigorous physical activity (MVPA) duration than trips with a personal motorised vehicle. Using public transport was associated with a lower number of transitions between sedentary behaviours and non-sedentary behaviours, and with a higher number of transitions between non-sedentary behaviours and MVPA than relying on a private motorised vehicle. CONCLUSIONS: This study is the first to assess the association of transport mode with physical activity and sedentary behaviours captured with thigh- and trunk-worn accelerometers at both the trip stage and trip levels. The results demonstrate that, in addition to active transport modes, encouraging people to use public transport increases physical activity and reduces sedentary time.

Food environment and socioeconomic status influence obesity rates in Seattle and in Paris.

OBJECTIVE: To compare the associations between food environment at the individual level, socioeconomic status (SES) and obesity rates in two cities: Seattle and Paris. METHODS: Analyses of the SOS (Seattle Obesity Study) were based on a representative sample of 1340 adults in metropolitan Seattle and King County. The RECORD (Residential Environment and Coronary Heart Disease) cohort analyses were based on 7131 adults in central Paris and suburbs. Data on sociodemographics, health and weight were obtained from a telephone survey (SOS) and from in-person interviews (RECORD). Both studies collected data on and geocoded home addresses and food shopping locations. Both studies calculated GIS (Geographic Information System) network distances between home and the supermarket that study respondents listed as their primary food source. Supermarkets were further stratified into three categories by price. Modified Poisson regression models were used to test the associations among food environment variables, SES and obesity. RESULTS: Physical distance to supermarkets was unrelated to obesity risk. By contrast, lower education and incomes, lower surrounding property values and shopping at lower-cost stores were consistently associated with higher obesity risk. CONCLUSION: Lower SES was linked to higher obesity risk in both Paris and Seattle, despite differences in urban form, the food environments and in the respective systems of health care. Cross-country comparisons can provide new insights into the social determinants of weight and health.

Neighborhood environments, mobility, and health: towards a new generation of studies in environmental health research.

While public policies seek to promote active transportation, there is a lack of information on the social and environmental factors associated with the adoption of active transportation modes. Moreover, despite the consensus on the importance of identifying obesogenic environmental factors, most published studies only take into account residential neighborhoods in the definition of exposures. There are at least three major reasons for incorporating daily mobility in public health research: (i) to identify specific population groups, including socially disadvantaged populations, who experience mobility or spatial accessibility deficits; (ii) to study the environmental determinants of transportation habits and investigate the complex relationships between transportation (as a source of physical activity, pollutants, and accidents) and physical activity and health; and (iii) to improve the assessment of spatial accessibility to resources and exposure to environmental hazards by accounting for daily trajectories for a better understanding of their health effects. There is urgent need to develop novel methods to better assess daily mobility. The RECORD Study relies on (i) an electronic survey of regular mobility to assess the chronic exposure to environmental conditions over a relatively long period, and (ii) Global Positioning System tracking to evaluate precisely acute environmental exposures over a much shorter period. The present article argues that future research should combine these two approaches. Gathering scientific evidence on the relationships between the environments, mobility/transportation, and health should allow public health and urban planning decision makers to better take into account the individual and environmental barriers to the adoption of active transportation and to define innovative intervention strategies addressing obesogenic environments to reduce disparities in excess weight.

Spatial accessibility to physical activity facilities and to food outlets and overweight in French youth.

OBJECTIVE: Some characteristics of the built environment have been associated with obesity in youth. Our aim was to determine whether individual and environmental socio-economic characteristics modulate the relation between youth overweight and spatial accessibility to physical activity (PA) facilities and to food outlets. DESIGN: Cross-sectional study. SUBJECTS: 3293 students, aged 12 ± 0.6 years, randomly selected from eastern France middle schools. MEASUREMENTS AND METHODS: Using geographical information systems (GIS), spatial accessibility to PA facilities (urban and nature) was assessed using the distance to PA facilities at the municipality level; spatial accessibility to food outlets (general food outlets, bakeries and fast-food outlets) was calculated at individual level using the student home address and the food outlets addresses. Relations of weight status with spatial accessibility to PA facilities and to food outlets were analysed using mixed logistic models, testing potential direct and interaction effects of individual and environmental socio-economic characteristics. RESULTS: Individual socio-economic status modulated the relation between spatial accessibility to PA facilities and to general food outlets and overweight. The likelihood of being overweight was higher when spatial accessibility to urban PA facilities and to general food outlets was low, but in children of blue-collar-workers only. The odds ratio (OR) (95% confidence interval) for being overweight of blue-collar-workers children compared with non-blue-collar-workers children was 1.76 (1.25-2.49) when spatial accessibility to urban PA facilities was low. This OR was 1.86 (1.20-2.86) when spatial accessibility to general food outlets was low. There was no significant relationship of overweight with either nature PA facilities or other food outlets (bakeries and fast-food outlets). CONCLUSION: These results indicate that disparities in spatial accessibility to PA facilities and to general food outlets may amplify the risk of overweight in socio-economically disadvantaged youth. These data should be relevant for influencing health policies and urban planning at both a national and local level.

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.

Leisure-time physical activity and sedentary behavior clusters and their associations with overweight in middle-aged French adults.

OBJECTIVE: To identify leisure-time physical activity (LTPA) and sedentary behavior patterns, as well as to investigate their relationships with overweight. DESIGN: Cross-sectional study. SUBJECTS: Men (n=2206) and women (n=2476) aged >45 years, living in France, enrolled in the SU.VI.MAX (Supplémentation en VItamines et Minéraux AntioXydants) study. MEASUREMENTS: LTPA and sedentary behavior were assessed using the Modifiable Activity Questionnaire whereas weight and height were measured from study participants. Clusters were defined, by gender, with multiple correspondence analysis and cluster analysis successively, taking into account the type (walking, gardening, etc.) and duration of each physical activity performed, as well as the time spent watching television (TV) as typical sedentary behavior. Logistic regression models were used to assess associations with overweight. RESULTS: Four physical activity and sedentary behavior clusters were identified among men and three among women. We chose as referent cluster the cluster associating 'walking and gardening-low TV' in men and the cluster associating 'walking and gardening-high TV' in women. Compared with the referent cluster and after adjustment for age, education level, smoking status and place of residence, the likelihood of overweight (defined as body mass index >or=25 kg m(-2)) in women was lower for a 'multiple activity-low TV' cluster (odds ratio (OR)=0.66, 95% confidence interval=0.54-0.81) and for a cluster associating 'endurance physical activity-low TV' (OR=0.42 (0.29-0.60)). Compared with the referent cluster and after adjustment, the likelihood of overweight in men was decreased for the 'endurance physical activity' cluster (OR=0.66, (0.52-0.84)), whereas no significant association was found with the other clusters. CONCLUSIONS: Patterns combining specific types of physical activity and sedentary behavior were identified and differed in their relations to overweight in adults. The identification of global patterns of activity allows us to go beyond a simple decreased activity-increased body weight approach and adds to our understanding of the associations of specific forms and grouping of activity with overweight in adults.

Context and disease when disease risk is low: the case of type 1 diabetes in Sweden.

BACKGROUND: Several European studies have found significant small area variation in the risk of childhood onset (type 1) diabetes (T1D) which has been interpreted as evidence for contextual determinants of T1D. However, this conclusion may be fallacious since the limited number of newborn infants and the low risk for T1D is a source of spurious variability not properly handled by usual statistical methods. This study investigates the existence of contextual effects in the genesis of T1D, compares conclusions in previous reports with results obtained in a multilevel regression framework and highlights analysis of variance as a useful approach in public health. METHODS: All singletons born in Sweden between 1987 and 1991 were identified in the Medical Birth Registry (n=560 766) and followed for diabetes until age 14 using the Hospital Discharge Registry. Area variation in the cumulative incidence of T1D was estimated by different statistical methods including multilevel logistic regression. RESULTS: The risk of T1D ranged from 4.3 to 6.5 per 1000 newborns across the counties (n=24) and from 0.0 to 19.2 per 1000 newborns across the municipalities (n=284). These differences were significant in standard statistical tests (counties, p=0.02; municipalities, p=0.007). However, according to multilevel analyses, the risk of T1D ranged from 4.7 to 5.7 and from 4.4 to 6.0 per 1000 newborns in counties and municipalities, respectively, and the area variation was small and without practical relevance (counties, sigma(2)=0.006; municipalities, sigma(2)=0.017). CONCLUSIONS: Previous reports based on standard statistical tests are misleading. According to multilevel analysis, administrative areas have minor relevance for individual risk of T1D in Sweden.

Individual and collective bodies: using measures of variance and association in contextual epidemiology.

BACKGROUND: Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body's geographical or cultural limits (eg "neighbourhood") are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). METHODS: Critical essay and literature review. RESULTS: The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). CONCLUSIONS: Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.

Neighbourhood social interactions and risk of acute myocardial infarction.

STUDY OBJECTIVE: Previous studies of neighbourhood effects on ischaemic heart disease (IHD) have used census or administrative data to characterise the residential context, most commonly its socioeconomic level. Using the ecometric approach to define neighbourhood social interaction variables that may be relevant to IHD, neighbourhood social cohesion and safety were examined to see how they related to acute myocardial infarction (AMI) mortality, after adjustment for individual and neighbourhood confounders. DESIGN: To construct social interaction variables, multilevel models were used to aggregate individual perceptions of safety and cohesion at the neighbourhood level. Linking data from the Health Survey in Scania, Sweden, and the Population, Hospital, and Mortality Registers, multilevel survival models were used to investigate determinants of AMI mortality over a three year and nine month period. PARTICIPANTS: 7791 Individuals aged 45 years and over. MAIN RESULTS: The rate of AMI mortality increased with decreasing neighbourhood safety and cohesion. After adjustment for individual health and socioeconomic variables, low neighbourhood cohesion, and to a lesser extent low safety, were associated with higher AMI mortality. Neighbourhood cohesion effects persisted after adjustment for various neighbourhood confounding factors (income, population density, percentage of residents from low-income countries, residential stability) and distance to the hospital. There was some evidence that neighbourhood cohesion effects on AMI mortality were caused by effects on one-day case-fatality, rather than on incidence. CONCLUSIONS: Beyond commonly evoked effects of the physical environment, neighbourhood social interaction patterns may have a decisive influence on IHD, with a particularly strong effect on survival after AMI.

Area-level determinants of specialty care utilization in France: a multilevel analysis.

OBJECTIVES: We investigated the effects of the density of specialists and of the area-level percentage of highly educated individuals on the odds of consulting a specialist, and examined whether these variables could explain the observed urban/rural contrast in utilization of specialty care. STUDY DESIGN: The study sample, representative of the French population aged 18-75 years in 1999, comprised 12,435 individuals. METHODS: Multilevel logistic models allowed us to investigate predictors of the odds of consulting a specialist occasionally, regularly and frequently over the previous 12 months. RESULTS: We observed a modest but significant clustering within areas of the utilization of specialty care, with higher levels of clustering for behaviours representing heavy consumption of care. After adjustment for individual factors, the odds of consulting a specialist were higher in larger cities compared with rural areas, but most of this effect was attributable to other area-level variables. These area-level effects were different in magnitude and nature among males and females. Among males, the odds of consulting a specialist increased with the area-level density of specialists. Among females, such an effect was not significant, but the odds of consulting a specialist increased with the area-level percentage of highly educated individuals. CONCLUSIONS: Further investigation is required to better understand the processes operating at the area level that were shown to affect healthcare utilization in a different way for males and females. Policies may be needed to address problems of geographical access to specialty care, as well as situations of overuse of specialty care without regular recourse to primary care.

[The contribution of multilevel models in contextual analysis in the field of social epidemiology: a review of literature]. / L'apport des modèles multiniveau dans l'analyse contextuelle en épidémiologie sociale: une revue de la littérature.

Using contextual factors beyond individual factors, contextual analysis allows a more accurate identification of at-risk populations, which could be useful when planning health programs. Multilevel models, widely used in British and North-American social epidemiology research but less frequently in France, are particularly suitable to analyse contextual data, because they take into account their hierarchical structure. This paper addresses methodological issues in the utilization of multilevel models, and reports some results which illustrate their potentials compared to those of more conventional statistical methods. As well as other methods, multilevel models are able to take into account the hierarchical structure of the data when estimating parameters. Furthermore, and more specifically, these models can also be viewed as useful tools to investigate contextual effects. Their particular interest is to disentangle individual-level variability and between-group variability. Comparing the group-level variance before and after introduction of individual-level characteristics allows to assess the extent to which between-group variability is linked to compositional effects. Multilevel models can also help examine whether the between-group variations affect all the members of the groups, or only specific sub-groups. Finally, they can estimate how much of this complex between-group variability is explained by the contextual factors included in the model. The overall conclusion is that multilevel statistical methods should be used in social epidemiology studies dealing with individual and contextual data, to produce results that are both richer and more consistent.