Total and specific dietary polyphenol intakes and 6-year anthropometric changes in a middle-aged general population cohort.

BACKGROUND: Dietary polyphenols are suggested antiobesogenic agents. Prospective evidence in general population of an association between polyphenol intakes and anthropometry is lacking. OBJECTIVE: To assess the associations between dietary polyphenol intakes and changes in body mass index (BMI) and waist circumference (WC) over a 6-year period. METHODS: Individual intakes of 264 different polyphenols (mg day-1) were estimated using the Phenol-Explorer database and the mean of 6-17 24-h dietary records collected in 1994-1996. BMI in kg m-2 and WC in cm were measured in 1995-1996, 1998-1999 and 2001-2002. Linear mixed-effect models allowed for the assessment of longitudinal associations between energy-adjusted quartiles of total polyphenol intake as well as intake of 15 polyphenol classes and changes of these respective polyphenol classes in anthropometry over the 6 years of follow-up. Adjustment variables included sex, age, socio-economic status, lifestyle, dietary intakes and health status. RESULTS: Participants in the highest quartile of intake of flavanones (BMI change: -0.28 (-0.43; -0.13), P=0.009), flavones (BMI change: -0.29 (-0.44; -0.14), P=0.008) and lignans (BMI change: -0.28 (-1.63; -0.09), P=0.01) experienced a less notable increase in BMI over time compared with their counterparts in the bottom quartile of intake of the respective polyphenol classes. Participants in the highest quartile of intake of flavanones (WC change: -1.39 (-2.02; -0.92), P=0.001), flavones (WC change: -1.57 (-2.32; -0.92), P=0.001), hydroxycinnamic acids (WC change: -1.27 (-1.92; -0.63), P=0.01), lignans (WC change: -1.16 (-1.80; -0.51), P=0.006) and total polyphenol intake (WC change: -1.39 (-2.05; -0.74), P=0.001) experienced a less notable increase in WC over time compared with their counterparts in the bottom quartile of intake of the respective polyphenols. CONCLUSIONS: Dietary polyphenol intakes may help reduce weight gain over time in the general population. This could have important public health implications because moderate increases in BMI and WC over time have been shown to increase disease risk.

Influence of the urban context on the relationship between neighbourhood deprivation and obesity.

BACKGROUND: In middle- and high-income countries, obesity is positively associated with neighbourhood deprivation. However, the moderating effect of the broader urban residential context on this relationship remains poorly understood. METHODS: In this study, we have examined the nonlinear and geographically varying relationship between neighbourhood deprivation and the likelihood of being a person with overweight among participants of the French NutriNet-Santé adult cohort study (n = 68,698), adjusted for age, gender and educational level. Ten urban residential contexts (e.g., suburbs, peri-urban or rural areas) were defined. We used a multilevel generalised additive modelling framework for analyses. RESULTS: We found that the relationship between neighbourhood deprivation and overweight differed according to urban context, in terms of both linearity and intensity. Overall, the deprivation-overweight relationship was strongly positive (with a higher prevalence of overweight in deprived neighbourhoods) in suburban areas of Paris and of other large French cities, while weak or null in small towns and rural areas, and intermediate in inner cities. In addition, we observed in suburbs of Paris and in peri-urban belts of large cities that beyond a certain level of neighbourhood deprivation, the relationship with overweight plateaued. DISCUSSION: In a French population from a high-income country, suburbs, as well as moderately deprived neighbourhoods of peri-urban areas of large cities, are potential targets for public health and urban planning policies aiming at preventing obesity. Our results emphasize the value of local analyses to better capture the complexity and contextual variations of socioeconomic determinants of non-communicable diseases such as obesity.

Perceived environmental correlates of cycling for transport among adults in five regions of Europe.

Regular cycling for transport is an important potential contributor to daily physical activity among adults. Characteristics of the physical environment are likely to influence cycling for transport. The current study investigated associations between perceived physical environmental neighbourhood factors and adults' cycling for transport across five urban regions across Europe, and whether such associations were moderated by age, gender, education and urban region. A total of 4,612 adults from five European regions provided information about their transport-related cycling and their neighbourhood physical environmental perceptions in an online survey. Hurdle models adjusted for the clustering within neighbourhoods were performed to estimate associations between perceived physical environmental neighbourhood factors and odds of engaging in cycling for transport and minutes of cycling for transport per week. Inhabitants of neighbourhoods that were perceived to be polluted, having better street connectivity, having lower traffic speed levels and being less pleasant to walk or cycle in had higher levels of cycling for transport. Moderation analyses revealed only one interaction effect by gender. This study indicates that cycling for transport is associated with a number of perceived physical environmental neighbourhood factors across five urban regions across Europe. Our results indicated that the majority of the outcomes identified were valid for all subgroups of age, gender, education and across regions in the countries included in the study.

Self-defined residential neighbourhoods: size variations and correlates across five European urban regions.

The neighbourhood is recognized as an important unit of analysis in research on the relation between obesogenic environments and development of obesity. One important challenge is to define the limits of the residential neighbourhood, as perceived by study participants themselves, in order to improve our understanding of the interaction between contextual features and patterns of obesity. An innovative tool was developed in the framework of the SPOTLIGHT project to identify the boundaries of neighbourhoods as defined by participants in five European urban regions. The aims of this study were (i) to describe self-defined neighbourhood (size and overlap with predefined residential area) according to the characteristics of the sampling administrative neighbourhoods (residential density and socioeconomic status) within the five study regions and (ii) to determine which individual or/and environmental factors are associated with variations in size of self-defined neighbourhoods. Self-defined neighbourhood size varies according to both individual factors (age, educational level, length of residence and attachment to neighbourhood) and contextual factors. These findings have consequences for how residential neighbourhoods are defined and operationalized and can inform how self-defined neighbourhoods may be used in research on associations between contextual characteristics and health outcomes such as obesity.

Neighbourhood typology based on virtual audit of environmental obesogenic characteristics.

Virtual audit (using tools such as Google Street View) can help assess multiple characteristics of the physical environment. This exposure assessment can then be associated with health outcomes such as obesity. Strengths of virtual audit include collection of large amount of data, from various geographical contexts, following standard protocols. Using data from a virtual audit of obesity-related features carried out in five urban European regions, the current study aimed to (i) describe this international virtual audit dataset and (ii) identify neighbourhood patterns that can synthesize the complexity of such data and compare patterns across regions. Data were obtained from 4,486 street segments across urban regions in Belgium, France, Hungary, the Netherlands and the UK. We used multiple factor analysis and hierarchical clustering on principal components to build a typology of neighbourhoods and to identify similar/dissimilar neighbourhoods, regardless of region. Four neighbourhood clusters emerged, which differed in terms of food environment, recreational facilities and active mobility features, i.e. the three indicators derived from factor analysis. Clusters were unequally distributed across urban regions. Neighbourhoods mostly characterized by a high level of outdoor recreational facilities were predominantly located in Greater London, whereas neighbourhoods characterized by high urban density and large amounts of food outlets were mostly located in Paris. Neighbourhoods in the Randstad conurbation, Ghent and Budapest appeared to be very similar, characterized by relatively lower residential densities, greener areas and a very low percentage of streets offering food and recreational facility items. These results provide multidimensional constructs of obesogenic characteristics that may help target at-risk neighbourhoods more effectively than isolated features.

Mismatch between perceived and objectively measured environmental obesogenic features in European neighbourhoods.

Findings from research on the association between the built environment and obesity remain equivocal but may be partly explained by differences in approaches used to characterize the built environment. Findings obtained using subjective measures may differ substantially from those measured objectively. We investigated the agreement between perceived and objectively measured obesogenic environmental features to assess (1) the extent of agreement between individual perceptions and observable characteristics of the environment and (2) the agreement between aggregated perceptions and observable characteristics, and whether this varied by type of characteristic, region or neighbourhood. Cross-sectional data from the SPOTLIGHT project (n = 6037 participants from 60 neighbourhoods in five European urban regions) were used. Residents' perceptions were self-reported, and objectively measured environmental features were obtained by a virtual audit using Google Street View. Percent agreement and Kappa statistics were calculated. The mismatch was quantified at neighbourhood level by a distance metric derived from a factor map. The extent to which the mismatch metric varied by region and neighbourhood was examined using linear regression models. Overall, agreement was moderate (agreement < 82%, kappa < 0.3) and varied by obesogenic environmental feature, region and neighbourhood. Highest agreement was found for food outlets and outdoor recreational facilities, and lowest agreement was obtained for aesthetics. In general, a better match was observed in high-residential density neighbourhoods characterized by a high density of food outlets and recreational facilities. Future studies should combine perceived and objectively measured built environment qualities to better understand the potential impact of the built environment on health, particularly in low residential density neighbourhoods.

Neighbourhood social capital: measurement issues and associations with health outcomes.

We compared ecometric neighbourhood scores of social capital (contextual variation) to mean neighbourhood scores (individual and contextual variation), using several health-related outcomes (i.e. self-rated health, weight status and obesity-related behaviours). Data were analysed from 5,900 participants in the European SPOTLIGHT survey. Factor analysis of the 13-item social capital scale revealed two social capital constructs: social networks and social cohesion. The associations of ecometric and mean neighbourhood-level scores of these constructs with self-rated health, weight status and obesity-related behaviours were analysed using multilevel regression analyses, adjusted for key covariates. Analyses using ecometric and mean neighbourhood scores, but not mean neighbourhood scores adjusted for individual scores, yielded similar regression coefficients. Higher levels of social network and social cohesion were not only associated with better self-rated health, lower odds of obesity and higher fruit consumption, but also with prolonged sitting and less transport-related physical activity. Only associations with transport-related physical activity and sedentary behaviours were associated with mean neighbourhood scores adjusted for individual scores. As analyses using ecometric scores generated the same results as using mean neighbourhood scores, but different results when using mean neighbourhood scores adjusted for individual scores, this suggests that the theoretical advantage of the ecometric approach (i.e. teasing out individual and contextual variation) may not be achieved in practice. The different operationalisations of social network and social cohesion were associated with several health outcomes, but the constructs that appeared to represent the contextual variation best were only associated with two of the outcomes.

Coil optimization for low-field MRI: a dedicated process for small animal preclinical studies.

We demonstrate a method for the fast in vivo quantification of small volumes, down to 25 µL, using low-field magnetic resonance imaging (MRI) coils. The coils were designed so as to maximize the signal-to-noise ratio (SNR) in the images. For this we developed an analytical model for describing the variations of the SNR with coil design and with size/shape suited to the object under observation. Based on the conclusions drawn from the model, the coil parameters were chosen in order to reach an SNR close to the maximum. For the validation of the model, coils were finally characterized in terms of quality factor using saline phantoms. The coil design procedure is illustrated here with two examples: first, the quantification of about 200 µL of intradermal injected gel on rabbits with a single loop surface coil and second, the imaging of the intervertebral disks in rat tails using a small volume coil to detect possible lesions. Such studies would not have been feasible for the clinical low-field MRI system at our disposal using any of the commercially available medium-sized manufactured coils. As a result of this simple optimization procedure, a wide range of applications is accessible even at low magnetic fields, leading to new opportunities for low-cost, though efficient, preclinical studies.