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Feuillet T, Valette JF, Charreire H, Kesse-Guyot E, Julia C, Vernez-Moudon A, Hercberg S, Touvier M, Oppert JM. Influence of the urban context on the relationship between neighbourhood deprivation and obesity. Soc Sci Med 2020; 265:113537. [PMID: 33250318 DOI: 10.1016/j.socscimed.2020.113537] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 09/22/2020] [Accepted: 11/16/2020] [Indexed: 10/22/2022]
Abstract
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.
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Affiliation(s)
- T Feuillet
- University Paris 8, LADYSS, UMR 7533 CNRS, Saint-Denis, France; Sorbonne Paris Nord University, Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France.
| | - J F Valette
- University Paris 8, LADYSS, UMR 7533 CNRS, Saint-Denis, France
| | - H Charreire
- Sorbonne Paris Nord University, Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France; University Paris Est, Lab Urba, Créteil, France
| | - E Kesse-Guyot
- Sorbonne Paris Nord University, Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France
| | - C Julia
- Sorbonne Paris Nord University, Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France; Public Health Department, Avicenne Hospital (AP-HP), Bobigny, France
| | - A Vernez-Moudon
- Architecture, Landscape Architecture, and Urban Design and Planning, University of Washington, 1107 NE 45th St, Suite 535, Box 354802, Seattle, WA, 98195, USA
| | - S Hercberg
- Sorbonne Paris Nord University, Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France; Public Health Department, Avicenne Hospital (AP-HP), Bobigny, France
| | - M Touvier
- Sorbonne Paris Nord University, Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France
| | - J M Oppert
- Sorbonne Paris Nord University, Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France; Sorbonne University, Department of Nutrition, Pitié-Salpêtrière Hospital (AP-HP), Institute of Cardiometabolism and Nutrition (ICAN), Paris, France
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2
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Perchoux C, Nazare JA, Benmarhnia T, Salze P, Feuillet T, Hercberg S, Hess F, Menai M, Weber C, Charreire H, Enaux C, Oppert JM, Simon C. Étude des disparités d’éducation du quartier sur la pratique du transport actif vers le lieu de travail/étude : l’effet modérateur de la distance (une étude ACTI-Cités). NUTR CLIN METAB 2017. [DOI: 10.1016/j.nupar.2016.10.067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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3
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Mertens L, Compernolle S, Gheysen F, Deforche B, Brug J, Mackenbach JD, Lakerveld J, Oppert JM, Feuillet T, Glonti K, Bárdos H, De Bourdeaudhuij I. Perceived environmental correlates of cycling for transport among adults in five regions of Europe. Obes Rev 2016; 17 Suppl 1:53-61. [PMID: 26879113 DOI: 10.1111/obr.12379] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 12/16/2015] [Indexed: 12/18/2022]
Abstract
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.
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Affiliation(s)
- L Mertens
- Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - S Compernolle
- Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - F Gheysen
- Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - B Deforche
- Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.,Department of Human Biometry and Biomechanics, Faculty of Physical Education and Physical Therapy, Vrije Universiteit Brussel, Brussels, Belgium
| | - J Brug
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - J D Mackenbach
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - J Lakerveld
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - J-M Oppert
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France.,Sorbonne Universités, Université Pierre et Marie Curie, Université Paris 06; Institute of Cardiometabolism and Nutrition, Department of Nutrition, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - T Feuillet
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France
| | - K Glonti
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - H Bárdos
- Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen, Hungary
| | - I De Bourdeaudhuij
- Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
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4
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Feuillet T, Charreire H, Roda C, Ben Rebah M, Mackenbach JD, Compernolle S, Glonti K, Bárdos H, Rutter H, De Bourdeaudhuij I, McKee M, Brug J, Lakerveld J, Oppert JM. Neighbourhood typology based on virtual audit of environmental obesogenic characteristics. Obes Rev 2016; 17 Suppl 1:19-30. [PMID: 26879110 DOI: 10.1111/obr.12378] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Accepted: 12/15/2015] [Indexed: 11/30/2022]
Abstract
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.
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Affiliation(s)
- T Feuillet
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France
| | - H Charreire
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France.,Paris Est University, Lab-Urba, UPEC, Urban School of Paris, Créteil, France
| | - C Roda
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France
| | - M Ben Rebah
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France
| | - J D Mackenbach
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - S Compernolle
- Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - K Glonti
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - H Bárdos
- Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen, Hungary
| | - H Rutter
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - I De Bourdeaudhuij
- Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - M McKee
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - J Brug
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - J Lakerveld
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - J-M Oppert
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France.,Sorbonne Universités, Université Pierre et Marie Curie, Université Paris 06, Institute of Cardiometabolism and Nutrition, Department of Nutrition, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
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5
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Charreire H, Feuillet T, Roda C, Mackenbach JD, Compernolle S, Glonti K, Bárdos H, Le Vaillant M, Rutter H, McKee M, De Bourdeaudhuij I, Brug J, Lakerveld J, Oppert JM. Self-defined residential neighbourhoods: size variations and correlates across five European urban regions. Obes Rev 2016; 17 Suppl 1:9-18. [PMID: 26879109 DOI: 10.1111/obr.12380] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Accepted: 12/15/2015] [Indexed: 11/28/2022]
Abstract
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.
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Affiliation(s)
- H Charreire
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Université Paris 13, Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Bobigny, France.,Paris Est University, Lab-Urba, UPEC, Urban School of Paris, Créteil, France
| | - T Feuillet
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Université Paris 13, Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Bobigny, France
| | - C Roda
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Université Paris 13, Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Bobigny, France
| | - J D Mackenbach
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Centre, Amsterdam, The Netherlands
| | - S Compernolle
- Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - K Glonti
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - H Bárdos
- Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Hungary
| | - M Le Vaillant
- CERMES3, UMR 8211-U988, CNRS, INSERM, Université Paris Descartes, EHESS, Villejuif, France
| | - H Rutter
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - M McKee
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - I De Bourdeaudhuij
- Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - J Brug
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Centre, Amsterdam, The Netherlands
| | - J Lakerveld
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Centre, Amsterdam, The Netherlands
| | - J-M Oppert
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Université Paris 13, Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Bobigny, France.,Sorbonne Universités, Université Pierre et Marie Curie, Université Paris 06; Institute of Cardiometabolism and Nutrition, Department of Nutrition Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
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6
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Mackenbach JD, Lakerveld J, van Lenthe FJ, Kawachi I, McKee M, Rutter H, Glonti K, Compernolle S, De Bourdeaudhuij I, Feuillet T, Oppert JM, Nijpels G, Brug J. Neighbourhood social capital: measurement issues and associations with health outcomes. Obes Rev 2016; 17 Suppl 1:96-107. [PMID: 26879117 DOI: 10.1111/obr.12373] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Accepted: 12/15/2015] [Indexed: 01/01/2023]
Abstract
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.
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Affiliation(s)
- J D Mackenbach
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU Medical Center Amsterdam, Amsterdam, The Netherlands
| | - J Lakerveld
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU Medical Center Amsterdam, Amsterdam, The Netherlands
| | - F J van Lenthe
- Department of Public Health, Erasmus Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - I Kawachi
- Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, USA
| | - M McKee
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - H Rutter
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - K Glonti
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - S Compernolle
- Department of Movement and Sport Sciences, Ghent University, Ghent, Belgium
| | - I De Bourdeaudhuij
- Department of Movement and Sport Sciences, Ghent University, Ghent, Belgium
| | - T Feuillet
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France
| | - J-M Oppert
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France.,Sorbonne Universités, Université Pierre et Marie Curie, Université Paris 06; Institute of Cardiometabolism and Nutrition, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - G Nijpels
- Department of General Practice and Elderly Care, EMGO Institute for Health and Care Research, VU Medical Center Amsterdam, The Netherlands
| | - J Brug
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU Medical Center Amsterdam, Amsterdam, The Netherlands
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7
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Roda C, Charreire H, Feuillet T, Mackenbach JD, Compernolle S, Glonti K, Ben Rebah M, Bárdos H, Rutter H, McKee M, De Bourdeaudhuij I, Brug J, Lakerveld J, Oppert JM. Mismatch between perceived and objectively measured environmental obesogenic features in European neighbourhoods. Obes Rev 2016; 17 Suppl 1:31-41. [PMID: 26879111 DOI: 10.1111/obr.12376] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 12/16/2015] [Indexed: 11/30/2022]
Abstract
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.
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Affiliation(s)
- C Roda
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France
| | - H Charreire
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France.,Paris Est University, Lab-Urba, UPEC, Urban School of Paris, Créteil, France
| | - T Feuillet
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France
| | - J D Mackenbach
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - S Compernolle
- Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - K Glonti
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - M Ben Rebah
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France
| | - H Bárdos
- Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen, Hungary
| | - H Rutter
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - M McKee
- ECOHOST - The Centre for Health and Social Change, London School of Hygiene and Tropical Medicine, London, UK
| | - I De Bourdeaudhuij
- Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - J Brug
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - J Lakerveld
- Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
| | - J-M Oppert
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Inserm (U1153), Inra (U1125), Cnam, COMUE Sorbonne Paris Cité, Université Paris 13, Bobigny, France.,Sorbonne Universités, Université Pierre et Marie Curie, Université Paris 06; Institute of Cardiometabolism and Nutrition, Department of Nutrition, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
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8
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Menai M, Charreire H, Christiane Weber C, Enaux C, Andreeva V, Serge Hercberg S, Simon C, Feuillet T, Oppert JM. O06: Pratique de la marche et du vélo en fonction de l’âge chez 32 907 adultes français de la cohorte NutriNet-Santé (Projet ACTI-Cités). NUTR CLIN METAB 2014. [DOI: 10.1016/s0985-0562(14)70582-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Feuillet T, Seurin MJ, Leveneur O, Viguier E, Beuf O. Coil optimization for low-field MRI: a dedicated process for small animal preclinical studies. Lab Anim 2014; 49:153-67. [PMID: 25359877 DOI: 10.1177/0023677214558103] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
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.
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Affiliation(s)
- T Feuillet
- Université de Lyon, CREATIS; CNRS UMR 5220; Inserm U1044; INSA-Lyon; Université Lyon 1, Villeurbanne, France Cirma, Marcy l'Etoile, France
| | | | - O Leveneur
- Institut Claude Bourgelat, VetAgro Sup, Campus Vétérinaire de Lyon, Marcy l'Etoile, France
| | - E Viguier
- Université de Lyon, VetAgro Sup, Campus Vétérinaire de Lyon, Marcy l'Etoile, France
| | - O Beuf
- Université de Lyon, CREATIS; CNRS UMR 5220; Inserm U1044; INSA-Lyon; Université Lyon 1, Villeurbanne, France
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