Cohort Profile: Residential and non-residential environments, individual activity spaces and cardiovascular risk factors and diseases--The RECORD Cohort Study

Over the last few decades, due to the geographic concentration of poverty, socio-economic disparities between cities and neighbourhoods have increased in considerable proportions in France,1 with negative consequences for the daily lives of residents of disadvantaged neighbourhoods. Despite this increase in the geographic component of social inequalities, neighbourhood determinants of health have been largely neglected in French research until recently.2,3 In this context, it is critical to monitor territorial disparities in health between affluent and disadvantaged neighbourhoods and understand the processes through which neighbourhood poverty may influence health.4–7 Such data are important for policymakers to identify priority targets to reduce socio-spatial disparities in health, even if socio-epidemiologists cannot make the a priori assumption that easily modifiable factors exist to substantially decrease health disparities without addressing fundamental inequalities in wealth or income and socio-spatial segregation itself. The RECORD Cohort Study (‘Residential Environment and Coronary heart Disease’, www.record-study.org) was established in 2007–08 to investigate environmental determinants of territorial disparities in health. In an urban health perspective,8 the cohort was recruited in peri-urban and urban municipalities of the Paris metropolitan area, a geographically coherent territory with the largest territorial income disparities among French regions.1 The RECORD Study is coordinated by Inserm and Université Pierre et Marie Curie, and developed in collaboration with the Centre d'Investigations Préventives et Cliniques (IPC). The University of Montreal has joined the consortium since the second wave of the study. The first aim of the study is to describe and quantify geographic disparities between socially advantaged and disadvantaged neighbourhoods in cardiovascular risk factors, related use of health-care services, cardiovascular disease prevalence and incidence, and other health outcomes. We hypothesize that socially disadvantaged populations from disadvantaged territories may be in double jeopardy, facing both a high incidence of risk factors and a poor health-care management of these conditions. The second aim is to investigate associations between numerous neighbourhood dimensions and all of these outcomes,4,7,9 and to assess whether such influences contribute to neighbourhood socio-economic disparities in health. Promoting an integrative view of the environment, our goal is to account for the physical environment, the service environment, the social–interactional environment (i.e. social interactions in the neighbourhood) and the symbolic environment (i.e. representations and identities, sometimes positive, sometimes stigmatizing, associated with the different neighbourhoods). The third aim is to examine whether and how individual mobility patterns, in shaping environmental exposures within activity spaces and as a source of physical activity,10–13 contribute to the health disparities documented between social groups and territories. The fourth aim is to explore the mediating mechanisms through which neighbourhood characteristics influence health outcomes.14 The potential mediators of interest include health and health-care utilization behaviour; the cognitive, affective and relational experiences made in one's environment; psychological characteristics of participants; and the psycho-cognitive determinants of behaviour.7 Finally, our project has a strong methodological component and is a platform for developing strategies to improve the measurement of neighbourhood exposures and the modelling of their effects on health.7,13,15,16 The French National Health Insurance System for Salaried Workers offers a free medical examination every 5 years to all working and retired employees and their families. In the RECORD Cohort Study, we recruited without a priori sampling people who were getting these 2-h-long preventive medical check-ups, in four of the centres of the Centre IPC, located in the Ile-de-France region (Paris, Argenteuil, Trappes and Mantes-la-Jolie). The following occupational categories are not insured by the National Health Insurance System for salaried workers and could not be recruited: shopkeepers, craftsmen, farmers, salaried farm workers and self-employed occupations (lawyers, architects, etc.). However, in the Ile-de-France region (comprising the Paris metropolitan area), working and retired employees and their families (eligible for recruitment) represent almost 95% of the population. Eligibility criteria were as follows: age 30–79 years; ability to complete study questionnaires and residence in one of the 10 (out of 20) administrative divisions of Paris or 111 other municipalities of the metropolitan area. These territories were selected a priori so as to include areas from contrasted socio-economic backgrounds and from peri-urban and urban areas. Among people presenting at the health centres and who were eligible based on age and residence, 10.9% were not selected for participation because of linguistic or cognitive difficulties in filling out study questionnaires. Of the persons selected for participation, 83.6% accepted to participate and completed the data collection protocol. Overall, 7290 participants were recruited between March 2007 and February 2008. The study protocol was approved by the French Data Protection Authority. In a recent publication,17 to address the fact that participants were recruited without a priori sampling and investigate possibly resulting participation-related selection biases for the neighbourhood–health associations of interest,18 we investigated whether individual age, gender and education and multiple neighbourhood characteristics related to the socio-economic, physical, service and social–interactional environments were associated with the rate of participation of populations in the RECORD Study. As shown in Figure 1, a multi-level analysis indicated that there were geographic variations in the rate of study participation, with higher participation rates in the western part of the territory where the recruiting health centres are located. Adjusted regression models showed higher participation rates for males and educated people, for populations from high socio-economic status neighbourhoods (as reflected independently by neighbourhood income and dwelling values) and for residents of low building density areas (as reflected by the proportion of built-up surface and building height). Our recently published article17 suggests that spatial variations in the participation rate biased the relationship of interest between neighbourhood socio-economic status and type 2 diabetes, but that we were able to correct some of these biases through the joint modelling of the neighbourhood determinants of both study participation and type 2 diabetes.19 Geographic variations between municipalities in the rate of participation in the RECORD Cohort Study, estimated from a multi-level model for study participation (only the central part of the RECORD Study territory is shown on the map; the fourth recruiting centre—Mantes-la-Jolie—is located outside the map). Based on the number of residents (from the 2006 population census) and number of participants per age group and sex per municipality, we estimated a multi-level Poisson model only adjusted for age and sex with people nested within municipalities. The map plots the municipality-level random effect of the multi-level model, interpretable as a log rate ratio for participation in each municipality compared with the whole study territory. High- and low-participation municipalities are areas with a rate ratio of participation respectively higher than 1.25 and lower than 1/1.25 = 0.80 (compared with the whole study territory). Municipalities in white colour are not part of the pre-defined study territory The participants were recruited in 2007–08. For the second wave of the RECORD Study, all of the participants are invited to have another health examination in 2011–12. In addition to this actual follow-up, we also conduct a virtual follow-up of participants through different national administrative registers (see details below). As summarized in Table 1, during the 2-h-long general health check-up, participants underwent biological and clinical examinations. The anthropometric and body composition assessment included among others, a measure of sitting height allowing the determination of leg length20 and bioelectrical impedance analysis.21 Types of data available in the RECORD Cohort Study Medical questionnaire (personal and family history of health conditions, self-rated health, angina pectoris and intermittent claudication, women's health, etc.) (W1 and W2) Fasting blood and urine samples (W1 and W2) ECG and blood pressure (W1 and W2) Body mass index and waist and hip circumferences (W1 and W2) Body composition through bioelectrical impedance (W1 and W2) Tricipital skinfold and arm circumference (W2) Sitting height (W1) Spirometry (W1) Dental examination (W1 and W2) Hearing and visual tests (W1 and W2) Hospitalization data over 4 years (SNIIR-AM) Age, sex and cohabitation status (W1 and W2) Country of citizenship (W1 and W2) Countries of birth of the participant, her/his parents and her/his grandparents (W2) Personal education level and parents’ education level (W1 and W2) Occupation, employment status, work conditions (W1 and W2) Household income, health insurance, housing tenure (W1 and W2) Lifetime and current financial difficulties (W1 and W2) Yearly individual income for the whole occupational career of retired participants of of and wealth (W1 and W2) during (W2) and physical activity (W1 and W2) physical activity over (W1) physical activity over (W1 and W2) and over (W1 and W2) over (W2) of and and (W1) (W2) of (W2) data on health-care utilization over 4 years biological (SNIIR-AM) and related to (W2) of blood pressure pressure strategies and related to status related to and body body and of in since as to health or waist circumference of in the neighbourhood and related to for to targets and related to health to health and of (W2) (W1 and W2) (W1 and W2) to the neighbourhood (W1) of (W1) of social (W1) of (W1) as a source of or (W1) of other services, (W1) of the neighbourhood of (W1) or in the neighbourhood (W1) from the (W1) with (W1) or the (W1) in associations in the neighbourhood (W1) in the neighbourhood (W1) for and (W1) over 4 years and type of service and spatial (SNIIR-AM) of work spatial of the of of residence, of and for or to which are and where people are (W2) of the neighbourhood (W2) mobility and (W2) (W2) to mobility (W2) at the (W2) address at history 2007–08 or socio-economic in or administrative areas on the physical and service environment with a geographic of the neighbourhood in W2) of the environment in W2) and of the neighbourhood (W2) (W2) of the environment (W2) in W2) (W2) in W2) of the neighbourhood in W2) Medical questionnaire (personal and family history of health conditions, self-rated health, angina pectoris and intermittent claudication, women's health, etc.) (W1 and W2) Fasting blood and urine samples (W1 and W2) ECG and blood pressure (W1 and W2) Body mass index and waist and hip circumferences (W1 and W2) Body composition through bioelectrical impedance (W1 and W2) Tricipital skinfold and arm circumference (W2) Sitting height (W1) Spirometry (W1) Dental examination (W1 and W2) Hearing and visual tests (W1 and W2) Hospitalization data over 4 years (SNIIR-AM) Age, sex and cohabitation status (W1 and W2) Country of citizenship (W1 and W2) Countries of birth of the participant, her/his parents and her/his grandparents (W2) Personal education level and parents’ education level (W1 and W2) Occupation, employment status, work conditions (W1 and W2) Household income, health insurance, housing tenure (W1 and W2) Lifetime and current financial difficulties (W1 and W2) Yearly individual income for the whole occupational career of retired participants of of and wealth (W1 and W2) during (W2) and physical activity (W1 and W2) physical activity over (W1) physical activity over (W1 and W2) and over (W1 and W2) over (W2) of and and (W1) (W2) of (W2) data on health-care utilization over 4 years biological (SNIIR-AM) and related to (W2) of blood pressure pressure strategies and related to status related to and body body and of in since as to health or waist circumference of in the neighbourhood and related to for to targets and related to health to health and of (W2) (W1 and W2) (W1 and W2) to the neighbourhood (W1) of (W1) of social (W1) of (W1) as a source of or (W1) of other services, (W1) of the neighbourhood of (W1) or in the neighbourhood (W1) from the (W1) with (W1) or the (W1) in associations in the neighbourhood (W1) in the neighbourhood (W1) for and (W1) over 4 years and type of service and spatial (SNIIR-AM) of work spatial of the of of residence, of and for or to which are and where people are (W2) of the neighbourhood (W2) mobility and (W2) (W2) to mobility (W2) at the (W2) address at history 2007–08 or socio-economic in or administrative areas on the physical and service environment with a geographic of the neighbourhood in W2) of the environment in W2) and of the neighbourhood (W2) (W2) of the environment (W2) in W2) (W2) in W2) of the neighbourhood in W2) first study second study National System of the Health Insurance Insurance Types of data available in the RECORD Cohort Study Medical questionnaire (personal and family history of health conditions, self-rated health, angina pectoris and intermittent claudication, women's health, etc.) (W1 and W2) Fasting blood and urine samples (W1 and W2) ECG and blood pressure (W1 and W2) Body mass index and waist and hip circumferences (W1 and W2) Body composition through bioelectrical impedance (W1 and W2) Tricipital skinfold and arm circumference (W2) Sitting height (W1) Spirometry (W1) Dental examination (W1 and W2) Hearing and visual tests (W1 and W2) Hospitalization data over 4 years (SNIIR-AM) Age, sex and cohabitation status (W1 and W2) Country of citizenship (W1 and W2) Countries of birth of the participant, her/his parents and her/his grandparents (W2) Personal education level and parents’ education level (W1 and W2) Occupation, employment status, work conditions (W1 and W2) Household income, health insurance, housing tenure (W1 and W2) Lifetime and current financial difficulties (W1 and W2) Yearly individual income for the whole occupational career of retired participants of of and wealth (W1 and W2) during (W2) and physical activity (W1 and W2) physical activity over (W1) physical activity over (W1 and W2) and over (W1 and W2) over (W2) of and and (W1) (W2) of (W2) data on health-care utilization over 4 years biological (SNIIR-AM) and related to (W2) of blood pressure pressure strategies and related to status related to and body body and of in since as to health or waist circumference of in the neighbourhood and related to for to targets and related to health to health and of (W2) (W1 and W2) (W1 and W2) to the neighbourhood (W1) of (W1) of social (W1) of (W1) as a source of or (W1) of other services, (W1) of the neighbourhood of (W1) or in the neighbourhood (W1) from the (W1) with (W1) or the (W1) in associations in the neighbourhood (W1) in the neighbourhood (W1) for and (W1) over 4 years and type of service and spatial (SNIIR-AM) of work spatial of the of of residence, of and for or to which are and where people are (W2) of the neighbourhood (W2) mobility and (W2) (W2) to mobility (W2) at the (W2) address at history 2007–08 or socio-economic in or administrative areas on the physical and service environment with a geographic of the neighbourhood in W2) of the environment in W2) and of the neighbourhood (W2) (W2) of the environment (W2) in W2) (W2) in W2) of the neighbourhood in W2) Medical questionnaire (personal and family history of health conditions, self-rated health, angina pectoris and intermittent claudication, women's health, etc.) (W1 and W2) Fasting blood and urine samples (W1 and W2) ECG and blood pressure (W1 and W2) Body mass index and waist and hip circumferences (W1 and W2) Body composition through bioelectrical impedance (W1 and W2) Tricipital skinfold and arm circumference (W2) Sitting height (W1) Spirometry (W1) Dental examination (W1 and W2) Hearing and visual tests (W1 and W2) Hospitalization data over 4 years (SNIIR-AM) Age, sex and cohabitation status (W1 and W2) Country of citizenship (W1 and W2) Countries of birth of the participant, her/his parents and her/his grandparents (W2) Personal education level and parents’ education level (W1 and W2) Occupation, employment status, work conditions (W1 and W2) Household income, health insurance, housing tenure (W1 and W2) Lifetime and current financial difficulties (W1 and W2) Yearly individual income for the whole occupational career of retired participants of of and wealth (W1 and W2) during (W2) and physical activity (W1 and W2) physical activity over (W1) physical activity over (W1 and W2) and over (W1 and W2) over (W2) of and and (W1) (W2) of (W2) data on health-care utilization over 4 years biological (SNIIR-AM) and related to (W2) of blood pressure pressure strategies and related to status related to and body body and of in since as to health or waist circumference of in the neighbourhood and related to for to targets and related to health to health and of (W2) (W1 and W2) (W1 and W2) to the neighbourhood (W1) of (W1) of social (W1) of (W1) as a source of or (W1) of other services, (W1) of the neighbourhood of (W1) or in the neighbourhood (W1) from the (W1) with (W1) or the (W1) in associations in the neighbourhood (W1) in the neighbourhood (W1) for and (W1) over 4 years and type of service and spatial (SNIIR-AM) of work spatial of the of of residence, of and for or to which are and where people are (W2) of the neighbourhood (W2) mobility and (W2) (W2) to mobility (W2) at the (W2) address at history 2007–08 or socio-economic in or administrative areas on the physical and service environment with a geographic of the neighbourhood in W2) of the environment in W2) and of the neighbourhood (W2) (W2) of the environment (W2) in W2) (W2) in W2) of the neighbourhood in W2) first study second study National System of the Health Insurance Insurance As part of the health check-up, participants out questionnaires related to their status, health family and medical and psychological In participants were invited to out a questionnaire developed for the RECORD Study. As in Table 1, this questionnaire on socio-economic physical activity over the to different and outside the the cognitive and relational experiences made by in their environment and the current and on different environmental dimensions to environmental at the neighbourhood In this modelling the of of participants from the neighbourhood to different on each environmental is with multi-level models that The and were all or with the participants over with of were to complete the We a number of related to the physical environment, service environment and social–interactional and symbolic environment, in neighbourhoods on we the where participants of their based on and and of the National Health Insurance for Salaried health-care data from the National National System of the Health Insurance are at the individual level to the RECORD Cohort Study on an from 2006 to The data include on all the health and biological tests and We are able to at the address level each health-care by the participants over the allowing to their activity from the National Insurance for each participant, we for the career the income and of the per to of work of on status and of be to the February all study participants are invited to another 2-h-long health at the Centre The examination all medical during the the skinfold and arm are to on body all on neighbourhood and health have on the of the second wave of the study is the assessment of each of (as in Figure 2 for different study Such on the activity be to examine whether effects of neighbourhood characteristics are for people with an activity to their we of to geographic environments that account the participants during their As in Figure are through the and of and a based on that to for and activity (see details of in Table In participants are invited to the of their as in Figure is completed by on the and of the of the of the neighbourhood and of the of of participants through the for different participants for the residence and for the neighbourhood on the As an the on the first map from the to the a a a another a a a and a an a the of residence, a another a a a and another and The of residence of the parents was also but is outside the map and questionnaires are on that of data and tests of and tests each of data collection that are or to through of the of the of the of of the use of the to in each of data collection is on a daily between the and the in to improve the of the data collection are to the psycho-cognitive of body and to the that disparities in status between affluent and neighbourhoods may be environmental factors, by in and related to body but data are also for are related to the with different for each environmental in to and environmental at the neighbourhood level (see details in Table As modelling a number of participants per neighbourhood to in the second wave of the we participants to for out of the study territory and to increase the rate of participation in areas where we not participants of this we all of the even if out of the study The other by the and physical activity with with of the first wave of the behaviour; socio-economic data of birth of their parents and and at the of the to for The we have so the of the cohort is we a to all study participants from which to identify through participants who have recently As of the we were for the address of Overall, since participants were over to complete of the questionnaire or for the follow-up of participants so have their to from the study. As of of the participants of the and participants (see participants have been in the second wave of the study in February from the work on neighbourhood determinants of study we investigated or are the between neighbourhood environments and risk documented strong associations between neighbourhood socio-economic status neighbourhood and body mass index or waist that these adjusted neighbourhood–health associations could be estimated without model in the study showed for socio-economic body mass index and waist circumference increased with of factors related to the physical and service environment of and etc.). these neighbourhood characteristics are with each we are developing strategies to assess whether the different associations be from each study documented increased blood pressure in neighbourhoods with a low indicated that body mass index and waist circumference of the relationship between neighbourhood education and blood In another analysis on heart were to investigate the spatial on which neighbourhood socio-economic were associated with heart data at the building level to neighbourhood within areas of different determinants of and were also different characteristics of the physical, service and social–interactional environments were associated with for the density of with and the of spaces with on the environment and have the environment in the neighbourhood of even if people not in their a different at the where participants of their we that participants who in the a body mass index and waist circumference than participants who in different participants who in and in a higher body mass index and waist if a low education Finally, our also among other health-care utilization related to cardiovascular risk factors, disparities in to and resulting associations with related to the RECORD Study be at of the RECORD Study, which is to neighbourhood effects on health, is ability to the environment and related individual experiences and to different environments related to the health-care utilization services, for and the second wave of the to the of of the study is that participants were recruited without a priori As in and investigated resulting participation in the study may the neighbourhood–health associations of if not during the we could not people who not French to the questionnaires and with the to the other study Such may to neighbourhood socio-economic disparities estimated for not health outcomes. The territory investigated neighbourhoods each is both a and a of the a because it offers of environmental characteristics allowing to their associations with health, a because it it to of neighbourhoods through based on the study not include on the daily spatial or with a that we are to address through the of the RECORD Study for a of the Finally, another to the of data on even if the second wave of the study include questionnaires on this Based on our with the study we are able to the data to only in the of with the study related to the use of RECORD Study data are and be with on the RECORD Cohort Study is at We are to the following for their financial the for Health the National for and Health National et from the financial for and the National of Health from and Health the French of and Health the National Health Insurance for Salaried Workers the Ile-de-France and the National from the Ile-de-France Health the of Paris the Ile-de-France and et the the for Health We of for and We are to Pierre for since the of the study. We also and from the Ile-de-France and and from the Ile-de-France for their in our We are to the French National of and which for the of the RECORD participants and to to data to and We for allowing to to the We are to from and to and from for their in the health-care data from the and the data on to the RECORD We also and the Paris for make this study of

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