Article

Neighborhood Effects on Health Correcting Bias From Neighborhood Effects on Participation

Inserm, U707, Research Unit in Epidemiology, Information Systems, and Modeling, Paris, France.
Epidemiology (Cambridge, Mass.) (Impact Factor: 6.18). 01/2011; 22(1):18-26. DOI: 10.1097/EDE.0b013e3181fd2961
Source: PubMed

ABSTRACT Studies of neighborhood effects on health that are based on cohort data are subject to bias induced by neighborhood-related selective study participation.
We used data from the RECORD Cohort Study (REsidential Environment and CORonary heart Disease) carried out in the Paris metropolitan area, France (n = 7233). We performed separate and joint modeling of neighborhood determinants of study participation and type-2 diabetes. We sought to identify selective participation related to neighborhood, and account for any biasing effect on the associations with diabetes.
After controlling for individual characteristics, study participation was higher for people residing close to the health centers and in neighborhoods with high income, high property values, high proportion of the population looking for work, and low built surface and low building height (contextual effects adjusted for each other). After individual-level adjustment, the prevalence of diabetes was elevated in neighborhoods with the lowest levels of educational attainment (prevalence odds ratio = 1.56 [95% credible interval = 1.06-2.31]). Neighborhood effects on participation did not bias the association between neighborhood education and diabetes. However, residual geographic variations in participation weakly biased the neighborhood education-diabetes association. Bias correction through the joint modeling of neighborhood determinants of participation and diabetes resulted in an 18% decrease in the log prevalence odds ratio for low versus high neighborhood education.
Researchers should develop a comprehensive, theory-based model of neighborhood determinants of participation in their study, investigate resulting biases for the environment-health associations, and check that unexplained geographic variations in participation do not bias these environment-health relationships.

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Available from: Frédérique Thomas, Oct 10, 2014
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    • "However, a limitation is that the RECORD sample is not strictly representative of the Paris Ile-de-France population from which it was drawn, even if we a priori selected a panel of municipalities from the region to ensure the presence of people from all socioeconomic backgrounds (neighborhood-related selective participation in the sample has been investigated elsewhere [49]). Furthermore, the existence of selective residential migration processes did not allow us to demonstrate that the relationships between specific environmental factors and walking for transportation were attributable to a causal effect of these environments on walking [17]. "
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    ABSTRACT: Assessing the contextual factors that influence walking for transportation is important to develop more walkable environments and promote physical activity. To advance previous research focused on residential environments and overall walking for transportation, the present study investigates objective environmental factors assessed around the residence, the workplace, the home - work itinerary, and the home - supermarket itinerary, and considered overall walking for transportation but also walking to work and to shops. Data from the RECORD Study involving 7290 participants recruited in 2007-2008, aged 30-79 years, and residing in the Paris metropolitan area were analyzed. Multilevel ordinal regression analyses were conducted to investigate environmental characteristics associated with self-reported overall walking for transportation, walking to work, and walking to shops. High individual education was associated with overall walking for transportation, with walking to work, and walking to shops. Among workers, a high residential neighborhood education was associated with increased overall walking for transportation, while a high workplace neighborhood education was related to an increased time spent walking to work. The residential density of destinations was positively associated with overall walking for transportation, with walking to work, and with walking to shops, while the workplace density of destinations was positively associated with overall walking for transportation among workers. Environmental factors assessed around the itineraries were not associated with walking to work or to the shops. This research improves our understanding of the role of the environments on walking for transportation by accounting for some of the environments visited beyond the residential neighborhood. It shows that workers' walking habits are more influenced by the density of destinations around the workplace than around the residence. These results provide insight for the development of policies and programs to encourage population level active commuting.
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    • "The absence of randomization in the recruitment of the participants led to a sample that was not representative of the background population. A previous work showed that a high individual education, a high neighborhood socioeconomic status, and a low building density were associated with higher odds of participation in the RECORD Study [38]. All these factors were included in the models or considered for adjustment to minimize bias. "
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    • "A limitation of this study is the heterogeneity in the source and in the quality of the original transportation noise data provided by municipalities, inter-municipalities, and government services [34]. Another limitation includes the absence of a priori sampling in the recruitment of the participants, with differences in the probability of participation according to neighborhood profiles [35]. However, it is not clear whether and how annoyance due to road traffic might influence participation in the study. "
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    ABSTRACT: Road traffic and related noise is a major source of annoyance and impairment to health in urban areas. Many areas exposed to road traffic noise are also exposed to rail and air traffic noise. The resulting annoyance may depend on individual/neighborhood socio-demographic factors. Nevertheless, few studies have taken into account the confounding or modifying factors in the relationship between transportation noise and annoyance due to road traffic. In this study, we address these issues by combining Geographic Information Systems and epidemiologic methods. Street network buffers with a radius of 500 m were defined around the place of residence of the 7290 participants of the RECORD Cohort in Ile-de-France. Estimated outdoor traffic noise levels (road, rail, and air separately) were assessed at each place of residence and in each of these buffers. Higher levels of exposure to noise were documented in low educated neighborhoods. Multilevel logistic regression models documented positive associations between road traffic noise and annoyance due to road traffic, after adjusting for individual / neighborhood socioeconomic conditions. There was no evidence that the association was of different magnitude when noise was measured at the place of residence or in the residential neighborhood. However, the strength of the association between neighborhood noise exposure and annoyance increased when considering a higher percentile in the distribution of noise in each neighborhood. Road traffic noise estimated at the place of residence and road traffic noise in the residential neighborhood (75th percentile) were independently associated with annoyance, when adjusted for each other. Interactions of effects indicated that the relationship between road traffic noise exposure in the residential neighborhood and annoyance was stronger in affluent and high educated neighborhoods. Overall, our findings suggest that it is useful to take into account (i) the exposure to transportation noise in the residential neighborhood rather than only at the residence, (ii) different percentiles of noise exposure in the residential neighborhood, and (iii) the socioeconomic characteristics of the residential neighborhood to explain variations in annoyance due to road traffic in the neighborhood.
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