A brief conceptual tutorial of multilevel analysis in social epidemiology: linking the statistical concept of clustering to the idea of contextual phenomenon (original) (raw)
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Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review
Journal of Epidemiology & Community Health, 2001
Purpose-Interest in the eVects of neighbourhood or local area social characteristics on health has increased in recent years, but to date the existing evidence has not been systematically reviewed. Multilevel or contextual analyses of social factors and health represent a possible reconciliation between two divergent epidemiological paradigms-individual risk factor epidemiology and an ecological approach.
Neighbourhood effects on health: Does it matter where you draw the boundaries?
Social Science & Medicine, 2008
There has been considerable discussion in health geography and related areas of neighbourhood effects on health: the idea that people's health in one geographical area may be influenced not only by the composition of that area's population, but also by the area's geographical context. Hence, the healthiness or otherwise of the neighbourhood may have an important effect on local people's health. Although neighbourhoods and their boundaries are sometimes obvious to local residents, it is more common to find considerable disagreement on the size and contents of a neighbourhood. In this paper, we use British census Enumeration Districts as building blocks to construct alternative zonal systems, and experiment to see if neighbourhoods defined in different ways have similar implications for health. The well known modifiable areal unit problem shows that analytical conclusions may differ substantially according to how data are aggregated. Boundaries can be drawn to maximize equality of size, compactness of shape, homogeneity in social composition, accordance with 'natural' boundaries, and probably many other factors; which of these criteria are more effective in defining zones relevant to health? One conclusion is that the effect of neighbourhood conditions should be looked at using several different ways to define neighbourhoods, and that the size and composition of these neighbourhoods may be different in different parts of a study area.
Revista de salud pública (Bogotá, Colombia)
Structural and social neighbourhood constructs have been developed for studying a neighbourhood's influence on a variety of health outcomes; community surveys are being increasingly used for capturing such information. This paper has proposed a six-fold approach which integrates existing methodologies (i.e. multilevel factor analysis, ecometrics, multilevel spatial multiple membership models and multilevel latent class analysis) for estimating reliable and valid measurement of neighbourhood conditions. The proposed approach used seven demographic and socio-economic variables reported in a community survey by 20,413 individuals residing in 244 neighbourhoods in Medellin, Colombia, to measure structural neighbourhood conditions. The set of variables reliably measured one neighbourhood construct: the deprivation index; this showed significant variation between neighbourhoods as well as significant spatial clustering across the city. The approach presented here should enable public ...
Demarcation of local neighborhoods to study relations between contextual factors and health
International Journal of Health Geographics, 2010
Background: Several studies have highlighted the importance of collective social factors for population health. One of the major challenges is an adequate definition of the spatial units of analysis which present properties potentially related to the target outcomes. Political and administrative divisions of urban areas are the most commonly used definition, although they suffer limitations in their ability to fully express the neighborhoods as social and spatial units. Objective: This study presents a proposal for defining the boundaries of local neighborhoods in Rio de Janeiro city. Local neighborhoods are constructed by means of aggregation of contiguous census tracts which are homogeneous regarding socioeconomic indicators. Methodology: Local neighborhoods were created using the SKATER method (TerraView software). Criteria used for socioeconomic homogeneity were based on four census tract indicators (income, education, persons per household, and percentage of population in the 0-4-year age bracket) considering a minimum population of 5,000 people living in each local neighborhood. The process took into account the geographic boundaries between administrative neighborhoods (a political-administrative division larger than a local neighborhood, but smaller than a borough) and natural geographic barriers. Results: The original 8,145 census tracts were collapsed into 794 local neighborhoods, distributed along 158 administrative neighborhoods. Local neighborhoods contained a mean of 10 census tracts, and there were an average of five local neighborhoods per administrative neighborhood. The local neighborhood units demarcated in this study are less socioeconomically heterogeneous than the administrative neighborhoods and provide a means for decreasing the well-known statistical variability of indicators based on census tracts. The local neighborhoods were able to distinguish between different areas within administrative neighborhoods, particularly in relation to squatter settlements. Conclusion: Although the literature on neighborhood and health is increasing, little attention has been paid to criteria for demarcating neighborhoods. The proposed method is well-structured, available in open-access software, and easily reproducible, so we expect that new experiments will be conducted to evaluate its potential use in other settings. The method is thus a potentially important contribution to research on intra-urban differentials, particularly concerning contextual factors and their implications for different health outcomes.
Journal of Epidemiology & Community Health, 2001
Study objectives-To study geographical diVerences in diastolic blood pressure and the influence of the social environment (census percentage of people with low educational achievement) on individual diastolic blood pressure level, after controlling for individual age and educational achievement. To compare the results of multilevel and ecological analyses. Design-Cross sectional analysis performed by multilevel linear regression modelling, with women at the first level and urban areas at the second level, and by single level ecological regression using areas as the unit of analysis. Setting-Malmö, Sweden (population 250 000). Participants-15 569 women aged 45 to 73, residing in 17 urban areas, who took part in the Malmö Diet and Cancer Study (1991-1996). Main results-In the "fixed eVects" multilevel analysis, low educational achievement at both individual (=1.093, SE=0.167) and area levels (=2.966, SE=1.250) were independently associated with blood pressure, although in the "random eVects" multilevel analysis almost none of the total variability in blood pressure across persons was attributable to areas (intraclass corre-lation=0.3%). The ecological analysis also found an association between the area educational variable and mean diastolic blood pressure (=4.058, SE=1.345). Conclusions-The small intraclass correlation found indicated very marginal geographical diVerences and almost no influence of the urban area on individual blood pressure. However, these slight diVerences were enough to detect an eVect of the social environment on blood pressure. The ecological study overestimated the associations found in the "fixed" eVects multilevel analysis, and neither distinguished individual from area levels nor provided information on the intraclass correlation. Ecological analyses are inadequate to evaluate geographical differences in health.
Neighbourhood Research: Conceptual Considerations for Population Health
A population health approach recognizes that influences on health operate at many levels, one of which is the neighbourhoods in which people live. Neighbourhood health research is useful for guiding policy and interventions to improve population health status. There is much debate in the literature surrounding the concept of neighbourhood and there is wide variability in how neighbourhood studies are conducted. This paper argues that a population health approach can assist with clarification of the concept of neighbourhood.
Do perceived neighbourhood cohesion and safety contribute to neighbourhood differences in health
Health & Place, 2009
This paper reports on a survey (N ¼ 3344) and in-depth interviews (N ¼ 80) from four socioeconomically contrasting postcode areas in Adelaide. Logistic regression was used to examine locational differences in self-rated health, controlling for demographic, socio-economic factors, health behaviours, individual social capital (social networks, support, reciprocity, trust) and perceived neighbourhood cohesion and safety. Statistically significant locational differences in health emerged. Perceived neighbourhood cohesion and safety accounted for this difference. Interviews explored perceptions of cohesion and safety and found that they were intricately related and varied between the areas. The implications of the findings for understanding locational differences in health are discussed.
Neighborhood Effects on Health
Epidemiology, 2011
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.