Literature DB >> 22795359

Bringing the individual back to small-area variation studies: a multilevel analysis of all-cause mortality in Andalusia, Spain.

Juan Merlo1, Francisco J Viciana-Fernández, Diego Ramiro-Fariñas.   

Abstract

We performed a multilevel analysis (including individuals, households, census tracts, municipalities and provinces) on a 10% sample (N=230,978) from the Longitudinal Database of the Andalusian Population (LDAP). We aimed to investigate place effects on 8-year individual mortality risk. Moreover, besides calculating association (yielding odds ratios, ORs) between area socio-economic circumstances and individual risk, we wanted to estimate variance and clustering using the variance partition coefficient (VPC). We explicitly proclaim the relevance of considering general contextual effects (i.e. the degree to which the context, as a whole, affects individual variance in mortality risk) under at least two circumstances. The first of these concerns the interpretation of specific contextual effects (i.e. the association between a particular area characteristic and individual risk) obtained from multilevel regression analyses. The second involves the interpretation of geographical variance obtained from classic ecological spatial analyses. The so-called "ecological fallacy" apart, the lack of individual-level information renders geographical variance unrelated to the total individual variation and, therefore, difficult to interpret. Finally, we stress the importance of considering the familial household in multilevel analyses. We observed an association between percentage of people with a low educational level in the census tract and individual mortality risk (OR, highest v. lowest quintile=1.14; 95% confidence interval, CI 1.08-1.20). However, only a minor proportion of the total individual variance in the probability of dying was at the municipality (M) and census tract (CT) levels (VPC(M)=0.2% and VPC(CT)=0.3%). Conversely, the household (H) level appeared much more relevant (VPC(H)=18.6%) than the administrative geographical areas. Without considering general contextual effects, both multilevel analyses of specific contextual effects and ecological studies of small-area variation may provide a misleading picture that overstates the role of administrative areas as contextual determinants of individual differences in mortality.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22795359     DOI: 10.1016/j.socscimed.2012.06.004

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  31 in total

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4.  Does Maternal Country of Birth Matter for Understanding Offspring's Birthweight? A Multilevel Analysis of Individual Heterogeneity in Sweden.

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Journal:  PLoS One       Date:  2015-05-28       Impact factor: 3.240

5.  Geographic remoteness, area-level socioeconomic disadvantage and inequalities in colorectal cancer survival in Queensland: a multilevel analysis.

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6.  Early-life school, neighborhood, and family influences on adult health: a multilevel cross-classified analysis of the Aberdeen children of the 1950s study.

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7.  Area deprivation across the life course and physical capability in midlife: findings from the 1946 British Birth cohort.

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Journal:  Am J Epidemiol       Date:  2013-06-20       Impact factor: 4.897

8.  Health, policy and geography: insights from a multi-level modelling approach.

Authors:  Adriana Castelli; Rowena Jacobs; Maria Goddard; Peter C Smith
Journal:  Soc Sci Med       Date:  2013-05-31       Impact factor: 4.634

9.  Residential selection across the life course: adolescent contextual and individual determinants of neighborhood disadvantage in mid-adulthood.

Authors:  Per E Gustafsson; Miguel San Sebastian; Urban Janlert; Töres Theorell; Hugo Westerlund; Anne Hammarström
Journal:  PLoS One       Date:  2013-11-21       Impact factor: 3.240

10.  Adolescents' utilisation of psychiatric care, neighbourhoods and neighbourhood socioeconomic deprivation: a multilevel analysis.

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Journal:  PLoS One       Date:  2013-11-15       Impact factor: 3.240

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