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Invited Commentary: Multilevel Analysis of Individual Heterogeneity-A Fundamental Critique of the Current Probabilistic Risk Factor Epidemiology

Merlo, Juan LU (2014) In American Journal of Epidemiology 180(2). p.208-212
Abstract
In this issue of the Journal, Dundas et al. (Am J Epidemiol. 2014;180(2):197-207) apply a hitherto infrequent multilevel analytical approach: multiple membership multiple classification (MMMC) models. Specifically, by adopting a life-course approach, they use a multilevel regression with individuals cross-classified in different contexts (i.e., families, early schools, and neighborhoods) to investigate self-reported health and mental health in adulthood. They provide observational evidence suggesting the relevance of the early family environment for launching public health interventions in childhood in order to improve health in adulthood. In their analyses, the authors distinguish between specific contextual measures (i.e., the... (More)
In this issue of the Journal, Dundas et al. (Am J Epidemiol. 2014;180(2):197-207) apply a hitherto infrequent multilevel analytical approach: multiple membership multiple classification (MMMC) models. Specifically, by adopting a life-course approach, they use a multilevel regression with individuals cross-classified in different contexts (i.e., families, early schools, and neighborhoods) to investigate self-reported health and mental health in adulthood. They provide observational evidence suggesting the relevance of the early family environment for launching public health interventions in childhood in order to improve health in adulthood. In their analyses, the authors distinguish between specific contextual measures (i.e., the association between particular contextual characteristics and individual health) and general contextual measures (i.e., the share of the total interindividual heterogeneity in health that appears at each level). By doing so, they implicitly question the traditional probabilistic risk factor epidemiology including classical "neighborhood effects" studies. In fact, those studies use simple hierarchical structures and disregard the analysis of general contextual measures. The innovative MMMC approach properly responds to the call for a multilevel eco-epidemiology against a widespread probabilistic risk factors epidemiology. The risk factors epidemiology is not only reduced to individual-level analyses, but it also embraces many current "multilevel analyses" that are exclusively focused on analyzing contextual risk factors. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
analysis of variance, cross-classified multilevel models, family, life, course, neighborhood, probabilistic approach, risk factors, school
in
American Journal of Epidemiology
volume
180
issue
2
pages
208 - 212
publisher
Oxford University Press
external identifiers
  • wos:000339808700009
  • scopus:84903975476
ISSN
0002-9262
DOI
10.1093/aje/kwu108
language
English
LU publication?
yes
id
c8f59cba-fc67-4595-aa78-7572979c1dc2 (old id 4667836)
date added to LUP
2014-10-01 07:23:06
date last changed
2017-09-10 03:24:22
@misc{c8f59cba-fc67-4595-aa78-7572979c1dc2,
  abstract     = {In this issue of the Journal, Dundas et al. (Am J Epidemiol. 2014;180(2):197-207) apply a hitherto infrequent multilevel analytical approach: multiple membership multiple classification (MMMC) models. Specifically, by adopting a life-course approach, they use a multilevel regression with individuals cross-classified in different contexts (i.e., families, early schools, and neighborhoods) to investigate self-reported health and mental health in adulthood. They provide observational evidence suggesting the relevance of the early family environment for launching public health interventions in childhood in order to improve health in adulthood. In their analyses, the authors distinguish between specific contextual measures (i.e., the association between particular contextual characteristics and individual health) and general contextual measures (i.e., the share of the total interindividual heterogeneity in health that appears at each level). By doing so, they implicitly question the traditional probabilistic risk factor epidemiology including classical "neighborhood effects" studies. In fact, those studies use simple hierarchical structures and disregard the analysis of general contextual measures. The innovative MMMC approach properly responds to the call for a multilevel eco-epidemiology against a widespread probabilistic risk factors epidemiology. The risk factors epidemiology is not only reduced to individual-level analyses, but it also embraces many current "multilevel analyses" that are exclusively focused on analyzing contextual risk factors.},
  author       = {Merlo, Juan},
  issn         = {0002-9262},
  keyword      = {analysis of variance,cross-classified multilevel models,family,life,course,neighborhood,probabilistic approach,risk factors,school},
  language     = {eng},
  number       = {2},
  pages        = {208--212},
  publisher    = {Oxford University Press},
  series       = {American Journal of Epidemiology},
  title        = {Invited Commentary: Multilevel Analysis of Individual Heterogeneity-A Fundamental Critique of the Current Probabilistic Risk Factor Epidemiology},
  url          = {http://dx.doi.org/10.1093/aje/kwu108},
  volume       = {180},
  year         = {2014},
}