A simple multilevel approach for analysing geographical inequalities in public health reports: : The case of municipality differences in obesity
(2019) In Health & Place 58.- Abstract
- The epidemiological analysis of geographical inequalities in individual outcomes is a fundamental theme in public health research. However, many traditional studies focus on analysing area differences in averages outcomes, disregarding individual variation around such averages. In doing so, these studies may produce misleading information and lead researchers to draw incorrect conclusions. Analysing individual and municipality differences in body mass index (BMI) and overweight/obesity status, we apply an analytical approach based on the multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). This analytical approach may be viewed as a reorganization of existing multilevel modelling concepts in order to... (More)
- The epidemiological analysis of geographical inequalities in individual outcomes is a fundamental theme in public health research. However, many traditional studies focus on analysing area differences in averages outcomes, disregarding individual variation around such averages. In doing so, these studies may produce misleading information and lead researchers to draw incorrect conclusions. Analysing individual and municipality differences in body mass index (BMI) and overweight/obesity status, we apply an analytical approach based on the multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). This analytical approach may be viewed as a reorganization of existing multilevel modelling concepts in order to provide a systematic approach to simultaneously considering both differences between area averages and individual heterogeneity around those averages. In doing so, MAIHDA provides an improved approach to the quantification and understanding of geographical inequalities as compared with traditional approaches. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/221b3fcc-bd9e-4240-8cea-c30a2a2e7520
- author
- Merlo, Juan LU ; Wagner, Philippe LU and Leckie, George LU
- organization
- publishing date
- 2019-06-10
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Health & Place
- volume
- 58
- article number
- 102145
- publisher
- Elsevier
- external identifiers
-
- scopus:85066937264
- pmid:31195211
- ISSN
- 1873-2054
- DOI
- 10.1016/j.healthplace.2019.102145
- project
- Multilevel analysis of individual heterogeneity
- language
- English
- LU publication?
- yes
- id
- 221b3fcc-bd9e-4240-8cea-c30a2a2e7520
- date added to LUP
- 2019-06-17 08:32:40
- date last changed
- 2023-04-09 15:44:23
@article{221b3fcc-bd9e-4240-8cea-c30a2a2e7520, abstract = {{The epidemiological analysis of geographical inequalities in individual outcomes is a fundamental theme in public health research. However, many traditional studies focus on analysing area differences in averages outcomes, disregarding individual variation around such averages. In doing so, these studies may produce misleading information and lead researchers to draw incorrect conclusions. Analysing individual and municipality differences in body mass index (BMI) and overweight/obesity status, we apply an analytical approach based on the multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). This analytical approach may be viewed as a reorganization of existing multilevel modelling concepts in order to provide a systematic approach to simultaneously considering both differences between area averages and individual heterogeneity around those averages. In doing so, MAIHDA provides an improved approach to the quantification and understanding of geographical inequalities as compared with traditional approaches.}}, author = {{Merlo, Juan and Wagner, Philippe and Leckie, George}}, issn = {{1873-2054}}, language = {{eng}}, month = {{06}}, publisher = {{Elsevier}}, series = {{Health & Place}}, title = {{A simple multilevel approach for analysing geographical inequalities in public health reports: : The case of municipality differences in obesity}}, url = {{http://dx.doi.org/10.1016/j.healthplace.2019.102145}}, doi = {{10.1016/j.healthplace.2019.102145}}, volume = {{58}}, year = {{2019}}, }