Which environmental factors are associated with lived health when controlling for biological health? - a multilevel analysis.
- Bostan C Department of Health Sciences and Health Policy, University of Lucerne, Lucerne, Switzerland. cristina.bostan@paraplegie.ch.
- Oberhauser C Department of Medical Informatics, Biometry and Epidemiology-IBE, Pettenkofer School of Public Health (PSPHLMU), Research Unit for Biopsychosocial Health, Ludwig Maximilian University (LMU), Munich, Germany. cornelia.oberhauser@med.uni-muenchen.de.
- Stucki G Department of Health Sciences and Health Policy, University of Lucerne, Lucerne, Switzerland. gerold.stucki@paraplegie.ch.
- Bickenbach J Department of Health Sciences and Health Policy, University of Lucerne, Lucerne, Switzerland. jerome.bickenbach@paraplegie.ch.
- Cieza A Swiss Paraplegic Research, Nottwil, Switzerland. a.cieza@soton.ac.uk.
- 2015-05-28
Published in:
- BMC public health. - 2015
Adult
Aged
Cross-Sectional Studies
Disability Evaluation
Disabled Persons
Employment
Environment
Female
Health Status
Humans
International Classification of Functioning, Disability and Health
Male
Middle Aged
Multilevel Analysis
Psychometrics
Residence Characteristics
Social Support
Spain
Surveys and Questionnaires
English
BACKGROUND
Lived health and biological health are two different perspectives of health introduced by the International Classification of Functioning, Disability and Health (ICF). Since in the concept of lived health the impact of the environment on biological health is inherently included, it seems intuitive that when identifying the environmental determinants of health, lived health is the appropriate outcome. The Multilevel Item Response Theory (MLIRT) model has proven to be a successful method when dealing with the relation between a latent variable and observed variables. The objective of this study was to identify environmental factors associated with lived health when controlling for biological health by using the MLIRT framework.
METHODS
We performed a psychometric study using cross-sectional data from the Spanish Survey on Disability, Independence and Dependency Situation. Data were collected from 17,303 adults living in 15,263 dwellings. The MLIRT model was used for each of the two steps of the analysis to: (1) calculate people's biological health abilities and (2) estimate the association between lived health and environmental factors when controlling for biological health. The hierarchical structure of individuals in dwellings was considered in both models.
RESULTS
Social support, being able to maintain one's job, the extent to which one's health needs are addressed and being discriminated against due to one's health problems were the environmental factors identified as associated with lived health. Biological health also had a strong positive association with lived health.
CONCLUSIONS
This study identified environmental factors associated with people's lived health differences within and between dwellings according to the MLIRT-model approach. This study paves the way for the future implementation of the MLIRT model when analysing ICF-based data.
Lived health and biological health are two different perspectives of health introduced by the International Classification of Functioning, Disability and Health (ICF). Since in the concept of lived health the impact of the environment on biological health is inherently included, it seems intuitive that when identifying the environmental determinants of health, lived health is the appropriate outcome. The Multilevel Item Response Theory (MLIRT) model has proven to be a successful method when dealing with the relation between a latent variable and observed variables. The objective of this study was to identify environmental factors associated with lived health when controlling for biological health by using the MLIRT framework.
METHODS
We performed a psychometric study using cross-sectional data from the Spanish Survey on Disability, Independence and Dependency Situation. Data were collected from 17,303 adults living in 15,263 dwellings. The MLIRT model was used for each of the two steps of the analysis to: (1) calculate people's biological health abilities and (2) estimate the association between lived health and environmental factors when controlling for biological health. The hierarchical structure of individuals in dwellings was considered in both models.
RESULTS
Social support, being able to maintain one's job, the extent to which one's health needs are addressed and being discriminated against due to one's health problems were the environmental factors identified as associated with lived health. Biological health also had a strong positive association with lived health.
CONCLUSIONS
This study identified environmental factors associated with people's lived health differences within and between dwellings according to the MLIRT-model approach. This study paves the way for the future implementation of the MLIRT model when analysing ICF-based data.
- Language
-
- English
- Open access status
- gold
- Identifiers
-
- DOI 10.1186/s12889-015-1834-y
- PMID 26012695
- Persistent URL
- https://sonar.ch/global/documents/19423
Statistics
Document views: 34
File downloads:
- Full-text: 0