Robustness in health research: do differences in health measures, techniques, and time frame matter?

TitleRobustness in health research: do differences in health measures, techniques, and time frame matter?
Publication TypeJournal Article
Year of Publication2008
AuthorsFrijters, P, Ulker, A
JournalJ Health Econ
Volume27
Issue6
Pagination1626-44
Date Published2008 Dec
ISSN Number0167-6296
Call Numbernewpubs20081205_NCER_WpNo28Jul08.pdf
KeywordsAged, Algorithms, Australia, Data Interpretation, Statistical, Female, Health Behavior, Health Services Research, Health Status Indicators, Humans, Male, Middle Aged, Morbidity, Mortality, Social Class
Abstract

Survey-based health research is in a boom phase following an increased amount of health spending in OECD countries and the interest in ageing. A general characteristic of survey-based health research is its diversity. Different studies are based on different health questions in different datasets; they use different statistical techniques; they differ in whether they approach health from an ordinal or cardinal perspective; and they differ in whether they measure short-term or long-term effects. The question in this paper is simple: do these differences matter for the findings? We investigate the effects of life-style choices (drinking, smoking, exercise) and income on six measures of health in the US Health and Retirement Study (HRS) between 1992 and 2002: (1) self-assessed general health status, (2) problems with undertaking daily tasks and chores, (3) mental health indicators, (4) BMI, (5) the presence of serious long-term health conditions, and (6) mortality. We compare ordinal models with cardinal models; we compare models with fixed effects to models without fixed-effects; and we compare short-term effects to long-term effects. We find considerable variation in the impact of different determinants on our chosen health outcome measures; we find that it matters whether ordinality or cardinality is assumed; we find substantial differences between estimates that account for fixed effects versus those that do not; and we find that short-run and long-run effects differ greatly. All this implies that health is an even more complicated notion than hitherto thought, defying generalizations from one measure to the others or one methodology to another.

Notes

PMID: 18639357

DOI10.1016/j.jhealeco.2008.06.003
User Guide Notes

http://www.ncbi.nlm.nih.gov/pubmed/18639357?dopt=Abstract

Endnote Keywords

Health Surveys/Methodology

Endnote ID

19530

Alternate JournalJ Health Econ
Citation Key7254
PubMed ID18639357