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Monitoring trends in socioeconomic health inequalities: it matters how you measure

BACKGROUND: Odds ratio (OR), a relative measure for health inequality, has frequently been used in prior studies for presenting inequality trends in health and health behaviors. Since OR is not a good approximation of prevalence ratio (PR) when the outcome prevalence is quite high, an important prob...

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Autores principales: Khang, Young-Ho, Yun, Sung-Cheol, Lynch, John W
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2266739/
https://www.ncbi.nlm.nih.gov/pubmed/18284701
http://dx.doi.org/10.1186/1471-2458-8-66
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author Khang, Young-Ho
Yun, Sung-Cheol
Lynch, John W
author_facet Khang, Young-Ho
Yun, Sung-Cheol
Lynch, John W
author_sort Khang, Young-Ho
collection PubMed
description BACKGROUND: Odds ratio (OR), a relative measure for health inequality, has frequently been used in prior studies for presenting inequality trends in health and health behaviors. Since OR is not a good approximation of prevalence ratio (PR) when the outcome prevalence is quite high, an important problem may arise when OR trends are used in data in which the outcome variable (e.g., smoking or ill-health) is of relatively high prevalence and varies significantly over time. This study is to compare time trends of odds ratio (OR) and prevalence ratio (PR) for examining time trends in socioeconomic inequality in smoking. METHODS: A total of 147,805 subjects (71,793 men and 76,017 women) aged 25–64 from three Social Statistics Surveys of Korea from 1999 to 2006 were analyzed. Socioeconomic position indicators were occupational class and education. RESULTS: While there were no significant p values for trend in ORs of occupational class among men, trends for PRs were significant. In women, p values for OR trends were similar to those for PR trends. In males, RII by log-binomial regression showed a significant increasing tendency while RII by logistic regression was stable between years. In females, trends of RIIs by logistic regression and log-binomial regression produced a similar level of p values. CONCLUSION: Different methods of measuring trends in socioeconomic health inequalities may lead to different conclusions about whether relative inequalities are increasing or decreasing. Trends in ORs may overstate or understate trends in relative inequality in health when the outcome is of relatively high prevalence and that prevalence varies significantly with time.
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spelling pubmed-22667392008-03-11 Monitoring trends in socioeconomic health inequalities: it matters how you measure Khang, Young-Ho Yun, Sung-Cheol Lynch, John W BMC Public Health Research Article BACKGROUND: Odds ratio (OR), a relative measure for health inequality, has frequently been used in prior studies for presenting inequality trends in health and health behaviors. Since OR is not a good approximation of prevalence ratio (PR) when the outcome prevalence is quite high, an important problem may arise when OR trends are used in data in which the outcome variable (e.g., smoking or ill-health) is of relatively high prevalence and varies significantly over time. This study is to compare time trends of odds ratio (OR) and prevalence ratio (PR) for examining time trends in socioeconomic inequality in smoking. METHODS: A total of 147,805 subjects (71,793 men and 76,017 women) aged 25–64 from three Social Statistics Surveys of Korea from 1999 to 2006 were analyzed. Socioeconomic position indicators were occupational class and education. RESULTS: While there were no significant p values for trend in ORs of occupational class among men, trends for PRs were significant. In women, p values for OR trends were similar to those for PR trends. In males, RII by log-binomial regression showed a significant increasing tendency while RII by logistic regression was stable between years. In females, trends of RIIs by logistic regression and log-binomial regression produced a similar level of p values. CONCLUSION: Different methods of measuring trends in socioeconomic health inequalities may lead to different conclusions about whether relative inequalities are increasing or decreasing. Trends in ORs may overstate or understate trends in relative inequality in health when the outcome is of relatively high prevalence and that prevalence varies significantly with time. BioMed Central 2008-02-20 /pmc/articles/PMC2266739/ /pubmed/18284701 http://dx.doi.org/10.1186/1471-2458-8-66 Text en Copyright © 2008 Khang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Khang, Young-Ho
Yun, Sung-Cheol
Lynch, John W
Monitoring trends in socioeconomic health inequalities: it matters how you measure
title Monitoring trends in socioeconomic health inequalities: it matters how you measure
title_full Monitoring trends in socioeconomic health inequalities: it matters how you measure
title_fullStr Monitoring trends in socioeconomic health inequalities: it matters how you measure
title_full_unstemmed Monitoring trends in socioeconomic health inequalities: it matters how you measure
title_short Monitoring trends in socioeconomic health inequalities: it matters how you measure
title_sort monitoring trends in socioeconomic health inequalities: it matters how you measure
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2266739/
https://www.ncbi.nlm.nih.gov/pubmed/18284701
http://dx.doi.org/10.1186/1471-2458-8-66
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