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Widespread and widely widening? Examining absolute socioeconomic health inequalities in northern Sweden across twelve health indicators

BACKGROUND: Socioeconomic inequalities in health is a widely studied topic. However, epidemiological research tends to focus on one or a few outcomes conditioned on one indicator, overlooking the fact that health inequalities can vary depending on the outcome studied and the indicator used. To bridg...

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Detalles Bibliográficos
Autores principales: Degerlund Maldi, Kinza, San Sebastian, Miguel, Gustafsson, Per E., Jonsson, Frida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6921510/
https://www.ncbi.nlm.nih.gov/pubmed/31852487
http://dx.doi.org/10.1186/s12939-019-1100-5
Descripción
Sumario:BACKGROUND: Socioeconomic inequalities in health is a widely studied topic. However, epidemiological research tends to focus on one or a few outcomes conditioned on one indicator, overlooking the fact that health inequalities can vary depending on the outcome studied and the indicator used. To bridge this gap, this study aims to provide a comprehensive picture of the patterns of socioeconomic health inequalities in Northern Sweden over time, across a range of health outcomes, using an ‘outcome-wide’ epidemiological approach. METHOD: Cross-sectional data from three waves of the ‘Health on Equal Terms’ survey, distributed in 2006, 2010 and 2014 were used. Firstly, socioeconomic inequalities by income and education for twelve outcomes (self-rated health, self-rated dental health, overweight, hypertension, diabetes, long-term illness, stress, depression, psychological distress, smoking, risky alcohol consumption, and physical inactivity) were examined by calculating the Slope Index of Inequality. Secondly, time trends for each outcome and socioeconomic indicator were estimated. RESULTS: Income inequalities increased for psychological distress and physical inactivity in men as well as for self-rated health, overweight, hypertension, long-term illness, and smoking among women. Educational inequalities increased for hypertension, long-term illness, and stress (the latter favouring lower education) in women. The only instance of decreasing income inequalities was seen for long-term illness in men, while education inequalities decreased for long-term illness in men and poor self-rated health, poor self-rated dental health, and smoking in women. CONCLUSION: Patterns of absolute socioeconomic inequalities in health vary by health and socioeconomic indicator, as well as between men and women. Overall, trends appear more stagnant in men while they fluctuate in women. Income inequalities seem to be generally greater than educational inequalities when looking across several different health indicators, a message that can only be derived from this type of outcome-wide study. These disparate findings suggest that generalised and universal statements about the development of health inequalities can be too simplistic and potentially misleading. Nonetheless, despite inequalities being complex, they do exist and tend to increase. Thus, an outcome-wide approach is a valuable method which should be utilised to generate evidence for prioritisations of policy decisions.