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      The role of lifestyle factors in the association between education and self-reported fibromyalgia: a mediation analysis

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          Abstract

          Background

          Socioeconomic status as measured by education, income, or occupation, has been associated with fibromyalgia but the underlying mechanism and the role of lifestyle factors are unclear. Thus, we examine the role of modifiable lifestyle factors (body mass index, physical activity, alcohol consumption and smoking) in the association between education and self-reported fibromyalgia.

          Methods

          We used data from 74,157 participants in the population-based prospective Norwegian Women and Cancer (NOWAC) study. Socioeconomic position, operationalized as years of educational attainment, and lifestyle factors were assessed via self-reported questionnaires. Multiple mediation analysis was used to decompose total effects into direct and indirect effects. Estimates were reported as hazard ratios (HRs) with 95% confidence intervals (CIs).

          Results

          The cumulative incidence of fibromyalgia was 3.2% after a median follow up time of 13 years. Fibromyalgia was inversely associated with years of educational attainment for ≤ 9 years (HR = 2.56; 95% CI 2.32–2.91) and for 10–12 years (HR = 1.84; 95% CI 1.72–2.02), compared with ≥ 13 years of education. Overall, all lifestyle factors together jointly mediated 17.3% (95% CI 14.3–21.6) and 14.1% (95% CI 11.3–18.9) of the total effect for ≤ 9 years and 10–12 years of education, respectively. Smoking and alcohol consumption contributed the most to the proportion mediated, for ≤ 9 years (5.0% and 7.0%) and 10–12 years (5.6% and 4.5%) of education.

          Conclusion

          The association between education and self-reported fibromyalgia was partly explained through lifestyle factors, mainly smoking and alcohol consumption.

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          Most cited references40

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          Indicators of socioeconomic position (part 1).

          This glossary presents a comprehensive list of indicators of socioeconomic position used in health research. A description of what they intend to measure is given together with how data are elicited and the advantages and limitation of the indicators. The glossary is divided into two parts for journal publication but the intention is that it should be used as one piece. The second part highlights a life course approach and will be published in the next issue of the journal.
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            Socioeconomic Inequalities in Health in 22 European Countries

            Comparisons among countries can help to identify opportunities for the reduction of inequalities in health. We compared the magnitude of inequalities in mortality and self-assessed health among 22 countries in all parts of Europe. We obtained data on mortality according to education level and occupational class from census-based mortality studies. Deaths were classified according to cause, including common causes, such as cardiovascular disease and cancer; causes related to smoking; causes related to alcohol use; and causes amenable to medical intervention, such as tuberculosis and hypertension. Data on self-assessed health, smoking, and obesity according to education and income were obtained from health or multipurpose surveys. For each country, the association between socioeconomic status and health outcomes was measured with the use of regression-based inequality indexes. In almost all countries, the rates of death and poorer self-assessments of health were substantially higher in groups of lower socioeconomic status, but the magnitude of the inequalities between groups of higher and lower socioeconomic status was much larger in some countries than in others. Inequalities in mortality were small in some southern European countries and very large in most countries in the eastern and Baltic regions. These variations among countries appeared to be attributable in part to causes of death related to smoking or alcohol use or amenable to medical intervention. The magnitude of inequalities in self-assessed health also varied substantially among countries, but in a different pattern. We observed variation across Europe in the magnitude of inequalities in health associated with socioeconomic status. These inequalities might be reduced by improving educational opportunities, income distribution, health-related behavior, or access to health care. Copyright 2008 Massachusetts Medical Society.
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              Indicators of socioeconomic position (part 2).

              This is the second part of a glossary on indicators of socioeconomic position used in health research (the first part was published in the January issue of the journal).
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                Author and article information

                Contributors
                faith.o.benebo@uit.no
                Journal
                BMC Womens Health
                BMC Womens Health
                BMC Women's Health
                BioMed Central (London )
                1472-6874
                17 April 2024
                17 April 2024
                2024
                : 24
                : 244
                Affiliations
                [1 ]Department of Community Medicine, UiT The Artic University of Norway, ( https://ror.org/00wge5k78) Tromsø, Norway
                [2 ]Department of Health and Care Sciences, UiT The Arctic University of Norway, ( https://ror.org/00wge5k78) Tromsø, Norway
                Article
                3060
                10.1186/s12905-024-03060-9
                11022321
                38632566
                8e43afd9-b74d-418d-ac12-c3b671704661
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 9 August 2023
                : 28 March 2024
                Funding
                Funded by: UiT The Arctic University of Norway (incl University Hospital of North Norway)
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Obstetrics & Gynecology
                fibromyalgia,lifestyle factors,mediation analyses,body mass index,physical activity,smoking,alcohol consumption,socioeconomic position,education

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