Kalliope
Senior Member (Voting Rights)
Now published - link here
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Preprint
Research Square
Socioeconomic determinants of myalgic encephalomyelitis/chronic fatigue syndrome in Norway: a registry study
Abstract
Background: Previous research has shown that socioeconomic status (SES) is a strong predictor of chronic disease. However, to the best of our knowledge, there has been no studies of how SES affects the risk of Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) that has not been based upon self-reporting or retrospectively screening of symptoms. As far as we know, this is therefore the rst study that isolate and describe socioeconomic determinants of ME/CFS and calculate how these factors relate to the risk of ME/CFS diagnosis by utilizing individual level registry data, which allows for objective operationalization of the ME/CFS population, and the utilization of different control groups.
Data and methods: We utilize health registry data from all adult patients diagnosed with ME/CFS from 2016-2018 in Norway, coupled with socioeconomic data from statistics Norway from 2009-2018. We operationalize SES as household income and educational attainment xed at the beginning of the study period. We compare the effects of SES on the risk of ME/CFS diagnosis to a population of patients with hospital diagnoses that share clinical characteristics of ME/CFS and a healthy random sample of the Norwegian population. Our models are estimated by logistic regression analyses.
Results: When comparing the risk of ME/CFS diagnosis with a population consisting of people with four specic chronic diseases, we nd that high educational attainment is associated with a 19% increase (OR: 1.19) in the risk of ME/CFS and that high household income is associated with a 18% increase (OR:0.82) in risk of ME/CFS. In model 2, when comparing with a healthy population sample, we nd that low educational attainment is associated with 69% decrease (OR:0.31) in the risk of ME/CFS and that low household income is associated with a 53% increase (OR: 1.53).
Conclusion: We nd statistically signicant associations between SES and the risk of ME/CFS. However, our more detailed analyses shows that our ndings vary according to which population we compare the ME/CFS patients with, and that the effect of SES is larger when comparing with a healthy population sample, as opposed to controls with selected hospital diagnoses.
*******
Preprint
Research Square
Socioeconomic determinants of myalgic encephalomyelitis/chronic fatigue syndrome in Norway: a registry study
Abstract
Background: Previous research has shown that socioeconomic status (SES) is a strong predictor of chronic disease. However, to the best of our knowledge, there has been no studies of how SES affects the risk of Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) that has not been based upon self-reporting or retrospectively screening of symptoms. As far as we know, this is therefore the rst study that isolate and describe socioeconomic determinants of ME/CFS and calculate how these factors relate to the risk of ME/CFS diagnosis by utilizing individual level registry data, which allows for objective operationalization of the ME/CFS population, and the utilization of different control groups.
Data and methods: We utilize health registry data from all adult patients diagnosed with ME/CFS from 2016-2018 in Norway, coupled with socioeconomic data from statistics Norway from 2009-2018. We operationalize SES as household income and educational attainment xed at the beginning of the study period. We compare the effects of SES on the risk of ME/CFS diagnosis to a population of patients with hospital diagnoses that share clinical characteristics of ME/CFS and a healthy random sample of the Norwegian population. Our models are estimated by logistic regression analyses.
Results: When comparing the risk of ME/CFS diagnosis with a population consisting of people with four specic chronic diseases, we nd that high educational attainment is associated with a 19% increase (OR: 1.19) in the risk of ME/CFS and that high household income is associated with a 18% increase (OR:0.82) in risk of ME/CFS. In model 2, when comparing with a healthy population sample, we nd that low educational attainment is associated with 69% decrease (OR:0.31) in the risk of ME/CFS and that low household income is associated with a 53% increase (OR: 1.53).
Conclusion: We nd statistically signicant associations between SES and the risk of ME/CFS. However, our more detailed analyses shows that our ndings vary according to which population we compare the ME/CFS patients with, and that the effect of SES is larger when comparing with a healthy population sample, as opposed to controls with selected hospital diagnoses.
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