Karin Jakobsson1, Lennart Jacobsson2, Kenneth Warrington1, Eric L Matteson1, Kimberly Liang1, Olle Melander1, Carl Turesson3. 1. Section of Rheumatology, Department of Clinical Sciences, Lund University, Malmö, Department of Rheumatology & Inflammation Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, MN, Division of Rheumatology and Clinical Immunology, University of Pittsburgh, Pittsburgh, PA, USA and Department of Clinical Sciences, Malmö, Lund University, Malmö, Sweden. 2. Section of Rheumatology, Department of Clinical Sciences, Lund University, Malmö, Department of Rheumatology & Inflammation Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, MN, Division of Rheumatology and Clinical Immunology, University of Pittsburgh, Pittsburgh, PA, USA and Department of Clinical Sciences, Malmö, Lund University, Malmö, Sweden. Section of Rheumatology, Department of Clinical Sciences, Lund University, Malmö, Department of Rheumatology & Inflammation Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, MN, Division of Rheumatology and Clinical Immunology, University of Pittsburgh, Pittsburgh, PA, USA and Department of Clinical Sciences, Malmö, Lund University, Malmö, Sweden. 3. Section of Rheumatology, Department of Clinical Sciences, Lund University, Malmö, Department of Rheumatology & Inflammation Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, MN, Division of Rheumatology and Clinical Immunology, University of Pittsburgh, Pittsburgh, PA, USA and Department of Clinical Sciences, Malmö, Lund University, Malmö, Sweden. carl.turesson@med.lu.se.
Abstract
OBJECTIVE: The aim of this study was to examine potential risk factors for GCA in a nested case-control study based on two prospective health surveys. METHODS: We used two population-based health surveys, the Malmö Preventive Medicine Program (MPMP) and the Malmö Diet Cancer Study (MDCS). Individuals who developed GCA after inclusion were identified by linking the MPMP and MDCS databases to several patient administrative registers. A structured review of the medical records of all identified cases was performed. Four controls for every confirmed case, matched for sex, year of birth and year of screening, were selected from the corresponding databases. Potential predictors of GCA were examined in conditional logistic regression models. RESULTS: Eighty-three patients (70% women, 64% biopsy positive, mean age at diagnosis 71 years) had a confirmed diagnosis of GCA after inclusion in the MPMP or MDCS. A higher BMI was associated with a significantly reduced risk of subsequent development of GCA [odds ratio (OR) 0.91/kg/m(2) (95% CI 0.84, 0.98)]. Smoking was not a risk factor for GCA overall [OR 1.36 (95% CI 0.77, 2.57)], although there was a trend towards an increased risk in female smokers [OR 2.14 (95% CI 0.97, 4.68)]. In multivariate analysis, adjusted for smoking and level of formal education, the inverse association between BMI and GCA remained significant (P = 0.027). CONCLUSION: In this study, GCA was predicted by a lower BMI at baseline. Potential explanations include an effect of reduced adipose tissue on hormonal pathways regulating inflammation.
OBJECTIVE: The aim of this study was to examine potential risk factors for GCA in a nested case-control study based on two prospective health surveys. METHODS: We used two population-based health surveys, the Malmö Preventive Medicine Program (MPMP) and the Malmö Diet Cancer Study (MDCS). Individuals who developed GCA after inclusion were identified by linking the MPMP and MDCS databases to several patient administrative registers. A structured review of the medical records of all identified cases was performed. Four controls for every confirmed case, matched for sex, year of birth and year of screening, were selected from the corresponding databases. Potential predictors of GCA were examined in conditional logistic regression models. RESULTS: Eighty-three patients (70% women, 64% biopsy positive, mean age at diagnosis 71 years) had a confirmed diagnosis of GCA after inclusion in the MPMP or MDCS. A higher BMI was associated with a significantly reduced risk of subsequent development of GCA [odds ratio (OR) 0.91/kg/m(2) (95% CI 0.84, 0.98)]. Smoking was not a risk factor for GCA overall [OR 1.36 (95% CI 0.77, 2.57)], although there was a trend towards an increased risk in female smokers [OR 2.14 (95% CI 0.97, 4.68)]. In multivariate analysis, adjusted for smoking and level of formal education, the inverse association between BMI and GCA remained significant (P = 0.027). CONCLUSION: In this study, GCA was predicted by a lower BMI at baseline. Potential explanations include an effect of reduced adipose tissue on hormonal pathways regulating inflammation.
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