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      Prevalence of metabolic syndrome in patients with psoriasis: A population-based study in the United Kingdom

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          Increasing epidemiological evidence suggests independent associations between psoriasis and cardiovascular and metabolic disease. Our objective was to test the hypothesis that directly-assessed psoriasis severity relates to the prevalence of metabolic syndrome and its components.

          Population-based, cross-sectional study using computerized medical records from The Health Improvement Network Study population included individuals aged 45-65 years with psoriasis and practice-matched controls. Psoriasis diagnosis and extent were determined using provider-based questionnaires. Metabolic syndrome was defined using National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III criteria.

          44,715 individuals were included: 4,065 with psoriasis and 40,650 controls. 2,044 participants had mild psoriasis (≤2% body surface area (BSA)), 1,377 had moderate (3-10% BSA), and 475 had severe psoriasis (>10% BSA). Psoriasis was associated with metabolic syndrome, adjusted odds ratio (OR) 1.41 (95% CI 1.31-1.51), varying in a “dose-response” manner, from mild (adj. OR 1.22, 95% CI 1.11-1.35) to severe psoriasis (adj. OR 1.98, 95% CI 1.62-2.43).

          Psoriasis is associated with metabolic syndrome and the association increases with increasing disease severity. Furthermore, associations with obesity, hypertriglyceridemia and hyperglycemia increase with increasing disease severity independent of other metabolic syndrome components. These findings suggest that screening for metabolic disease should be considered for psoriasis, especially when extensive.

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          Most cited references 24

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          Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001.

          Obesity and diabetes are increasing in the United States. To estimate the prevalence of obesity and diabetes among US adults in 2001. Random-digit telephone survey of 195 005 adults aged 18 years or older residing in all states participating in the Behavioral Risk Factor Surveillance System in 2001. Body mass index, based on self-reported weight and height and self-reported diabetes. In 2001 the prevalence of obesity (BMI > or =30) was 20.9% vs 19.8% in 2000, an increase of 5.6%. The prevalence of diabetes increased to 7.9% vs 7.3% in 2000, an increase of 8.2%. The prevalence of BMI of 40 or higher in 2001 was 2.3%. Overweight and obesity were significantly associated with diabetes, high blood pressure, high cholesterol, asthma, arthritis, and poor health status. Compared with adults with normal weight, adults with a BMI of 40 or higher had an odds ratio (OR) of 7.37 (95% confidence interval [CI], 6.39-8.50) for diagnosed diabetes, 6.38 (95% CI, 5.67-7.17) for high blood pressure, 1.88 (95% CI,1.67-2.13) for high cholesterol levels, 2.72 (95% CI, 2.38-3.12) for asthma, 4.41 (95% CI, 3.91-4.97) for arthritis, and 4.19 (95% CI, 3.68-4.76) for fair or poor health. Increases in obesity and diabetes among US adults continue in both sexes, all ages, all races, all educational levels, and all smoking levels. Obesity is strongly associated with several major health risk factors.
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            Causation and causal inference in epidemiology.

            Concepts of cause and causal inference are largely self-taught from early learning experiences. A model of causation that describes causes in terms of sufficient causes and their component causes illuminates important principles such as multi-causality, the dependence of the strength of component causes on the prevalence of complementary component causes, and interaction between component causes. Philosophers agree that causal propositions cannot be proved, and find flaws or practical limitations in all philosophies of causal inference. Hence, the role of logic, belief, and observation in evaluating causal propositions is not settled. Causal inference in epidemiology is better viewed as an exercise in measurement of an effect rather than as a criterion-guided process for deciding whether an effect is present or not.
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              Psoriasis and systemic inflammatory diseases: potential mechanistic links between skin disease and co-morbid conditions.

              Psoriasis is now classified as an immune-mediated inflammatory disease (IMID) of the skin. It is being recognized that patients with various IMIDs, including psoriasis, are at higher risk of developing "systemic" co-morbidities, e.g., cardiovascular disease (CVD), metabolic syndrome, and overt diabetes. In non-psoriatic individuals, the pathophysiology of obesity, aberrant adipocyte metabolism, diabetes, and CVDs involves immune-mediated or inflammatory pathways. IMIDs may impact these co-morbid conditions through shared genetic risks, common environmental factors, or common inflammatory pathways that are co-expressed in IMIDs and target organs. Given that pathogenic immune pathways in psoriasis are now well worked out and a large number of inflammatory mediators have been identified in skin lesions, in this review we will consider possible mechanistic links between skin inflammation and increased risks of (1) obesity or metabolic alterations and (2) CVD. In particular, we will discuss how well-established risk factors for CVD can originate from inflammation in other tissues.

                Author and article information

                J Invest Dermatol
                The Journal of Investigative Dermatology
                29 November 2011
                24 November 2011
                March 2012
                1 September 2012
                : 132
                : 3
                : 556-562
                [1 ]Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK
                [2 ]Department of Dermatology, University of Pennsylvania, Philadelphia, PA, USA
                [3 ]Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
                [4 ]Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
                [5 ]Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, USA
                Author notes
                Correspondence to: Dr Sinéad Langan, Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK. sinead.langan@ , Tel: +44 2079272680; Fax: +44 2075806897
                Funded by: National Heart, Lung, and Blood Institute : NHLBI
                Award ID: R01 HL089744-04 || HL
                Funded by: National Heart, Lung, and Blood Institute : NHLBI
                Award ID: R01 HL089744-03 || HL



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