BACKGROUND: Psoriasis (PS) has been suggested to be associated with the metabolic syndrome (MetS) in numerous studies with conflicting results. The vast majority of previous data were based on PS subjects from hospitals, and when based on data from the general population the PS subjects were often identified in insurance health databases. Furthermore, many studies used a single method approach, e.g. self-reported diagnosis. OBJECTIVE: We have therefore investigated a possible association between PS and MetS on PS subjects from the hospital as well as the general population using combined methods, i.e. self-reported diagnosis, physical examinations and blood samples. METHODS: A population- and hospital-based cross-sectional study of the possible association between PS and MetS. RESULTS: Thirty-six hospital PS subjects, 860 population PS subjects and 14,016 non-PS subjects were identified. The odds ratios (ORs) for hospital PS subjects and population PS subjects vs. population non-PS subjects, respectively, were 5.14 (2.47-10.69) and 1.29 (1.09-1.53) for MetS, 4.55 (1.91-10.85) and 1.16 (0.85-1.59) for diabetes, 1.92 (0.87-4.22) and 1.00 (0.86-1.17) for hypertension, 4.34 (1.86-10.10) and 1.15 (1.00-1.34) for hypertriglyceridaemia, 3.88 (1.96-7.69) and 1.19 (1.01-1.42) for hypoHDL, 5.77 (2.89-11.52) and 1.19 (1.00-1.41) for general obesity and 2.92 (1.45-5.88) and 1.34 (1.16-1.55) for abdominal obesity. Obesity acted as a possible confounder. A uniform pattern of higher ORs for hospital PS subjects when compared to population PS subjects was observed. The severity and duration of PS did not seem to affect the results. As this is a cross-sectional study we cannot demonstrate causality. CONCLUSION: The data suggested an association between PS and MetS as well as its individual parameters on a hospital-based level, with the exception of hypertension. On a population-based level the associations were only significant for MetS, hypoHDL and abdominal obesity.
BACKGROUND:Psoriasis (PS) has been suggested to be associated with the metabolic syndrome (MetS) in numerous studies with conflicting results. The vast majority of previous data were based on PS subjects from hospitals, and when based on data from the general population the PS subjects were often identified in insurance health databases. Furthermore, many studies used a single method approach, e.g. self-reported diagnosis. OBJECTIVE: We have therefore investigated a possible association between PS and MetS on PS subjects from the hospital as well as the general population using combined methods, i.e. self-reported diagnosis, physical examinations and blood samples. METHODS: A population- and hospital-based cross-sectional study of the possible association between PS and MetS. RESULTS: Thirty-six hospital PS subjects, 860 population PS subjects and 14,016 non-PS subjects were identified. The odds ratios (ORs) for hospital PS subjects and population PS subjects vs. population non-PS subjects, respectively, were 5.14 (2.47-10.69) and 1.29 (1.09-1.53) for MetS, 4.55 (1.91-10.85) and 1.16 (0.85-1.59) for diabetes, 1.92 (0.87-4.22) and 1.00 (0.86-1.17) for hypertension, 4.34 (1.86-10.10) and 1.15 (1.00-1.34) for hypertriglyceridaemia, 3.88 (1.96-7.69) and 1.19 (1.01-1.42) for hypoHDL, 5.77 (2.89-11.52) and 1.19 (1.00-1.41) for general obesity and 2.92 (1.45-5.88) and 1.34 (1.16-1.55) for abdominal obesity. Obesity acted as a possible confounder. A uniform pattern of higher ORs for hospital PS subjects when compared to population PS subjects was observed. The severity and duration of PS did not seem to affect the results. As this is a cross-sectional study we cannot demonstrate causality. CONCLUSION: The data suggested an association between PS and MetS as well as its individual parameters on a hospital-based level, with the exception of hypertension. On a population-based level the associations were only significant for MetS, hypoHDL and abdominal obesity.
Authors: Lenka Borska; Jan Kremlacek; Ctirad Andrys; Jan Krejsek; Kvetoslava Hamakova; Pavel Borsky; Vladimir Palicka; Vit Rehacek; Andrea Malkova; Zdenek Fiala Journal: Int J Mol Sci Date: 2017-10-25 Impact factor: 5.923
Authors: Hyun Ji Lee; Kyung Do Han; Hae Eun Park; Ju Hee Han; Chul Hwan Bang; Young Min Park; Ji Hyun Lee Journal: Sci Rep Date: 2021-12-15 Impact factor: 4.379