Browsing by Subject "Lifestyle factors"

Sort by: Order: Results:

Now showing items 1-3 of 3
  • Aghdassi, Ali A.; Schneider, Alexander; Kahl, Matthias; Schuette, Kerstin; Kuliaviene, Irma; Salacone, Paola; Lutz, Jon; Tukiainen, Eija; Simon, Peter; Schauer, Birgit; Uomo, Generoso; Hauge, Truls; Ceyhan, Gueralp O. (2017)
    Background & objectives: Chronic pancreatitis (CP) and liver cirrhosis (LC) are common gastroentero-logical disorders but their co-incidence is considered to be rare. This study was designed to identify lifestyle factors that are associated with the development of concomitant LC in patients with CP. Methods: In a retrospective case-control study between 2000 and 2005 122 patients with both CP and LC and 223 matched control patients with CP and no known liver disease were identified in 11 European university medical centers. Another 24 patients and 48 CP controls were identified in the period between 2006 and 2012. Results: Alcoholism was most commonly regarded as aetiology for both CP (82.2%; 95% confidence interval (CI): 75.0-88.0%) and LC (79.5%; 95% CI: 72.0-85.7%) as compared to controls with CP only (68.6%; 95% CI: 62.7-74.1%). The preferred type of alcoholic beverage and pattern of alcohol intake were the only significant lifestyle factors in multivariate analysis. Frequency of alcohol intake (p = 0.105) and smoking status (p = 0.099) were not significant in bivariate analysis and dropped out of the multivariate model. Recurrent and chronic pancreatic pain was observed more often in patients with only CP, whereas gallstones were more common in individuals with both chronic disorders. Conclusions: These findings indicate that certain lifestyle factors might be important for the development of concomitant CP and LC. More studies will be needed to identify additional genetic and environmental factors underlying this association. (C) 2017 IAP and EPC. Published by Elsevier B.V. All rights reserved.
  • van der Lee, Sven J.; Teunissen, Charlotte E.; Pool, Rene; Shipley, Martin J.; Teumer, Alexander; Chouraki, Vincent; van Lent, Debora Melo; Tynkkynen, Juho; Fischer, Krista; Hernesniemi, Jussi; Haller, Toomas; Singh-Manoux, Archana; Verhoeven, Aswin; Willemsen, Gonneke; de Leeuw, Francisca A.; Wagner, Holger; van Dongen, Jenny; Hertel, Johannes; Budde, Kathrin; van Dijk, Ko Willems; Weinhold, Leonie; Ikram, M. Arfan; Pietzner, Maik; Perola, Markus; Wagner, Michael; Friedrich, Nele; Slagboom, P. Eline; Scheltens, Philip; Yang, Qiong; Gertzen, Robert E.; Egert, Sarah; Li, Shuo; Hankemeier, Thomas; van Beijsterveldt, Catharina E. M.; Vasan, Ramachandran S.; Maier, Wolfgang; Peeters, Carel F. W.; Grabe, Hans Joergen; Ramirez, Alfredo; Seshadri, Sudha; Metspalu, Andres; Kivimäki, Mika; Salomaa, Veikko; Demirkan, Ayse; Boomsma, Dorret I.; van der Flier, Wiesje M.; Amin, Najaf; van Duijn, Cornelia M. (2018)
    Introduction: Identifying circulating metabolites that are associated with cognition and dementia may improve our understanding of the pathogenesis of dementia and provide crucial readouts for preventive and therapeutic interventions. Methods: We studied 299 metabolites in relation to cognition (general cognitive ability) in two discovery cohorts (N total = 5658). Metabolites significantly associated with cognition after adjusting for multiple testing were replicated in four independent cohorts (N total = 6652), and the associations with dementia and Alzheimer's disease (N = 25,872) and lifestyle factors (N = 5168) were examined. Results: We discovered and replicated 15 metabolites associated with cognition including subfractions of high-density lipoprotein, docosahexaenoic acid, ornithine, glutamine, and glycoprotein acetyls. These associations were independent of classical risk factors including high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, glucose, and apolipoprotein E (APOE) genotypes. Six of the cognition-associated metabolites were related to the risk of dementia and lifestyle factors. Discussion: Circulating metabolites were consistently associated with cognition, dementia, and lifestyle factors, opening new avenues for prevention of cognitive decline and dementia. (C) 2018 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer's Association.
  • Vornanen, Marleena; Konttinen, Hanna; Peltonen, Markku; Haukkala, Ari (2021)
    Background Perceived disease risk may reflect actual risk indicators and/or motivation to change lifestyle. Yet, few longitudinal studies have assessed how perceived risk relates to risk indicators among different disease risk groups. We examined in a 5-year follow-up, whether perceived risks of diabetes and cardiovascular disease predicted physical activity, body mass index (BMI kg/m(2)), and blood glucose level, or the reverse. We examined further whether perceived risk, self-efficacy, and outcome beliefs together predicted changes in these risk indicators. Method Participants were high diabetes risk participants (N = 432) and low/moderate-risk participants (N = 477) from the national FINRISK 2002 study who were followed up in 2007. Both study phases included questionnaires and health examinations with individual feedback letters. Data were analyzed using gender- and age-adjusted structural equation models. Results In cross-lagged autoregressive models, perceived risks were not found to predict 5-year changes in physical activity, BMI, or 2-h glucose. In contrast, higher BMI and 2-h glucose predicted 5-year increases in perceived risks (beta-values 0.07-0.15,P-values <0.001-0.138). These associations were similar among high- and low/moderate-risk samples. In further structural equation models, higher self-efficacy predicted increased physical activity among both samples (beta-values 0.10-0.16,P-values 0.005-0.034). Higher outcome beliefs predicted lower BMI among the low/moderate-risk sample (beta-values - 0.04 to - 0.05,P-values 0.008-0.011). Conclusion Perceived risk of chronic disease rather follows risk indicators than predicts long-term lifestyle changes. To promote sustained lifestyle changes, future intervention studies need to examine the best ways to combine risk feedback with efficient behavior change techniques.