Relationship between cigarette smoking and abdominal obesity

Background: Although smokers tend to have a lower body-mass index (BMI) than non-smokers, smoking may affect body fat (BF) distribution. Some studies have assessed the association between smoking, BMI and waist circumference (WC), but, to our knowledge, no population-based studies assessed the relation between smoking and BF composition. We assessed the association between amount of cigarette smoking, BMI, WC and BF composition. Method: Data was analysed from a cross-sectional population-based study including 6'187 Caucasians aged 32-76 and living in Switzerland. Height, weight and WC were measured. BF, expressed in percent of total body weight, was measured by electrical bioimpedance. Abdominal obesity was defined as a WC 0102 cm for men and 088 cm for women and normal WC as <94 cm for men and <80 cm for women. In men, excess BF was defined as %BF 028.1, 28.7, 30.6 and 32.6 for age groups 32-44, 45-54, 55-64 and 65-76, respectively; the corresponding values for women were 35.9, 36.5, 40.5 and 44.4. Cigarette smoking was assessed using a self-reported questionnaire. Results: 29.3% of men and 25.0% of women were smokers. Prevalence of obesity, abdominal obesity, and excess of BF was 16.9% and 26.6% and 14.2% in men and 15.0%, 33.0% and 27.5% in women, respectively. Smokers had lower age-adjusted mean WC and percent of BF compared to non-smokers. However, among smokers, mean age-adjusted WC and BF increased with the number of cigarettes smoked per day: among light (1-10 cig/day), moderate (11-20) and heavy smokers (>20), mean ± SE %BF was 22.4 ± 0.3, 23.1 ± 0.3 and 23.5 ± 0.4 for men, and 31.9 ± 0.3, 32.6 ± 0.3 and 32.9 ± 0.4 for women, respectively. Mean WC was 92.9 ± 0.6, 94.0 ± 0.5 and 96.0 ± 0.6 cm for men, and 80.2 ± 0.5, 81.3 ± 0.5 and 83.3 ± 0.7 for women, respectively. Compared with light smokers, the age-adjusted odds ratio (95% Confidence Interval) for excess of BF was 1.04 (0.58 to 1.85) for moderate smokers and 1.06 (0.57 to 1.99) for heavy smokers in men (p-trend = 0.9), and 1.35 (0.92 to 1.99) and 2.26 (1.38 to 3.72), respectively, in women (p-trend = 0.04). Odds ratio for abdominal obesity vs. normal WC was 1.32 (0.81 to 2.15) for moderate smokers and 1.95 (1.16 to 3.27) for heavy smokers in men (p-trend <0.01), and 1.15 (0.79 to 1.69) and 2.36 (1.41 to 3.93) in women (p-trend = 0.03). Conclusion: WC and BF were positively and dose-dependently associated with the number of cigarettes smoked per day in women, whereas only WC was dose dependently and significantly associated with the amount of cigarettes smoked per day in men. This suggests that heavy smokers, especially women, are more likely to have an excess of BF and to accumulate BF in the abdomen compared to lighter smokers.

No interaction between alcohol consumption and HDL-related genes on HDL cholesterol levels.

OBJECTIVE: To assess the relationships and possible interactions between polymorphisms related to HDL levels and alcohol consumption. METHODS: Cross-sectional population-based study including 2863 women and 2546 men aged 35-75 years (CoLaus study). Alcohol intake was assessed by the reported alcohol consumption of the last 7 days. Nineteen candidate genes known to influence HDL levels were studied. RESULTS: Alcohol consumption increased HDL cholesterol levels in both genders. After multivariate adjustment for gender, age, body mass index, smoking, hypolipidaemic drug treatment, physical activity and alcohol consumption, APOA5, CETP, LIPC and LPL gene polymorphisms were significantly (10(-5) threshold) related with HDL cholesterol levels, while no genexalcohol intake interaction was found for all SNPs studied. ABCA1 polymorphisms were related to HDL cholesterol levels on bivariate analysis but the relationship was no longer significant after multivariate analysis. CONCLUSION: Our data confirm the association of alcohol consumption and of APOA5, CETP, LIPC and LPL gene polymorphisms with HDL cholesterol levels. Conversely, no genexalcohol consumption interactions were found, suggesting that the effect of alcohol consumption on HDL cholesterol levels is not mediated via a modulation of HDL related genes.

Prevalence of the metabolic syndrome in the Seychelles according to different definitions, contribution of components, and agreement between different definitions

Background: The metabolic syndrome (MS) represents a cluster of metabolic disorders that predicts diabetes and cardiovascular disease. Several definitions exist and further descriptive and prospective data are needed to compare these definitions and their significance in different populations. Objective: We examined, in a country of the African region, i) the prevalence of MS according to three major definitions (ATP, IDF, WHO); ii) the contribution of individual MS components; and iii) the agreement between the three considered definitions. We also examined the prevalence among diabetics and non-diabetics. Methods: We conducted an examination survey in a sample representative of the general population aged 25-64 of the Seychelles (Indian Ocean, African region), attended by 1255 persons (participation rate of 80.2%). Results: The prevalence of MS was similar with either definition of MS in men (24%--25%) but differed in women (WHO: 25%, ATP: 32%; IDF: 35%). Upon exclusion of diabetic persons, the prevalence was 5-10% lower for all three MS definitions: most diabetic persons had MS although a substantial proportion of diabetic men aged 45--64 did not have MS. The following components were found most often among persons with MS: 90% had high blood pressure (HBP) and 78% had obesity (ATP); 95% had obesity and 84% had HBP (WHO), and 89% had HBP and 75% had impaired glucose regulation (IDF) - not considering impaired glucose regulation and obesity that are compulsory components of the WHO and IDF definitions, respectively. Among persons with MS based on either of the three definitions (37% of total population), less than 80% met both ATP and IDF criteria, 67% both WHO and IDF criteria, 54% both WHO and ATP criteria and only 37% met all three definitions. Conclusion: We found a fairly high prevalence of MS in an African population. However, because there was only poor agreement between the 3 MS definitions, the fairly similar proportions of MS based on ATP, IDF or WHO definitions identified, to a substantial extent, different subjects as having MS.

Prevalence, awareness, treatment and control of hypertension in a Swiss general population: the CoLaus Study

Objective: To assess the prevalence levels of awareness, treatment and control of hypertension and associated factors in Switzerland. Methods: Population-based cross-sectional study of 6,182 subjects (52.5% women) aged 35-75 years living in Lausanne, Switzerland. Hypertension was defined as blood pressure ≥140/90 mm Hg or current antihypertensive medication. Results: The overall prevalence of hypertension was 36% (95% CI: 35-38%). Among hypertensive participants, 63% were aware of having hypertension. Among aware hypertensives, 78% were treated, and among treated hypertensives 48% were controlled (BP <140/90 mmHg). In multivariate analysis, prevalence of hypertension was associated with older age, male gender, low educational level, high alcohol intake, awareness of diabetes, awareness of dyslipidaemia, obesity and parental history of myocardial infarction (MI). Awareness of hypertension was associated with older age, female gender, awareness of diabetes, awareness of dyslipidaemia, obesity and parental history of MI. Control was associated with younger age, higher educational level and no alcohol intake. Alone or in combination, sartans were the most often prescribed antihypertensive medication category (41%), followed by diuretics, beta-blockers, ACE inhibitors and calcium channel blockers. Only 31% of treated hypertensives were taking ≥2 antihypertensive medications. Conclusion: Although more than half of the participants with hypertension were aware of being hypertensive and more than three quarters of them received a pharmacological treatment, less than half of those treated were adequately controlled. Treated hypertensive subjects should be followed up more closely.

Pathology as the Cornerstone of Human Tissue Banking: European Consensus Expert Group Report

Aside from ethical considerations, the primary requirement for usage of human tissues in basic or translational research is the thorough characterization of tissues. The second, but equally essential, requirement is that tissues be collected, processed, annotated, and preserved in optimal conditions. These requirements put the pathologist at the center of tissue banking activities and of research aimed at discovering new biomarkers. Pathologists not only provide information identifying the specimen but also make decisions on what materials should be biobanked, on the preservation conditions, and on the timeline of events that precede preservation and storage. This central position calls for increased recognition of the role of the pathologist by the biomolecular community and places new demands on the pathologist's workload and scope of scientific activities. These questions were addressed by an Expert Group Meeting of the European Biological and Biomolecular Research Infrastructure (BBMRI). While detailed recommendations are published elsewhere (Bevilacqua et al., Virchows Archivs, 2010, in press), this article outlines the strategic and technological issues identified by the Expert Group and identifies ways forward for better integration of pathology in the current thrust for development of biomarker-based "personalized medicine.

Table de transcodage des opérations : VESKA (version 1979) - ICD-9-CM

Travaux effectués dans le cadre de l'étude "Case Mix" menée par l'Institut universitaire de médecine sociale et préventive de Lausanne et le Service de la santé publique et de la planification sanitaire du canton de Vaud, en collaboration avec les cantons de Berne, Fribourg, Genève, Jura, Neuchâtel, Soleure, Tessin et Valais.

Differences in self-reported prevalence and management of cardiovascular risk factors in Switzerland, 2007

Purpose: To assess the prevalence of four self-reported cardiovascular risk factors (CV RFs: smoking, hypertension, dyslipidaemia and diabetes) and their reported management in seven Swiss regions (Léman, MiUelland, Zurich, North-West Switzerland, Oriental Switzerland, Central Switzerland and Tessin). Methods: National health interview survey conducted in 2007 in a representative sample of the Swiss population (17,879 subjects). Age-adjusted data on prevalence of self-reported CV RFs, treatment among participants reporting a RF, control of RFs among treated participants and CV RF screening in the last 12 months levels were computed after weighting. Results: The prevalence of hypertension was highest in North-West Switzerland (27.3%) and lowest in Central Switzerland (21.0%, p<0.001). Antihypertensive treatment was highest in Léman region (62.7%) and lowest in Oriental Switzerland (55.2%, p<0.001). Screening was higher in Tessin (89.3%) and lowest in Léman region (81.8%, p<0.001). Prevalence of dyslipidaemia was highest in Tessin and Léman region (20.7% and 20.1 %, respectively) and lowest in Oriental Switzerland (14.5%, p<0.001). Lipid-Iowering treatment was highest in Tessin and Léman region (44.3% each) and lowest in Central Switzerland (30.7%, p<0.001). Dyslipidaemia screening was highest in Tessin (76.6%) and lowest in Central Switzerland (58.6%, p<0.001). Prevalence of diabetes was highest in North-West Switzerland (5.4%) and lowest in Central Switzerland (3.3%, p<0.05). Diabetes screening was highest in Tessin (78.1%) and lowest in Oriental Switzerland (64.0%, p<0.001). Conversely, no between-region differences were found for hypertension or dyslipidaemia control (see table). Conclusion: there are significant differences between the Swiss regions in self-reported prevalence and management of CV RFs. Screening is beUer in Tessin than in the other regions.

Swiss survey on salt intake: main results

[Contents] 1. Executive summary. 2. Introduction. 3. Methods. 4. Main results. 4.1. Participants. 4.2. Estimation of dietary salt intake using 24-hour urine collection. 4.3. Blood pressure and hypertension. 4.4. Anthropometric data (Body weight, height and body mass index BMI; prevalence of overweight and obesity; waist circumference;...). 4.5. Knowledge and behaviors towards salt. 5. Discussion.