Prevalence of overweight and obesity in the Swiss population

Introduction: The latest data on prevalence of overweight (OW) and obesity (OB) in the general Swiss resident population rely on the Swiss Health Survey (SHS), a telephonic interview performed in 2007. However, body mass index (BMI) is underestimated when self-reported, leading to a misclassification of up to 60% of obese subjects. The last survey with measured BMI performed in the 3 linguistic regions of Switzerland dates back to 1977. We explored the regional prevalences of OW and OB by measured BMI in the general Swiss resident population. Methods: Cross-sectional population-based survey in the 3 linguistic regions of Switzerland in 2010-2011. Data on 1471 participants aged 15-95 years (712 men, 759 women) were available for the analysis. BMI was calculated from measured height and weight and categorized into 3 groups according to WHO classification: lean (<25 kg/m2), overweight (25-30 kg/m2) and obese (>= 30 kg/m2). Data on medication, smoking, education, physical activity and dietary habitudes were collected using a questionnaire. Results: The overall prevalence of OW and OB was 32.1% and 13.9%, respectively. OB prevalence was similar across the 3 linguistic regions (13.5% in German-, 15.6% in French- and 12.0% in Italian-speaking Switzerland, p = 0.40), unlike OW prevalence, which significantly differed in unadjusted analyses (35.4%, 29.1% and 25.4%, respectively, p = 0.005). In analyses including age, sex, smoking, physical activity and education as covariates, living in the Italian-speaking region was associated neither with BMI (linear regression) nor with OW or OB (logistic regressions) . Age (beta coefficient [SE]: 0.064[0.006] kg/m2 per year, p <0.001) and sex (-1.76 [0.23] kg/m2 in women, p <0.001) were significantly associated with BMI. Conclusions: Overweight and obesity affect nearly half of the Swiss population aged >15 years. We observed no significant differences across regions once we accounted for age, sex, education and lifestyle. Public health interventions addressing modifiable behavioral factors to reduce overweight and obesity in Switzerland can be expected to have substantial benefits.

Obesity in Switzerland: a critical assessment of prevalence in children and adults.

The objective was to analyze the situation in Switzerland regarding the prevalence of overweight or obesity in children, adolescents and adults. The data were compared with France, an adjacent much larger country. The results showed that there is a definitive lack of objective information in Switzerland on the prevalence of obesity at different ages. As in other European studies, the fact that many national surveys are classically based on subject interviews (self-reported weights and heights rather than measured values) implies that the overweight/obesity prevalence is largely underestimated in adulthood. For example, in a recent Swiss epidemiological study, the prevalence of obesity (BMI greater than 30 kg/m(2)) averaged 6-7% in young men and women (25-34 y), the prevalence being underestimated by a factor of two to three when body weight was self-reported rather than measured. This phenomenon has already been observed in previous European studies. It is concluded that National Surveys based on telephone interviews generally produce biased obesity prevalence results, although the direction of the changes in prevalence of obesity and its evolution with repeated surveys using strict standardized methodology may be evaluated correctly. Therefore, these surveys should be complemented by large-scale epidemiological studies (based on measured anthropomeric variables rather than declared) covering the different linguistic areas of Switzerland. An epidemiological body weight (BMI) monitoring surveillance system, using a harmonized methodology among European countries, would help to accurately assess differences in obesity prevalence across Europe without methodological bias. It will permit monitoring of the dynamic evolution of obesity prevalence as well as the development of appropriate strategies (taking into account the specificity of each country) for obesity prevention and treatment.

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. METHODS: Data was analysed from a cross-sectional population-based study including 6187 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. Obesity was defined as a BMI>=30 kg/m2 and normal weight as a BMI<25 kg/m2. Abdominal obesity was defined as a WC>=102 cm for men and >=88 cm for women and normal WC as <94 cm for men and <80 cm for women. In men, excess BF was defined as %BF >=28.1, 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 BMI, WC and percent of BF compared to non-smokers. However, among smokers,mean age-adjusted BMI,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. Mean BMI was 25.7+/−0.2, 26.0+/−0.2, and 26.1+/−0.2 kg/m2 for men; and 23.6+/−0.2, 24.0+/−0.2 and 24.1+/−0.3 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) formoderatesmokers 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). Odds ratio for obesity vs. normal weight was 1.35 (0.76 to 2.41) for moderate smokers and 1.33 (0.71 to 2.49) for heavy smokers in men (p-trend = 0.9) and 0.78 (0.45 to 1.35) and 1.44 (0.73 to 2.85), in women (p-trend = 0.08). CONCLUSIONS: WC and BF were positively and dose-dependently associated with the number of cigarettes smoked per day in women, whereas onlyWC 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.

Insulin degradation by adipose tissue is increased in human obesity

White adipose tissue samples from obese and lean patients were used for the estimation ofinsulin protease and insulin:glutathione transhydrogenase using 1251-labeled insulin. There was no activity detected in the absence of reduced glutathione, which indicates that insulin is cleaved in human adipose "tissue through reduction of the disulfide bridge between the chains. O bese patients showed higher transhydrogenase activity (per U tissue protein wt, per U tissue wt, and in the total adipose tissue mass) than the lean group. There is a significant correlation between the activity per U tissue wt, and protein and total activity in the whole adipose tissue with respect to body mass index, with a higher activity in obese patients. The potential ofinsulin cleavage by adipose tissue in obese patients was a mean 5.6-fold higher than that in controla. The coexistence of high insulinemia and high cleavage capability implies that insulin secretion and turnover are increased in the o bese. Thus, white adipose tissue may be crucial in the control of energy availability through modulation ofinsulin cleavage.

Different effects of hyperlipidic diets in human lactation and adulthood: growth versus the development of obesity

After birth, the body shifts from glucose as primary energy substrate to milk-derived fats, with sugars from lactose taking a secondary place. At weaning, glucose recovers its primogeniture and dietary fat role decreases. In spite of human temporary adaptation to a high-fat (and sugars and protein) diet during lactation, the ability to thrive on this type of diet is lost irreversibly after weaning. We could not revert too the lactating period metabolic setting because of different proportions of brain/muscle metabolism in the total energy budget, lower thermogenesis needs and capabilities, and absence of significant growth in adults. A key reason for change was the limited availability of foods with high energy content at weaning and during the whole adult life of our ancestors, which physiological adaptations remain practically unchanged in our present-day bodies. Humans have evolved to survive with relatively poor diets interspersed by bouts of scarcity and abundance. Today diets in many societies are largely made up from choice foods, responding to our deeply ingrained desire for fats, protein, sugars, salt etc. Consequently our diets are not well adjusted to our physiological needs/adaptations but mainly to our tastes (another adaptation to periodic scarcity), and thus are rich in energy roughly comparable to milk. However, most adult humans cannot process the food ingested in excess because our cortical-derived craving overrides the mechanisms controlling appetite. This is produced not because we lack the biochemical mechanisms to use this energy, but because we are unprepared for excess, and wholly adapted to survive scarcity. The thrifty mechanisms compound the effects of excess nutrients and damage the control of energy metabolism, developing a pathologic state. As a consequence, an overflow of energy is generated and the disease of plenty develops.

Cigarette smoking and endometrial cancer risk: the modifying effect of obesity.

The objective of this study was to evaluate the association between cigarette smoking and endometrial cancer risk by investigating potential modifying effects of menopausal status, obesity, and exogenous hormones. We pooled data from three case-control studies with the same study design conducted in Italy and Switzerland between 1982 and 2006. Overall, 1446 incident endometrial cancers and 4076 hospital controls were enrolled. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using logistic regression models, conditioned on study and centre, and adjusted for age, period of interview, age at menarche, parity, and body mass index. In comparison with never smokers, current smokers showed reduced endometrial cancer risk (OR: 0.80; 95% CI: 0.66-0.96), with a 28% decrease in risk for smoking >/=20 cigarettes/day. The association did not vary according to menopausal status, oral contraceptive use, or hormone replacement therapy. However, heterogeneity emerged according to body mass index among postmenopausal women, with obese women showing the greatest risk reduction for current smoking (OR: 0.47; 95% CI: 0.27-0.81). In postmenopausal women, obesity turned out to be an important modifier of the association between cigarette smoking and the risk of endometrial cancer. This finding calls for caution in interpreting the favorable effects of cigarette smoking, considering the toxic and carcinogenic effects of tobacco.

Obesity and the incidence of chronic diseases: a seemingly unrelated probit approach

Western societies can reduce avoidable mortality and morbidity by better understanding the relationship between obesity and chronic disease. This paper examines the joint determinants of obesity and of heart disease, diabetes, hypertension, and elevated cholesterol. It analyzes a broadly representative Spanish dataset, the 1999 Survey on Disabilities, Impairments and Health Status, using a health production theoretical framework together with a seemingly unrelated probit model approach that controls for unobserved heterogeneity and endogeneity. Its findings provide suggestive evidence of a positive and significant, although specification-dependent, association between obesity and the prevalence of chronic illness

Decomposing Cross-Country Gaps in Obesity and Overweight: Does the Social Environment Matter?

[cat] Una qüestió clau sobre la producció de salut relativament poc explorada es refereix a la influència dels factors socioeconòmics i mediambientals sobre el pes i l’obesitat. Aquesta problemàtica adquireix particular rellevància quan es comparen dos països Mediterranis com Itàlia i Espanya. És interessant adonar-se que l’obesitat a Espanya és 5 punts percentual més elevada al 2003 mentre que a l’any 1990 era aproximadament la mateixa en ambdós països. Aquesta article presenta una descomposició no lineal dels gaps o diferencials en taxes de sobrepès (índex de massa corporal – IMC- entre 25 i 29.9 9 kg/m2), obesitat classe 1 (IMC≥30 kg/m2) i classe 2 (IMC≥35 kg/m2) entre Espanya i Itàlia per gènere i grups d’edat. En explicar aquests gaps entre països aïllem les influències dels estils de vida, els efectes socioeconòmics i els mediambientals. Els nostres resultats indiquen que quan no es controla pels efectes mediambientals (efectes de grup o ‘peer effects’) els hàbits alimentaris i el nivell educatiu són els principals predictors del gaps totals entre països (36-52%), si bé aquests dos factors exerceixen un impacte diferenciat segons gènere i edat. Un tant paradoxalment, quan controlem pels efectes de grup aquests predictors perden la seva capacitat explicativa i els efectes de grup passen a explicar entre el 46-76% dels gaps en sobrepès i obesitat i mostren un patró creixent amb l’edat.

Cancer du sein et obésité, une liaison dangereuse [Breast cancer and obesity, a dangerous relation].

Obesity is associated with different cancers including breast cancer, whose incidence is increased in postmenopausal women. It has an adverse impact on the prognosis of the patients, regardless of their menopausal status. The fact of receiving a systemic adjuvant therapy does not neutralize the prognostic role of obesity. Moderate weight loss after cancer diagnosis could improve the outcome of the patients, while a weight gain during treatment seems without significant effect. Currently available data are still too incomplete to justify systematic programs to lose weight with an oncologic therapeutic aim. However, it is worth to encourage and support our patients to have an optimal diet, physical activity, and to lose weight as promotion of general health.

A common biological basis of obesity and nicotine addiction.

Smoking influences body weight such that smokers weigh less than non-smokers and smoking cessation often leads to weight increase. The relationship between body weight and smoking is partly explained by the effect of nicotine on appetite and metabolism. However, the brain reward system is involved in the control of the intake of both food and tobacco. We evaluated the effect of single-nucleotide polymorphisms (SNPs) affecting body mass index (BMI) on smoking behavior, and tested the 32 SNPs identified in a meta-analysis for association with two smoking phenotypes, smoking initiation (SI) and the number of cigarettes smoked per day (CPD) in an Icelandic sample (N=34,216 smokers). Combined according to their effect on BMI, the SNPs correlate with both SI (r=0.019, P=0.00054) and CPD (r=0.032, P=8.0 × 10(-7)). These findings replicate in a second large data set (N=127,274, thereof 76,242 smokers) for both SI (P=1.2 × 10(-5)) and CPD (P=9.3 × 10(-5)). Notably, the variant most strongly associated with BMI (rs1558902-A in FTO) did not associate with smoking behavior. The association with smoking behavior is not due to the effect of the SNPs on BMI. Our results strongly point to a common biological basis of the regulation of our appetite for tobacco and food, and thus the vulnerability to nicotine addiction and obesity.

Underdiagnosed and undertreated: obesity in the portuguese population.

Comment on: Post RE, Mainous AG 3rd, Gregorie SH, Knoll ME, Diaz VA, Saxena SK. The influence of physician acknowledgment of patients' weight status on patient perceptions of overweight and obesity in the United States. Arch Intern Med. 2011 Feb 28;171(4):316-21. PMID: 21357807.