Determining the best population-level alcohol consumption model and its impact on estimates of alcohol-attributable harms.

BACKGROUND: The goals of our study are to determine the most appropriate model for alcohol consumption as an exposure for burden of disease, to analyze the effect of the chosen alcohol consumption distribution on the estimation of the alcohol Population- Attributable Fractions (PAFs), and to characterize the chosen alcohol consumption distribution by exploring if there is a global relationship within the distribution. METHODS: To identify the best model, the Log-Normal, Gamma, and Weibull prevalence distributions were examined using data from 41 surveys from Gender, Alcohol and Culture: An International Study (GENACIS) and from the European Comparative Alcohol Study. To assess the effect of these distributions on the estimated alcohol PAFs, we calculated the alcohol PAF for diabetes, breast cancer, and pancreatitis using the three above-named distributions and using the more traditional approach based on categories. The relationship between the mean and the standard deviation from the Gamma distribution was estimated using data from 851 datasets for 66 countries from GENACIS and from the STEPwise approach to Surveillance from the World Health Organization. RESULTS: The Log-Normal distribution provided a poor fit for the survey data, with Gamma and Weibull distributions providing better fits. Additionally, our analyses showed that there were no marked differences for the alcohol PAF estimates based on the Gamma or Weibull distributions compared to PAFs based on categorical alcohol consumption estimates. The standard deviation of the alcohol distribution was highly dependent on the mean, with a unit increase in alcohol consumption associated with a unit increase in the mean of 1.258 (95% CI: 1.223 to 1.293) (R2 = 0.9207) for women and 1.171 (95% CI: 1.144 to 1.197) (R2 = 0. 9474) for men. CONCLUSIONS: Although the Gamma distribution and the Weibull distribution provided similar results, the Gamma distribution is recommended to model alcohol consumption from population surveys due to its fit, flexibility, and the ease with which it can be modified. The results showed that a large degree of variance of the standard deviation of the alcohol consumption Gamma distribution was explained by the mean alcohol consumption, allowing for alcohol consumption to be modeled through a Gamma distribution using only average consumption.

The association between cigarettes smoking, cannabis use and alcohol consumption in a population of young men: results of a population-based survey.

BACKGROUND: Cigarette smoking is often initiated at a young age as well as other risky behaviors such as alcohol drinking, cannabis and other illicit drugs use. Some studies suggest that cigarette smoking may have an influence on other risky behaviors but little is known about the chronology of occurrence of those different habits. The aim of this study was to assess, by young men, what were the other risky behaviors associated with cigarette smoking and the joint prevalence and chronology of occurrence of those risky behaviors. METHODS: Cross-sectional analyses of a population-based census of 3526 young men attending the recruitment for the Swiss army, aged between 17 and 25 years old (mean age: 19 years old), who filled a self reported questionnaire about their alcohol, cigarettes, cannabis and other illicit drugs habits. Actual smoking was defined as either regular smoking (¡Ý1 cigarette/day, on every day) or occasional smoking, binge drinking as six or more drinks at least twice a month, at risk drinking as 21 drinks or more per week, recent cannabis use as cannabis consumption at least once during the last month, and use of illicit drugs as consumption once or more of illicit drugs other than cannabis. Age at begin was defined as age at first use of cannabis or cigarette smoking. RESULTS: In this population of young men, the prevalence of actual smoking was 51.2% (36.5% regular smoking, 14.6% occasionnal smoking). Two third of participamnts (60.1%) declared that they ever used cannabis, 25.2% reported a recent use of cannabis. 53.8% of participants had a risky alcohol consumption considered as either binge or at risk drinking. Cigarette smoking was significantly associated with recent cannabis use (Odds Ratio (OR): 3.85, 95% Confidence Interval (CI): 3.10- 4.77), binge drinking (OR: 3.48, 95% CI: 3.03-4.00), at risk alcohol drinking (OR: 4.04, 95% CI: 3.12-5.24), and ever use of illicit drugs (OR: 4.34, 95% CI: 3.54-5.31). In a multivariate logistic regression, odds ratios for smoking were increased for cannabis users (OR 3.10,, 95% CI: 2.48-3.88), binge drinkers (OR: 1.77, 95% CI: 1.44-2.17), at risk alcohol drinkers (OR 2.26, 95% CI: 1.52-3.36) and ever users of illicit drugs (OR: 1.56, 95% CI: 1.20-2.03). The majority of young men (57.3%) initiated smoking before cannabis and mean age at onset was 13.4 years old, whereas only 11.1% began to use cannabis before smoking cigarettes and mean age at onset was slightly older (14.4 years old). 31.6% started both cannabis and tobacco at the same age (15 years old). About a third of participants (30.5%) did have a cluster of risky behaviours (smoking, at risk drinking, cannabis use) and 11.0% did cumulate smoking, drinking, cannabis and ever use of illegal drugs. More than half of the smokers (59.6%) did cumulate cannabis use and at risk alcohol drinking whereas only 18.5% of non-smokers did. CONCLUSIONS: The majority of young smokers initiated their risky behaviors by first smoking and then by other psychoactive drugs. Smokers have an increased risk to present other risky behaviors such as cannabis use, at risk alcohol consumtion and illicit drug use compared to nonsmokers. Prevention by young male adults should focus on smoking and also integrate interventions on other risky behaviors.

Rice Consumption in the United States: New Evidence from Food Consumption Surveys, July 2005

Evidence from recent U.S. food consumption surveys provides new information on the distribution of rice consumption, the characteristics of rice consumers, and the diets of people who consume rice. Recently available data from nationally representative surveys of food consumed by individuals in the United States allowed comparison of consumption today (2001-02) with consumption in the mid-1990s. Data come from the Continuing Survey of Food Intakes by Individuals (1994-96) and the National Health and Nutrition Examination Survey (2001-02). Rice is consumed by a significant portion of the U.S. adult population. In 2001-02, over 18 percent (18.2 percent) of adults reported eating at least half a serving of white or brown rice in one day of observed intake. This share was slightly higher than that of 1994-96 (17.4 percent). Compared with others, individuals who consumed at least half a serving of white or brown rice in the observed day of intake consumed a smaller share of calories per day from fat and saturated fat; less discretionary fat or added sugar; and more fiber, dietary folate, fruit, vegetables, and enriched grains. Consumers eating rice were more likely to eat a diet that included choices of foods consistent with the 2005 U.S. Dietary Guidelines.

Dairy Food Consumption, Production, and Policy in Japan, August 2005

We explore and investigate Japanese dairy markets. We first provide an overview of consumer demand and how it evolved after World War II. Using historical data and econometric estimates of Japanese dairy demand, we identify economic, cultural, and demographic forces that have been shaping consumption patterns. Then we summarize the characteristics of Japanese milk production and dairy processing and policies affecting them. We next describe the import regime and trade flows in dairy products. The analysis of the regulatory system of the dairy sector shows how its incentive structure affects the long-term prospects of various segments of the industry. The paper concludes with policy recommendations of how to reform the Japanese dairy sector.

Body mass index and health-related quality of life among young Swiss men.

BACKGROUND: Studies about the association between body mass index (BMI) and health-related quality of life (HRQOL) are often limited, because they 1) did not include a broad range of health-risk behaviors as covariates; 2) relied on clinical samples, which might lead to biased results; and 3) did not incorporate underweight individuals. Hence, this study aims to examine associations between BMI (from being underweight through obesity) and HRQOL in a population-based sample, while considering multiple health-risk behaviors (low physical activity, risky alcohol consumption, daily cigarette smoking, frequent cannabis use) as well as socio-demographic characteristics. METHODS: A total of 5 387 young Swiss men (mean age = 19.99; standard deviation = 1.24) of a cross-sectional population-based study were included. BMI was calculated (kg/m²) based on self-reported height and weight and divided into 'underweight' (<18.5), 'normal weight' (18.5-24.9), 'overweight' (25.0-29.9) and 'obese' (≥30.0). Mental and physical HRQOL was assessed via the SF-12v2. Self-reported information on physical activity, substance use (alcohol, cigarettes, and cannabis) and socio-demographic characteristics also was collected. Logistic regression analyses were conducted to study the associations between BMI categories and below average mental or physical HRQOL. Substance use variables and socio-demographic variables were used as covariates. RESULTS: Altogether, 76.3% were normal weight, whereas 3.3% were underweight, 16.5% overweight and 3.9% obese. Being overweight or obese was associated with reduced physical HRQOL (adjusted OR [95% CI] = 1.58 [1.18-2.13] and 2.45 [1.57-3.83], respectively), whereas being underweight predicted reduced mental HRQOL (adjusted OR [95% CI] = 1.49 [1.08-2.05]). Surprisingly, obesity decreased the likelihood of experiencing below average mental HRQOL (adjusted OR [95% CI] = 0.66 [0.46-0.94]). Besides BMI, expressed as a categorical variable, all health-risk behaviors and socio-demographic variables were associated with reduced physical and/or mental HRQOL. CONCLUSIONS: Deviations from normal weight are, even after controlling for important health-risk behaviors and socio-demographic characteristics, associated with compromised physical or mental HRQOL among young men. Hence, preventive programs should aim to preserve or re-establish normal weight. The self-appraised positive mental well-being of obese men noted here, which possibly reflects a response shift, might complicate such efforts.

Smoking and adolescence: Exploring tobacco consumption and related attitudes in three different age groups in Switzerland

The present study constitutes an investigation of tobacco consumption, related attitudes and individual differences in smoking or non-smoking behaviors in a sample of adolescents of different ages in the French-speaking part of Switzerland. We investigated three school-age groups (7th-grade, 9th-grade, and the second-year of high school) for differences in attitude and social and cognitive dimensions. We present both descriptive and inferential statistics. On an inferential level, we present a binary logistic regression-based model predicting risk of smoking. The resulting model most importantly suggests a strong relationship between smoking and alcohol consumption (both regular and sporadic). We interpret this result in terms of both the impact of the actual campaigns and the cognitive processes associated with adolescence.

Voluntary alcohol consumption is controlled via the neuropeptide Y Y1 receptor.

We have shown previously that voluntary ethanol consumption and resistance to ethanol-induced sedation are inversely related to neuropeptide Y (NPY) levels in NPY-knock-out (NPY(-/-)) and NPY-overexpressing mice. In the present report, we studied knock-out mice completely lacking the NPY Y1 receptor (Y1(-/-)) to further characterize the role of the NPY system in ethanol consumption and neurobiological responses to this drug. Here we report that male Y1(-/-) mice showed increased consumption of solutions containing 3, 6, and 10% (v/v) ethanol when compared with wild-type (Y1(+/+)) control mice. Female Y1(-/-) mice showed increased consumption of a 10% ethanol solution. In contrast, Y1(-/-) mice showed normal consumption of solutions containing either sucrose or quinine. Relative to Y1(+/+) mice, male Y1(-/-) mice were found to be less sensitive to the sedative effects of 3.5 and 4.0 gm/kg ethanol as measured by more rapid recovery from ethanol-induced sleep, although plasma ethanol levels did not differ significantly between the genotypes. Finally, male Y1(-/-) mice showed normal ethanol-induced ataxia on the rotarod test after administration of a 2.5 gm/kg dose. These data suggest that the NPY Y1 receptor regulates voluntary ethanol consumption and some of the intoxicating effects caused by administration of ethanol.

Réduction de la consommation de sel: opportunité, impact et stratégies. [Population reduction of salt consumption: opportunities, impact and strategies].

A national survey showed that Swiss people eat high quantity of salt (9.1 g per day on average). The Swiss Federal Office of Public Health (FOPH) has launched a strategy to reduce salt intake in the population in order to decrease cardiovascular morbidity and mortality, mainly via blood pressure reduction. The most effective public health measures are to reduce the salt content of processed food rich in salt because they do not need to change consumers' eating behaviours. The FOPH has chosen to collaborate with the food industry on a voluntary basis. Regular population-based surveys will be needed to monitor the impact of current measures on salt consumption, hypertension prevalence as well as cardiovascular morbidity and mortality in the years to come.

Challenging the "inoffensiveness" of regular cannabis use by its associations with other current risky substance use--a census of 20-year-old Swiss men.

3,537 men enrolling in 2007 for mandatory army recruitment procedures were assessed for the co-occurrence of risky licit substance use among risky cannabis users. Risky cannabis use was defined as at least twice weekly; risky alcohol use as 6+ drinks more than once/monthly, or more than 20 drinks per week; and risky tobacco use as daily smoking. Ninety-five percent of all risky cannabis users reported other risky use. They began using cannabis earlier than did non-risky users, but age of onset was unrelated to other risky substance use. A pressing public health issue among cannabis users stems from risky licit substance use warranting preventive efforts within this age group.

L'adolescent consommateur de substances face au réseau de soins [Substance abuse adolescents and the health care network]

Substance user adolescents were asked to report on each contact they had had with any type of care providers since they had begun to use alcohol or illegal drugs regularly. Primary care doctors and social workers represent the main access to the care network. In one out of two contacts substance use was not discussed.

Predictable Life-Cycle Shocks, Income Risk and Consumption Inequality

Was the increase in income inequality in the US due to permanent shocks or merely to an increase in the variance of transitory shocks? The implications for consumption and welfare depend crucially on the answer to this question. We use CEX repeated cross-section data on consumption and income to decompose idiosyncratic changes in income into predictable life-cycle changes, transitory and permanent shocks and estimate the contribution of each to total inequality. Our model fits the joint evolution of consumption and income inequality well and delivers two main results. First, we find that permanent changes in income explain all of the increase in inequality in the 1980s and 90s. Second, we reconcile this finding with the fact that consumption inequality did not increase much over this period. Our results support the view that many permanent changes in income are predictable for consumers, even if they look unpredictable to the econometrician, consistent with models of heterogeneous income profiles.