Do breaks in online gambling affect neuropsychological arousal? Conceptual approach and lessons learned from the TESSA-pilot trial.

Introduction: Mandatory breaks have been discussed as a harm reduction strategy in the context of gambling for several years, but their effectiveness remains unclear. The TESSA pilot study examines the association of physiological arousal (PA) and mandatory breaks during gambling with an aim to conceptualize the framework for a subsequent randomized controlled trial. Material and methods: In a one-armed experimental pilot study 28 participants engaged in a simulated online slot game with mandatory breaks. PA, disentangled into fear, anger, joy, attraction, balance, and retraction, was continuously monitored via skin conductivity and skin temperature. The occurrence of PA in distinct phases (phase 1: initiation, phase 2: pre-break, phase 3: post-break) was contrasted by multilevel logistic regression. Results: Fear and attraction did not change. Compared to phase 1, anger (OR = 0.698; p = 0.015) and joy (OR = 0.714; p = 0.032) were less likely in phase 2, with joy also being less likely in phase 3 (OR = 0.690; p = 0.023). Balance was more likely in phase 2 (OR = 5.073; p < 0.0001) than in phase 1 and less likely in phase 3 (OR = 0.348; p < 0.0001) whilst retraction declined from phase to phase. Discussion: Mandatory breaks appear suited to offset changes in PA response evolving during gambling, but a sustained effect on initial PA levels should not to be expected. However, to sensitively judge the role of breaks additional framework conditions that impact on gambling behavior (e. g. wins/losses) should be considered.

Analyzing the Influence of Wine and Beer Drinking, Smoking, and Leisure Time Screen Viewing Activity on Body Weight: A Cross-Sectional Study in Germany.

The increasing global prevalence of overweight and obesity highlights an urgent need to explore modifiable obesogenic factors. This study investigated the impact of lifestyle factors, such as beer and wine drinking, cigarette smoking, and leisure time screen viewing activities, on body weight and the development of obesity. Individual level data were selected from a random sample of 3471 German adults using a two-stage disproportionate random sampling procedure. The empirical analysis employed a two-stage equations system and combined the endogenous treatment effects model with the quantile regression technique. Our estimations showed that the decisions to smoke and consume wine and beer were positively interrelated, especially in women. Frequent beer/wine drinkers of normal weight were found to have a lower BMI in the male subsample. Quantile regression estimates indicated a significant influence of smoking on BMI in both genders, with smokers' BMI following an upward trend, especially in the upper quantiles of the distribution. Leisure time screen activity was found to have a major impact on females' BMI. Prolonged television viewing and regular computer gaming had a strong relationship with weight increase in overweight women, whereas internet surfing was inversely correlated with the BMI of normal weight and slightly overweight female participants. Nutrition and health policies should direct individuals toward alternative recreational activities in order to substitute screen usage and reduce sedentary time. This study also raised doubts about the general belief that smokers have a lower body weight. As unhealthy behaviors usually co-occur or cluster together, obesity prevention interventions might also contribute to a decrease in smoking.

An empirical investigation of the impact of smoking on body weight using an endogenous treatment effects model approach: the role of food consumption patterns.

BACKGROUND: This study explored the influence of cigarette smoking and food consumption patterns on BMI after adjusting for various socio-demographic characteristics. Since weight-based stereotypes may have an impact on smoking behaviour and both obesity and smoking have been associated with detrimental health effects, an interdependency between them is quite possible. METHODS: Cross-sectional data were collected via a formal standardized questionnaire administered in personal interviews and two additional self-completion questionnaires from a random sample of 3471 German adults. The empirical framework considered potential endogeneity between smoking and body weight by employing an endogenous treatment effects model with an ordered outcome. The estimations derived from the endogenous treatment effects approach were also compared to the univariate ordered probit model results. RESULTS: Our findings showed that ignoring potential endogeneity may affect both the statistical significance of the smoking estimate and the direction of the influence of smoking on BMI. Smoking was positively associated with BMI in both male (ß = 1.236, p < 0.01) and female (ß = 0.634, p < 0.10) participants. Smokers presented a 23.1% higher risk of obesity and a 24.3% lower likelihood of being within a healthy weight range. Male smokers also appeared to have a considerably augmented probability of being obese compared to their female counterparts (23.6% vs 15.1%). The relationship between smoking and BMI may be attributed to dietary practices, since smoking was correlated with poor dietary habits characterized by the frequent intake of more energy-dense foods (meat products and white-toasted bread) and less frequent consumption of healthy food items, such as whole-grain bread, vegetables and fruits. Concerning the impact of eating habits on body weight, frequent consumption of meat products and confectionery was found to have a direct association with BMI in both genders. Furthermore, white-toasted bread consumption was negatively linked with body weight in males (ß = - 0.337, p < 0.01). CONCLUSIONS: Our findings raised questions about the general belief that smoking is an effective weight control tool. Health interventions should be oriented toward a simultaneous decrease in smoking and obesity, since both behaviours seem to be interdependent. Nutrition programmes should also be designed according to the characteristics of different target groups in order to promote a healthy lifestyle.

Investigating the influence of eating habits, body weight and television programme preferences on television viewing time and domestic computer usage.

BACKGROUND: The present study explored the influence of eating habits, body weight and television programme preference on television viewing time and domestic computer usage, after adjusting for sociodemographic characteristics and home media environment indicators. In addition, potential substitution or complementarity in screen time was investigated. METHODS: Individual level data were collected via questionnaires that were administered to a random sample of 2,946 Germans. The econometric analysis employed a seemingly unrelated bivariate ordered probit model to conjointly estimate television viewing time and time engaged in domestic computer usage. RESULTS: Television viewing and domestic computer usage represent two independent behaviours in both genders and across all age groups. Dietary habits have a significant impact on television watching with less healthy food choices associated with increasing television viewing time. Body weight is found to be positively correlated with television screen time in both men and women, and overweight individuals have a higher propensity for heavy television viewing. Similar results were obtained for age groups where an increasing body mass index (BMI) in adults over 24 years old is more likely to be positively associated with a higher duration of television watching. With respect to dietary habits of domestic computer users, participants aged over 24 years of both genders seem to adopt more healthy dietary patterns. A downward trend in the BMI of domestic computer users was observed in women and adults aged 25-60 years. On the contrary, young domestic computer users 18-24 years old have a higher body weight than non-users. Television programme preferences also affect television screen time with clear differences to be observed between genders and across different age groups. CONCLUSIONS: In order to reduce total screen time, health interventions should target different types of screen viewing audiences separately.