The prevalence of overweight and obesity in children and adolescents is increasing globally. In high-income countries, the prevalence of obesity has plateaued, although the rate is still high.^1,2 Children with overweight and obesity are likely to stay obese into adulthood and tend to develop certain diseases, such as pulmonary, cardiovascular and metabolic diseases, more frequently and at a younger age.^3,4 Overweight and obesity develop as a consequence of the imbalance between energy intake and energy expenditure, and they are heavily influenced by poor eating habits, inadequate sleep and low physical activity level.^5,6 Only about 20% of 13–15-year-old adolescents worldwide achieve the recommended 60 min per day of moderate-to-vigorous physical activity.⁷ At the same time, the number of hours per day that children and adolescents sit in front of a screen, especially in front of a computer screen, is increasing.⁸

We aimed to identify different eating habits among Finnish children and to evaluate their association with meal patterns, breakfast consumption, and socio-demographic characteristics in a large, nationwide cohort of children. We evaluated 10,569 children aged 9–14 years into the Finnish Health in Teens cohort in a cross-sectional design. The hierarchical K-means method was used to identify groups of children with different eating habits, based on five factors obtained through factor analysis of 10 food items. Multiple correspondence analysis was used to show associations between groups with different eating habits and meal patterns, breakfast patterns, gender, age, and language spoken at home. Analyses identified three groups: unhealthy eaters (12.3%), fruit and vegetable avoiders (43.3%), and healthy eaters (44.1%). Most children had regular meal and breakfast patterns. The proportion of boys was higher among unhealthy eaters. Unhealthy eaters also showed irregular meal and breakfast patterns, and had parents with low education level. There was a higher proportion of girls among healthy eaters. Healthy eaters also showed regular meal and breakfast patterns, and had parents with high education level. Although the number of unhealthy eaters was small, special attention should be still paid to these, mostly male children, as they have poor eating habits and they lack regular eating routine. Skipping breakfast was more common among older children and girls, although girls had healthier eating habits overall. Our results can contribute to public health efforts to improve eating behaviours, especially among children with poor eating habits and those skipping healthy food items.

OBJECTIVE: To assess the association between oral health and hygiene practices and oral cancer. METHODS: Hospital-based case-control study in the metropolitan area of São Paulo, southeastern Brazil, from 1998 to 2002. A total 309 patients with squamous cell carcinoma of the mouth and the pharynx and 468 controls matched by sex and age were included in the study. Cases were recruited in seven reference hospitals and controls were selected in five out of the seven participating hospitals. Detailed information on smoking, alcohol consumption, schooling, oral health status and hygiene practices were obtained through interviews. Odds ratios (OR) and 95% confidence intervals (95% CI), adjusted by sex, age, schooling, smoking, alcohol consumption as well as the variables oral health status and hygiene practices were estimated using unconditional logistic regression analyses. RESULTS: The use of complete dental prosthesis was not associated with oral cancer but regular gum bleeding showed a strong association (OR 3.1; 95% CI 1.2-7.9). Those who never attended a dental visit were more likely to have oral cancer (OR 2.5; 95% CI 1.3-4.8). Daily mouthwash use showed a stronger association to pharynx (OR 4.7; 95% CI 1.8-12.5) than mouth cancer (OR 3.2; 95% CI 1.6-6.3). CONCLUSIONS: Gum bleeding, no dental care, and daily mouthwash use were factors associated with oral cancer regardless of tobacco and alcohol consumption.

Picky eating (PE) is the most common cause of early-life feeding problems. However, the consequences of PE on food intake and weight development in general populations have not been established. This study aims to investigate the associations of PE and food neophobia (FN) with weight status in 5700 Finnish preadolescents. In addition, we described food consumption by PE/FN status. We utilised the Finnish Health in Teens (Fin-HIT) cohort of 9-12-year-old preadolescents, who were categorised as having PE and FN based on answers from parental questionnaires. Weight was categorised as underweight, normal weight, and overweight/obesity based on body mass index (BMI) according to IOTF age- and sex-specific cut-offs. Eating patterns were obtained with a 16-item food frequency questionnaire. Multinomial logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (CIs). The overall prevalence of PE and FN were 34% and 14%, respectively. PE was inversely associated with overweight/obesity (OR = 0.7; 95% CI 0.6-0.8) and led to a higher risk of underweight (OR = 2.0; 95% CI 1.7-2.4), while this was not observed with FN. Compared with preadolescents without PE/FN, those with PE/FN reported consuming unhealthy foods such as pizza, hamburgers/hot dogs, and salty snacks more frequently (p < 0.0038). By the same token, these preadolescents reported consuming healthy foods such as cooked vegetables, fresh vegetables/salad, fruit/berries, milk/soured milk, and dark bread less frequently. Among Finnish preadolescents, only PE was associated with a higher risk for underweight and inversely with overweight/obesity. PE and FN were accompanied with unhealthy eating patterns. Management of PE in children may be explored as a potential strategy for improving healthy eating and avoiding underweight in preadolescents.

This cross-sectional study examined the associations of recreational screen time (viewing TV programs on any screen-based device and computer use, performed while sitting) with body mass index (BMI) categories and waist-to-height ratio (WHtR) tertiles in 10,228 children (mean age 11.1 years, SD 0.8). We categorized the children into Light, Medium and Heavy TV viewers and computer users, and into Low, Medium and High exercise groups. Compared with Light TV viewers, Medium (OR: 1.30, 95% CI: 1.11–1.52, when adjusted for age, sex, language, sleep duration and exercise) and Heavy (OR: 1.57, 95% CI: 1.34–1.83) TV viewers had a higher risk of being overweight. Similarly, Heavy computer users had a higher risk of being overweight (OR: 1.42, 95% CI: 1.21–1.67). We observed interactions between exercise and TV viewing (p = 0.012) or computer use (p = 0.010). However, Heavy TV viewers had a higher risk of being overweight in all exercise groups. The associations of TV viewing and computer use were similar with BMI and WHtR. To conclude, heavy sedentary screen time is associated with overweight and central adiposity in children. Moreover, heavy TV viewers have a higher risk for overweight and central adiposity, regardless of weekly exercise duration.

We aimed to examine whether sedentary screen time changes when transitioning from childhood to adolescence and whether children's screen time, separately for school days and weekends, affects body mass index (BMI) in adolescents. This prospective 3-year follow-up study included 5,084 children with a mean (standard deviation) age of 11 (1) years at baseline and 14 (1) years at follow-up. Children reported screen time, more specifically, time spent viewing TV programs and using a computer outside school while sitting. We categorized children into light, medium, and heavy TV viewers and computer users separately for school days and weekends. We also calculated the age- and gender-specific BMI z-score (BMIz). Time spent viewing TV changed from baseline to follow-up on school days and on weekends (p < .001 for both); the proportion of heavy TV viewers on school days (≥3 h/d) increased from 16% to 23% and on weekends (≥4 h/d) from 19% to 30%. Heavy TV viewers and computer users on both school days and on weekends had a higher BMIz 3 years later (p < .001 for all). After adjusting for age, gender, language, baseline BMIz, sleep duration, eating habits, exercise, and the other screen-time variables, heavy TV viewing on weekends remained significantly associated with an increased BMIz at follow-up (B = .078; p = .013). The proportion of heavy screen users increases when transitioning from childhood to adolescence. Moreover, heavy screen use, especially on weekends in 11-year-old children, is associated with an increased BMI 3 years later.