Body mass index and potential correlates among elementary school children in Jordan

Influence of eating while watching TV on food preference and overweight/obesity among adolescents in China: a longitudinal study

Background

Eating while watching TV was found associated with unhealthy food preferences and obesity in adolescents in foreign studies, which is not clear in China. The study aims to explore the influence of eating while watching TV on food preferences and overweight/obesity in Chinese adolescents.

Methods

Data from 1768 adolescents (aged 12-17 years) in the 2006, 2009, 2011, and 2015 China Health and Nutrition Survey (CHNS) was analyzed. The height and weight were measured. Mixed effect models were used to identify the associations between eating while watching TV and adolescents' food preferences and overweight/obesity.

Results

Adolescents eating while watching TV ≥1 time/week were more likely to prefer fast food, salty snacks and soft drinks than those eating while watching TV <1 time/week. Adolescents eating meals while watching TV ≥1 time/week were less likely to prefer vegetables than those eating meals while watching TV <1 time/week. In addition, adolescents eating snacks while watching TV ≥1 time/week were more likely to be overweight/obesity than those eating meals while watching TV <1 time/week (odds ratio [OR] = 7.16; 95% confidence interval [CI] 1.39-36.93).

Conclusion

Eating snacks while watching TV was positively associated with adolescents' unhealthy food preferences and overweight/obesity. Eating meals while watching TV was associated with adolescents' unhealthy food preferences. Implementing web-based Community-based participatory research (CBPR) about reducing eating while watching TV may be a practical strategy to develop healthy food preferences and prevent overweight/obesity in Chinese adolescents.

Prevalence and Determinants of Obesity and Overweight Among Children and Adolescents in the Middle East and North African Countries: An Updated Systematic Review

In recent years, the countries of the Middle East and North Africa (MENA) region have experienced alarming increases in the prevalence of childhood overweight and obesity. This updated systematic review sought to measure the prevalence and determinants of obesity and overweight among children and adolescents in MENA countries. A literature search for relevant observational studies published in English was conducted using PubMed, Web of Science, Google Scholar, and Saudi Digital Library. The risk of bias was evaluated using the Newcastle-Ottawa Scale. Twenty-one published articles during the past five years were included in the systematic review. Varied approaches were used to diagnose childhood overweight and obesity, including the International Obesity Taskforce (IOTF), Centre for Disease Control (CDC), World Health Organization (WHO), and Saudi Growth Pattern Curves. We found that the combined prevalence of childhood overweight and obesity in the Middle East is up to 49.4%, depending on the methods applied in their studies. Risk factors identified were age, male gender, lack of sufficient physical activity, consumption of fried food, perceived stress level, number of family members, family size, mother's occupation, education level, family history of obesity, high energy consumption from carbohydrates, ≥2 hours spent on watching television on weekend days with overweight, and always eating breakfast while watching television with obesity. The results of this review indicate that the issue of childhood and adolescent overweight and obesity in the Middle East is substantial and concerning. Most of the risk factors identified are modifiable and, if given appropriate attention, could significantly reduce the burden of associated chronic complications.

Determination of Chewing Count from Video Recordings Using Discrete Wavelet Decomposition and Low Pass Filtration

Several studies have shown the importance of proper chewing and the effect of chewing speed on the human health in terms of caloric intake and even cognitive functions. This study aims at designing algorithms for determining the chew count from video recordings of subjects consuming food items. A novel algorithm based on image and signal processing techniques has been developed to continuously capture the area of interest from the video clips, determine facial landmarks, generate the chewing signal, and process the signal with two methods: low pass filter, and discrete wavelet decomposition. Peak detection was used to determine the chew count from the output of the processed chewing signal. The system was tested using recordings from 100 subjects at three different chewing speeds (i.e., slow, normal, and fast) without any constraints on gender, skin color, facial hair, or ambience. The low pass filter algorithm achieved the best mean absolute percentage error of 6.48%, 7.76%, and 8.38% for the slow, normal, and fast chewing speeds, respectively. The performance was also evaluated using the Bland-Altman plot, which showed that most of the points lie within the lines of agreement. However, the algorithm needs improvement for faster chewing, but it surpasses the performance of the relevant literature. This research provides a reliable and accurate method for determining the chew count. The proposed methods facilitate the study of the chewing behavior in natural settings without any cumbersome hardware that may affect the results. This work can facilitate research into chewing behavior while using smart devices.