Social Inequalities in Children's Lifestyle Behaviors and Health Ourtcomes

The main aim of this thesis was to study social inequalities in children’s lifestyle behaviors and child overweight, asthma, and health-related quality of life (HRQoL). The studies conducted in this thesis were embedded in the Generation R Study. Several conclusions can be drawn from the studies presented in this thesis

Sociodemographic factors and social media use in 9-year-old children:the Generation R Study

Abstract Background We aimed to investigate the associations between sociodemographic factors and instant messaging and social network site exposure among 9-year-old children. Methods Data of 4568 children from the Generation R study, a population-based cohort study performed in Rotterdam, the Netherlands, were analyzed. Instant messaging exposure was defined as using online chat applications such as MSN, chat boxes, WhatsApp, and Ping. Social network site exposure was defined as using Hyves or Facebook. A series of multiple logistic regression analyses were performed, adjusting for covariates. Results Children of low educated mothers had a higher odds ratio (OR) for instant messaging (OR: 1.44, 95% CI: 1.12, 1.86) and social network site exposure (OR: 1.73, 95% CI: 1.13, 2.66) than their counterparts. Being a child from a single-parent family was associated with instant messaging (OR: 1.48, 95% CI: 1.16, 1.88) and social network site exposure (OR: 1.34, 95% CI: 1.01, 1.78) more often than their counterparts. Children of low educated fathers (OR: 1.48, 95% CI: 1.12, 1.95) or from families with financial difficulties (OR: 1.28, 95% CI: 1.04, 1.59) were associated with a higher OR of social network site exposure than their counterparts. Conclusion The findings suggest that several indicators of lower social position are associated with higher social network site and instant messaging exposure among 9-year-old children. More research is needed in younger children to understand the determinants and impact of social media use

Based on the Integration of “Internet + Ideology and Politics”, the Practice of Online and Offline Mixed Teaching Mode of Modern Medical Courses in Traditional Chinese Medicine Majors

The purpose of this paper is to explore how to implement the online and offline mixed teaching mode in the modern medical courses of TCM specialty under the guidance of the concept of “Internet + ideological and political integration”, and to explore its practical experience and remarkable results. With the power of today’s Internet technology, we will organically integrate ideological and political education into the modern medicine course of traditional Chinese medicine, so as to effectively promote the overall cultivation of students’ comprehensive quality, and further enhance the attraction of the course and educational benefits

Social Media Use and Health-Related Quality of Life Among Adolescents:Cross-sectional Study

BACKGROUND: Using social media is a time-consuming activity of children and adolescents. Health authorities have warned that excessive use of social media can negatively affect adolescent social, physical, and psychological health. However, scientific findings regarding associations between time spent on social media and adolescent health-related quality of life (HRQoL) are not consistent. Adolescents typically use multiple social media platforms. Whether the use of multiple social media platforms impacts adolescent health is unclear. OBJECTIVE: The aim of this study was to examine the relationship between social media use, including the number of social media platforms used and time spent on social media, and adolescent HRQoL. METHODS: We analyzed the data of 3397 children (mean age 13.5, SD 0.4 years) from the Generation R Study, a population-based cohort study in the Netherlands. Children reported the number of social media platforms used and time spent on social media during weekdays and weekends separately. Children’s HRQoL was self-reported with the EuroQol 5-dimension questionnaire–youth version. Data on social media use and HRQoL were collected from 2015 to 2019. Multiple logistic and linear regressions were applied. RESULTS: In this study, 72.6% (2466/3397) of the children used 3 or more social media platforms, and 37.7% (1234/3276) and 58.3% (1911/3277) of the children used social media at least 2 hours per day during weekdays and weekends, respectively. Children using more social media platforms (7 or more platforms) had a higher odds of reporting having some or a lot of problems on “having pain or discomfort” (OR 1.55, 95% CI 1.20 to 1.99) and “feeling worried, sad or unhappy” (OR 1.99, 95% CI 1.52 to 2.60) dimensions and reported lower self-rated health (β –3.81, 95% CI –5.54 to –2.09) compared with children who used 0 to 2 social media platforms. Both on weekdays and weekends, children spent more time on social media were more likely to report having some or a lot of problems on “doing usual activities,” “having pain or discomfort,” “feeling worried, sad or unhappy,” and report lower self-rated health (all P<.001). CONCLUSIONS: Our findings indicate that using more social media platforms and spending more time on social media were significantly related to lower HRQoL. We recommend future research to study the pathway between social media use and HRQoL among adolescents

FTFDNet: Learning to Detect Talking Face Video Manipulation with Tri-Modality Interaction

DeepFake based digital facial forgery is threatening public media security, especially when lip manipulation has been used in talking face generation, and the difficulty of fake video detection is further improved. By only changing lip shape to match the given speech, the facial features of identity are hard to be discriminated in such fake talking face videos. Together with the lack of attention on audio stream as the prior knowledge, the detection failure of fake talking face videos also becomes inevitable. It's found that the optical flow of the fake talking face video is disordered especially in the lip region while the optical flow of the real video changes regularly, which means the motion feature from optical flow is useful to capture manipulation cues. In this study, a fake talking face detection network (FTFDNet) is proposed by incorporating visual, audio and motion features using an efficient cross-modal fusion (CMF) module. Furthermore, a novel audio-visual attention mechanism (AVAM) is proposed to discover more informative features, which can be seamlessly integrated into any audio-visual CNN architecture by modularization. With the additional AVAM, the proposed FTFDNet is able to achieve a better detection performance than other state-of-the-art DeepFake video detection methods not only on the established fake talking face detection dataset (FTFDD) but also on the DeepFake video detection datasets (DFDC and DF-TIMIT).Comment: arXiv admin note: substantial text overlap with arXiv:2203.0517

SSR-2D: Semantic 3D Scene Reconstruction from 2D Images

Most deep learning approaches to comprehensive semantic modeling of 3D indoor spaces require costly dense annotations in the 3D domain. In this work, we explore a central 3D scene modeling task, namely, semantic scene reconstruction without using any 3D annotations. The key idea of our approach is to design a trainable model that employs both incomplete 3D reconstructions and their corresponding source RGB-D images, fusing cross-domain features into volumetric embeddings to predict complete 3D geometry, color, and semantics with only 2D labeling which can be either manual or machine-generated. Our key technical innovation is to leverage differentiable rendering of color and semantics to bridge 2D observations and unknown 3D space, using the observed RGB images and 2D semantics as supervision, respectively. We additionally develop a learning pipeline and corresponding method to enable learning from imperfect predicted 2D labels, which could be additionally acquired by synthesizing in an augmented set of virtual training views complementing the original real captures, enabling more efficient self-supervision loop for semantics. In this work, we propose an end-to-end trainable solution jointly addressing geometry completion, colorization, and semantic mapping from limited RGB-D images, without relying on any 3D ground-truth information. Our method achieves state-of-the-art performance of semantic scene reconstruction on two large-scale benchmark datasets MatterPort3D and ScanNet, surpasses baselines even with costly 3D annotations. To our knowledge, our method is also the first 2D-driven method addressing completion and semantic segmentation of real-world 3D scans

Change in neighborhood socioeconomic status and childhood weight status and body composition from birth to adolescence

Background: We aim to assess the associations between the change in neighborhood socioeconomic score (SES) between birth and 6 years and childhood weight status and body composition from 6 to 13 years.Methods: Data for 3909 children from the Generation R Study, a prospective population-based cohort in the Netherlands were analyzed. The change in neighborhood SES between birth and 6 years was defined as static-high, static-middle, static-low, upward, and downward mobility. Child body mass index (BMI), overweight and obesity (OWOB), fat mass index (FMI) and lean mass index (LMI) were measured at age 6, 10, and 13 years. The associations were explored using generalized estimating equations. The effect modification by child sex was examined. Results: In total, 19.5% and 18.1% of children were allocated to the upward mobility and downward mobility neighborhood SES group. The associations between the change in neighborhood SES and child weight status and body composition were moderated by child sex (p &lt; 0.05). Compared to girls in the static-high group, girls in the static-low group had relatively higher BMI-SDS (β, 95% confidence interval (CI): 0.24, 0.09–0.40) and higher risk of OWOB (RR, 95% CI: 1.98, 1.35–2.91), together with higher FMI-SDS (β, 95% CI: 0.27, 0.14–0.41) and LMI-SDS (β, 95% CI: 0.18, 0.03–0.33). The associations in boys were not significant. Conclusions: An increased BMI and fat mass, and higher risk of OWOB from 6 to 13 years were evident in girls living in a low-SES neighborhood or moving downward from a high- to a low-SES neighborhood. Support for children and families from low-SES neighborhoods is warranted.</p

Clustering of sedentary behaviours, physical activity, and energy-dense food intake in six-year-old children

This study examined the clustering of lifestyle behaviours in children aged six years from a prospective cohort study in the Netherlands. Additionally, we analysed the associations between socioeconomic status and the lifestyle behaviour clusters that we identified. Data of 4059 children from the Generation R Study were analysed. Socioeconomic status was measured by maternal educational level and net household income. Lifestyle behaviours including screen time, physical activity, calorie-rich snack consumption and sugar-sweetened beverages consumption were measured via a parental questionnaire. Hierarchical and non-hierarchical cluster analyses were applied. The associations between socioeconomic status and lifestyle behaviour clusters were assessed using logistic regression models. Three lifestyle clusters were identified: “relatively healthy lifestyle” cluster (n = 1444), “high screen time and physically inactive” cluster (n = 1217), and “physically active, high snacks and sugary drinks” cluster (n = 1398). Children from high educated mothers or high-income households were more likely to be allocated to the “relatively healthy lifestyle” cluster, while children from low educated mothers or from low-income households were more likely to be allocated in the “high screen time and physically inactive” cluster. Intervention development and prevention strategies may use this information to further target programs promoting healthy behaviours of children and their families