Association between nutritional literacy and nutrition label use in Chinese community residents

IntroductionNutritional literacy (NL) has a critical influence on food choices. The objective of the present study was to examine the association of NL with nutrition label use.MethodsA cross-sectional study was conducted in Bengbu, China. In total, 955 adults were interviewed using a questionnaire designed for the present study to collect information on demographics, lifestyle, nutrition label use, and NL. Binary logistic regression models were used to calculate odds ratios (OR) and 95% confidence intervals (CI) for nutrition label use and its predictive variables.ResultsIn total, 40.4% of the participants reported looking at nutrition label when purchasing prepackaged foods. NL was significantly positively associated with nutrition label use and specifically with checking nutrition facts table, purported nutrition benefits and purported health benefits. In terms of specific facets of NL, nutrition knowledge, applying skills, and critical skills were associated with nutrition label use. After stratification by monthly income and education, the association between NL and nutrition label use was discovered only in individuals with low monthly income. Additionally, nutrition knowledge was associated with nutrition label use only in adults with high education level, whereas applying skills were associated with nutrition label use only in those with low education level.ConclusionThe use of nutrition label remains low among Chinese community residents, especially the purported nutritional benefits and purported health benefits. NL is positively associated with nutrition label use, especially with respect to functional and critical NL, with differences based on socioeconomic status. The findings highlight the need for NL interventions targeting individuals with different levels of education and income to encourage use of nutrition label in China

Treatment Outcomes for Toddlers with Behaviour Problems from Families in Poverty

Background. Relatively few treatment studies address mental health issues in very young children. This study examined the effectiveness of a treatment program for toddlers whose behavior problems were further complicated by living in poverty. Method. An empirically-validated treatment program was adapted for use in the homes of 102 toddlers for an average of 12 weekly sessions. Results. Significant improvements were found for the children’s behavior problems and their compliance to parent requests. Discussion. The inherent challenges in working with at-risk families and the challenges in delivering mental health services for very young children living in poverty are discussed

Behavior problems and prevalence of asthma symptoms among Brazilian children.

OBJECTIVE: Asthma is the most common chronic disease in childhood and has been designated a public health problem due to the increase in its prevalence in recent decades, the amount of health service expenditure it absorbs and an absence of consensus about its etiology. The relationships among psychosocial factors and the occurrence, symptomatology, and severity of asthma have recently been considered. There is still controversy about the association between asthma and a child's mental health, since the pathways through which this relationship is established are complex and not well researched. This study aims to investigate whether behavior problems are associated with the prevalence of asthma symptoms in a large urban center in Latin America. METHODS: It is a cross-section study of 869 children between 6 and 12 years old, residents of Salvador, Brazil. The International Study of Allergy and Asthma in Childhood (ISAAC) instrument was used to evaluate prevalence of asthma symptoms. The Child Behavior Checklist (CBCL) was employed to evaluate behavioral problems. RESULTS: 19.26% (n=212) of the children presented symptoms of asthma. 35% were classified as having clinical behavioral problems. Poisson's robust regression model demonstrated a statistically significant association between the presence of behavioral problems and asthma symptoms occurrence (PR: 1.43; 95% CI: 1.10-1.85). CONCLUSION: These results suggest an association between behavioral problems and pediatric asthma, and support the inclusion of mental health care in the provision of services for asthma morbidity

Experimental observation of topological Fermi arcs in type-II Weyl semimetal MoTe2

Weyl semimetal is a new quantum state of matter [1-12] hosting the condensed matter physics counterpart of relativisticWeyl fermion [13] originally introduced in high energy physics. The Weyl semimetal realized in the TaAs class features multiple Fermi arcs arising from topological surface states [10, 11, 14-16] and exhibits novel quantum phenomena, e.g., chiral anomaly induced negative mag-netoresistance [17-19] and possibly emergent supersymmetry [20]. Recently it was proposed theoretically that a new type (type-II) of Weyl fermion [21], which does not have counterpart in high energy physics due to the breaking of Lorentz invariance, can emerge as topologically-protected touching between electron and hole pockets. Here, we report direct spectroscopic evidence of topological Fermi arcs in the predicted type-II Weyl semimetal MoTe2 [22-24]. The topological surface states are confirmed by directly observing the surface states using bulk-and surface-sensitive angle-resolved photoemission spectroscopy (ARPES), and the quasi-particle interference (QPI) pattern between the two putative Fermi arcs in scanning tunneling microscopy (STM). Our work establishes MoTe2 as the first experimental realization of type-II Weyl semimetal, and opens up new opportunities for probing novel phenomena such as exotic magneto-transport [21] in type-II Weyl semimetals.Comment: submitted on 01/29/2016. Nature Physics, in press. Spectroscopic evidence of the Fermi arcs from two complementary surface sensitive probes - ARPES and STS. A comparison of the calculated band structure for T_d and 1T' phase to identify the topological Fermi arcs in the T_d phase is also included in the supplementary informatio

Maximizing the potential of early childhood education to prevent externalizing behavior problems: A meta-analysis

Early childhood education (ECE) programs offer a promising mechanism for preventing early externalizing behavior problems and later antisocial behavior; yet, questions remain about how to best maximize ECE's potential. Using a meta-analytic database of 31 studies, we examined the overall effect of ECE on externalizing behavior problems and the differential effects of 3 levels of practice, each with increasing specificity and intensity aimed at children's social and emotional development. In short, we found that each successive level of programs did a better job than the prior level at reducing externalizing behavior problems. Level 1 programs, or those without a clear focus on social and emotional development, had no significant effects on externalizing behavior problems relative to control groups (ES=.13 SD, p<.10). On the other hand, level 2 programs, or those with a clear but broad focus on social and emotional development, were significantly associated with modest decreases in externalizing behavior problems relative to control groups (ES=-.10 SD, p<.05). Hence, level 2 programs were significantly better at reducing externalizing behavior problems than level 1 programs (ES=-.23 SD, p<.01). Level 3 programs, or those that more intensively targeted children's social and emotional development, were associated with additional significant reductions in externalizing behavior problems relative to level 2 programs (ES=-.26 SD, p<.05). The most promising effects came from level 3 child social skills training programs, which reduced externalizing behavior problems half of a standard deviation more than level 2 programs (ES=-.50 SD, p<.05)

A Neural Topic Modeling Study Integrating SBERT and Data Augmentation

Topic models can extract consistent themes from large corpora for research purposes. In recent years, the combination of pretrained language models and neural topic models has gained attention among scholars. However, this approach has some drawbacks: in short texts, the quality of the topics obtained by the models is low and incoherent, which is caused by the reduced word frequency (insufficient word co-occurrence) in short texts compared to long texts. To address these issues, we propose a neural topic model based on SBERT and data augmentation. First, our proposed easy data augmentation (EDA) method with keyword combination helps overcome the sparsity problem in short texts. Then, the attention mechanism is used to focus on keywords related to the topic and reduce the impact of noise words. Next, the SBERT model is trained on a large and diverse dataset, which can generate high-quality semantic information vectors for short texts. Finally, we perform feature fusion on the augmented data that have been weighted by an attention mechanism with the high-quality semantic information obtained. Then, the fused features are input into a neural topic model to obtain high-quality topics. The experimental results on an English public dataset show that our model generates high-quality topics, with the average scores improving by 2.5% for topic coherence and 1.2% for topic diversity compared to the baseline model