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BackgroundThe ongoing COVID-19 pandemic is characterized by different morbidity and mortality rates across different states, cities, rural areas, and diverse neighborhoods. The absence of a national strategy for battling the pandemic also leaves state and local governments responsible for creating their own response strategies and policies. ObjectiveThis study examines the content of COVID-19–related tweets posted by public health agencies in Texas and how content characteristics can predict the level of public engagement. MethodsAll COVID-19–related tweets (N=7269) posted by Texas public agencies during the first 6 months of 2020 were classified in terms of each tweet’s functions (whether the tweet provides information, promotes action, or builds community), the preventative measures mentioned, and the health beliefs discussed, by using natural language processing. Hierarchical linear regressions were conducted to explore how tweet content predicted public engagement. ResultsThe information function was the most prominent function, followed by the action or community functions. Beliefs regarding susceptibility, severity, and benefits were the most frequently covered health beliefs. Tweets that served the information or action functions were more likely to be retweeted, while tweets that served the action and community functions were more likely to be liked. Tweets that provided susceptibility information resulted in the most public engagement in terms of the number of retweets and likes. ConclusionsPublic health agencies should continue to use Twitter to disseminate information, promote action, and build communities. They need to improve their strategies for designing social media messages about the benefits of disease prevention behaviors and audiences’ self-efficacy.

With the aging of the global population and the transformation of lifestyle, the incidence of chronic non-communicable diseases continues to rise, thus having brought great challenges to global public health. In this context, medical and health services must adapt to this growing trend, which necessitates carrying out research on the medical prevention integration mode, and gradually strengthening its application in clinical practice. This paper aims to explore the application status quo, and future development trends of the treatment-prevention integration mode, as well as the challenges it faces from the perspective of chronic non-communicable disease management. We first introduce the background of chronic non-communicable disease management, and then describe the integration of treatment and prevention from multiple aspects in chronic disease management, including multidisciplinary collaboration, patient follow-up system, family doctor signing services, and health education on chronic diseases, so as to realize the comprehensive, chronic disease management throughout the life cycle, and improve patients' health level and living quality. Finally, we believe that in the future, it is necessary to strengthen scientific and interdisciplinary research, intensify the training and education of medical staff, and enhance the development of digital medical technology, in order to better meet the growing health needs of the people. Therefore, this paper has significant reference value for exploring the management methods of chronic non-communicable diseases and promoting public health services.

BackgroundSchizophrenic patients have metabolic disorders， impaired language and information processing function. Inflammatory factors may play an important role in the occurrence and development of schizophrenia.ObjectiveTo explore the relationship of the inflammatory factor levels with metabolic levels， language fluency and information processing function in patients with schizophrenia， so as to provide references for clinical understanding of the neuropathological mechanisms of schizophrenia.MethodsA total of 96 patients with schizophrenia were included in the study group， who were hospitalized in the Fourth People's Hospital of Hefei from January 2021 to December 2022 as well as met the diagnostic criteria of Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） and Mini-International Neuropsychiatric Interview （MINI） 6.0 .Meanwhile， population who underwent physical examination at the same hospital were included in the control group （n=42）. A high-sensitivity multi factor electrochemiluminescence analyzer was used to detect the levels of inflammatory factors IL-4， IL-5， IL-7， IL-8， IL-10 and IL-13. A fully automated biochemical analyzer was used to detect the levels of metabolic indicators such as fasting blood glucose， triglycerides， high-density lipoprotein， apolipoprotein A， creatinine and urea nitrogen. Verbal fluency and information processing function of all participants were assessed by using Verbal Fluency Test （VFT） and Stroop Color Word Test （SCWT）.ResultsThere were statistically significant differences in the levels of IL-4， IL-5， IL-7， IL-8， IL-10， IL-13 and IL-15 between the study group and the control group （P

Purposes Aiming at the problem that Granger Causality (GC) analysis in EEG emotion recognition does not consider the interaction between nodes when constructing brain network, a method of constructing brain network by combining fuzzy cognitive map (FCM) and GC analysis is proposed. Methods First, on the basis of the correspondence between the structure of FCM and GC brain network, the GC brain network is modeled and improved by using the causal attributes among FCM nodes, and the FCM-GC brain network is constructed, by taking into account the cooperative interaction among nodes. Furthermore, in order to deeply integrate FCM with GC brain network, the spatial position information of EEG electrode channel is added to FCM training, and a new IFCM-GC brain network is constructed. On the basis of DEAP emotional EEG database, the features of IFCM-GC brain network are extracted, and the support vec tor machine is used as the recognition model. The average recognition rates in valence dimension and incentive dimension are 97.10% and 97.00%, respectively, which are more than 8% higher than the existing research on GC improvement. Findings The GC brain network constructed by this method takes into account the cooperative interaction among multiple nodes, and effectively improves the performance of emotion recognition system.

There is considerably greater variation in metabolic rates between men than between women, in terms of basal, activity and total (daily) energy expenditure (EE). One possible explanation is that EE is associated with male sexual characteristics (which are known to vary more than other traits) such as musculature and athletic capacity. Such traits might be predicted to be most prominent during periods of adolescence and young adulthood, when sexual behaviour develops and peaks. We tested this hypothesis on a large dataset by comparing the amount of male variation and female variation in total EE, activity EE and basal EE, at different life stages, along with several morphological traits: height, fat free mass and fat mass. Total EE, and to some degree also activity EE, exhibit considerable greater male variation (GMV) in young adults, and then a decreasing GMV in progressively older individuals. Arguably, basal EE, and also morphometrics, do not exhibit this pattern. These findings suggest that single male sexual characteristics may not exhibit peak GMV in young adulthood, however total and perhaps also activity EE, associated with many morphological and physiological traits combined, do exhibit GMV most prominently during the reproductive life stages.

BackgroundCertain product characteristics, such as flavor, may increase adolescents' willingness to try vaped nicotine and cannabis (marijuana) products.MethodsA discrete choice experiment embedded within the 2021-2022 California Teens Nicotine and Tobacco Project Online Survey was administered to a non-probability sample of N = 2342 adolescents ages 12-17. Participants were sequentially presented four randomly-generated pairs of hypothetical vape products that varied in device type (disposable, refillable), content (nicotine, marijuana, "just vapor"), and flavor (seven options) and asked which of these (or neither) they would be more willing to try if a best friend offered. Conditional logistic regression quantified associations between product characteristics and participants' selections, including interactions by past 30-day use of e-cigarettes, marijuana, or both.ResultsCandy/dessert, fruit, and fruit-ice combination flavors were all associated with greater willingness to try a vape product (versus tobacco flavor) among participants not using e-cigarettes or marijuana, those using only e-cigarettes, and those co-using e-cigarettes and marijuana. Among participants only using marijuana, the most preferred flavors were no flavor, candy/dessert, and icy/frost/menthol. Among participants not using e-cigarettes or marijuana, model-predicted willingness to try a displayed vape product was greater when products were sweet or fruit flavored than tobacco or unflavored, regardless of whether displayed options contained nicotine (fruit/sweet: 21 %, tobacco/unflavored: 4 %), marijuana (fruit/sweet: 18 %, tobacco/unflavored: 6 %), or "just vapor" (fruit/sweet: 29 %, tobacco/unflavored: 16 %).ConclusionsIn this online non-probability sample, flavors in nicotine and cannabis vape products increased adolescents' willingness to try them. Comprehensive bans on flavored vapes would likely reduce adolescent use.

Obesity is caused by a prolonged positive energy balance1,2. Whether reduced energy expenditure stemming from reduced activity levels contributes is debated3,4. Here we show that in both sexes, total energy expenditure (TEE) adjusted for body composition and age declined since the late 1980s, while adjusted activity energy expenditure increased over time. We use the International Atomic Energy Agency Doubly Labelled Water database on energy expenditure of adults in the United States and Europe (n = 4,799) to explore patterns in total (TEE: n = 4,799), basal (BEE: n = 1,432) and physical activity energy expenditure (n = 1,432) over time. In males, adjusted BEE decreased significantly, but in females this did not reach significance. A larger dataset of basal metabolic rate (equivalent to BEE) measurements of 9,912 adults across 163 studies spanning 100 years replicates the decline in BEE in both sexes. We conclude that increasing obesity in the United States/Europe has probably not been fuelled by reduced physical activity leading to lowered TEE. We identify here a decline in adjusted BEE as a previously unrecognized factor.

BackgroundIn the United States, disparities in gestational age at birth by maternal race, ethnicity, and geography are theorized to be related, in part, to differences in individual- and neighborhood-level socioeconomic status (SES). Yet, few studies have examined their combined effects or whether associations vary by maternal race and ethnicity and United States Census region.MethodsWe assembled data from 34 cohorts in the Environmental influences on Child Health Outcomes (ECHO) program representing 10,304 participants who delivered a liveborn, singleton infant from 2000 through 2019. We investigated the combined associations of maternal education level, neighborhood deprivation index (NDI), and Index of Concentration at the Extremes for racial residential segregation (ICERace) on gestational weeks at birth using linear regression and on gestational age at birth categories (preterm, early term, post-late term relative to full term) using multinomial logistic regression.ResultsAfter adjustment for NDI and ICERace, gestational weeks at birth was significantly lower among those with a high school diploma or less (-0.31 weeks, 95% CI: -0.44, -0.18), and some college (-0.30 weeks, 95% CI: -0.42, -0.18) relative to a master's degree or higher. Those with a high school diploma or less also had an increased odds of preterm (aOR 1.59, 95% CI: 1.20, 2.10) and early term birth (aOR 1.26, 95% CI: 1.05, 1.51). In adjusted models, NDI quartile and ICERace quartile were not associated with gestational weeks at birth. However, higher NDI quartile (most deprived) associated with an increased odds of early term and late term birth, and lower ICERace quartile (least racially privileged) associated with a decreased odds of late or post-term birth. When stratifying by region, gestational weeks at birth was lower among those with a high school education or less and some college only among those living in the Northeast or Midwest. When stratifying by race and ethnicity, gestational weeks at birth was lower among those with a high school education or less only for the non-Hispanic White category.ConclusionIn this study, maternal education was consistently associated with shorter duration of pregnancy and increased odds of preterm birth, including in models adjusted for NDI and ICERace.