Relationships Between Cognitive Disengagement Syndrome, Personality Factors, and Lifestyle Factors in Late Childhood: A Comparison with Inattentive Symptoms

According to the triangular theory of love, passion is an indispensable component of romantic love. Some brain imaging studies have shown that passionate arousal in intimate relationships is associated with the reward circuits in the brain. We hypothesized that the individual reward sensitivity trait is also related to passion in intimate relationships, and two separate studies were conducted in the present research. In the first study, 558 college students who were currently in love were selected as participants. The correlation between intimacy and reinforcement sensitivity in individuals identifying as heterosexual was explored using the Sensitivity to Punishment and Sensitivity to Reward Questionnaire, the Passionate Love Scale, and the Triangular Love Scale. In the second study, participants were 42 college students who were also currently in love. Functional near-infrared spectroscopy (fNIRS) was adopted to explore the neurophysiological interaction between reward sensitivity and emotional arousal induced in participants when presented a photograph of their partner, a friend, or a stranger. The results showed that reward sensitivity was positively correlated with passion, and punishment sensitivity was negatively correlated with intimacy and commitment. Significant interactions between reward sensitivity and photograph type were found, and the triangular part of the inferior frontal gyrus showed a particular relevance to the reward-sensitive personality trait toward partners. Overall, the findings support reinforcement sensitivity theory and suggest that reinforcement-sensitive personality traits (personality traits of reward and punishment sensitivity) are associated with all three components of love, with only reward sensitivity being related to passion.

This study aimed to examine the association between lifestyle factors and metabolic syndrome risk in South Korean adults. Korea National Health and Nutrition Examination Survey 2016–2018 data were used. The study included 6,995 subjects (2835 male; 4,160 female). Multiple logistic regression was used to estimate the relationship between the lifestyle factors, including sedentary time, sleep duration, alcohol consumption, smoking status, and dietary intake. Metabolic syndrome prevalence in healthy adults was 25.6% and 12.4% in men and women, respectively. Male with over four lifestyle risk factors had a higher OR for metabolic syndrome risk (over four lifestyle factors: OR 1.97, CI 1.18–3.27). Female with more than one lifestyle risk factor had a higher OR for metabolic syndrome risk (one lifestyle factor: OR 1.58, CI 1.10–2.28; two lifestyle factors: OR 2.08, CI 1.39–3.11; three lifestyle factors: OR 1.94, CI 1.20–3.13). In particular, female with more lifestyle factors had increased likelihood of abdominal obesity, hypertension, and high triglycerides. Male with more lifestyle factors had increased likelihood of high triglycerides. Sedentary time was significantly associated with increased metabolic syndrome in male and female. This study found a significant association between the number of lifestyle risk factors and the risk of metabolic syndrome in Korean adults. The greater the number of lifestyle risk factors, the higher the risk of metabolic syndrome in both sexes. People with a greater number of poor lifestyle behaviors tended to exhibit increased likelihood of especially elevated triglyceride levels.

Background Night work impacts sleep and is unavoidable in healthcare. Different sleep components have been studied, such as quality, duration and disturbances, which need to be considered different fundamental components of sleep. In the general population sociodemographic, lifestyle and work factors are associated with these sleep components, but less is known among night workers. Therefore, this study assessed among hospital night workers i) to what extent sleep quality, sleep duration and sleep disturbances overlap, and ii) associations between sociodemographic, lifestyle and work factors and these sleep components. Methods Data were used from 467 hospital night workers from the Klokwerk+ study, a prospective cohort study with two measurements. Sleep quality was measured by the Pittsburgh Sleep Quality Index, sleep duration and disturbances were measured by the Medical Outcomes Study Sleep Scale. The proportions of overlap between the three sleep measures were calculated and visualized with a Venn diagram. Associations of sociodemographic, lifestyle, and work factors with the three sleep outcomes were estimated using between-within Poisson regression models. Results About 50% of the hospital night workers had at least one poor sleep outcome. Overlap in poor sleep outcomes was apparent for 36.8% of these workers, while the majority had a poor outcome in only one sleep component (63.1%). Former smoking had a significant association with poor sleep quality. For most independent variables no associations with poor sleep outcomes were observed. Conclusions Our findings suggest that sleep quality, duration and disturbances are separate entities and should be studied separately. Lifestyle and work factors were generally not associated with poor sleep. Since these factors can have acute effects on sleep, future research should consider ecological momentary assessment to examine how exposure and outcomes (co)vary within-persons, over time, and across contexts. Key messages • Sleep quality, sleep duration and sleep disturbances are separate entities of sleep and should be studied as such. • Lifestyle factors and work characteristics were generally not associated with poor sleep among hospital night workers.

Parsing the link between reinforcement sensitivity theory and eating behavior: A systematic review

Lifestyle factors sleep duration and media time during childhood differ between countries. This study examined whether sleep duration and media time affect metabolic risk factors insulin resistance (IR), blood lipid profile, and liver enzymes, and whether there is a relationship between sleep time and media time in Turkish obese children and adolescents. Subjects included 108 obese children and adolescents (aged 10-15 years) whose lifestyle factors were assessed using a survey containing questions about sleep durations, television viewing, media use, and demographic factors. Metabolic risk factors were compared among groups categorized according to sleep and media duration. Aspartate aminotransferase (AST), alanine aminotransferase (ALT), and triglyceride (TG) levels and homeostasis model assessment of insulin resistance (HOMA-IR) values were higher in subjects who spent >5 hours/day on media. Children 10-13 years old who slept <9 hours/day were more likely to have higher insulin and HOMA-IR (p < 0.05) levels and lower high-density lipoprotein cholesterol (HDL-C) levels compared with subjects who slept 9-10 hours/day and >10 hours/day. Correlation analysis revealed a negative relationship between sleep time and media time (r = -0.471, p = 0.000). Short sleep duration was associated with IR and an elevated plasma lipoprotein profile in children and adolescents. Our results suggest that insufficient sleep and excessive media exposure may contribute to metabolic risk in the context of obesity, and therefore, working to improve sleep duration and limit media time could help reduce metabolic risk in obese children and adolescents.

The purpose of the present study was to examine the relationship between long sleep duration and functional capacities. We conducted a cross-sectional study at the Department of Kinanthropology at the University of Quebec at Montreal. Forty eight non-frail postmenopausal women aged between 49 to 75 years were recruited using advertisements in local papers. Body weight, body mass index, fat mass, skeletal muscle mass, number of steps per day, SF-36 total (healthy questionnaire), resting metabolic rate, total energy intake, sleep duration, knee extensor strength (dynamometer), chair stand test and balance opened eyes test were measured. WE FOUND A SIGNIFICANT NEGATIVE CORRELATION BETWEEN HOURS OF SLEEP AND FUNCTIONAL CAPACITY: chair stand test (r = -0.33, p = 0.02), balance opened eyes test (r = -0.45, p = 0.001), muscle strength (r = -0.43, p = 0.002) and skeletal muscle mass (r = -0.39, p = 0.007). In addition, long sleepers (> 9 h) had significantly lower values for skeletal muscle mass (p = 0.03), muscle strength (p = 0.01), chair stand test (p = 0.03), and balance opened eyes test (p = 0.001). Finally, linear regression analysis showed that sleep duration was an independent predictor of the chair stand test (p = 0.024), balance opened eyes test (p = 0.001), and muscle strength (p = 0.035) in our cohort. Long sleepers were associated with lower functional capacities in our cohort of sedentary postmenopausal women.

BackgroundCardiorespiratory fitness (CRF) and sleep habits are lifestyle factors with potential to prevent cardiovascular disease (CVD). CVD is the leading cause of death worldwide. It is therefore important to establish a healthy lifestyle at a young age. In the Lifestyle, Biomarkers and Atherosclerosis (LBA) study we have examined 834 healthy non-smoking adults, aged 18–25 years. The general purpose of the LBA study was to study the effect of lifestyle on traditional biomarkers known to influence CVD risk. The aims of the present study were to evaluate sleep habits of young adult women and men participating in the LBA study, and to compare the importance of sleep and other lifestyle habits on clinically relevant biomarkers for CVD. An additional aim was to find easy and reliable non-invasive biomarkers to detect young adults with increased risk of developing CVD later in life.MethodsThe participants had previously been examined for lifestyle factors, biomarkers and CVD risk score. They filled in a validated computerized questionnaire about their general physical and mental health. The questionnaire included questions on sleep duration and experienced quality of sleep.ResultsIn total 27% of the young adult participants reported difficulties falling asleep or experienced troubled sleep with frequent awakenings per night. The experienced troubled sleep was not related to a higher CVD risk score, but sleep quality and duration were correlated. Shorter sleep duration was significantly associated to higher body mass index (BMI), body fat (%), homeostasis model assessment of insulin resistance (HOMA-IR) and CVD risk. The modifiable lifestyle factor with the highest odds ratio (OR) for CVD risk was CRF. Sleep duration was the second most influential lifestyle factor, more important than moderate- and vigorous physical activity (MVPA) and food habits. Correlations between CRF and heart rate (HR), (P < 0.01) and HOMA-IR and BMI (P < 0.01) were observed, indicating that BMI and resting HR in combination with questions about sleep patterns are easy and reliable non-invasive biomarkers to detect young adults who need counselling on a healthy lifestyle.ConclusionDecreased sleep duration in combination with decreased CRF, in young adults, is a serious health issue.

Using the resting state functional network as a stable neural trait indicator, this study employed a panel cross-lag model to construct a dynamic, causal ‘brain-behavior-time’ framework. It identified key risk pathways from stable neural traits to addictive behaviors, mediated by psychological traits, thereby providing methodological support for targeted intervention. A recent study by He and colleagues has made a pivotal methodological contribution to addiction research by elucidating the dynamic, causal pathways through which stable neural traits, mediated by psychological vulnerabilities, predispose individuals to addictive behaviors [1]. The study's innovative integration of resting-state functional connectivity with panel cross-lagged modeling provides a breakthrough idea for addiction research and intervention, and its methodological value and practical significance are worth exploring. The study's strength lies in its rigorous methodology. It used a cross-sectional sample of 1142 college students for behavioral-brain analysis and a longitudinal follow-up cohort of 303 students for behavioral tracking. The functional connectivity strength between the limbic network (LN) and six other functional networks served as the core neural indicator. Resting-state functional networks, which reflect the brain's intrinsic activity patterns, demonstrate temporal stability [2] and function as biological markers. Specifically, the functional state of LN is directly associated with an individual's perception and response to reward and punishment signals [3, 4]. By correlating this stable neural characteristic with long-term psychological trait data—including reward sensitivity and punishment sensitivity—the study revealed significant findings that LN strength showed a positive correlation with reward sensitivity and a negative correlation with punishment sensitivity. Furthermore, the functional connectivity strength between LN and other networks also demonstrated relationships with reward and punishment sensitivity. These findings establish a foundational ‘brain-behavior’ link that exhibits considerable stability. The study further revealed the dynamic causal relationship between variables through a panel cross-lag model: reward sensitivity at baseline measurement (T1) positively predicted online game addiction tendencies at follow-up measurement (T2); the Iowa Gambling Task net score at T1 negatively predicted reward sensitivity at T2; and punishment sensitivity exerted an indirect effect on addictive tendencies by positively influencing reward sensitivity at T2. The punishment sensitivity also acts indirectly on addictive tendencies by positively affecting reward sensitivity in T2. These results break through the static limitations of cross-sectional studies [5] and provide strong evidence that ‘high reward sensitivity is a core risk factor for addiction’ with both chronological and causal orientation and upgrade the ‘brain-behavior’ model to a dynamic developmental model. He and colleagues integrated LN strength into the panel cross-lag model. Their analysis revealed that T1 LN strength not only directly shapes reward sensitivity at T1 and negatively influences punishment sensitivity at T1, but also predicts reward sensitivity at T2. This establishes the complete pathway from neural traits to psychological traits and finally to behavioral outcomes. This study provides a more coherent theoretical framework for understanding the underlying mechanisms of addiction development by defining how neural features predict behavior through psychological mediating factors. This research paradigm offers insights for clinical intervention and public health. Clinically, the ‘neural indicators → psychological traits → behavioral outcomes’ model can be used to predict individual addictive tendencies by evaluating the functional status of core brain regions like the LN [6], thereby enabling personalized intervention plans. In the field of public health, it facilitates the screening of at-risk adolescents based on characteristics such as abnormal LN function and high reward sensitivity, achieving early identification and prevention of addictive behaviors and promoting a shift from ‘passive treatment’ to ‘active early warning’. In summary, this study successfully translates fundamental discoveries into clinical and public health impacts through its innovative methodology. By mapping key risk pathways and enabling precisely targeted interventions, it establishes a new paradigm for neurobehavioral research. This approach not only provides a framework for understanding addiction mechanisms, but also paves the way for innovative strategies in preventing and treating a broad spectrum of mental health disorders, thereby offering substantial scientific and societal benefits. Zihan Lv: Writing—original draft. Xiaoming Li: Project administration; resources; supervision; validation; writing—review and editing. Xiaochu Zhang: Project administration; resources; supervision; validation; writing—review and editing. This work was supported by grants from National Key R&D Program of China (2024YFF0507600), the Chinese National Programs for Brain Science and Brain-like Intelligence Technology (2021ZD0202101), the National Natural Science Foundation of China (32571266, 32171080, 32400919 and 32200914), the Project of Guizhou Key Laboratory of Artificial Intelligence and Brain-inspired Computing QianKeHe Platform [ZSYS(2024)001], Natural Science Foundation of Anhui Province (2408085QC081), the Humanities and Social Science Fund of the Ministry of Education of China (24YJCZH014) and Shanghai Key Laboratory of Brain-Machine Intelligence for Information Behavior. None.

Objectives To measure the distributed characteristics of Traditional Chinese Medicine (TCM) constitutions, as well as related factors with biased TCM constitutions among the elderly individuals in Macau. Methods The elderly individuals from elderly healthcare centers located in Macao Peninsula, Taipa, and Coloane were selected as research samples. The basic information questionnaire and the Constitution in Chinese Medicine Questionnaire (CCMQ) for elderly were employed. Descriptive analysis was applied to illustrate demographical characteristics and TCM constitution distribution. Exploratory factor analysis (EFA) was conducted to explore potential factors influencing biased constitutions, and weight of each variable for constitution was further calculated. Results A total of 313 participants were recruited. Eighty-six (27.48%) elderly were identified as balanced constitution; others were biased constitutions accounting for 72.52%. Distribution differences related to gender and age were identified among participants with unbalanced constitutions. Four biased constitutions were further analyzed with EFA. For qi-stagnation and yang-deficiency constitutions, three similar factors were determined in the domains of education, sleeping habits, and lifestyle behaviors, successively. Although four factors were identified in phlegm-dampness constitution, the latter two belonged to lifestyle behaviors and the former two were education and sleeping habits. For yin-deficiency constitution, education, tobacco-alcohol consumption, sleeping habits, and exercise were four dimensions of potential influential factors. Tobacco consumption, sleep, and exercise duration weighted the most for qi-stagnation constitution; sleep duration, education level, and sugar-containing beverage intake for phlegm-dampness; length of education, alcohol consumption, and education level for yang-deficiency constitution; and weekly exercise hours, sleep duration, and education level for yin-deficiency constitution. Conclusion The prevalence rate of biased constitutions was relatively high among elderly residents in Macau. Relations between demographical and lifestyle behavioral factors and biased constitutions were identified in this study. Controlling these influential factors might be beneficial for health management of Macau elderly individuals.

Reinforcement sensitivity, depression and anxiety: A meta-analysis and meta-analytic structural equation model

Allergic rhinitis (AR) is the most common chronic disorder in the pediatric population. Although several studies have investigated the correlation between AR and sleep-related issues, the association between the duration and time of sleep and AR has not been analyzed in long-term national data. This study investigated the relationship between sleep time and duration and AR risk in middle- and high-school students (adolescents aged 12–18). We analyzed national data from the Korea Youth Risk Behavior Web-based Survey by the Korea Centers for Disease Control and Prevention from 2007–2012. The sample size was 274,480, with an average response rate of 96.2%. Multivariate logistic regression analyses were conducted to determine the relationship between sleep and AR risk. Furthermore, to determine the best-fitted model among independent variables such as sleep duration, sleep time, and the combination of sleep duration and sleep time, we used Akaike Information Criteria (AIC) to compare models. A total of 43,337 boys and 41,665 girls reported a diagnosis of AR at baseline. The odds ratio increased with age and with higher education and economic status of the parents. Further, students in mid-sized and large cities had stronger relationships to AR than those in small cities. In both genders, AR was associated with depression and suicidal ideation. In the analysis of sleep duration and sleep time, the odds ratio increased in both genders when sleep duration was <7 hours, and when the time of sleep was later than 24∶00 hours. Our results indicate an association between sleep time and duration and AR. This study is the first to focus on the relationship between sleep duration and time and AR in national survey data collected over 6 years.

I read the article by Countryman et al. with interest [1]. They analyzed the relationship among metabolic syndrome, sleep, and inflammation in combination with physical activity and aerobic fitness for pediatrics. They used two models to elucidate the relationship among several key factors. They set the average value of sleep duration and physical activity as predictors of metabolic syndrome and systemic inflammation, and peak VO2 was used as a mediator on the relationship in a structural equation model. They selected adolescents in cohorts 2 and 3, who had some elevated blood pressure and waist circumferences were also high from the data in their Table 1. They selected the majority of the sample from ethnic minorities, and the target adolescents had already suffered from cardiovascular risk. I fundamentally agree with their speculation that undesirable lifestyle and behavioral factors have a risk of metabolic syndrome in youth. But before accepting their conclusion, I have a query as follows. Their conclusion is difficult to accept because standardized coefficients were insignificant between sleep and metabolic syndrome or inflammation. Insignificant relationships were also observed between physical activity and both metabolic syndrome and inflammation. In addition, aerobic fitness as a mediator from sleep and physical activity, which was measured by peak VO2, showed significant, but not high standardized coefficients with sleep and physical activity. Significant and high standardized coefficients of aerobic fitness for metabolic syndrome or inflammation were observed in their study, and a strong correlation between metabolic syndrome and inflammation showed that sleep and physical activity were not core predictors of metabolic syndrome or inflammation. I understand that lifestyle factors such as sleep and physical activity associate with pathophysiology of metabolic components, including inflammation, but their conclusion should be verified by more epidemiological evidences. Bornhorst et al. conducted a cross-sectional study and concluded the existence of an inverse relationship between sleep duration and body mass index (BMI) [2], and the serum insulin significantly attenuated the association between sleep duration and BMI. Sung et al. reported that there was no significant association between sleep duration and homeostatic model assessment of insulin resistance in obese adolescents [3]. These reports also recommend further study if insulin resistance becomes a mediator of the association between sleep and obesity. I previously conducted a 3-year follow-up study on the effect of habitual exercise on the metabolic syndrome [4], presenting insignificant odds ratio (95 % confidence interval) of 0.90 (0.66–1.2). I also conducted a cross-sectional study on the association between metabolic syndrome and lifestyle factors [5]. In this study for male adult workers, odds ratio of sleep duration ≥7 h against <6 h was 0.615 (95 % CI 0.415–0.911, p=0.015), although causality could not be determined. Countryman et al. did not describe their definition of metabolic syndrome, which is indispensable to allow comparison with other studies. Currently, further studies with adolescents are needed to better understand the link between sleep duration, metabolic syndrome, and inflammation.

Preterm infants are babies born before completion of 37 w of gestation. Their organs are immature especially brain. Sleep has a vital role in brain development and maturation in infants. Neonatal intensive care unit is a place where infant’s comfort is disturbed by many environmental stimuli. So the sleep is disrupted. Nesting facilitates transformation of sleep pattern from erratic disturbed spells to deep peaceful nights and contented days. This study aimed to investigate the effect of nesting on sleep pattern of infants hospitalized in NICUs. This crossover clinical trial was performed at a tertiary Neonatal Intensive Care Unit (NICU). 21 preterm infants who met the inclusion criteria were enrolled. They were randomly assigned to two groups of nest and routine procedure. Sleep status was evaluated by using neonatal sleep assessment Scale. Duration of Total Sleep Time per cycle (TST) and duration of each stage such as quiet sleep, active sleep indeterminate sleep were recorded and analysed by using paired t-test. Duration of Total Sleep Time per cycle (TST) and duration of each stage were significantly higher among preterm with nesting than usual procedure of care (p<0.001). Duration of sleep time in each stages shows, duration of active sleep is significantly reduced (34.76) with nesting as compared to routine care (39.55) although which is not significant (t=1.134, P=0.270) there is significant increase in quiet sleep (63.62 ± 17.957) with nesting than with routine care and indeterminate sleep time was increased with nesting as compared with sleep in routine care which is highly significant (t=4.570, p<0.001), (t=2.297, p=0.003) at 0.05 level of significance. The present study results supports the use of nesting aids in increase sleep and duration of quiet sleep and aids in stability of physiological parameters. Thus using nesting for preterm infant is recommended to facilitate infant’s quality of sleep in NICU.

Great expectations. Eating expectancies as mediators of reinforcement sensitivity and eating

Sleep duration and psychological well-being among New Zealanders