Psychological assessment of children and adolescents with obesity

Smartphone-based application to control and prevent overweight and obesity in children: design and evaluation

BACKGROUND

Obesity is a multifaceted condition that impacts individuals across various age, racial, and socioeconomic demographics, hence rendering them susceptible to a range of health complications and an increased risk of premature mortality. The frequency of obesity among adolescent females in Iran has exhibited an increase from 6 to 9%, while among boys, it has risen from 2 to 7%. Due to the increasing prevalence and advancements in technology, the primary objective of this study was to develop and evaluate a smartphone-based app that would serve as an educational tool for parents about the matter of childhood overweight and obesity. Additionally, the app aimed to enhance parents' capacity to effectively address and manage their children's weight-related concerns.

METHODS

The design of the present study is of an applied-developmental type. In the first phase, the content of related smartphone-based app was determined based on the needs identified in similar studies and the findings of a researcher-made questionnaire. The versions of the app were designed in the android studio 3 programming environment, using the Java 8 programming language and SQLite database. Then, in order to evaluate the app's usability, ease of access, and different features, the standard usability evaluation questionnaire and the user satisfaction questionnaire (QUIS) were completed by the users.

RESULTS

The developed app has five main sections: the main page, recommendation section (with eight parts), charts over the time, child psychology, and reminders for each user. The designed app was given to 20 people including nutritionists and parents with children under 18 years of age for conducting usability evaluation. According to the scores of participants about the usability evaluation of the app, it can be concluded that groups participating in the study could use the program, and they rated the app at a "good" level. Overall performance of the app, screen capabilities, terms and information of the program, learnability, and general features are scored higher than 7.5 out of 9.

CONCLUSION

By using this app, people can become familiar with the causes and symptoms of weight imbalance and manage their weight as best as possible. This app can be considered as a model for designing and creating similar broader systems and programs for the prevention, management, treatment and care of diseases, which aim to help control diseases as much as possible and increase the quality of life and reduce complications for be patients.

Associations between body mass index, sleep-disordered breathing, brain structure, and behavior in healthy children

Pediatric overweight/obesity can lead to sleep-disordered breathing (SDB), abnormal neurological and cognitive development, and psychiatric problems, but the associations and interactions between these factors have not been fully explored. Therefore, we investigated the associations between body mass index (BMI), SDB, psychiatric and cognitive measures, and brain morphometry in 8484 children 9-11 years old using the Adolescent Brain Cognitive Development dataset. BMI was positively associated with SDB, and both were negatively correlated with cortical thickness in lingual gyrus and lateral orbitofrontal cortex, and cortical volumes in postcentral gyrus, precentral gyrus, precuneus, superior parietal lobule, and insula. Mediation analysis showed that SDB partially mediated the effect of overweight/obesity on these brain regions. Dimensional psychopathology (including aggressive behavior and externalizing problem) and cognitive function were correlated with BMI and SDB. SDB and cortical volumes in precentral gyrus and insula mediated the correlations between BMI and externalizing problem and matrix reasoning ability. Comparisons by sex showed that obesity and SDB had a greater impact on brain measures, cognitive function, and mental health in girls than in boys. These findings suggest that preventing childhood obesity will help decrease SDB symptom burden, abnormal neurological and cognitive development, and psychiatric problems.

The Impact of Obesity on Perioperative Outcomes for Children Undergoing Appendectomy for Acute Appendicitis: A Systematic Review

Today, the prevalence of obesity in the pediatric population has increased dramatically. Acute appendicitis (AA) is the most common surgical condition among pediatric patients. We aimed to investigate the impact of obesity on postoperative outcomes in terms of operative time (OT), length of stay (LOS), surgical site infection (SSI), overall complications, adverse events, and mortality in children undergoing appendectomy for acute appendicitis. An extensive search of the literature in PubMed and Google Scholar was conducted to evaluate the outcomes of normal weight (NW), overweight (OW), and obese (OB) children who underwent appendectomy. Although no statistically significant differences were noted in perioperative outcomes and overall postoperative complications between OW/OB and NW children in the majority of the included studies, prolonged OT and LOS and SSI were found in some studies. Moreover, no differences in terms of readmissions and ED visits were recorded. We conclude that the impact of obesity on postoperative outcomes for children undergoing appendectomy for AA is unclear, and, therefore, no safe conclusions can be drawn with the currently available data. Due to the lack of high-quality studies, further research is required to optimize the surgical approach and prevent unwarranted complications.

Applied machine learning to identify differential risk groups underlying externalizing and internalizing problem behaviors trajectories: A case study using a cohort of Asian American children

BACKGROUND

Internalizing and externalizing problems account for over 75% of the mental health burden in children and adolescents in the US, with higher burden among minority children. While complex interactions of multilevel factors are associated with these outcomes and may enable early identification of children in higher risk, prior research has been limited by data and application of traditional analysis methods. In this case example focused on Asian American children, we address the gap by applying data-driven statistical and machine learning methods to study clusters of mental health trajectories among children, investigate optimal predictions of children at high-risk cluster, and identify key early predictors.

METHODS

Data from the US Early Childhood Longitudinal Study 2010-2011 were used. Multilevel information provided by children, families, teachers, schools, and care-providers were considered as predictors. Unsupervised machine learning algorithm was applied to identify groups of internalizing and externalizing problems trajectories. For prediction of high-risk group, ensemble algorithm, Superlearner, was implemented by combining several supervised machine learning algorithms. Performance of Superlearner and candidate algorithms, including logistic regression, was assessed using discrimination and calibration metrics via crossvalidation. Variable importance measures along with partial dependence plots were utilized to rank and visualize key predictors.

FINDINGS

We found two clusters suggesting high- and low-risk groups for both externalizing and internalizing problems trajectories. While Superlearner had overall best discrimination performance, logistic regression had comparable performance for externalizing problems but worse for internalizing problems. Predictions from logistic regression were not well calibrated compared to those from Superlearner, however they were still better than few candidate algorithms. Important predictors identified were combination of test scores, child factors, teacher rated scores, and contextual factors, which showed non-linear associations with predicted probabilities.

CONCLUSIONS

We demonstrated the application of data-driven analytical approach to predict mental health outcomes among Asian American children. Findings from the cluster analysis can inform critical age for early intervention, while prediction analysis has potential to inform intervention programing prioritization decisions. However, to better understand external validity, replicability, and value of machine learning in broader mental health research, more studies applying similar analytical approach is needed.

The effect of air pollution and emotional and behavioral problems on preschoolers' overweight and obesity

Childhood overweight and obesity (OWO) has risen dramatically in both developed and developing countries over the past few decades, creating a huge burden of disease. Ambient air pollution and emotional and behavioral problems are important influencing factors of OWO in preschoolers, but few studies have evaluated the impact of air pollution and emotional and behavioral problems on OWO of preschoolers in rural areas and their potential interactions. This study selected 3802 preschool children from 26 kindergartens in 4 rural areas of Anhui Province for a cross-sectional study. A total of 3636 individuals were included in the final analysis. In this study, outdoor air pollutants (PM_2.5 and O₃) were derived from the China Air Pollution Tracking (TAP) data set, matching preschoolers' external air pollution exposure according to their kindergarten address codes to neighborhoods or administrative villages. OWO were assessed based on WHO Child Growth and Development Standards. Generalized linear model (GLM) and interplot model were used to evaluate the separate effects and potential interactions of air pollutants and emotional and behavioral problems on preschoolers' OWO. In the separate analysis, we found a significant positive association between air pollution and emotional and behavioral problems and OWO among preschoolers. In the interaction analysis, air pollution could enhance the positive effect of emotional and behavioral problems on OWO in preschoolers. In addition, the effect of air pollution and emotional and behavioral problems on overweight and obesity was stronger in preschoolers aged 5 to 6 years. Finally, we also found a stronger positive association between emotional and behavioral problems among girls, macrosomia, non-left-behind children, and preschoolers without eating problems. This study provided a scientific basis for the control of air pollution and overweight and obesity among preschool children in Anhui Province.

Association between Physical Fitness Index and Psychological Symptoms in Chinese Children and Adolescents

The aim of this study was to determine the relationship between different physical fitness indices (PFIs) and psychological symptoms and each dimension (emotional symptoms, behavioral symptoms, social adaptation difficulties) of Chinese children and adolescents. Methods: A total of 7199 children and adolescents aged 13−18 in Jiangxi Province, China, were tested for grip strength, standing long jump, sit-ups, sit and reach, repeated straddling, 50 m run, 20 m shuttle run test (20 m SRT) items. The physical fitness indicators were standardized, converted to Z score and added up to obtain the PFI, and the self-assessment of the psychological section of the multidimensional sub-health questionnaire of adolescents (MSQA) to test the psychological symptoms, using the chi-square test to determine the psychological symptoms of different types of children and adolescents and binary logistic regression analysis to determine the association between psychological symptoms and different PFI grades. Results: The higher the PFI of Chinese children and adolescents, the lower the detection rate of psychological symptoms, emotional symptoms and social adaptation difficulties, from 25.0% to 18.4%, 31.3% to 25.7% and 20.1% to 14.4%, respectively. These results were statistically significant (χ2 = 14.073, 9.332, 12.183, p < 0.05). Taking the high-grade PFI as a reference, binary logistic regression analysis was performed. Generally, compared with the high-grade PFI, children and adolescents with a low-grade PFI (OR = 1.476, 95% CI: 1.200−1.814) or medium-grade PFI (OR = 1.195, 95% CI: 1.010−1.413) had a higher risk of psychological symptoms (p < 0.05). Conclusions: The lower the PFI of Chinese children and adolescents, the higher the detection rate of psychological symptoms, showing a negative correlation. In the future, measures should be taken to improve the physical fitness level of children and adolescents in order to reduce the incidence of psychological symptoms and promote the healthy development of children and adolescents.

An Intelligent Clinical Psychological Assessment Method Based on AHP-LSSVR Model

Clinical psychology is a branch of applied psychology. Clinical psychology has a clear understanding of individual behavior ability and behavior characteristics through psychological measurement analysis, observation, and other methods and combines the situation learned from individual psychosomatic diagnosis and life history with the observation and analysis of individual living conditions. Psychological quality and its evaluation methods have been widely used in many fields, which has greatly promoted the development of this field. However, the current assessment methods are mainly based on a simple statistical analysis, and the results are not accurate. To this end, this article proposes the analytic hierarchy process (AHP) and least-squares support vector regression algorithm (LSSVR). Specifically, through the construction of the specific object’s psychological quality evaluation index system, the design and implementation of the psychological quality evaluation model based on AHP-LSSVR and the proposed method were discussed in the experiment.

NMR-based Metabolomics and Fatty Acid Profiles to Unravel Biomarkers in Preclinical Animal Models of Compulsive Behavior

Compulsivity is a key manifestation of inhibitory control deficit and a cardinal symptom of psychopathological conditions such as obsessive-compulsive and attention-deficit hyperactivity disorders, in which metabolic alterations have raised attention as putative biomarkers for early identification. The present study assessed the metabolic profile in a preclinical model of a compulsive phenotype of rats. We used the schedule-induced polydipsia (SIP) method to classify male Wistar rats into high drinkers (HDs) or low drinkers (LDs) according to their compulsive drinking rate developed by exposure to a fixed-time 60 s (FT-60) schedule of reinforcement with water available ad libitum during 20 sessions. Before and after SIP, blood samples were collected for subsequent serum analysis by nuclear magnetic resonance spectroscopy coupled to multivariate analysis. Although no differences existed in the pre-SIP set, the compulsive drinking behavior induced remarkable metabolic alterations: HD rats selected by SIP exhibited a hyperlipidemic, hypoglycemic, and hyperglutaminergic profile compared with their low-compulsive counterparts. Interestingly, these alterations were not attributable to the mere exposure to reward pellets because a control experiment did not show differences between HDs and LDs after 20 sessions of pellet consumption without intermittent reinforcement. Our results shed light toward the implication of dietary and metabolic factors underpinning the vulnerability to compulsive behaviors.

Psychological impact of overweight/obesity among pediatric age group before and during COVID-19 lockdown in Saudi Arabia

Objectives:

Obesity is a primary public health concern in Saudi Arabia. The COVID-19 pandemic has profoundly affected people's lives, putting considerable pressure on children and adolescents, leading to psychological problems. Therefore, we aimed to assess obesity's psychological and behavioral impact among children and adolescents before and during the COVID-19 lockdown in Jeddah.

Materials and Methods:

A cross-sectional study was conducted in the pediatric endocrine outpatient clinic at King Abdulaziz University Hospital(KAUH). The sample included 360 participants. Data were collected through clinical interviews by telecommunication from April to June 2020. Demographic factors and answers to questions about behavior, feelings, and daily life (pre and during home quarantine) were assessed against the participants’ body mass index (BMI) and reported daily life difficulties. The BMI standard deviation was calculated based on the Center of Disease Control and Prevention standards.

Results:

Compared to other groups, a significantly higher percentage of overweight/obese participants reported low self-confidence (22.1%), 61.7% reported that their friends or family rarely bullied or picked on them and 66.4% reported that the people who they lived with rarely made fun of or bullied them due to their weight before home quarantine.

Conclusion:

Children with a higher BMI reported lower self-confidence than their average weight peers before home quarantine. However, a higher BMI did not increase the risk of being bullied by family members and friends. The majority of the participants changed for the worse in every research aspect during quarantine.

Female obesity and infertility: outcomes and regulatory guidance

Obesity has been associated with reduced fertility, although the dynamics and mechanisms which link excess weight to reduced fertility are not yet fully clarified. Obese women, especially those with central obesity, are less likely to conceive per cycle. Obese women suffer from perturbations of the hypothalamus-pituitary-ovary axis, disturbances of the menstrual cycle and are up to three times more likely to suffer from oligo/anovulation. A delicate hormonal balance regulates follicular development and the maturation of oocytes and it has been observed that obesity can alter the hormonal environment: adipocytes, in fact, are responsible for the production of a hormone called leptin (present in high quantities in obese women) which has been associated with reduced fecundity. In addition to compromising ovulation, obesity negatively affects the development and implantation of the endometrium. The expression of polycystic ovary syndrome (PCOS) is regulated, in part, by weight, so obese women with PCOS often have a more severe phenotype and higher subfertility rates. Furthermore, obesity impairs women's response to medically assisted procreation (MAP) treatments. The authors have set out to delineate a broad-ranging overview of obesity's impact on female fertility, by drawing upon sources spanning the 1994-2022 period. Assisted reproductive technology (ART) procedures are also discussed as they relate to obese patients. In addition the dynamics by which maternal obesity reportedly affects fetal, neonatal and child development have also been briefly enunciated.

The same storm but not the same boat: Effects of COVID-19 stay-at-home order on mental health in individuals with overweight

OBJECTIVE

To describe the effects of stay-at-home orders and social distancing during the coronavirus disease (COVID-19) outbreak on mental health and to compare these outcomes between individuals with normal weight and overweight.

METHODS

This cross-sectional study included 1857 Brazilian adults, who were invited through social media to answer an online questionnaire from 5 May 2020 to 17 May 2020. The instrument included questions related to health behaviour, mental health (anxiety, depression, self-esteem, sadness and stress) and overall health. Overweight was defined as body mass index (BMI) ≥ 25 Kg/m² . Multiple logistic regression was conducted to identify whether overweight is associated with mental health variables.

RESULTS

Women reported increased anxiety (36.5% vs 22.2%, P < .01), depression (16.2% vs 8.8%, P < .01), low self-esteem (19.8% vs 10.6%, P < .01), sadness (17.7% vs 10.2%, P < .01), and stress (29.5% vs 19.3%, P < .01) relative to men. Women with overweight are more likely to report higher feeling of anxiety (OR 1.62, CI 95% 1.22-2.14), depression (OR 1.79, CI 95% 1.25-2.55), low self-esteem (OR 1.82, CI95% 1.28-2.58) and sadness (OR 1.51, CI 95% 1.08-2.10), adjusted for age, social isolation days, educational level, chronic diseases, smoke, alcohol intake and physical activity.

CONCLUSION

Women, specially those with overweight are more vulnerable to the deleterious effects of stay-at-home orders on mental health during the COVID-19 pandemic.

Biobehavioral Dysregulation and its Association with Obesity and Severe Obesity Trajectories from 2 to 15 Years of Age: A Longitudinal Study

OBJECTIVE

This study aimed to identify obesity trajectories from childhood to adolescence (2-15 years of age) and investigate differences in behavioral, eating, and adrenocortical regulation by trajectory membership.

METHODS

A total of 1,077 households from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development were included. Anthropometrics were measured 11 times between ages 15 months and 15 years. Behavioral self-regulation was assessed at ages 3 and 4 years. Disordered eating behaviors and awakening cortisol were assessed at age 15 years.

RESULTS

Latent growth curve modeling identified four BMI trajectories: two nonoverweight trajectories based on average BMI at the 40th and 70th percentiles and overweight/obesity and severe obesity trajectories. Youth in the severe obesity trajectory exhibited lower behavioral self-regulation in early childhood and lower awakening cortisol at age 15 years compared with youth in the nonoverweight trajectories. Youth in the overweight/obesity and severe obesity trajectories showed higher levels of disordered eating behaviors at age 15 years.

CONCLUSIONS

Obesity trajectories were associated with biobehavioral markers of dysregulation in early childhood and adolescence. Dysregulation across biobehavioral domains was particularly apparent among youth who developed severe obesity. Further work is needed to better understand resilience factors that distinguish youth who develop obesity and severe obesity from those who do not.

Broken Energy Homeostasis and Obesity Pathogenesis: The Surrounding Concepts

Obesity represents an abnormal fat accumulation resulting from energy imbalances. It represents a disease with heavy consequences on population health and society economy due to its related morbidities and epidemic proportion. Defining and classifying obesity and its related parameters of evaluation is the first challenge toward understanding this multifactorial health problem. Therefore, within this review we report selected illustrative examples of the underlying mechanisms beyond the obesity pathogenesis which is systemic rather than limited to fat accumulation. We also discuss the gut-brain axis and hormones as the controllers of energy homeostasis and report selected impacts of obesity on the key metabolic tissues. The concepts of "broken energy balance" is detailed as the obesity starting key step. Sleep shortage and psychological factors are also reported with influences on obesity development. Importantly, describing such mechanistic pathways would allow clinicians, biologists and researchers to develop and optimize approaches and methods in terms of diagnosis, classification, clinical evaluation, treatment and prognosis of obesity.