Paediatric obesity-related asthma: Disease burden and effects on pulmonary physiology

Mendelian randomization analysis to analyze the genetic causality between different levels of obesity and different allergic diseases

BACKGROUND

The causal relationship between obesity and different allergic diseases remains controversial.

METHODS

The Two Sample MR package and Phenoscanner database were used to obtain and filter Genome-Wide Association Study (GWAS) data from the Open GWAS database. Mendelian randomization (MR) analysis was used to study the causal relationship between different levels of obesity and different allergic diseases. The data sets related to obesity and asthma were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by the limma package. Cluster Profiler and GO plot packages were used for enrichment analysis to verify the results of MR analysis.

RESULTS

Two-sample MR analysis showed a causal relationship between obesity and childhood allergy (age < 16), allergic asthma and atopic dermatitis (P < 0.05). In addition, there was also a causal relationship between allergic asthma and obesity (P < 0.05), while there was no genetic causal relationship between obesity and allergic rhinitis, eczema, lactose intolerance and so on (P > 0.05). Subgroup analysis revealed a causal relationship between both class 1 and class 2 obesity and childhood allergy (age < 16) (P < 0.05). Obesity class 1 was associated with allergic asthma, while obesity class 3 was associated with atopic dermatitis (P < 0.05). Bioinformatics analysis shows that there were common DEGs between obesity and allergic asthma.

CONCLUSION

Obesity is a risk factor for childhood allergy (age < 16), allergic asthma and atopic dermatitis, while allergic asthma is also a risk factor for obesity. Class 1 and class 2 obesity are both causally associated with childhood allergy (age < 16). In addition, there is a causal relationship between milder obesity and allergic asthma, while heavier obesity is causally related to atopic dermatitis.

The Impact of Dietary Intervention in Obese Children on Asthma Prevention and Control

The prevalence of both asthma and obesity in the pediatric population is steadily increasing, and even the obese-asthma phenotypes are postulated. Obese children with asthma experience more asthma symptoms, more frequent exacerbations, and worse response to treatment; they also report a lower quality of life compared with lean asthmatics. Some of the etiological factors for asthma and obesity may overlap. Perhaps asthma and obesity share a common genetic and immunologic origin. Diet is a compelling modifiable factor in obesity and asthma prevention and control, although the relationship between these two diseases is certainly multifactorial. In this article, we analyze the impact of dietary intervention and weight loss in obese children on asthma prevention and control.

Needs and expectations for an AR program for asthma education for school-age children in South Korea: The perspectives of children, parents, and teachers

Purpose

This study examined the needs for asthma education programs as perceived by school-age children, parents, and teachers and investigated parents' and teachers' expectations for incorporating augmented reality (AR) in asthma education.

Methods

This descriptive, cross-sectional study included 339 participants: 125 school-age children, 132 parents, and 82 teachers. Data were collected from children, parents, and teachers on the need for asthma education, the requirements for asthma education, and the expectations of parents and teachers for incorporating AR in asthma education. Data were analyzed using descriptive statistics, the t-test, analysis of variance, and the Scheffé test.

Results

Asthmatic children and their peers, parents, and teachers all felt there was a significant need for education about asthma, with education on how to deal with an asthma attack being needed the most. The incorporation of AR programs in asthma education was viewed positively by both parents and teachers.

Conclusion

An AR children's asthma education program should be developed in which children with asthma and their peers, parents, and teachers can participate together. Furthermore, it is expected that children with asthma will independently undertake more effective disease management after attending an AR asthma education program.

An increased asthma risk continued until young adulthood after early-childhood hospitalisation for wheezing

AIM

The aim of this cohort study was to evaluate doctor-diagnosed and self-reported asthma in young adults after early-childhood hospitalisation for wheezing.

METHODS

In this prospective-controlled follow-up, questionnaires were sent to 95 subjects aged 24-28 years, who had been hospitalised for their first episodes of wheezing under 24 months of age. Fifty-eight cases and 100 controls returned the questionnaires.

RESULTS

The risk of doctor-diagnosed asthma was 2.14-fold (95% confidence interval 0.61-7.41), and the risk of self-reported asthma 2.39-fold (1.14-4.99) in cases compared to controls. The increased risk of self-reported asthma remained as statistically significant in analyses adjusted for current smoking, overweight and allergic rhinitis. Study subjects presented with wheezing symptoms, use of bronchodilators and inhaled corticosteroids, and with seasonal symptoms presumptive for allergic rhinitis during the last 12 months, more often than controls. The identification of a respiratory syncytial virus or rhinovirus during hospitalisation in early childhood was not anymore associated with asthma risk in adulthood. As expected, previous asthma during early childhood was a strong risk factor for asthma in young adulthood.

CONCLUSION

In this controlled questionnaire study, early-childhood hospitalisation for lower respiratory infection with wheezing was an independently significant risk factor of asthma in young adults.

Pediatric Obesity-Related Asthma: The Role of Nutrition and Nutrients in Prevention and Treatment

Childhood obesity rates have dramatically risen in numerous countries worldwide. Obesity is likely a factor in increased asthma risk, which is already one of the most widespread chronic respiratory pathologies. The pathogenic mechanism of asthma risk has still not yet been fully elucidated. Moreover, the role of obesity-related inflammation and pulmonary overreaction to environmental triggers, which ultimately result in asthma-like symptoms, and the importance of dietary characteristics is well recognized. Diet is an important adjustable element in the asthma development. Food-specific composition of the diet, in particular fat, sugar, and low-quality nutrients, is likely to promote the chronic inflammatory state seen in asthmatic patients with obesity. An unbalanced diet or supplementation as a way to control asthma more efficiently has been described. A personalized dietary intervention may improve respiratory symptoms and signs and therapeutic response. In this narrative review, we presented and discussed more recent literature on asthma associated with obesity among children, focusing on the risk of asthma among children with obesity, asthma as a result of obesity focusing on the role of adipose tissue as a mediator of systemic and local airway inflammation implicated in asthma regulation, and the impact of nutrition and nutrients in the development and treatment of asthma. Appropriate early nutritional intervention could possibly be critical in preventing and managing asthma associated with obesity among children.

Associations of Body Mass Index with Demographics, Lifestyle, Food Intake, and Mental Health among Postpartum Women: A Structural Equation Approach

As postpartum obesity is becoming a global public health challenge, there is a need to apply postpartum obesity modeling to determine the indicators of postpartum obesity using an appropriate statistical technique. This research comprised two phases, namely: (i) development of a previously created postpartum obesity modeling; (ii) construction of a statistical comparison model and introduction of a better estimator for the research framework. The research model displayed the associations and interactions between the variables that were analyzed using the Structural Equation Modeling (SEM) method to determine the body mass index (BMI) levels related to postpartum obesity. The most significant correlations obtained were between BMI and other substantial variables in the SEM analysis. The research framework included two categories of data related to postpartum women: living in urban and rural areas in Iran. The SEM output with the Bayesian estimator was 81.1%, with variations in the postpartum women's BMI, which is related to their demographics, lifestyle, food intake, and mental health. Meanwhile, the variation based on SEM with partial least squares estimator was equal to 70.2%, and SEM with a maximum likelihood estimator was equal to 76.8%. On the other hand, the output of the root mean square error (RMSE), mean absolute error (MSE) and mean absolute percentage error (MPE) for the Bayesian estimator is lower than the maximum likelihood and partial least square estimators. Thus, the predicted values of the SEM with Bayesian estimator are closer to the observed value compared to maximum likelihood and partial least square. In conclusion, the higher values of R-square and lower values of MPE, RMSE, and MSE will produce better goodness of fit for SEM with Bayesian estimators.