The prevalence of childhood asthma: interpreting falling rates in the context of shifting measurement and the COVID-19 pandemic

Evaluating and Reducing Subgroup Disparity in AI Models: An Analysis of Pediatric COVID-19 Test Outcomes

Artificial Intelligence (AI) fairness in healthcare settings has attracted significant attention due to the concerns to propagate existing health disparities. Despite ongoing research, the frequency and extent of subgroup fairness have not been sufficiently studied. In this study, we extracted a nationally representative pediatric dataset (ages 0-17, n=9,935) from the US National Health Interview Survey (NHIS) concerning COVID-19 test outcomes. For subgroup disparity assessment, we trained 50 models using five machine learning algorithms. We assessed the models' area under the curve (AUC) on 12 small (<15% of the total n) subgroups defined using social economic factors versus the on the overall population. Our results show that subgroup disparities were prevalent (50.7%) in the models. Subgroup AUCs were generally lower, with a mean difference of 0.01, ranging from -0.29 to +0.41. Notably, the disparities were not always statistically significant, with four out of 12 subgroups having statistically significant disparities across models. Additionally, we explored the efficacy of synthetic data in mitigating identified disparities. The introduction of synthetic data enhanced subgroup disparity in 57.7% of the models. The mean AUC disparities for models with synthetic data decreased on average by 0.03 via resampling and 0.04 via generative adverbial network methods.

National prevalence of atopic dermatitis in Korean adolescents from 2009 to 2022

Previous studies have examined the prevalence of allergic diseases in adolescents 1-2 years after the emergence of the COVID-19 pandemic. However, more data is needed to understand the long-term impact of COVID-19 on allergic diseases. Thus, we aimed to examine the trend of the atopic dermatitis prevalence in Korean adolescents before and during the COVID-19 pandemic across 14 years. Additionally, we analyze the risk factors of atopic dermatitis (AD) based on the results. The Korean Disease Control and Prevention Agency conducted the Korea Youth Risk Behavior Web-based Survey from 2009 to 2022, from which the data for this study were obtained. Prevalence trends were compared across subgroups, and the β difference (βdiff) was calculated. We computed odds ratios to examine changes in the disease prevalence before and during the pandemic. This study included a total of 917,461 participants from 2009 to 2022. The prevalence of atopic dermatitis increased from 6.79% (95% CI 6.66-6.91) in 2009-2011 to 6.89% (95% CI 6.72-7.05) in 2018-2019, then decreased slightly to 5.82% (95% CI 5.60-6.04) in 2022. Across the 14 years, middle school student status, low parent's highest education level, low household income, non-alcohol consumption, non-smoker smoking status, no suicidal thoughts, and no suicide attempts were associated with increased risk of atopic dermatitis, while female sex, rural residence, high BMI, low school performance, low household income, and no feelings of sadness and despair was associated with a small increase. This study examined the prevalence of atopic dermatitis across an 18-year, and found that the prevalence increased in the pre-pandemic then decreased during the start of the pandemic and remained constant throughout the pandemic. This trend could be explained mainly by the large scale social and political changes that occurred during the COVID-19 pandemic.

Addressing School Connectedness, Belonging, and Culturally Appropriate Care for Newly Immigrated Students and Families

School connectedness is the degree to which students experience acceptance, inclusion, and care by school personnel and peers. A sense of belonging incorporates an emotional connection to the community. School connectedness and belonging are protective factors that promote student engagement, accomplishment, and community performance. Despite the rise in students from immigrant families in the United States, belonging and connectedness for youth from diverse cultural and linguistic experiences are understudied. School-based nurses, our term, is inclusive of advanced practice pediatric, family, and psychiatric nurse practitioners, are well-positioned to support school connectedness for youth who may encounter hurdles to health care because of cultural and linguistic differences. We present practice suggestions for language, culture, and inclusion using three health conditions experienced by youth: anxiety, asthma, and obesity. School-based nurses and other school personnel who provide linguistic and culturally appropriate care can support students in feeling connected and included in their school communities.

Maternal gestational diabetes mellitus and the childhood asthma in offspring: a meta-analysis

BACKGROUND

Maternal diabetes might be related to a high risk of allergic disease in offspring. However, it remains unknown if maternal gestational diabetes mellitus (GDM) is also associated with a high incidence of childhood asthma in offspring. A systematic review and meta-analysis was performed to investigate the above association.

METHODS

Relevant observational studies were obtained by search of electronic databases including Medline, Embase, Cochrane Library, and Web of Science. A randomized-effects model was selected to pool the data by incorporating the influence of potential heterogeneity. The Newcastle-Ottawa Scale was used for study quality evaluation. Subgroup analyses were performed to evaluate the potential influences of study characteristics on the outcome.

RESULTS

Ten datasets from seven moderate to high quality cohort studies, involving 523,047 mother-child pairs were included in the meta-analysis. Overall, maternal GDM was associated with a higher risk of childhood asthma in offspring (risk ratio [RR]: 1.22, 95% confidence interval [CI]: 1.07 to 1.39, p = 0.003; I2 = 30%). Subgroup analyses showed that the association was not significantly affected by study design, validation methods for GDM, or diagnostic strategy for asthma (p for subgroup analyses all > 0.05). The association between maternal GDM and asthma in offspring was more remarkable after adjusting maternal body mass index in early pregnancy (RR: 1.50 versus 1.06, p < 0.001), but significantly weakened after adjusting hypertensive disorders during pregnancy (RR: 1.08 versus 1.50, p = 0.001).

CONCLUSIONS

Maternal GDM may be associated with an increased incidence of childhood asthma in offspring.