Socioeconomic and Environmental Risk Factors for Pediatric Asthma in an American Indian Community

The influence of social and environmental determinants of health on hospitalizations for pediatric asthma

BACKGROUND

Asthma is the most common chronic disease of childhood, and has several social, environmental, and demographic factors potentially influential to its disease burden. This study sought to determine the influence of these factors on hospital admissions and readmissions for pediatric asthma.

METHODS

This was a retrospective cohort study using data from the Indiana Network for Patient Care, a state-wide health information exchange in the United States. Study participants were children 2-18 years old admitted to the hospital with a respiratory diagnostic code between 2010 and 2021. Clinical variables were obtained from electronic health record data, and social and environmental determinants of health data were obtained from the Indiana Social Assets and Vulnerabilities Indicators using geocoding systems. Negative binomial models were used to examine community level social and environmental risk factors modifying the relationship between patient characteristics and the risk of asthma-related hospitalizations and 30-day readmissions.

RESULTS

The study sample included 25,063 patients with an average follow-up of 9 (SD = 5) years. Of these, there were 17,816 asthma-related admissions. There were a total of 1,037 asthma-related 30-day readmissions, with an incidence rate of readmissions relative to total visits of 0.028 per person-year. A high social vulnerability index (SVI) was associated with an increased rate of hospital admissions (Proportion attributable ratio: 1.09, 95%CI (1.03,1.15), p < 0.05). No environmental determinants of health were significantly associated with hospitalization rate.

CONCLUSION

High SVI was significantly associated with increased risk of total hospital admissions for pediatric asthma.

Social determinants of respiratory health from birth: still of concern in the 21st century?

Respiratory symptoms are ubiquitous in children and, even though they may be the harbinger of poor long-term outcomes, are often trivialised. Adverse exposures pre-conception, antenatally and in early childhood have lifetime impacts on respiratory health. For the most part, lung function tracks from the pre-school years at least into late middle age, and airflow obstruction is associated not merely with poor respiratory outcomes but also early all-cause morbidity and mortality. Much would be preventable if social determinants of adverse outcomes were to be addressed. This review presents the perspectives of paediatricians from many different contexts, both high and low income, including Europe, the Americas, Australasia, India, Africa and China. It should be noted that there are islands of poverty within even the highest income settings and, conversely, opulent areas in even the most deprived countries. The heaviest burden of any adverse effects falls on those of the lowest socioeconomic status. Themes include passive exposure to tobacco smoke and indoor and outdoor pollution, across the entire developmental course, and lack of access even to simple affordable medications, let alone the new biologicals. Commonly, disease outcomes are worse in resource-poor areas. Both within and between countries there are avoidable gross disparities in outcomes. Climate change is also bearing down hardest on the poorest children. This review highlights the need for vigorous advocacy for children to improve lifelong health. It also highlights that there are ongoing culturally sensitive interventions to address social determinants of disease which are already benefiting children.

How Schools Can Help Address Social Determinants of Health in Asthma Management

Schools are in a unique position to address social determinants of health (SDOHs) in pediatric asthma management because of their potential to provide resources and facilitate collaboration with health care providers and services for children at risk within their community. SDOHs include economic factors, educational attainment and health literacy, neighborhood factors and the built environment, social and community aspects including discrimination and racism, and health care access and quality. These factors have a significant impact on asthma health in children, and certain populations such as minoritzed populations and those living in high-poverty environments have been shown to be at greater risk for adverse effects of SDOHs on asthma outcomes. School-based asthma programs address several SDOHs including health literacy, the built environment, and health care quality and access and have been shown to improve asthma outcomes. Key components include connection between the school and the health care team, self-management education, and directly observed therapy. School nurses play a key role in directing and managing effective programs because they can evaluate and support a student's health while considering the effect of SDOHs at interpersonal, institutional, community, and policy levels.

Epidemiology of Current Asthma in Children Under 18: A Two-Decade Overview Using National Center for Health Statistics (NCHS) Data

OBJECTIVE

 This study conducted a comprehensive two-decade analysis of current asthma among children under 18 in the United States using National Center for Health Statistics (NCHS) data. The primary objective was to assess the prevalence of current asthma, evaluate temporal trends, and identify disparities based on gender, age, insurance status, household poverty levels, and race/ethnicity.

METHODS

 Data spanning 2003-2019 from NCHS were analyzed, focusing on current asthma prevalence among children under 18. Age-adjusted prevalence rates were calculated and stratified by various factors, including gender, age groups, health insurance status, poverty levels, and race/ethnicity.

RESULTS

 The study revealed substantial disparities in current asthma prevalence. Over the two-decade period, the overall prevalence of current asthma fluctuated. It increased from 2003 (8.5%) to 2009 (9.6%) and then decreased by 2019 (7.0%). Gender disparities were evident, with males (9.9%) consistently reporting a higher prevalence than females (7.5%). Older children aged between 10-17 years (10.4%) consistently had a higher prevalence of asthma than younger children aged 0-4 (5.3%) and 5-9 years (9.5%). Children with Medicaid insurance (11.2%) had the highest prevalence, followed by insured (8.9%), privately insured (7.7%), and uninsured children (6.1%). Children living below the federal poverty level (FPL) consistently reported the highest prevalence (11.3%), while children above 400% of the FPL (7.1%) had the lowest prevalence. Racial disparities were observed, with Black children (14.3%) having higher asthma prevalence, followed by White (7.6%) and Asian children (5.4%).

CONCLUSION

The study highlights significant disparities in current asthma prevalence over the two-decade period analyzed. While the overall prevalence showed fluctuations, it generally increased from 2003 to 2009 and then decreased by 2019. Gender disparities were evident, with males consistently reporting a higher prevalence compared to females. Older children in the 10-17 age group consistently had a higher asthma prevalence than younger age groups. Moreover, disparities based on insurance status and income levels were also apparent, with children on Medicaid and those living below the FPL reporting higher asthma prevalence. Racial disparities were observed, with Black children having the highest prevalence, followed by White and Asian children. These findings emphasize the importance of addressing these disparities and tailoring interventions to improve asthma management and prevention across different demographic groups.

Efficacy and feasibility of the BREATHE asthma intervention with American Indian children: a randomized controlled trial

American Indian (AI) children experience significant disparities in asthma prevalence, severity, and burden of disease, yet few asthma education interventions are tested in this population. This study aimed to evaluate the efficacy and feasibility of the BREATHE intervention with parents and AI children, during a 3-year follow-up period (n = 108), using a randomized controlled design. Children with asthma identified by electronic medical records (EMR) were screened and matched with 2 controls. The intervention included an initial educational and 24 months of follow-up. The control group continued their usual care. The primary outcome was the frequency of EMR documented, emergency department (ED) visits or hospitalization for respiratory complaints. There was no statistical difference in mean primary outcomes (1.34 (1.98) vs 1.22 (1.95), - 0.88 to 0.63, 95% CI of the difference, p = 0.75), nor percent with any ED visit or hospitalization (29/53, 55% vs 30/55, 54%, p = 0.99) between the intervention or control groups respectively. After 365 days, there was a borderline significant difference in time to primary outcome. Although limited in power, the present study did not demonstrate a persistent effect of this intervention. We recommend that AI pediatric asthma interventions are culturally-designed, use feasible procedures, and repeat education at least every 12 months.

Parental education moderates the association between indoor moisture environment and asthma in adolescents: the Greek Global Asthma Network (GAN) cross-sectional study

Objective

Asthma is a major contributor to childhood morbidity. Several environmental and socioeconomic status (SES) factors have been implicated in its etiopathogeneses such as indoor moisture and parental education level. Our study examined the association between exposure to indoor dampness and/or mould (IDM) with adolescent asthma and how parental education could modify or mediate this relationship.

Method

A total of 1934 adolescents (boys: 47.5%, mean age (standard variation): 12.7(0.6) years) and their parents were voluntarily enrolled and completed a validated questionnaire on adolescents’ asthma status, parental educational level, and adolescents’ indoor exposure to IDM during three different lifetime periods, i.e., pregnancy, the first year of life and the current time.

Results

There was a significant modification effect of parental education only for the current exposure; higher parental education lowered almost 50% the odds of IDM and asthma (adjusted odds ratio (aOR): 1.96, 95% Confidence Intervals (CI): (1.05–3.68) and aOR:1.55, 95% CI (1.04–2.32), for primary/secondary and tertiary parental education, respectively).

Conclusion

Adolescents whose parents had a higher education level had lesser odds to have asthma, even if they were exposed to a moisture home environment. This could be attributed to the increased knowledge about asthma risk factors and the improved measures for the amelioration of moisture-home environment that highly educated parents are more likely to take. Further research is needed in order to elucidate the interweaved role of family SES in the aforementioned relation.

Ten year trends in hospital encounters for pediatric asthma: an Indiana experience

INTRODUCTION

Pediatric asthma is a common cause of emergency department visits, hospital admissions, and mortality. Population incidence studies have historically used large-scale survey data. We measured these epidemiologic trends using a health information exchange.

METHODS

In this retrospective cohort study, we used electronic health record data from a regional health information exchange to study clinical trends in pediatric patients presenting to the hospital for asthma in the State of Indiana. Data was obtained from 2010 to 2019 and included all patients ages 2-18 years. Study participants were identified using international classification of disease codes. The measured outcomes were number of hospital encounters per year, percentage of admissions per year, and mortality rates.

RESULTS

Data included 50,393 unique patients and 88,772 unique encounters, with 57% male patients. Over the ten-year period, hospital encounters ranged from 5000 to 8000 per year with no change in trajectory. Between 2010 and 2012, the percent of encounters admitted to the hospital was ∼30%. This decreased to ∼20-25% for 2015-2019. Patient mortality rates increased from 1 to 3 per 1000 patient encounters in 2010-2014 to between 5 and 7 per 1000 patient encounters from 2016 to 2019. White patients had a significantly higher admission percentage compared to other racial groups, but no difference in mortality rate.

CONCLUSIONS

Asthma continues to be a common condition requiring hospital care for pediatric patients. Regional health information exchanges can enable public health researchers to follow asthma trends in near real time, and have potential for informing patient-level public health interventions.

Spatial Modeling of Asthma-Prone Areas Using Remote Sensing and Ensemble Machine Learning Algorithms

In this study, asthma-prone area modeling of Tehran, Iran was provided by employing three ensemble machine learning algorithms (Bootstrap aggregating (Bagging), Adaptive Boosting (AdaBoost), and Stacking). First, a spatial database was created with 872 locations of asthma patients and affecting factors (particulate matter (PM10 and PM2.5), ozone (O3), sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), rainfall, wind speed, humidity, temperature, distance to street, traffic volume, and a normalized difference vegetation index (NDVI)). We created four factors using remote sensing (RS) imagery, including air pollution (O3, SO2, CO, and NO2), altitude, and NDVI. All criteria were prepared using a geographic information system (GIS). For modeling and validation, 70% and 30% of the data were used, respectively. The weight of evidence (WOE) model was used to assess the spatial relationship between the dependent and independent data. Finally, three ensemble algorithms were used to perform asthma-prone areas mapping. According to the Gini index, the most influential factors on asthma occurrence were distance to the street, NDVI, and traffic volume. The area under the curve (AUC) of receiver operating characteristic (ROC) values for the AdaBoost, Bagging, and Stacking algorithms was 0.849, 0.82, and 0.785, respectively. According to the findings, the AdaBoost algorithm outperforms the Bagging and Stacking algorithms in spatial modeling of asthma-prone areas.