The Joint Effects of Thunderstorms and Power Outages on Respiratory-Related Emergency Visits and Modifying and Mediating Factors of This Relationship.

BACKGROUND: While limited studies have evaluated the health impacts of thunderstorms and power outages (POs) separately, few have assessed their joint effects. We aimed to investigate the individual and joint effects of both thunderstorms and POs on respiratory diseases, to identify disparities by demographics, and to examine the modifications and mediations by meteorological factors and air pollution. METHODS: Distributed lag nonlinear models were used to examine exposures during three periods (i.e., days with both thunderstorms and POs, thunderstorms only, and POs only) in relation to emergency department visits for respiratory diseases (2005-2018) compared to controls (no thunderstorm/no PO) in New York State (NYS) while controlling for confounders. Interactions between thunderstorms and weather factors or air pollutants on health were assessed. The disparities by demographics and seasons and the mediative effects by particulate matter with aerodynamic diameter ≤2.5µm (PM2.5) and relative humidity (RH) were also evaluated. RESULTS: Thunderstorms and POs were independently associated with total and six subtypes of respiratory diseases in NYS [highest risk ratio (RR) = 1.12; 95% confidence interval (CI): 1.08, 1.17], but the impact was stronger when they co-occurred (highest RR = 1.44; 95% CI: 1.22, 1.70), especially during grass weed, ragweed, and tree pollen seasons. The stronger thunderstorm/PO joint effects were observed on chronic obstructive pulmonary diseases, bronchitis, and asthma (lasted 0-10 d) and were higher among residents who lived in rural areas, were uninsured, were of Hispanic ethnicity, were 6-17 or over 65 years old, and during spring and summer. The number of comorbidities was significantly higher by 0.299-0.782/case. Extreme cold/heat, high RH, PM2.5, and ozone concentrations significantly modified the thunderstorm-health effect on both multiplicative and additive scales. Over 35% of the thunderstorm effects were mediated by PM2.5 and RH. CONCLUSION: Thunderstorms accompanied by POs showed the strongest respiratory effects. There were large disparities in thunderstorm-health associations by demographics. Meteorological factors and air pollution levels modified and mediated the thunderstorm-health effects. https://doi.org/10.1289/EHP13237.

MicroRNA-26a in respiratory diseases: mechanisms and therapeutic potential.

MicroRNAs (miRNAs) are short, non-coding single-stranded RNA molecules approximately 22 nucleotides in length, intricately involved in post-transcriptional gene expression regulation. Over recent years, researchers have focused keenly on miRNAs, delving into their mechanisms in various diseases such as cancers. Among these, miR-26a emerges as a pivotal player in respiratory ailments such as pneumonia, idiopathic pulmonary fibrosis, lung cancer, asthma, and chronic obstructive pulmonary disease. Studies have underscored the significance of miR-26a in the pathogenesis and progression of respiratory diseases, positioning it as a promising therapeutic target. Nevertheless, several challenges persist in devising medical strategies for clinical trials involving miR-26a. In this review, we summarize the regulatory role and significance of miR-26a in respiratory diseases, and we analyze and elucidate the challenges related to miR-26a druggability, encompassing issues such as the efficiency of miR-26a, delivery, RNA modification, off-target effects, and the envisioned therapeutic potential of miR-26a in clinical settings.

When the smoke gets in your lungs: short-term effects of Indonesia's 2015 forest fires on health care use.

BACKGROUND: The forest fires that ravaged parts of Indonesia in 2015 were the most severely polluting of this century but little is known about their effects on health care utilization of the affected population. We estimate their short-term impact on visit rates to primary and hospital care with particular focus on visits for specific smoke-related conditions (respiratory disease, acute respiratory tract infection (ARTI) and common cold). METHOD: We estimate the short-term impact of the 2015 forest fire on visit rates to primary and hospital care by combining satellite data on Aerosol Optical Depth (AOD) with administrative records from Indonesian National Health Insurance Agency (BPJS Kesehatan) from January 2015-April  2016. The 16 months of panel data cover 203 districts in the islands of Sumatra and Kalimantan before, during and after the forest fires. We use the (more efficient) ANCOVA version adaptation of a fixed effects model to compare the trends in healthcare use of affected districts (with AOD value above 0.75) with control districts (AOD value below 0.75). Considering the higher vulnerability of children's lungs, we do this separately for children under 5 and the rest of the population adults (> 5), and for both urban and rural areas, and for both the period during and after the forest fires. RESULTS: We find little effects for adults. For young children we estimate positive effects for care related to respiratory problems in primary health care facilities in urban areas. Hospital care visits in general, on the other hand, are negatively affected in rural areas. We argue that these patterns arise because accessibility of care during fires is more restricted for rural than for urban areas. CONCLUSION: The severity of the fires and the absence of positive impact on health care utilization for adults and children in rural areas indicate large missed opportunities for receiving necessary care. This is particularly worrisome for children, whose lungs are most vulnerable to the effects. Our findings underscore the need to ensure ongoing access to medical services during forest fires and emphasize the necessity of catching up with essential care for children after the fires, particularly in rural areas.

Ambient fine particulate matter and daily mortality: a comparative analysis of observed and estimated exposure in 347 cities.

BACKGROUND: Model-estimated air pollution exposure products have been widely used in epidemiological studies to assess the health risks of particulate matter with diameters of ≤2.5 µm (PM2.5). However, few studies have assessed the disparities in health effects between model-estimated and station-observed PM2.5 exposures. METHODS: We collected daily all-cause, respiratory and cardiovascular mortality data in 347 cities across 15 countries and regions worldwide based on the Multi-City Multi-Country collaborative research network. The station-observed PM2.5 data were obtained from official monitoring stations. The model-estimated global PM2.5 product was developed using a machine-learning approach. The associations between daily exposure to PM2.5 and mortality were evaluated using a two-stage analytical approach. RESULTS: We included 15.8 million all-cause, 1.5 million respiratory and 4.5 million cardiovascular deaths from 2000 to 2018. Short-term exposure to PM2.5 was associated with a relative risk increase (RRI) of mortality from both station-observed and model-estimated exposures. Every 10-µg/m3 increase in the 2-day moving average PM2.5 was associated with overall RRIs of 0.67% (95% CI: 0.49 to 0.85), 0.68% (95% CI: -0.03 to 1.39) and 0.45% (95% CI: 0.08 to 0.82) for all-cause, respiratory, and cardiovascular mortality based on station-observed PM2.5 and RRIs of 0.87% (95% CI: 0.68 to 1.06), 0.81% (95% CI: 0.08 to 1.55) and 0.71% (95% CI: 0.32 to 1.09) based on model-estimated exposure, respectively. CONCLUSIONS: Mortality risks associated with daily PM2.5 exposure were consistent for both station-observed and model-estimated exposures, suggesting the reliability and potential applicability of the global PM2.5 product in epidemiological studies.

Cold waves and fine particulate matter in high-altitude Chinese cities: assessing their interactive impact on outpatient visits for respiratory disease.

BACKGROUND: Extreme weather events like heatwaves and fine particulate matter (PM2.5) have a synergistic effect on mortality, but research on the synergistic effect of cold waves and PM2.5 on outpatient visits for respiratory disease, especially at high altitudes in climate change-sensitive areas, is lacking. METHODS: we collected time-series data on meteorological, air pollution, and outpatient visits for respiratory disease in Xining. We examined the associations between cold waves, PM2.5, and outpatient visits for respiratory disease using a time-stratified case-crossover approach and distributional lag nonlinear modeling. Our analysis also calculated the relative excess odds due to interaction (REOI), proportion attributable to interaction (AP), and synergy index (S). We additionally analyzed cold waves over time to verify climate change. RESULTS: Under different definitions of cold waves, the odds ratio for the correlation between cold waves and outpatient visits for respiratory disease ranged from 0.95 (95% CI: 0.86, 1.05) to 1.58 (1.47, 1.70). Exposure to PM2.5 was significantly associated with an increase in outpatient visits for respiratory disease. We found that cold waves can synergize with PM2.5 to increase outpatient visits for respiratory disease (REOI > 0, AP > 0, S > 1), decreasing with stricter definitions of cold waves and longer durations. Cold waves' independent effect decreased over time, but their interaction effect persisted. From 8.1 to 21.8% of outpatient visits were due to cold waves and high-level PM2.5. People aged 0-14 and ≥ 65 were more susceptible to cold waves and PM2.5, with a significant interaction for those aged 15-64 and ≥ 65. CONCLUSION: Our study fills the gap on how extreme weather and PM2.5 synergistically affect respiratory disease outpatient visits in high-altitude regions. The synergy of cold waves and PM2.5 increases outpatient visits for respiratory disease, especially in the elderly. Cold wave warnings and PM2.5 reduction have major public health benefits.

Improved pediatric ICU mortality prediction for respiratory diseases: machine learning and data subdivision insights.

The growing concern of pediatric mortality demands heightened preparedness in clinical settings, especially within intensive care units (ICUs). As respiratory-related admissions account for a substantial portion of pediatric illnesses, there is a pressing need to predict ICU mortality in these cases. This study based on data from 1188 patients, addresses this imperative using machine learning techniques and investigating different class balancing methods for pediatric ICU mortality prediction. This study employs the publicly accessible "Paediatric Intensive Care database" to train, validate, and test a machine learning model for predicting pediatric patient mortality. Features were ranked using three machine learning feature selection techniques, namely Random Forest, Extra Trees, and XGBoost, resulting in the selection of 16 critical features from a total of 105 features. Ten machine learning models and ensemble techniques are used to make accurate mortality predictions. To tackle the inherent class imbalance in the dataset, we applied a unique data partitioning technique to enhance the model's alignment with the data distribution. The CatBoost machine learning model achieved an area under the curve (AUC) of 72.22%, while the stacking ensemble model yielded an AUC of 60.59% for mortality prediction. The proposed subdivision technique, on the other hand, provides a significant improvement in performance metrics, with an AUC of 85.2% and an accuracy of 89.32%. These findings emphasize the potential of machine learning in enhancing pediatric mortality prediction and inform strategies for improved ICU readiness.

Nursing diagnoses and hospital readmission of patients with respiratory diseases: Findings from a case-control study.

AIM: The rate of readmission after hospitalisation for respiratory diseases has become a common and challenging clinical problem. Social and functional patient variables could help identify cases at high risk of readmission. The aim was to identify the nursing diagnoses that were associated with readmission after hospitalisation for respiratory disease in Spain. DESIGN: Case-control study within the cohort of patients admitted for respiratory disease during 2016-19 in a tertiary public hospital in Spain (n = 3781). METHODS: Cases were patients who were readmitted within the first 30 days of discharge, and their controls were the remaining patients. All nursing diagnoses (n = 130) were collected from the electronic health record. They were then grouped into 29 informative diagnostic categories. Clinical confounder-adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using logistic regression models. RESULTS: The readmission rate was 13.1%. The nursing diagnoses categories 'knowledge deficit' (OR: 1.61; 95%CI: 1.13-2.31), 'impaired skin integrity and risk of ulcer infection' (OR: 1.45; 95%CI: 1.06-1.97) and 'activity intolerance associated with fatigue' (OR: 1.56; 95%CI: 1.21-2.01) were associated with an increased risk of suffering an episode of hospital readmission rate at 30% after hospital discharge, and this was independent of sociodemographic background, care variables and comorbidity. PATIENT OR PUBLIC CONTRIBUTION: The nursing diagnoses assigned as part of the care plan of patients during hospital admission may be useful for predicting readmissions.

Lag effect of ambient temperature on respiratory emergency department visits in Beijing: a time series and pooled analysis.

BACKGROUND: Although the association between ambient temperature and mortality of respiratory diseases was numerously documented, the association between various ambient temperature levels and respiratory emergency department (ED) visits has not been well studied. A recent investigation of the association between respiratory ED visits and various levels of ambient temperature was conducted in Beijing, China. METHODS: Daily meteorological data, air pollution data, and respiratory ED visits data from 2017 to 2018 were collected in Beijing. The relationship between ambient temperature and respiratory ED visits was explored using a distributed lagged nonlinear model (DLNM). Then we performed subgroup analysis based on age and gender. Finally, meta-analysis was utilized to aggregate the total influence of ambient temperature on respiratory ED visits across China. RESULTS: The single-day lag risk for extreme cold peaked at a relative risk (RR) of 1.048 [95% confidence interval (CI): 1.009, 1.088] at a lag of 21 days, with a long lag effect. As for the single-day lag risk for extreme hot, a short lag effect was shown at a lag of 7 days with an RR of 1.076 (95% CI: 1.038, 1.114). The cumulative lagged effects of both hot and cold effects peaked at lag 0-21 days, with a cumulative risk of the onset of 3.690 (95% CI: 2.133, 6.382) and 1.641 (95% CI: 1.284, 2.098), respectively, with stronger impact on the hot. Additionally, the elderly were more sensitive to ambient temperature. The males were more susceptible to hot weather than the females. A longer cold temperature lag effect was found in females. Compared with the meta-analysis, a pooled effect of ambient temperature was consistent in general. In the subgroup analysis, a significant difference was found by gender. CONCLUSIONS: Temperature level, age-specific, and gender-specific effects between ambient temperature and the number of ED visits provide information on early warning measures for the prevention and control of respiratory diseases.

Investigating pulmonary neuroendocrine cells in human respiratory diseases with airway models.

Despite accounting for only ∼0.5% of the lung epithelium, pulmonary neuroendocrine cells (PNECs) appear to play an outsized role in respiratory health and disease. Increased PNEC numbers have been reported in a variety of respiratory diseases, including chronic obstructive pulmonary disease and asthma. Moreover, PNECs are the primary cell of origin for lung neuroendocrine cancers, which account for 25% of aggressive lung cancers. Recent research has highlighted the crucial roles of PNECs in lung physiology, including in chemosensing, regeneration and immune regulation. Yet, little is known about the direct impact of PNECs on respiratory diseases. In this Review, we summarise the current associations of PNECs with lung pathologies, focusing on how new experimental disease models, such as organoids derived from human pluripotent stem cells or tissue stem cells, can help us to better understand the contribution of PNECs to respiratory diseases.

Comparison for the effects of different components of temperature variability on mortality: A multi-country time-series study.

BACKGROUND: Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects. OBJECTIVES: We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality. METHODS: We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates. RESULTS: Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0-7 (0.9 °C). An IQR increase in inter-day TV0-7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0-7 and inter-day TV0-7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type. CONCLUSIONS: Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.

Overview of artificial intelligence in point-of-care ultrasound. New horizons for respiratory system diagnoses.

Throughout the past decades ultrasonography did not prove to be a procedure of choice if regarded as part of the routine bedside examination. The reason was the assumption defining the lungs and the bone structures as impenetrable by ultrasound. Only during the recent several years has the approach to the use of such tool in clinical daily routines changed dramatically to offer so-called point-of-care ultrasonography (POCUS). Both vertical and horizontal artefacts became valuable sources of information about the patient's clinical condition, assisting therefore the medical practitioner in differential diagnosis and monitoring of the patient. What is important is that the information is delivered in real time, and the procedure itself is non-invasive. The next stage marking the progress made in this area of diagnostic imaging is the development of arti-ficial intelligence (AI) based on machine learning algorithms. This article is intended to present the available, innovative solutions of the ultrasound systems, including Smart B-line technology, to ensure automatic identification process, as well as interpretation of B-lines in the given lung area of the examined patient. The article sums up the state of the art in ultrasound artefacts and AI applied in POCUS.

Epidemiological characteristics of chronic non-communicable diseases in Dongfang, China, 2021: a cross-sectional survey.

OBJECTIVES: The study aimed to understand the composition, epidemiological characteristics and disease burden of chronic non-communicable diseases and to evaluate the association between sociodemographic factors and chronic non-communicable diseases. DESIGN: A cross-sectional study. SETTING AND PARTICIPANTS: Medical records of 196 761 residents were collected from Dongfang disease surveillance system from January to December 2021. PRIMARY OUTCOME: Prevalence and disability burden were recorded. Logistic regression was used to investigate the relationship between sociodemography factors and diseases. RESULTS: Cardiovascular diseases, chronic lower respiratory diseases and other upper respiratory tract diseases were the main chronic non-communicable diseases. In multivariable analysis, men were associated with increased risk of cardiovascular diseases (OR=1.210, 95% CI 1.162 to 1.261) and chronic lower respiratory diseases (OR=1.128, 95% CI 1.079 to 1.180). Older age was associated with increased risk of cardiovascular diseases (OR=83.952, 95% CI 58.954 to 119.550), whereas was associated with decreased risk of chronic lower respiratory diseases (OR=0.442, 95% CI 0.415 to 0.471) and other upper respiratory tract diseases (OR=0.450, 95% CI 0.411 to 0.493). The unemployed and poor household were associated with decreased risk of cardiovascular diseases (OR=0.463, 95% CI 0.412 to 0.521 and OR=0.390, 95% CI 0.342 to 0.444, respectively), whereas were associated with increased risk of chronic lower respiratory diseases (OR=12.219, 95% CI 6.343 to 23.539 and OR=10.954, 95% CI 5.666 to 21.177, respectively) and other upper respiratory tract diseases (OR=2.246, 95% CI 1.719 to 2.936 and OR=3.035, 95% CI 2.308 to 3.991, respectively). Gender and age moderated the association between personnel category and major diseases. CONCLUSIONS: The spectrum and epidemiological characteristics of chronic diseases observed in Dongfang is good evidence for developing prevention guides and health policies for region.

Exploring the role of the ocular surface in the lung-eye axis: Insights into respiratory disease pathogenesis.

Chronic respiratory diseases (CRDs) represent a significant proportion of global health burden, with a wide spectrum of varying, heterogenic conditions largely affecting the pulmonary system. Recent advances in immunology and respiratory biology have highlighted the systemic impact of these diseases, notably through the elucidation of the lung-eye axis. The current review focusses on understanding the pivotal role of the lung-eye axis in the pathogenesis and progression of chronic respiratory infections and diseases. Existing literature published on the immunological crosstalk between the eye and the lung has been reviewed. The various roles of the ocular microbiome in lung health are also explored, examining the eye as a gateway for respiratory virus transmission, and assessing the impact of environmental irritants on both ocular and respiratory systems. This novel concept emphasizes a bidirectional relationship between respiratory and ocular health, suggesting that respiratory diseases may influence ocular conditions and vice versa, whereby this conception provides a comprehensive framework for understanding the intricate axis connecting both respiratory and ocular health. These aspects underscore the need for an integrative approach in the management of chronic respiratory diseases. Future research should further elucidate the in-depth molecular mechanisms affecting this axis which would pave the path for novel diagnostics and effective therapeutic strategies.

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OBJECTIVES: To investigate the differences in clinical characteristics among children on prolonged mechanical ventilation (PMV) due to different primary diseases. METHODS: A retrospective analysis was performed on the clinical data of 59 pediatric patients requiring PMV from July 2017 to September 2022. According to the primary disease, they were divided into respiratory disease (RD) group, central nervous system (CNS) group, neuromuscular disease (NMD) group, and other disease group. The four groups were compared in terms of general information, treatment, and outcome. RESULTS: There were significant differences among the four groups in age, body weight, Pediatric Logistic Organ Dysfunction-2 (PELOD-2) score, Pediatric Risk of Mortality III (PRISM Ⅲ) score, analgesic and sedative treatment, nutrition supply, rehabilitation treatment, tracheotomy, successful ventilator weaning, and outcomes (P<0.05). Compared with the RD group, the CNS group and the other disease group had a significantly higher age and a significantly higher proportion of children receiving rehabilitation treatment, and the CNS group had a significantly higher proportion of children receiving tracheotomy (P<0.008). Compared with the other disease group, the CNS group and the NMD group had significantly lower PELOD-2 and PRISM III scores, and the CNS group had a significantly higher proportion of children with successful ventilator weaning and a significantly higher proportion of children who were improved and discharged (P<0.008). CONCLUSIONS: There are differences in clinical characteristics among children receiving PMV due to different etiologies. Most children in the RD group have a younger age, and children in the CNS group have a relatively good prognosis.

Associations between vaping and self-reported respiratory symptoms in young people in Canada, England and the US.

BACKGROUND: Prevalence of youth nicotine vaping has increased, heightening concerns around negative health effects. This study aimed to compare self-reported respiratory symptoms among youth by vaping behaviours. METHODS: Participants (n = 39,214) aged 16-19 from the 2020 and 2021 International Tobacco Control Policy Evaluation Project (ITC) Youth Tobacco and Vaping Surveys (Canada, England, US). Weighted multivariable logistic regression assessed associations between reporting any of five respiratory symptoms in the past week (shortness of breath, wheezing, chest pain, phlegm, cough) and: past 30-day smoking and/or vaping; lifetime/current vaping. Among past-30-day vapers (n = 4644), we assessed associations between symptoms and vaping frequency, use of nicotine salts, usual flavour and device type(s). RESULTS: Overall, 27.8% reported experiencing any of the five respiratory symptoms. Compared with youth who had only vaped, those who had only smoked had similar odds of symptoms [adjusted odds ratio, OR (95% confidence interval, CI): 0.97 (0.85-1.10)], those who both smoked and vaped had higher odds [1.26 (1.12-1.42)], and those who had done neither, lower odds [0.67 (0.61-0.72)]. Compared with those who had never vaped, past use, experimentation and current regular or occasional use were all associated with higher odds. Reporting usually using nicotine salts was associated with higher odds of symptoms [1.43 (1.22-1.68)] than non-salt but was often uncertain. Compared with tobacco flavour (including with menthol), menthol/mint and sweets flavours were associated with similar odds; fruit [1.44 (1.07-1.93)], multiple [1.76 (1.30-2.39)] and 'other' [2.14 (1.45-3.16)] flavours with higher odds. All device types were associated with similar odds. CONCLUSIONS: Among youth, vaping was associated with increased reporting of past-week respiratory symptoms. Among those who vaped, some flavour types and potentially nicotine salts were associated with respiratory symptoms.

Imaging of Large Airway Disorders.

Large airway disorders encompass a large variety of diseases and pathology, with broad categories including anatomic variants, congenital abnormalities, acquired abnormalities, inflammatory/infiltrative causes, infection, and tumors. The most common diseases in each category are discussed with a focus on the salient imaging findings. Pitfalls to beware of are discussed through the article, and concludes with a general method to approaching large airways pathology that should provide the reader with a basic framework and understanding of this complex topic.

Environmental Determinants of Post-Discharge Acute Respiratory Illness among Preterm Infants with Bronchopulmonary Dysplasia.

OBJECTIVE: To analyze the association of components of the Centers for Disease Control and Prevention (CDC) Environmental Justice Index (EJI) with respiratory health outcomes among infants with bronchopulmonary dysplasia (BPD) within one year after discharge from the neonatal intensive care unit. METHODS: This was a retrospective cohort study of a cohort of preterm infants with BPD. Multivariable logistic regression models estimated associations of EJI and its components with medically attended acute respiratory illness, defined as an ED visit or inpatient readmission, within one year of discharge from the neonatal intensive care unit. A mediation analysis was conducted to evaluate how environmental injustice may contribute to racial disparities in acute respiratory illness. RESULTS: Greater EJI was associated with an increased risk of medically attended respiratory illness (per EJI standard deviation increment, aOR 1.38, 95% CI: 1.12-1.69). Of the index's components, the Environmental Burden Module's Air pollution domain had the greatest association (aOR 1.44, 95% CI: 1.44-2.61). With respect to individual indicators within the EJI, Diesel Particulate Matter (DSLPM) and Air Toxic Cancer Risk (ATCR) demonstrated the strongest relationship (aOR 2.06, 95% CI: 1.57-2.71 and aOR 2.10, 95% CI: 1.59-2.78, respectively). Among non-Hispanic Black infants, 63% experienced a medically attended acute respiratory illness as compared to 18% of non-Hispanic White infants. DSLPM mediated 39% of the Black-White disparity in medically attended acute respiratory illness (p = 0.004). CONCLUSIONS: Environmental exposures, particularly air pollution, are associated with post-discharge respiratory health outcomes among preterm infants with BPD after adjusting for clinical, demographic, and social vulnerability risk factors. Certain types of air pollutants, namely, DSLPM, are more greatly associated with acute respiratory illness. Environmental exposures may contribute to racial disparities in medically attended acute respiratory illness among infants with BPD.

Nursing terminology for the care of people with respiratory diseases and Covid-19.

OBJECTIVES: To build a specialized nursing terminology for the care of people with respiratory diseases and Covid-19 or who have respiratory diseases after Covid-19, based on ICNP®. METHOD: Methodological study developed in two stages: (1) identification of the relevant concepts for the health priority chosen from the literature; (2) cross-mapping of the identified concepts with the concepts contained in ICNP® version 2019/2020. RESULTS: 9460 terms were extracted from the literature, of which 4065 terms were excluded because they were not related to the object of study and 5395 were submitted to the mapping technique, resulting in 290 constant terms in the ICNP® and 5134 non-constant terms. The constant terms were classified into the following axes: 120 in the Focus axis, 13 in Judgment, 48 in Action, 23 in Location, 38 in Means, eight in Time and one in Client. In addition, 36 nursing diagnoses/outcomes and three nursing interventions were mapped. CONCLUSION: The terminology will support the quality of care provided by the nursing team and the manual and electronic recording of patient data.