Increased risk of emergency department presentations for bronchiolitis in infants exposed to air pollution

Air pollution has been linked to an increased risk of several respiratory diseases in children, especially respiratory tract infections. The present study aims to evaluate the association between pediatric emergency department (PED) presentations for bronchiolitis and air pollution. PED presentations due to bronchiolitis in children aged less than 1 year were retrospectively collected from 2007 to 2018 in Padova, Italy, together with daily environmental data. A conditional logistic regression based on a time-stratified case-crossover design was performed to evaluate the association between PED presentations and exposure to NO₂, PM2.5, and PM10. Models were adjusted for temperature, relative humidity, atmospheric pressure, and public holidays. Delayed effects in time were evaluated using distributed lag non-linear models. Odds ratio for lagged exposure from 0 to 14 days were obtained. Overall, 2251 children presented to the PED for bronchiolitis. Infants’ exposure to higher concentrations of PM10 and PM2.5 in the 5 days before the presentation to the PED increased the risk of accessing the PED by more than 10%, whereas high concentrations of NO₂ between 2 and 12 days before the PED presentation were associated with an increased risk of up to 30%. The association between pollutants and infants who required hospitalization was even greater. A cumulative effect of NO₂ among the 2 weeks preceding the presentation was also observed. In summary, PM and NO₂ concentrations are associated with PED presentations and hospitalizations for bronchiolitis. Exposure of infants to air pollution could damage the respiratory tract mucosa, facilitating viral infections and exacerbating symptoms.     

Small area estimation for longitudinal surveys

Over the last few years many studies have been carried out in Italy to identify reliable small area labour force indicators. Considering the rotated sample design of the Italian Labour Force Survey, the aim of this work is to derive a small area estimator which borrows strength from individual temporal correlation, as well as from related areas. Two small area estimators are derived as extensions of an estimation strategies proposed by Fuller (1990) for partial overlap samples. A simulation study is carried out to evaluate the gain in efficiency provided by our solutions. Results obtained for different levels of autocorrelation between repeated measurements on the same outcome and different population settings show that these estimators are always more reliable than the traditional composite one, and in some circumstances they are extremely advantageous.The present paper is financially supported by Murst-Cofin (2001) Lutilizzo di informazioni di tipo amministrativo nella stima per piccole aree e per sottoinsiemi della popolazione (National Coordinator Prof. Carlo Filippucci).     

Predicting Severity of Foreign Body Injuries in Children in Upper Airways: An Approach Based on Regression Trees

The entry of a small item into the upper airways is one of the leading causes of injuries in children up to 14 years old. The aim of this study is to characterize types of objects causing choking along with the features of the children involved in the accident and compare results with current standards. The European Survey on Foreign Bodies Injuries Study (ESFBI) collected data on foreign body injuries from 19 European countries. The data from ESFBI were selected according to the ICD-9-CM codes 933 (foreign body in the pharynx and larynx) and 934 (foreign body in the trachea, bronchi, and lungs). Both a classification tree and a linear discriminant analysis (LDA) have been set up to predict the probability that an injured child experiences a hospitalization. The classification tree provides flowchart-type decision rules and allows for analyzing the impact of the item features, the children characteristics, and the circumstances of the accidents on the severity of the foreign body injuries. Results showed that children younger than 3.5 who are involved in an accident have a high probability to experience a hospitalization.     

A Gender Lens on Quality of Life: The Role of Sense of Community,Perceived Social Support,Self-Reported Health and Income

Quality of life (QoL) refers to a subjective evaluation that is embedded in a cultural, social and environmental context. It is a multidimensional concept and its assessment covers four domains: physical health, psychological health, social relationships, and environment. Although many studies report on QoL, literature rarely addressed the question of the QoL predictors from a gender perspective. Present study aimed at investigating gender differences in the determinants of QoL. Specifically, gender was considered as a moderator in the relationship between predictors of QoL (i.e. socio-demographic characteristics, perceived health, income, social support and sense of community) and each dimension of QoL. 654 Italian adults participated in the study. Results show that men outscore women on the physical, the psychological and the environmental domains of QoL. Considering determinants of QoL, sense of community and self-reported health operate in a similar fashion for both genders. On the contrary, social support is more predictive for women’s QoL, whereas the income level is more significant for men’s QoL. Implications are discussed.     

Psychometric Properties of the Medical Outcome Study Social Support Survey with a General Population Sample of Undergraduate Students

Among non-clinical populations, perceived social support is an important factor in health maintenance and well-being. Among measures that purport to assess perceived social support, the Medical Outcomes Study Social Support Survey (MOS-SSS) is based on a strong conceptual framework and has been subjected to a rigorous psychometric evaluation. Since no studies have investigated its psychometric properties with a young, non-clinical population, the purpose of this study is to investigate the psychometric properties (construct validity, internal consistency, and test–retest reliability) of an Italian version of the MOS-SSS with a non-clinical population sample. A convenience sample of 485 undergraduate students (73.0 % female; mean age = 21.81 ± 1.52) has been recruited. With regards to scale dimensionality, the best fit measurement model found support for the four subscales proposed by the original version: emotional and informational support, tangible support, positive social interactions, and affectionate support (χ ²/df = 4.49; CFI = .92; TLI = .91; RMSEA = .08). MOS-SSS subscales showed good internal consistency (Cronbach’s alpha for the subscales ranged from .848 to .939). Significant correlations were found with measures of psychological well-being (Ryff’s Scales of Psychological Well-Being) and depression (Beck-Depression Inventory-II). Test–retest stability was tested by examining a subsample (N = 225) over a 10-week period (correlation coefficients for the subscales ranged from .502 to .579). The findings suggest that MOS-SSS presents good psychometric characteristics with a young general population sample. Therefore, the MOS-SSS seems to be a psychometrically sound measure for the evaluation of perceived social support among young non-clinical populations.     

The Gamma-count distribution in the analysis of experimental underdispersed data

Event counts are response variables with non-negative integer values representing the number of times that an event occurs within a fixed domain such as a time interval, a geographical area or a cell of a contingency table. Analysis of counts by Gaussian regression models ignores the discreteness, asymmetry and heteroscedasticity and is inefficient, providing unrealistic standard errors or possibly negative predictions of the expected number of events. The Poisson regression is the standard model for count data with underlying assumptions on the generating process which may be implausible in many applications. Statisticians have long recognized the limitation of imposing equidispersion under the Poisson regression model. A typical situation is when the conditional variance exceeds the conditional mean, in which case models allowing for overdispersion are routinely used. Less reported is the case of underdispersion with fewer modeling alternatives and assessments available in the literature. One of such alternatives, the Gamma-count model, is adopted here in the analysis of an agronomic experiment designed to investigate the effect of levels of defoliation on different phenological states upon the number of cotton bolls. Data set and code for analysis are available as online supplements. Results show improvements over the Poisson model and the semi-parametric quasi-Poisson model in capturing the observed variability in the data. Estimating rather than assuming the underlying variance process leads to important insights into the process.     

“Trying to be positive in the face of the storm”: The experiences of independent college students during the COVID-19 pandemic

The COVID-19 pandemic created multiple stressors for college students, particularly for young adults experiencing multiple forms of disadvantage. Little is known about the pandemic experiences of independent college students, many of whom are emancipated minors, former wards of the state, and other students who lack familial financial and practical support as they pursue higher education. Twenty-three independent students, ages 18–23, from one northeastern university were interviewed to understand how independent students were affected by the COVID-19 pandemic, and their needs for support from the university during this time. Most participants were identified as Black or Latinx, and two thirds were first-generation college students. Participants reported an overall lack of support from their families prior to the pandemic. During the pandemic, they experienced compounding academic, economic, and mental health-related stressors. Students responded to these stressors in resilient and resourceful ways, by adapting to their new realities, expressing gratitude, and finding opportunities for self-growth. Participants recommend that institutions of higher education support independent students during periods of emergency through providing financial assistance, offering opportunities for connection with both adults and peers, and demonstrating administrative flexibility and understanding of their unique needs.     

Who’s About to Leave? A Global Survey of Aspirations and Intentions to Migrate

This article analyses aspirations and intentions to migrate based on Gallup World Poll for the period 2010–2015. We estimate individual‐level traits associated with aspirations and intentions to migrate across groups of countries in different regions and with different income levels. This paper brings together previous hypotheses regarding migration aspirations and tests them under several specifications, while keeping separate findings according to migration aspirations and intentions to appreciate differences between them. Being dissatisfied with one’s own standard of living is associated with a higher probability of desiring to move, while the relation with the actual preparation to migrate is less clear. Some individual traits remain significant across (almost) all specifications: being male, foreign‐born, highly educated, and having networks abroad are associated with higher probability of preparing for international migration. Aspects related to one’s economic situation are not consistently significant across specifications, signalling the importance of contextual analyses for these factors.