Pre-existing Health Research Articles

Long COVID is not the same for everyone: a hierarchical cluster analysis of Long COVID symptoms 9 and 12 months after SARS-CoV-2 test

BackgroundIdentifying symptom clusters in Long COVID is necessary for developing effective therapies for this diverse condition and improving the quality of life of those affected by this heterogeneous condition. In this study, we aimed to identify and compare symptom clusters at 9 and 12 months after a SARS-CoV-2 positive test and describe each cluster regarding factors at infection.MethodsThis is a cross-sectional study with individuals randomly selected from the Portuguese National System of Epidemiological Surveillance (SINAVE) database. Individuals who had a positive SARS-CoV-2 test in August 2022 were contacted to participate in a telephonic interview approximately 9 and 12 months after the test. A hierarchical clustering analysis was performed, using Euclidean distance and Ward’s linkage. Clustering was performed in the 35 symptoms reported 9 and 12 months after the SARS-CoV-2 positive test and characterised considering age, sex, pre-existing health conditions and symptoms at time of SARS-CoV-2 infection.Results552 individuals were included at 9 months and 458 at 12 months. The median age was 52 years (IQR: 40–64 years) and 59% were female. Hypertension and high cholesterol were the most frequently reported pre-existing health conditions. Memory loss, fatigue or weakness and joint pain were the most frequent symptoms reported 9 and 12 months after the positive test. Four clusters were identified at both times: no or minor symptoms; multi-symptoms; joint pain; and neurocognitive-related symptoms. Clusters remained similar in both times, but, within the neurocognitive cluster, memory loss and concentration issues increased in frequency at 12 months. Multi-symptoms cluster had older people, more females and more pre-existing health conditions at 9 months. However, at 12 months, older people and those with more pre-existing health conditions were in joint pain cluster.ConclusionsOur results suggest that Long COVID is not the same for everyone. In our study, clusters remained similar at 9 and 12 months, except for a slight variation in the frequency of symptoms that composed each cluster. Understanding Long COVID clusters might help identify treatments for this condition. However, further validation of the observed clusters and analysis of its risk factors is needed.

Depressive and anxiety symptoms among university students during the later stages of the COVID-19 pandemic in Germany - Results from the COVID 19 German Student Well-being Study (C19 GSWS).

Data on the mental health of university students in Germany during the later stages of the pandemic is still limited. This study aimed to determine (1) the prevalence of anxiety and depressive symptoms among university students 1.5 years after the first COVID-19 restrictions and (2) which factors were associated with these outcomes. The cross-sectional COVID-19 German Student Well-being Study (C19 GSWS) collected data of 6,996 students at five German universities. Associations between anxiety and depressive symptoms with sociodemographic and other factors were analyzed using multivariable logistic regression models. The mean age of the participants was 23.9 years (SD = 4.8), 67% were female and 31% male. The prevalence for depressive symptoms was 29 and 32% for anxiety. The lack of a trusted person and financial difficulties were associated with anxiety and depressive symptoms. Being worried that someone in one's personal network had become severely ill with COVID-19 and concern about (re)infection with COVID-19 were associated with anxiety symptoms. Those with pre-existing health conditions had an up to 1.98-times higher chance for reporting depressive symptoms (OR, 95% CI: 1.01-3.88) and an up to 2.27-times higher chance for anxiety symptoms, respectively (OR, 95% CI: 1.15-4.46). Concepts for prevention and counseling to tackle mental health problems in students are needed and programs should take specific stressors in times of crises into account.

Syrian refugees in Canada: a qualitative report of the impact of the COVID-19 pandemic on psychosocial adaptation

Purpose Since March 2020, the global COVID-19 pandemic has disproportionately impacted refugees by compounding preexisting and systemic health, social and economic inequities. In Canada, approximately 50,000 Syrian refugees arrived between 2015 and 2020 and were in the process of rebuilding their lives when the pandemic started. This study aims to explore the impact of the COVID-19 pandemic for Syrian refugees in Canada and identify supports needed. Design/methodology/approach Drawing on frameworks for refugee psychosocial adaptation and social integration and a qualitative descriptive design, the study used thematic analysis to examine semi-structured interviews with 10 Syrians. Findings Findings indicated four themes that provide a snapshot of impacts relatively early in the pandemic: facing ongoing development, inequity and insecurity during integration; disruption of settlement, integration and adaptation due to the pandemic; ongoing adaptation and resilience during integration in Canada; and ongoing needs and solutions for integration and adaptation. Originality/value This study builds upon growing research concerning Syrian refugees and psychosocial adaptation, particularly during the pandemic. The findings highlight the impacts of the pandemic on a population already facing inequities in a resettlement country. While the findings emphasize the resilience of the Syrian refugee community, the study also demonstrates the need for ongoing supports and justice-oriented action to fulfill resettlement commitments, especially in the face of additional stressors like the COVID-19 pandemic. Implications for policy, practice and future research are discussed.

Lessons from the COVID-19 pandemic to strengthen NCD care and policy in humanitarian settings: a mixed methods study exploring humanitarian actors’ experiences

BackgroundThe COVID-19 pandemic and response severely impacted people living with non-communicable diseases (PLWNCDs) globally. It exacerbated pre-existing health inequalities, severely disrupted access to care, and worsened clinical outcomes for PLWNCDs, who were at higher risk of morbidity and mortality from the virus. The pandemic’s effects were likely magnified in humanitarian settings, where there were pre-existing gaps in continuity of care for non-communicable diseases (NCDs). We sought to explore factors affecting implementation of NCD care in crisis settings during the COVID-19 pandemic and the adaptations made to support implementation.MethodsGuided by the Consolidated Framework for Implementation Research, we undertook an online survey of 98 humanitarian actors from multiple regions and organization types (March-July 2021), followed by in-depth interviews with 13 purposively selected survey respondents (October-December 2021). Survey data were analysed using descriptive statistics, while interview data were analysed thematically, using both deductive and inductive approaches.ResultsInitially, humanitarian actors faced challenges influenced by external actors’ priorities, such as de-prioritisation of NCD care by governments, travel restrictions and supply chain interruptions. With each infection wave and lockdown, humanitarian actors were better able to adapt and maintain NCD services. The availability of COVID-19 vaccines was a positive turning point, especially for the risk management of people with NCDs and protection of health workers. Key findings include that, despite pre-existing challenges, humanitarian actors largely continued NCD services during the crisis. Enabling factors that supported continuity of NCD services included the ability to quickly pivot to remote means of communication with PLWNCDs, flexibility in medicine dispensing, and successful advocacy to prioritize NCD management within health systems. Key lessons learned included the importance of partnerships and cooperation with other health actors, and the mobilisation or repurposing of community health workers/volunteer networks.ConclusionsThe COVID-19 experience should prompt national and global health stakeholders to strengthen inclusion of NCDs in emergency preparedness, response, and resilience planning. Key lessons were learned around remote care provision, including adapting to NCD severity, integrating community health workers, providing context-adapted patient information, combating misinformation, and strengthening cross-sectoral partnerships.

An Insight Into the Bacteriological Profile: Escalating Antimicrobial Resistance Patterns and the Spectrum of Multidrug-Resistant Enterobacteriaceae at a Tertiary Care Center in Western Maharashtra.

Enterobacteriaceae are a group of aerobic and facultative anaerobic Gram-negative bacilli known to cause various infections in healthy folks and those with preexisting health conditions. Current research focuses on analyzing the bacteriological profile of clinical isolates, examining their antimicrobial susceptibility and the spectrum of drug resistance. The study was conducted on patients admitted to the inpatient/outpatient department at Krishna Hospital, Karad. Clinical samples from patients with suspected infections, including pus, sputum, urine, blood, and other body fluids, were examined. The 156 bacterial isolates were identifiedusing Gram staining and biochemical tests following the standard protocol. Of the 156 isolates, Klebsiella pneumoniaewas the most commonisolate, with 79 (50.6%), followed by Escherichia coli, with 52 (33.3%). The maximum resistance was demonstrated toward co-trimoxazole (96.3%), ciprofloxacin (88.7%), and ceftazidime (84.6%). During the study,the prevalence of metallo-β-lactamase(MBL), extended-spectrum β-lactamase (ESBL), and AmpC increased significantly. The study data showedthe overall prevalence of MBL, ESBL, and AmpC to be 67.3%, 37.8%, and 38.4%, respectively. Further, the rate of multidrug-resistant isolates was noteworthy (92.6%). Thus, comprehending the resistance pattern and epidemiology of the organismwithin a specific demographic areacan help create better guidelines to curtail such infections.

Stability and Volatility in the Contextual Predictors of Working-Age Mortality in the United States.

The contextual predictors of mortality in the United States are well documented, but the COVID-19 pandemic may have upended those associations. Informed by the social history of disease framework (SHDF), this study examined how the importance of county contexts on adult deaths from all causes, drug poisonings, and COVID-19-related causes fluctuated during the pandemic. Using 2018 to 2021 vital statistics data, for each quarter, we estimated associations between county-level deaths among adults ages 25 to 64 and prepandemic county-level contexts (economic conditions, racial-ethnic composition, population health profile, and physician supply). The pandemic significantly elevated the importance of county contexts-particularly median household income and counties' preexisting health profile-on all-cause and drug poisoning deaths. The elevated importance of household income may be long-lasting. Contextual inequalities in COVID-19-related deaths rose and then fell, as the SHDF predicts, but rose again along with socio-political disruptions. The findings support and extend the SHDF.

Factors affecting UK anaesthetic trainees' wellbeing and stress: a scoping review.

Poor wellbeing and stress in UK anaesthetic trainees impacts significantly on clinical performance, workforce retention and patient care. This study aimed to provide an overview of the evidence in this field and to explore the factors affecting wellbeing and stress in UK anaesthetic trainees. MEDLINE, Embase, PsycINFO, and ERIC were searched, in addition to organisational websites. Literature reporting factors affecting wellbeing and stress in UK anaesthetic trainees from 2009 to present were included. Following exclusions, 45 studies were identified. Only five papers included qualitative analyses. Within these studies, 28 different phenomena related to wellbeing and stress were investigated. Thirty-one different factors affecting anaesthetic trainees' wellbeing and stress were identified in this review. These have been summarised as individual; training; clinical role; progression; work patterns; resources; rest; support; and cultural factors. External factors were described as affecting wellbeing and stress more frequently than internal factors. The most frequently cited individual factors were fatigue and pre-existing health status. The wide scope of phenomena of interest and measurement tools emphasises the challenge of defining and researching the concept of wellbeing. Despite these limitations, we have created a novel conceptual model of individual and external factors affecting UK anaesthetic trainees' wellbeing and stress. This supports an increased awareness and understanding of these factors, so that improvements can be made to practice and policy.

Unraveling the Nexus Between Ambient Air Pollutants and Cardiovascular Morbidity: Mechanistic Insights and Therapeutic Horizons.

Air pollution poses a significant threat to cardiovascular health, contributing to the development and progression of various heart diseases. This review delves into the intricate relationship between ambient air pollutants and cardiovascular morbidity, elucidating the underlying mechanisms and exploring potential therapeutic approaches. We discuss the major types of air pollutants, including particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO), and their respective roles in exacerbating cardiovascular conditions. The review highlights the key mechanisms by which air pollutants adversely impact the cardiovascular system, including systemic inflammation, oxidative stress, endothelial dysfunction, autonomic nervous system imbalance, and dysregulation of blood coagulation and thrombosis. Vulnerable populations, including children, the elderly, and those with pre-existing health conditions, are disproportionately affected. Air quality regulations aim to mitigate these effects by reducing pollutant levels, with the overall goal of lowering cardiovascular morbidity and improving public health outcomes. Specifically, stringent regulations focus on curbing vehicular emissions and industrial pollutants and promoting cleaner energy sources. Recent data underscore the importance of addressing environmental and behavioral risk factorsto prevent the growing global burden of cardiovascular disease. This review synthesizes the mechanistic pathways through which pollutants contribute to cardiovascular damage and highlights the urgent need for early detection strategies and targeted therapies. Improving public health through stricter air quality control measures and raising awareness of the health risks associated with pollution is crucial for mitigating the long-term cardiovascular impacts of air pollution.

The course of children's mental health symptoms during and beyond the COVID-19 pandemic.

The COVID-19 pandemic is associated with increases in child mental health problems, but the persistence of these changes in the post-pandemic era remains uncertain. Additionally, it is unclear whether changes in mental health problems during the pandemic exceed the anticipated increases as children age. This study controls for the linear effect of age in 1399 children, investigating the course of child-reported anxiety, depression, hyperactivity, and inattention symptoms during and after the pandemic, and identifies risk and protective factors that predict these mental health trajectories. Children (51% male; ages 9-11 at the first timepoint) provided mental health ratings at three pandemic timepoints (July-August 2020; March-April 2021; November 2021-January 2022) and one post-pandemic timepoint (January-July 2023). Mothers reported pre-pandemic mental health (2017-2019) and socio-demographic factors. Children reported socio-demographic factors, risk (e.g. screen time, sleep), and resilience (e.g. optimism) factors during the first timepoint. Average mental health symptoms increased over time, with more children exceeding clinical cut-offs for poor mental health at each subsequent pandemic timepoint. Growth curve modeling, adjusting for age-related effects, revealed a curvilinear course of mental health symptoms across all domains. Examination of risk and protective factors revealed that pre-existing mental health symptoms and optimism were associated with the course of symptoms. After considering age effects, children's mental health follows a curvilinear pattern over time, suggesting an initial decline followed by a rising trend in symptoms post-COVID. These findings underscore the continued need for additional resources and timely, evidence-based mental health prevention and intervention for children.

Making Sense of the COVID-19 Pandemic: The Use of Blogging by People with Inflammatory Bowel Disease

ABSTRACT During the global COVID-19 pandemic one population that faced special challenges was individuals with preexisting chronic health conditions. In this study, we examined how people with inflammatory bowel disease (IBD) managed their autoimmune disease, considering their increased susceptibility to contracting COVID-19. Specifically, we analyzed how people with IBD made sense of their precarious position through the writing of publicly accessible blogs. We found that for IBD patients, navigating healthcare needs in the context of pandemic-related concerns and restrictions meant grappling with several salient, but conflicting tensions: separation vs. connection, safety vs. exposure, uncertainty vs. control, and resilience vs. vulnerability. People with IBD struggled to find a balance between living with IBD while keeping themselves and their loved ones safe from the virus. While the worst of the COVID-19 pandemic may be over, the underlying disease, and the tensions the disease causes, is still present for people with IBD.

The unequal impacts of the COVID-19 pandemic on young adults' mental health. Predictors of vulnerability and resilience using longitudinal birth cohort data in the UK.

Previous studies have demonstrated deteriorations in young adult mental health during the COVID-19 pandemic, but evidence suggests heterogeneity in the mental health impacts of the pandemic. We sought to identify factors which may predict changes in psychological distress and wellbeing during the COVID-19 pandemic in UK young adults. A total of 2607 young adults from the Millennium Cohort Study were included. Psychological distress and mental wellbeing were measured using the Kessler-6 and Short Warwick-Edinburgh Mental Wellbeing Scale, respectively. Assessment occurred at three timepoints between the ages of 17-19: 2018/19 (pre-COVID Baseline), May 2020 (COVID Wave 1) and September/October 2020 (COVID Wave 2). Latent change score models were used to study change in distress and wellbeing across the study period, as well as the impact of sex, relative family poverty, parental education, preexisting mental health difficulties and perceived social support on these changes. The latent change score models suggested both distress and wellbeing tended to increase across the study period. Being female and in relative poverty predicted greater increases in distress and/or poorer wellbeing. Higher levels of parental education and greater perceived social support were protective against increased distress and associated with improved wellbeing. The impact of the COVID-19 pandemic on UK young adult mental health is complex. We provide further evidence for a distinction between symptoms of poor mental health and wellbeing. Research is urgently needed to assess the long-term impacts of the COVID-19 pandemic on the mental health and wellbeing of young people, particularly in more vulnerable groups.

Suicide ideation and intentional self-harm as a risk factor for readmission within one year following a trauma alert: A 10 year retrospective analysis

The objective of this analysis is to study physical traumatic injury as a risk factor for suicide ideation and attempts. The analysis is retrospective, focusing on inpatient readmission with suicide ideation or intentional self-harm within one year of hospitalization as a trauma alert (TA). Injured patients were divided into TA and emergencies without activation (EMWA) of trauma services. We estimated the probability of readmission with suicide ideation or intentional self-harm using a logistic regression. Rates of readmission with intentional self-harm and suicide ideation were on average 60 and 45% higher for the TA group (p < 0.01). Over 80% of patients readmitted with intentional self-harm or suicide ideation had a preexisting mental health condition, compared to approximately 45% in the overall sample. Logistic regression results indicate these patients had an odds-ratio of near six, predicting the readmission. When patients with a preexisting mental health condition were excluded from the analysis, TA patients were significantly more likely to experience a readmission with intentional self-harm and suicide ideation. Demographic and socioeconomic characteristics (gender, age, race, insurance status, and median incomes) as well as injury type (traumatic brain injury or TBI) also help predict readmission with suicide ideation and intentional self-harm. The main risk factors for reengagement with self-harm and suicidal ideation/attempt include preexisting mental health conditions, TA status, and socioeconomic status. Targeted, sustained, and prolonged rehabilitation and trauma-informed therapy for this high-risk group of severely injured patients may yield significant health and social benefits.

Quantifying the Impact of Climate Change on Mortality Rates: A Stochastic Actuarial Approach in Uganda

Purpose: The aim of the study was to analyze the quantifying the impact of climate change on mortality rates: a stochastic actuarial approach in Uganda. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that climate change significantly increases mortality rates, particularly through the rise in extreme weather events and temperature-related illnesses. Using stochastic actuarial models, the research demonstrated a strong correlation between climate variability and higher mortality, especially among vulnerable populations such as the elderly and those with pre-existing health conditions. The findings underscore the urgent need for climate adaptation strategies in Uganda's public health planning to mitigate the adverse effects of climate change on mortality. Unique Contribution to Theory, Practice and Policy: Risk theory, ecological theory &amp; actuarial life table theory may be used to anchor future studies on analyze the quantifying the impact of climate change on mortality rates: a stochastic actuarial approach in Uganda. Practitioners should integrate climate data into actuarial models used for mortality forecasting and risk assessment. Policymakers should develop and enforce regulatory standards that require the inclusion of climate change considerations in actuarial assessments and reporting.

Assessment of Ambient Air Pollution Levels: A Five-Year Analysis of PM2.5, NO, NO2, NOX, CO, and SO2

The study conducted on the air quality of five highly polluted cities in India over the last five years (2015-2020) sheds light on the detrimental effects of air pollution and the need for monitoring and mitigation. The research focused on six major air pollutants: PM2.5, NO, NO2, NOX, CO, and SO2. The study's findings reveal that the concentrations of these air pollutants consistently exceeded the limits set by the National Ambient Air Quality Standards 2009 and the World Health Organization's Ambient Air Quality Standards. This indicates that the air quality in these cities was consistently poor and posed a significant health risk to the population. The study emphasises that certain subpopulations, such as the elderly, young children, and individuals with pre-existing health conditions like asthma, are more vulnerable to the harmful effects of air pollutants. Elevated levels of pollutants in the air can lead to severe health effects and contribute to the development of serious diseases. Furthermore, the study highlights that the air quality significantly improved in 2020 due to the nationwide lockdown imposed in response to the COVID-19 pandemic. The restrictions on mobility and industrial activities resulted in reduced emissions, leading to a temporary improvement in air quality. These conclusions underscore the critical importance of understanding the harmful effects of air pollutants and taking measures to protect human health and preserve the quality of the environment.

Telerehabilitation for Geriatric with Dementia and Long Covid-19

Rehabilitation is crucial for individuals who have survived COVID-19, particularly those who are older and have pre-existing health conditions. These survivors may experience long covid symptoms up to four months after infection. Elderly individuals suffering from long covid face difficulties in undergoing conventional rehabilitation methods due to limitations in mobility, lack of social interaction, and inadequate healthcare accessibility. As a result, telerehabilitation has arisen as an alternate form of care. This case report intends to present empirical evidence on the enhancement of functional status in a geriatric long covid patient following telerehabilitation. We present a case of an elderly woman with underlying dementia who developed long covid. The symptoms included of dyspnea and mobility impairment. We provide a telerehabilitation program for three weeks with an active-assisted range of motion exercises. Following three sessions of telerehabilitation, we could see improvement in her Physical Mobility Scale (PMS). After 20 days, the patient's PMS score increased by 3 points.

Combined Influence of Multiple Factors on Lung Cancer and Anxiety: A Probit Model Analysis

Lung cancer remains a leading cause of cancer-related mortality worldwide, significantly impacting public health. Concurrently, anxiety is a prevalent psychological disorder known to influence the development and progression of various cancers. This research paper aims to examine the combined influence of various factors, including demographic characteristics, environmental exposures, and physical conditioning data, on the incidence of lung cancer and anxiety. Given the binary nature of both lung cancer and anxiety outcomes, the analyses will first employ separate binary probit regression models to identify significant predictors for each condition independently. Then, joint modeling techniques will be implemented with dual purposes. First, by comparing the results of the individual and joint models, the reliability and robustness of the findings will be enhanced through cross-validation. Second, joint models will enable an investigation into potential endogeneity between lung cancer and anxiety. Addressing this endogeneity is crucial as it can potentially improve model robustness and provide deeper insights into the interrelationship between these two health outcomes. For the study purpose, the demographic factors considered include age and gender. Environmental factors encompass smoking history, alcohol consumption, and peer pressure. Physical conditioning data includes pre-existing health conditions such as yellow fingers, anxiety, chronic disease, fatigue, allergy, wheezing, coughing, shortness of breath, swallowing difficulty, and chest pain. By leveraging advanced statistical modeling techniques, this research seeks to uncover nuanced relationships and potential causal pathways that may exist between lung cancer and anxiety. The findings from this study will contribute to the existing body of knowledge by providing additional case study showing the relationship among a multitude of factors on lung cancer and anxiety, respectively. Also, the endogeneity checking among lung cancer and anxiety may enhance the efficiency of models done by others in the future. The research paper's analysis on lung cancer incidences reveals that age and wheezing are significant predictors. In examining anxiety levels, smoking emerged as a significant predictor, indicating a higher likelihood of anxiety among smokers. In addition, the joint probit models confirmed these findings, with age and wheezing significantly predicting lung cancer incidence, and smoking significantly predicting anxiety levels. No significant endogeneity was observed between lung cancer and anxiety, suggesting that these health outcomes are influenced by different sets of factors. These findings underscore the importance of considering demographic, environmental, and physical conditioning data in understanding and addressing lung cancer and anxiety, and checking their potential endogeneity

Microscale Temperature-Humidity Index (THI) Distribution Estimated at the City Scale: A Case Study in Maebashi City, Gunma Prefecture, Japan

Global warming and climate change are significantly impacting local climates, causing more intense heat during the summer season, which poses risks to individuals with pre-existing health conditions and negatively affects overall human health. While various studies have examined the Surface Urban Heat Island (SUHI) phenomenon, these studies often focus on small to large geographic regions using low-to-moderate-resolution data, highlighting general thermal trends across large administrative areas. However, there is a growing need for methods that can detect microscale thermal patterns in environments familiar to urban residents, such as streets and alleys. The temperature-humidity index (THI), which incorporates both temperature and humidity data, serves as a critical measure of human-perceived heat. However, few studies have explored microscale THI variations within urban settings and identified potential THI hotspots at a local level where SUHI effects are pronounced. This research aims to address this gap by estimating THI at a finer resolution scale using data from multiple sensor platforms. We developed a model with the random forest algorithm to assess THI trends at a resolution of 0.5 m, utilizing various variables from different sources, including Landsat 8 land surface temperature (LST), unmanned aerial system (UAS)-derived LST, Sentinel-2 NDVI and NDMI, a wind exposure index, solar radiation modeled from aircraft and UAS-derived Digital Surface Models, and vehicle density and building floor area from social big data. Two models were constructed with different variables: Modelnatural, which includes variables related to only natural factors, and Modelmix, which includes all variables, including anthropogenic factors. The two models were compared to reveal how each source contributes to the model development and SUHI effects. The results show significant improvements, as Modelnatural had a fitting R2 = 0.5846, a root mean square error (RMSE) = 0.5936 and a mean absolute error (MAE) = 0.4294. Moreover, when anthropogenic factors were introduced, Modelmix performed even better, with R2 = 0.9638, RMSE = 0.1751, and MAE = 0.1065 (n = 923). This study contributes to the future of microscale SUHI analysis and offers important insights into urban planning and smart city development.

Worried (and) sick: how environmental hazards affect Americans’ health-related risk attitudes

This study explores risk attitudes towards environmental hazards by adapting the Comprehensive Conceptual Risk Perception Model (CCRPM) and applying it in the context of health-related implications of these hazards. We argue that personal experience and a deeper understanding of environmental hazards increase risk perceptions, while a strong social context reduces health concerns. Utilizing data from a national survey (N = 1207), our findings reveal higher health-related risk perceptions among individuals with pre-existing health conditions. Additionally, those with greater knowledge of environmental threats exhibit heightened concern about health complications. Conversely, individuals in communities with robust social ties report lower risk attitudes. An in-depth analysis further indicates that residents of high-risk communities, characterized by higher levels of air pollution, have increased risk perceptions compared to those in less polluted areas. These findings reinforce the dimensions described in the CCRPM and highlight the significance of structural conditions in shaping individuals' risk perceptions.

The effects of potentially traumatic events on the recovery from pre-existing anxiety and depression symptomatology and the risk of PTSD.

The extent to which recent potentially traumatic events (PTEs) hinder the recovery from pre-existing mental health problems is largely unknown. The same applies to the extent to which non-recovery from pre-existing mental health problems increases the risk of posttraumatic stress disorder (PTSD). The aim of the present study is to gain insight in these effects. Data were extracted from six annual surveys of the Dutch population-based Victims in Modern Society (VICTIMS) study. Of the adult respondents who participated in two subsequent surveys (labeled T1 and T2, n = 6942), those with severe anxiety and depression symptoms (ADS) at T1 (n = 487) were selected. We distinguished respondents exposed to PTEs (PTE-group, n = 162) and not exposed to PTEs (comparison group, n = 325) between T1 and T2. We applied five indicators of recovery [based on the Reliable Change Index (RCI), degrees of symptom reduction, and the cut-off score at T2]. Differences in the recovery from ADS and probable PTSD at T2 were examined using multivariate logistic regression. The PTE group less often recovered from severe ADS between T1 and T2 than the comparison group according to all five indicators of recovery, while controlling for 11 different variables (0.40 ≤ adjusted OR's ≤ 0.66). Those in the PTE group who did not recover, considerably more often suffered from probable PTSD at T2 (63%-82%) than those who did recover (0%-29%; 8.96 ≤ adjusted OR ≤ 26.33). Recent potentially traumatic events hinder the recovery from pre-existing anxiety and depression symptomatology and thereby increase the risk of probable PTSD.

A Population-Based Study on Women Who Used Alcohol during Pregnancy and Their Neonates in Ontario, Canada.

Data from birth registries can be studied to assess the prevalence of prenatal alcohol use and associated maternal and neonatal outcomes. Linked maternal and neonatal data (2015-2018) for alcohol-exposed pregnancies were obtained from the Better Outcomes Registry and Network (BORN) Ontario. Descriptive statistics were generated for maternal demographics, prenatal substance use, mental health/substance use history, and neonatal outcomes. Logistic regression models were performed to assess the odds of prenatal heavy (binge or weekly) alcohol and other substance use based on mental health/substance use history and other maternal demographics, and the impacts of heavy alcohol use and other prenatal substance exposures on neonatal outcomes. A total of 10,172 (2.4%) women reported alcohol use during pregnancy. One-third had pre-existing or current mental health and/or substance use problems, which was associated with significantly higher odds of heavy alcohol use during pregnancy. Prenatal exposure to heavy alcohol use was associated with increased odds of neonatal abstinence syndrome (2.5 times); respiratory distress syndrome (2.3 times); neonatal intensive care unit (NICU) admission (58%); and hyperbilirubinemia (57%). Prenatal exposure to one or more substances in addition to alcohol was associated with significantly higher odds of fetal/maternal/placental pregnancy complications; preterm birth; NICU admission; low APGAR scores; one or more confirmed congenital anomalies at birth; respiratory distress syndrome; and intrauterine growth restriction. It is crucial to routinely screen childbearing-age and pregnant women for alcohol and other substance use as well as mental health problems in order to prevent adverse maternal and neonatal outcomes.