Project description:BackgroundThe Covid-19 pandemic and its accompanying public-health orders (PHOs) have led to (potentially countervailing) changes in various risk factors for overdose. To assess whether the net effects of these factors varied geographically, we examined regional variation in the impact of the PHOs on counts of nonfatal overdoses, which have received less attention than fatal overdoses, despite their public health significance.MethodsData were collected from the Overdose Detection Mapping Application Program (ODMAP), which recorded suspected overdoses between July 1, 2018 and October 25, 2020. We used segmented regression models to assess the impact of PHOs on nonfatal-overdose trends in Washington DC and the five geographical regions of Maryland, using a historical control time series to adjust for normative changes in overdoses that occurred around mid-March (when the PHOs were issued).ResultsThe mean level change in nonfatal opioid overdoses immediately after mid-March was not reliably different in the Covid-19 year versus the preceding control time series for any region. However, the rate of increase in nonfatal overdose was steeper after mid-March in the Covid-19 year versus the preceding year for Maryland as a whole (B = 2.36; 95% CI, 0.65 to 4.06; p = .007) and for certain subregions. No differences were observed for Washington DC.ConclusionsThe pandemic and its accompanying PHOs were associated with steeper increases in nonfatal opioid overdoses in most but not all of the regions we assessed, with a net effect that was deleterious for the Maryland region as a whole.
Project description:ObjectiveThe purpose of the study is to examine the prevalence of loneliness in Europe in 2016 and during the first months - April-July 2020 - of the COVID-19 pandemic, and to assess whether the risk factors associated with loneliness have changed after the outbreak of the pandemic.MethodThe analysis is based on two cross-country surveys, namely the 2016 European Quality of Life Survey and the 2020 Living, Working and COVID-19 Online Survey.ResultsThe COVID-19 pandemic has magnified already worrying levels of loneliness in Europe. Young adults have been the most severely hit by social distancing measures. Living alone has made social distancing measures more painful. Health and financial status are strong associates of loneliness, irrespective of the time period.ConclusionThis analysis will help anticipate the potential consequences that forced social isolation might have triggered in the population and identify populations more vulnerable to loneliness. Further monitoring is important to assess whether the registered increase in loneliness is transient or chronic and to design targeted loneliness interventions.
Project description:BackgroundLoneliness has become a significant public health concern for older people. However, little is known about the association of loneliness, loneliness literacy, and changes in loneliness during the COVID-19 pandemic with mental well-being. The purpose of this study was to explore whether loneliness literacy is related to a lower risk of loneliness, increased loneliness during the COVID-19 pandemic, and improved mental well-being for community-based older adults.MethodsA telephone survey was conducted to collect data from older adults aged 65 years or older in Taiwan (n = 804). Loneliness, change in loneliness during COVID-19, and loneliness literacy were the main variables. Mental well-being was assessed by depressive symptoms and life satisfaction. Related factors included personal level (demographics, health conditions, health behaviors, and problem-focused/ emotion-focused coping strategies), interpersonal level (marital status, living arrangements, social support, social participation, leisure activities, and social interactions during COVID-19), and societal level (areas and regions) factors.ResultsFour dimensions of loneliness literacy were identified by factor analysis: self-efficacy, social support, socialization, and in-home support. Self-efficacy and in-home support were related to lower loneliness. Lower self-efficacy, higher social support, and higher socialization were related to changes (increases) in loneliness during COVID-19. In-home support may prevent depressive symptoms, while self-efficacy was beneficial for better life satisfaction. In addition, emotion-focused coping may increase loneliness during COVID-19, while satisfaction with family support would be a protective factor against loneliness.ConclusionLoneliness literacy is related to loneliness and increased loneliness during the COVID-19 pandemic. Building up an age-friendly community with embedded services/information and learning positive coping and mental resilience strategies are suggested.
Project description:In the turbulent year 2020, overshadowed by the global COVID-19 pandemic, Austria experienced multiple waves of increased case incidence. While governmental measures to curb the numbers were based on current knowledge of infection risk factors, a retrospective analysis of incidence and lethality at the district level revealed correlations of relative infection risk with socioeconomic, geographical, and behavioral population parameters. We identified unexpected correlations between political orientation and smoking behavior and COVID-19 infection risk and/or mortality. For example, a decrease in daily smokers by 2.3 percentage points would be associated with an increase in cumulative incidence by 10% in the adjusted model, and an increase in voters of the right-wing populist party by 1.6 percentage points with an increase in cumulative mortality by 10%. While these parameters are apparently only single elements of complex causal chains that finally lead to individual susceptibility and vulnerability levels, our findings might have identified ecological parameters that can be utilized to develop fine-tuned communications and measures in upcoming challenges of this and other pandemics.
Project description:Healthcare costs in the Netherlands are rising and vary considerably among regions. Explaining regional differences in healthcare costs can help policymakers in targeting appropriate interventions in order to restrain costs. Factors usually taken into account when analyzing regional differences in healthcare costs are demographic structure and socioeconomic status (SES). However, health, lifestyle, loneliness and mastery have also been linked to healthcare costs. Therefore, this study analyzes the contribution of health, lifestyle factors (BMI, alcohol consumption, smoking and physical activity), loneliness, and mastery to regional differences in healthcare costs. Analyses are performed in a linked dataset (n = 334,721) from the Dutch Public Health Services, Statistics Netherlands, the National Institute for Public Health and the Environment (year 2016), and the healthcare claims database Vektis (year 2017) with Poisson and zero-inflated binomial regressions. Regional differences in general practitioner consult costs remain significant even after taking into account health, lifestyle, loneliness, and mastery. Regional differences in costs for mental, pharmaceutical, and specialized care are less pronounced and can be explained to a large extent. For total healthcare costs, regional differences are mostly explained through the factors included in this study. Hence, addressing lifestyle factors, loneliness and mastery can help policymakers in restraining healthcare costs. In this study, the region of Zuid-Limburg represents the reference region. Use compare regions for health and healthcare costs (Regiovergelijker gezondheid en zorgkosten) in order to select all other Dutch regions as reference region.Supplementary informationThe online version of this article (10.1007/s12508-022-00369-4) contains supplementary material, which is available to authorized users.
Project description:Expression level of genes in lymphoblasts from individuals in three HapMap populations (CEU, CHB, JPT) were compared. More than 1,000 genes were found to be significantly different (Pc<0.05) in mean expression level between the CEU and CHB+JPT samples. Keywords: Comparison of Gene Expression Profiles from Lymphoblastoid cells
Project description:Consistent inter-individual differences in behaviour, that is, personalities, can emerge as a result of inter-individual differences in ontogenetic experience, and predation risk is a potent one. As personalities develop over lifetime, however, they may also be broken by ontogenetic transitions of the individual. Here we first tested the hypothesis that consistent inter-individual differences in larval behaviour arise under predation challenge, and are entangled with differences in body size. We then tested the hypothesis that adult behavioural type is related to body size rather than to larval behavioural phenotype. To test these hypotheses, we performed a longitudinal study following the development of about 50 moor frogs, Rana arvalis. We manipulated their larval and current environment, and recorded their behaviours repeatedly, under control conditions, invertebrate predators' chemical cues or in live predator presence. Partially in line with our predictions, the ontogenetic experience of predator presence led to personality emergence in tadpoles, yet their behaviour was not explained by their body size. This pattern was lost over metamorphosis. According to predictions, pre-adult moor frog behaviour was affected by their body size-time to exit shelter was shorter in larger frogs-but neither by their behaviour as tadpoles nor by their larval environment, that is, tadpole predator-exposure experience. Our results show that individual behavioural tendencies can be well decoupled between prior and post metamorphosis, which adds to the growing empirical evidence supporting adaptive decoupling hypothesis.
Project description:Standard epidemiological models for COVID-19 employ variants of compartment (SIR or susceptible-infectious-recovered) models at local scales, implicitly assuming spatially uniform local mixing. Here, we examine the effect of employing more geographically detailed diffusion models based on known spatial features of interpersonal networks, most particularly the presence of a long-tailed but monotone decline in the probability of interaction with distance, on disease diffusion. Based on simulations of unrestricted COVID-19 diffusion in 19 US cities, we conclude that heterogeneity in population distribution can have large impacts on local pandemic timing and severity, even when aggregate behavior at larger scales mirrors a classic SIR-like pattern. Impacts observed include severe local outbreaks with long lag time relative to the aggregate infection curve, and the presence of numerous areas whose disease trajectories correlate poorly with those of neighboring areas. A simple catchment model for hospital demand illustrates potential implications for health care utilization, with substantial disparities in the timing and extremity of impacts even without distancing interventions. Likewise, analysis of social exposure to others who are morbid or deceased shows considerable variation in how the epidemic can appear to individuals on the ground, potentially affecting risk assessment and compliance with mitigation measures. These results demonstrate the potential for spatial network structure to generate highly nonuniform diffusion behavior even at the scale of cities, and suggest the importance of incorporating such structure when designing models to inform health care planning, predict community outcomes, or identify potential disparities.
Project description:The COVID-19 pandemic and measures aimed at its mitigation, such as physical distancing, have been discussed as risk factors for loneliness, which increases the risk of premature mortality and mental and physical health conditions. To ascertain whether loneliness has increased since the start of the pandemic, this study aimed to narratively and statistically synthesize relevant high-quality primary studies. This systematic review with meta-analysis was registered at PROSPERO (ID CRD42021246771). Searched databases were PubMed, PsycINFO, Cochrane Library/Central Register of Controlled Trials/EMBASE/CINAHL, Web of Science, the World Health Organization (WHO) COVID-19 database, supplemented by Google Scholar and citation searching (cutoff date of the systematic search December 5, 2021). Summary data from prospective research including loneliness assessments before and during the pandemic were extracted. Of 6,850 retrieved records, 34 studies (23 longitudinal, 9 pseudolongitudinal, 2 reporting both designs) on 215,026 participants were included. Risk of bias (RoB) was estimated using the risk of bias in non-randomised studies-of interventions (ROBINS-I) tool. Standardized mean differences (SMD, Hedges' g) for continuous loneliness values and logOR for loneliness prevalence rates were calculated as pooled effect size estimators in random-effects meta-analyses. Pooling studies with longitudinal designs only (overall N = 45,734), loneliness scores (19 studies, SMD = 0.27 [95% confidence interval = 0.14-0.40], Z = 4.02, p < .001, I 2 = 98%) and prevalence rates (8 studies, logOR = 0.33 [0.04-0.62], Z = 2.25, p = .02, I 2 = 96%) increased relative to prepandemic times with small effect sizes. Results were robust with respect to studies' overall RoB, pseudolongitudinal designs, timing of prepandemic assessments, and clinical populations. The heterogeneity of effects indicates a need to further investigate risk and protective factors as the pandemic progresses to inform targeted interventions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Project description:The main objective of the study is to assess the impact of regional heterogeneity on the severity of COVID-19 in Japan. We included 27,865 cases registered between January 2020 and February 2021 in the COVID-19 Registry of Japan, to examine the relationship between the National Early Warning Score (NEWS) of COVID-19 patients on the day of admission and the prefecture where the patients live. A hierarchical Bayesian model was used to examine the random effect of each prefecture in addition to the patients' backgrounds. Additionally, we compared the results of two models; one model included the number of beds secured for COVID-19 patients in each prefecture as one of the fixed effects, and the other model did not. The results indicated that the prefecture had a substantial impact on the severity of COVID-19 on admission, even when considering the effect of the number of beds separately. Our analysis revealed a possible association between regional heterogeneity and increased/decreased risk of severe COVID-19 infection on admission. This heterogeneity was derived not only from the number of beds secured in each prefecture but also from other factors.