Relationship between Depressive Symptoms and Weather Conditions

Examining illness perceptions over time: an exploratory prospective analysis of causal attributions in individuals with depressive symptoms

BACKGROUND

According to the Common-Sense Model of Illness Representations, illness beliefs, such as causal attributions, can influence the way people assess and cope with their illness and vice versa. To date, causal attributions in people with depressive symptoms have been studied mainly cross-sectionally, quantitatively and independently. The purpose of this study is to examine the causal attributions of people with depressive symptoms in terms of their stability over time, dependence on treatment experience, and differentiation of causal concepts.

METHODS

In a population-based prospective sample, people with at least mild depressive symptoms (PHQ-9 Score ≥ 5) were interviewed via telephone at T0 and twelve months later (T1). Causal attributions were assessed using the Brief Illness Perception Questionnaire. After the open responses were qualitatively analysed using a deductive-inductive approach, stability over time was assessed for causal attributions and concepts by comparing answers between the two time points. Subsequent exploratory quantitative analyses were conducted using chi-square tests, t-tests, and logistic regression analyses.

RESULTS

A total of 471 individuals (age M = 53.9, 53.6% female) with a mean PHQ-9 Score of 8.4 were included in the analyses. Causal attributions related to participants' social environment, workplace, and past are the most stable over time. However, individuals with and without a time-stable causal concept showed no differences in terms of sociodemographic characteristics, severity of depressive symptoms, risk of comorbidity, and treatment experiences. Overall, the causal concepts of people with depressive symptoms appear to be very diverse. Those with treatment experience (M = 2.21, SD = 0.80) named significantly more causal attributions compared to people without treatment experience (M = 1.98, SD = 0.81, t(471) = -3.060, p < 0.01). In addition, logistic regression analyses revealed that treatment-experienced respondents were more likely to attribute "childhood/youth/parental home" and "predisposition".

CONCLUSIONS

Our study reveals that people with treatment experience tend to report treatment-congruent causal attributions, such as childhood and family environment, as well as predisposition, more frequently. Understanding how causal attributions and concepts are formed and change can be helpful for addressing causal attributions in treatment. Future studies should take into account the benefits of employing qualitative survey methods for exploring causal attributions.

Feasibility of Deploying Home-Based Digital Technology, Environmental Sensors, and Web-Based Surveys for Assessing Behavioral Symptoms and Identifying Their Precipitants in Older Adults: Longitudinal, Observational Study

BACKGROUND

Apathy, depression, and anxiety are prevalent neuropsychiatric symptoms experienced by older adults. Early detection, prevention, and intervention may improve outcomes.

OBJECTIVE

We aim to demonstrate the feasibility of deploying web-based weekly questionnaires inquiring about the behavioral symptoms of older adults with normal cognition, mild cognitive impairment, or early-stage dementia and to demonstrate the feasibility of deploying an in-home technology platform for measuring participant behaviors and their environment.

METHODS

The target population of this study is older adults with normal cognition, mild cognitive impairment, or early-stage dementia. This is an observational, longitudinal study with a study period of up to 9 months. The severity of participant behavioral symptoms (apathy, depression, and anxiety) was self-reported weekly through web-based surveys. Participants' digital biomarkers were continuously collected at their personal residences and through wearables throughout the duration of the study. The indoor physical environment at each residence, such as light level, noise level, temperature, humidity, or air quality, was also measured using indoor environmental sensors. Feasibility was examined, and preliminary correlation analysis between the level of symptoms and the digital biomarkers and between the level of symptoms and the indoor environment was performed.

RESULTS

At 13 months after recruitment began, a total of 9 participants had enrolled into this study. The participants showed high adherence rates in completing the weekly questionnaires (response rate: 275/278, 98.9%), and data collection using the digital technology appeared feasible and acceptable to the participants with few exceptions. Participants' severity of behavioral symptoms fluctuated from week to week. Preliminary results show that the duration of sleep onset and noise level are positively correlated with the anxiety level in a subset of our participants.

CONCLUSIONS

This study is a step toward more frequent assessment of older adults' behavioral symptoms and holistic in situ monitoring of older adults' behaviors and their living environment. The goal of this study is to facilitate the development of objective digital biomarkers of neuropsychiatric symptoms and to identify in-home environmental factors that contribute to these symptoms.

Multilevel and general linear modeling of weather and time effects on the emotional and behavioral states of children with profound intellectual and multiple disabilities

Introduction

Eliciting the emotional and behavioral states of children with severe or profound intellectual disabilities (IDs) and profound intellectual and multiple disabilities (PIMD) due to their complex and atypical developmental trajectories has become increasingly elusive. It is evident that the environment, influenced by weather conditions and time of the day, plays a pivotal role in molding children's behaviors, emotions, and interactions. This underscores the significance of the environment as a critical factor in exploring the communication dynamics of children with PIMD/IDs.

Methods

Over five months during fall and winter seasons, we conducted 105 video-recorded sessions with 20 children aged 8 to 16 with PIMD/IDs. These sessions aimed to capture the emotional and behavioral states interpreted by caregivers while simultaneously collecting indoor and outdoor weather indices, location, and time data. Using cross-classified multilevel and general linear models adjusted for individual characteristics and location variability with subsequent simple slope analyses, we examined the main and seasonal interaction effects of indoor and outdoor weather indices and time of the day on the emotional and behavioral states of children with PIMD/IDs.

Results

The models revealed that higher atmospheric pressure (atm), indicative of pleasant and favorable weather conditions, was associated with increased engagement (indoor: p < 0.01; outdoor: p < 0.01) and interest (outdoor: p < 0.01) behaviors. In contrast, engagement levels decreased before lunchtime (p < 0.01; p < 0.001), and inclement or unstable weather conditions characterized by low-pressure systems (p < 0.05) and stronger wind speed (p < 0.05) led to more refusal or disagreement. During winter, children displayed significantly more agreement with their caregivers (p < 0.001). Interestingly, they also engaged more on cloudy days (p < 0.05). Furthermore, simple slope analyses revealed that high atm conditions in fall were linked to more engagement (p < 0.05) while humid conditions predicted more assent behaviors (p < 0.001). However, cloudy weather predicted less attentional focusing (p < 0.05) and interest (p < 0.01) behaviors in winter.

Conclusion

This study confirms that fluctuations in weather indices, including seasonal changes and time of the day, can provide potential pathway indicators and supplement behavioral observations to elicit the behavioral states of children with PIMD/IDs. These findings highlight the importance of considering these factors when designing meaningful interactions and communication interventions for this population.

Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study

BACKGROUND

The literature has discussed the relationship between environmental factors and depressive disorders; however, the results are inconsistent in different studies and regions, as are the interaction effects between environmental factors. We hypothesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity.

AIM

To investigate the effects of meteorological factors and air pollution on depressive disorders, including their lagged effects and interactions.

METHODS

The samples were obtained from a class 3 hospital in Harbin, China. Daily hospital admission data for depressive disorders from January 1, 2015 to December 31, 2022 were obtained. Meteorological and air pollution data were also collected during the same period. Generalized additive models with quasi-Poisson regression were used for time-series modeling to measure the non-linear and delayed effects of environmental factors. We further incorporated each pair of environmental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders.

RESULTS

Data for 2922 d were included in the study, with no missing values. The total number of depressive admissions was 83905. Medium to high correlations existed between environmental factors. Air temperature (AT) and wind speed (WS) significantly affected the number of admissions for depression. An extremely low temperature (-29.0 ℃) at lag 0 caused a 53% [relative risk (RR)= 1.53, 95% confidence interval (CI): 1.23-1.89] increase in daily hospital admissions relative to the median temperature. Extremely low WSs (0.4 m/s) at lag 7 increased the number of admissions by 58% (RR = 1.58, 95%CI: 1.07-2.31). In contrast, atmospheric pressure and relative humidity had smaller effects. Among the six air pollutants considered in the time-series model, nitrogen dioxide (NO2) was the only pollutant that showed significant effects over non-cumulative, cumulative, immediate, and lagged conditions. The cumulative effect of NO2 at lag 7 was 0.47% (RR = 1.0047, 95%CI: 1.0024-1.0071). Interaction effects were found between AT and the five air pollutants, atmospheric temperature and the four air pollutants, WS and sulfur dioxide.

CONCLUSION

Meteorological factors and the air pollutant NO2 affect daily hospital admissions for depressive disorders, and interactions exist between meteorological factors and ambient air pollution.

Residential greenness for mitigating impacts of extreme heat events on depression and supporting mental health

Background

Residential green spaces (RGS) are a crucial aspect of urban life, which provide residents with a positive living environment both for mental and physical well-being. However, extreme heat events caused by global warming and local urban heat island effects are threatening the public health of rapidly growing populations. This is especially true for mental health. Depression is a mental illness that can be impacted by extreme heat events, i.e., heatwaves.

Objective

This study aimed to investigate the potential for residential green spaces (RGS) to alleviate depression by reducing heat stress sensitivity during extreme heat events.

Methods

We conducted a literature review using scientometric analysis with CiteSpace to summarize existing research on the relationships between RGS, depression, and heatwaves. We proposed a conceptual framework for the relationship between RGS and depression, and that extreme heat events may be an important contributor to depression.

Results

Our review found that RGS can provide ecosystem services that lower ambient temperatures through evaporative cooling, radiation reflection, humidity regulation, and shading. Different types of RGS, i.e., small green spaces, green roofs, green walls, and street trees, have varying cooling capacities. The mechanisms by which RGS alleviate depression during heatwaves involve green space composition, exposure, physical activity, social contacts, and cohesion. And we proposed a conceptual framework for the relationship between RGS and depression, and that extreme heat events may be an important contributor to depression.

Conclusion

We present a multidimensional RGS evaluation roadmap to inform green space design for reducing depression during heatwaves. Establishing RGS multidimensional evaluation can guide future research on leveraging RGS to build resilience against extreme heat and improve public mental health.

Meteorological extremes and their impact on tinnitus-related emergency room visits: a time-series analysis

PURPOSE

Extreme weather events are rising due to the accelerating pace of climate change. These events impact human health and increase emergency room visits (EV) for many morbidities. Tinnitus is a common cause of EVs within otolaryngology in Germany and Austria. The effect of extreme weather conditions on tinnitus-related EVs is unknown.

METHODS

A total of 526 tinnitus-related EVs at a tertiary care hospital in Vienna were identified. A distributed lag non-linear model with a maximum lag period of 14 days was fitted to investigate the immediate and delayed effect of single-day and prolonged (three-day) extreme atmospheric pressure, relative humidity, mean temperature, precipitation and mean wind speed on EV rates. Extreme conditions were defined as the 1st, 5th, 95th, and 99th percentile of the meteorological variables. Relative risk (RR) is defined as risk for tinnitus-related EVs at an extreme condition compared to the risk at the median weather condition. Cumulative RR (cRR) is the total cumulated EV risk for a given time period.

RESULTS

High relative humidity increased same-day RR for tinnitus-related EVs to 1.75. Both low and high atmospheric pressure raised cRR as early as three days after an event to a maximum of 3.24. Low temperatures mitigated cRR within 4 days, while high temperatures tended to increase risk. Prolonged precipitation reduced cRR within one day.

CONCLUSION

Extreme meteorological conditions are associated with tinnitus-related EV rates. Further investigation into potential causative links and underlying pathophysiological mechanisms is warranted.

Short-term impact of noise, other air pollutants and meteorological factors on emergency hospital mental health admissions in the Madrid region

BACKGROUND

A number of environmental factors, such as air pollution, noise in urbanised settings and meteorological-type variables, may give rise to important effects on human health. In recent years, many studies have confirmed the relation between various mental disorders and these factors, with a possible impact on the increase in emergency hospital admissions due to these causes. The aim of this study was to analyse the impact of a range of environmental factors on daily emergency hospital admissions due to mental disorders in the Madrid Autonomous Region (MAR), across the period 2013-2018.

METHODOLOGY

Longitudinal ecological time series study analysed by Generalised Linear Models with Poisson regression, with the dependent variable being daily Emergency Hospital Mental Health Admissions (EHMHA) in the MAR, and the independent variable being mean daily concentrations of chemical pollutants, noise levels and meteorological variables.

RESULTS

EHMHA were related statistically significantly in the short term with diurnal noise levels. Relative risks (RRs) for total admissions due to mental disorders and self-inflicted injuries, in the case of diurnal noise was RR: 1.008 95%CI (1.003 1.013). Admissions attributable to diurnal noise account for 5.5% of total admissions across the study period. There was no association between hospital admissions and chemical air pollution.

CONCLUSION

Noise is a variable that shows a statistically significant short-term association with EHMHA across all age groups in the MAR region. The results of this study may serve as a basis for drawing up public health guidelines and plans, which regard these variables as risk factors for mental disorders, especially in the case of noise, since this fundamentally depends on anthropogenic activities in highly urbanised areas with high levels of traffic density.