Does the weather make us sad? Meteorological determinants of mood and depression in the general population

The Role of Season, Sunlight, and Light Sensitivity in Self-Reported Depressive Symptoms by Adults With Visual Impairment

Purpose

Depression is common in people with visual impairment, and the onset may be influenced by aspects related to light. The aim was to explore the associations of season, sunlight, and light sensitivity with depressive symptoms in this population.

Methods

Data regarding self-reported depressive symptoms from seven cross-sectional studies conducted between 2009 and 2018 were combined with information concerning sensitivity to light, season on the date of self-report, and potential sunlight exposure in the 2 weeks prior to self-report. The latter was calculated by summing up the daily sunlight hours detected by the weather station nearest to the residence of each participant. Logistic regression analyses were performed to investigate the associations.

Results

Participants (N = 1925) experienced clinically significant depressive symptoms most often in winter (32.8%), followed by summer (27.4%), spring (26.2%), and fall (24.2%). The odds of experiencing depression in fall were significantly lower compared with winter (odds ratio [OR] = 0.67, P = 0.007). An increase in the hours of sunlight in the participant's environment was associated with lower odds to experience depressive symptoms (OR = 0.995, P = 0.011). People who were sensitive to bright light had higher odds of experiencing depressive symptoms (OR = 1.80, P < 0.001). Other differences found between subgroups were not consistent.

Conclusions

It seems likely that season, sunlight, and light sensitivity play a role in depression among people with visual impairment. Further research is needed, exploring the experiences in this population, the actual sunlight exposure using objective measures, and treatment options.

Translational Relevance

Clinicians should consider these factors when treating visually impaired patients with depressive symptoms.

How ambient temperature affects mood: an ecological momentary assessment study in Switzerland

BACKGROUND

Recent research has suggested that an increase in temperature can negatively affect mental health and increase hospitalization for mental illness. It is not clear, however, what factors or mechanisms mediate this association. We aimed to (1) investigate the associations between ambient temperatures and bad daily mood, and (2) identify variables affecting the strength of these associations (modifiers) including the time, the day of the week and the year of the mood rating, socio-demographic characteristics, sleep quality, psychiatric disorders and the personality trait neuroticism in the community.

METHODS

Data stemmed from the second follow-up evaluation of CoLaus|PsyCoLaus, a prospective cohort study conducted in the general population of Lausanne (Switzerland). The 906 participants rated their mood level four times a day during seven days using a cell phone app. Mixed-effects logistic regression was used to determine the association between daily maximum temperature and mood level. Participant ID was inserted as a random effect in the model, whereas the time of the day, the day of the week and the year were inserted as fixed effects. Models were controlled for several confounders (socio-demographic characteristics, sleep quality, weather parameters and air pollutants). Stratified analyses were conducted based on socio-demographic characteristics, sleep quality, presence of psychiatric disorders or a high neuroticism.

RESULTS

Overall, the probability of having a bad mood for the entire day decreased by 7.0% (OR: 0.93: 95% CI 0.88, 0.99) for each 5 °C increase in maximum temperature. A smaller and less precise effect (-3%; OR: 0.97: 95% CI 0.91, 1.03) was found when controlling for sunshine duration. A higher association was found in participants with bipolar disorder (-23%; OR: 0.77: 95% CI 0.51, 1.17) and in participants with a high neuroticism (-13%; OR: 0.87 95% CI 0.80, 0.95), whereas the association was reversed for participants with anxiety (20%; OR: 1.20: 95% CI 0.90, 1.59), depression (18%; OR: 1.18 95% CI 0.94, 1.48) and schizophrenia (193%; OR: 2.93 95% CI 1.17, 7.73).

CONCLUSIONS

According to our findings, rising temperatures may positively affect mood in the general population. However, individuals with certain psychiatric disorders, such as anxiety, depression, and schizophrenia, may exhibit altered responses to heat, which may explain their increased morbidity when exposed to high temperatures. This suggests that tailored public health policies are required to protect this vulnerable population.

Association Between Sunlight Exposure and Mental Health: Evidence from a Special Population Without Sunlight in Work

Purpose

In recent years, mental health problems have become the most serious social problems worldwide. Past studies have proposed that some links exist between sunlight and mental health; however, relevant studies examining low-dose sunlight exposure populations are lacking. We conducted a study among a group of operating room nurses (ORNs) who work long hours in operating rooms and have limited sunlight exposure. We aim to add to and refine previous researches on the association between mental health and sunlight exposure in community population.

Patients and Methods

A total of 787 ORNs were interviewed and analyzed. Mental health, sunlight exposure duration, sociodemographic and work-related variables, and chronic diseases were evaluated. The Kessler 10 scale (K10) was used to assess participants' mental health status, and their sunlight exposure duration was assessed using their self-reports. Multiple linear regression analysis was adopted to examine the association between sunlight exposure and mental health.

Results

The average K10 score of ORNs was 25.41. ORNs exhibit poorer mental health than other populations. Poor mental health was negatively associated with greater sunlight exposure hours per day (β=-0.378) and sleep regularity (β=-3.341). Poor mental health was positively associated with chronic disease (β=3.514).

Conclusion

This study indicated that the positive association between sunlight exposure and mental health existed. Appropriate enhancement of sunlight exposure will be beneficial to mental health. Hospitals, related organizations and individuals should pay greater attention to ORNs' mental health and sunlight exposure conditions. More policy recommendations as well as building structure recommendations should be proposed.

Study on Emotional Perception of Hangzhou West Lake Scenic Area in Spring under the Influence of Meteorological Environment

Human perception of the meteorological environment is an important research area in the context of global climate change. Human physical and mental health can be affected by the meteorological environment, which can manifest in emotional responses. The experiment was conducted at spring in Hangzhou West Lake Scenic Area (China). Three types of weather circumstances were examined by four emotional measures. The purpose of this study was to examine how meteorological parameters influence an individual's emotional perception, such as air temperature, ground temperature, wind direction, precipitation, and relative humidity. Box plots were used to examine the distribution of scores on each emotional scale index. Perceptual models of positive, negative, regenerative, state anxiety, trait anxiety, and subjective vitality were developed using multiple linear regressions. The results indicate that meteorological conditions have a significant impact on human emotions: (1) there are other meteorological factors that affect individual emotions, besides precipitation; (2) the meteorological factors do not affect negative emotions; and (3) on sunny days, subjective energy and positive emotions are stronger, and on rainy days, perceptions of recovery are more favorable.

Effects of sunshine duration on daily outpatient visits for depression in Suzhou, Anhui Province, China

Previous epidemiological studies have reported seasonal variation patterns of depression symptoms, which may be influenced by bad weather conditions, such as a lack of sunlight. However, evidence on the acute effects of sunshine duration on outpatient visits for depression is limited, especially in developing countries, and the results are inconsistent. We collected daily outpatient visits for depression from the local mental health centre in Suzhou, Anhui Province, China, during 2017-2019. We defined the 5th and 95th sunshine percentiles as short and long sunshine durations, respectively. A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to quantitatively assess the effects of short and long sunshine durations on outpatient visits for depression. Stratified analyses were further performed by gender, age and number of visits to identify vulnerable populations. A total of 26,343 depression cases were collected during the study period. An approximate U-shaped exposure-response association was observed between sunshine duration and depression outpatient visits. The cumulative estimated relative risks (RRs) for short and long sunshine durations at lag 0-21 days were 1.53 [95% confidence intervals (CI): 1.14, 2.06] and 1.13 (95% CI: 0.88, 1.44), respectively. Moreover, a short sunshine duration was associated with a greater disease burden than a long sunshine duration, with attributable fractions (AFs) of 16.64% (95% CI: 7.8%, 23.89%) and 2.24% (95% CI: -2.65%, 5.74%), respectively. Subgroup analysis showed that males, people aged less than 45 years and first-visit cases may be more susceptible to a lack of sunlight. For a long sunshine duration, no statistically significant associations were found in any population groups. Our study found that a short sunshine duration was associated with an increased risk of depression. The government, medical institutions, family members and patients themselves should fully recognize the important role of sunlight and take active measures to prevent depression.

Impact of the COVID-19 pandemic on risk of burn-out syndrome and recovery need among secondary school teachers in Flanders: A prospective study

Background

Due to the COVID-19 pandemic, schools were closed, teachers had to teach from home and after a while, they had to return to the classroom while the pandemic was still on-going. Even before the pandemic, teachers were already more at risk for burn-out syndrome compared to the general population. Furthermore, not much research pertaining to this population has been carried out during the pandemic and so the impact of the pandemic on teachers' risk of burn-out syndrome and recovery need remains unclear. The aim of the current study was to fill this knowledge gap and map out the impact on risk of burn-out syndrome and recovery need at different time points during the pandemic.

Methods and findings

At baseline, 2,167 secondary school teachers in Flanders were included in this prospective study. Questionnaire data were obtained at ten different time points between September 2019 and August 2021. To assess risk of burn-out syndrome and its dimensions, the Utrecht Burn-out Scale for Teachers was administered. Need for recovery was assessed using questions adopted from the Short Inventory to Monitor Psychosocial Hazards. The results revealed an initial positive effect of the first lockdown (Mar/Apr 2020) with a decrease in risk of burn-out syndrome [Odds ratio (OR) Jan/Feb 2020-Mar/Apr 2020 = 0.33, p < 0.001], emotional exhaustion (EMM Jan/Feb 2020-Mar/Apr 2020 = -0.51, p < 0.001), depersonalization (EMM Jan/Feb 2020-Mar/Apr 2020 = -0.13, p < 0.001) and recovery need [Estimated marginal mean (EMM) Jan/Feb 2020-Mar/Apr 2020 = -0.79, p < 0.001]. No significant effect on personal accomplishment was found (p = 0.410). However, as the pandemic went on, higher risk of burn-out syndrome, emotional exhaustion, depersonalization and recovery need, and lower personal accomplishment were observed.

Conclusions

Despite the initial positive impact on risk of burn-out syndrome, its dimensions and recovery need, a negative long-term impact of the COVID-19 pandemic became visible. This study highlights once again the importance for interventions to reduce teachers' risk of burn-out syndrome, especially in such difficult times as a pandemic.

Effects of extreme precipitation on hospital visit risk and disease burden of depression in Suzhou, China

Background

The purpose of this study was to explore the impact of extreme precipitation on the risk of outpatient visits for depression and to further explore its associated disease burden and vulnerable population.

Methods

A quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) was used to investigate the exposure-lag-response relationship between extreme precipitation (≥95th percentile) and depression outpatient visits from 2017 to 2019 in Suzhou city, Anhui Province, China.

Results

Extreme precipitation was positively associated with the outpatient visits for depression. The effects of extreme precipitation on depression firstly appeared at lag4 [relative risk (RR): 1.047, 95% confidence interval (CI): 1.005–1.091] and lasted until lag7 (RR = 1.047, 95% CI: 1.009–1.087). Females, patients aged ≥65 years and patients with multiple outpatient visits appeared to be more sensitive to extreme precipitation. The attributable fraction (AF) and numbers (AN) of extreme precipitation on outpatient visits for depression were 5.00% (95% CI: 1.02–8.82%) and 1318.25, respectively.

Conclusions

Our findings suggested that extreme precipitation may increase the risk of outpatient visits for depression. Further studies on the burden of depression found that females, aged ≥65 years, and patients with multiple visits were priority targets for future warnings. Active intervention measures against extreme precipitation events should be taken to reduce the risk of depression outpatient visits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14085-w.

Relationship between Depressive Symptoms and Weather Conditions

Background: Weather is a well-known factor worldwide in psychiatric problems such as depression, with the elderly and females being particularly susceptible. The aim of this study was to detect associations between the risk of depressive symptoms (DS) and weather variables. Methods: 6937 participants were assessed in the baseline survey of the Health Alcohol Psychosocial Factors in Eastern Europe (HAPIEE) study during 2006−2008. To assess the risk of DS, a multivariate logistic model was created with predictors such as socio-demographic factors, health behaviors, and weather variables. Results: DS were found in 23.4% of the respondents, in 15.6% of males and in 29.9% in females. A higher risk of DS (by 25%) was associated with November−December, a rising wind speed, and relative humidity (RH) < 94% and snowfall during the cold period occurring 2 days before the survey. A higher air temperature (>14.2 °C) predominant during May−September had a protective impact. A higher risk of DS in males was associated with lower atmospheric pressure (<1009 hPa) 2 days before. Females were more sensitive to the monthly variation, snowfall, and RH. Conclusions: The findings of our study suggest that some levels of weather variables have a statistically significant effect on DS.

Exposure to Abnormally Hot Temperature and the Demand for Commercial Health Insurance

Using the China Health and Retirement Longitudinal Study, this paper studies the impact of abnormal hot temperature on residents' demand for commercial health insurance. The results show that for every 1°F rise in abnormal temperature, the probability of people buying commercial health insurance increased by 6%. Furthermore, the abnormal hot temperature has a more significant impact on the commercial health insurance demand of women, residents in the South and residents in the East. Channel analysis shows that abnormal hot temperature affects the demand for commercial health insurance through two channels: increasing residents' concern about climate risk and affecting health. This paper provides evidence for actively promoting sustainable development and improving the construction of medical security system.

A Data-Driven Analysis of Sociocultural, Ecological, and Economic Correlates of Depression Across Nations

The prevalence of depression varies widely across nations, but we do not yet understand what underlies this variation. Here we use estimates from the Global Burden of Disease study to analyze the correlates of depression across 195 countries and territories. We begin by identifying potential cross-correlates of depression using past clinical and cultural psychology literature. We then take a data-driven approach to modeling which factors correlate with depression in zero-order analyses, and in a multiple regression model that controls for covariation between factors. Our findings reveal several potential correlates of depression, including cultural individualism, daylight hours, divorce rate, and GDP per capita. Cultural individualism is the only factor that remains significant across all our models, even when adjusting for spatial autocorrelation, mental healthcare workers per capita, multicollinearity, and outliers. These findings shed light on how depression varies around the world, the sociocultural and environmental factors that underlie this variation, and potential future directions for the study of culture and mental illness.

The effect of climate change on depression in urban areas of western Iran

Objective

Human is accustomed to climatic conditions of the environment where they are born and live throughout their lifetime. The aim of this study is to examine mood swings and depression caused by sudden climate changes that have not yet given the humans a chance to adapt.

Results

Our results showed that depression could be affected by climate change and as a result, the behavior of climatic elements and trends has damaged mental health in the western regions of Iran. By investigating the trends and changes of climatic time series and their relationship with the rate of depression in urban areas of western Iran, it can be said that climate change is probably a mental health challenge for urban populations. Climate change is an important and worrying issue that makes the life difficult. Rapid climate changes in western Iran including rising air temperature, changes in precipitation, its regime, changes cloudiness and the amount of sunlight have a negative effects on health. The results showed that type of increasing or decreasing trend, as well as different climatic elements in various seasons did not have the same effect on the rate of depression in the studied areas.

Emergency department visits for panic attacks and ambient temperature: A time-stratified case-crossover analysis

BACKGROUND

Panic disorder is a common anxiety disorder affecting up to 5% of the population. Although its pathogenesis is unclear, evidence about its association with ambient temperature is limited. We aimed to investigate the association between short-term exposure to increased ambient temperature and exacerbation of panic attacks requiring emergency department visits.

METHODS

From the national emergency database of South Korea, we identified 1,926 patients who presented with panic attacks at the emergency department in Seoul from 2008 to 2014. Using a time-stratified case-crossover design and conditional logistic regression analysis, we compared ambient temperature levels on emergency department visits and correspondingly matched-control days.

RESULTS

Increased ambient temperature levels were significantly associated with panic attacks. The risk of a panic attack increased by 2.2% (95% confidence interval, 0.7-3.8%) per every 1°C increase in temperature. This association was significant after adjusting for air pollutants.

CONCLUSIONS

Our results provide new evidence that short-term exposure to increased ambient temperature may increase the risk of exacerbation of panic attacks. These findings may provide a basis for further research to establish the association between panic attacks and ambient temperature, thus establishing preventive measures for panic attacks.

Intraday weather conditions can influence self-report of depressive symptoms

The weather is arguably one of the most common topics in daily conversation. However, it is also a well-known factor in psychiatric problems worldwide such as depression, where particularly elders and females are prone to the condition. Previous studies have mostly focused on the association between long-term climate/season change and depressive symptoms to test the belief that people feel depressed when the weather is bad. Yet, little is known about the relationship between intraday weather conditions and depressive symptoms. This study aimed to decompose this association and explore age and gender differences in depressive symptoms' report under different intraday weather conditions. We analyzed data with a total sample size of 20,987 individuals aged 15-96 years obtained via the China Labor-force Dynamic Survey (CLDS) project in 2016. The surveyors filled in the intraday weather conditions (i.e., sunny, cloudy, overcast, light rain, moderate rain, and heavy rain) in the questionnaire with depression being self-reported using the Center for Epidemiologic Studies Depression (CES-D) Scale. In the survey, 17.3% [95% confidence interval (CI) = 16.8%, 17.8%] individuals were assessed to have depressive symptoms (CES-D scores >15). Overcast day was the peak weather condition for depressive symptoms, while gender and age differences of depressive symptoms were biggest in the weather condition of moderate rain. Multivariate logistic regression revealed that female and middle-old age individuals were more likely to report having depressive symptoms, and people under overcast day were more likely to report having depressive symptoms compared to under sunny day [odds ratio (OR) = 1.25, 95%CI = 1.11, 1.39]. This intraday weather conditions-depression link was significant in males and middle-old age individuals but not in females and youngsters.

Sensitivity to Climate and Weather Changes in Euthymic Bipolar Subjects: Association With Suicide Attempts

BACKGROUND

Climate and weather are known to affect multiple areas of human life, including mental health. In bipolar disorder (BD), seasonality represents an environmental trigger for mood switches, and climatic variables may contribute to recurrences. Several studies reported seasonal and climatic-related variations in the rate of suicide attempts. Suicide risk is relevant in BD, with approximately 25% of patients attempting suicide. Therefore, this study aimed to assess sensitivity to weather and climatic variations in BD subjects and its relationship with lifetime suicide attempts.

METHODS

Three hundred fifty-two euthymic BD and 352 healthy control subjects, homogeneous with respect to socio-demographic characteristics, were enrolled. All participants were administered the METEO-Questionnaire (METEO-Q) to evaluate susceptibility to weather and climatic changes. We also investigated the potential relationship between sensitivity to climate and weather and lifetime suicide attempts in BD patients.

RESULTS

METEO-Q scores and the number of subjects reaching the cut-off for meteorosensitivity/meteoropathy were significantly higher in BD patients. Within the clinical group, BD subjects with lifetime suicide attempts obtained higher METEO-Q scores, with no differences between BD-I and BD-II. The number of suicide attempts directly correlated with METEO-Q scores. The presence of suicide attempts was associated with the physical and psychological symptoms related to weather variations.

DISCUSSION

Our findings support the relevance of sensitivity to weather and climate variations in a large sample of BD subjects and point out the association of this feature with lifetime suicide attempts.

Seasonality and symptoms of depression: A systematic review of the literature

AIMS

Lay opinions and published papers alike suggest mood varies with the seasons, commonly framed as higher rates of depression mood in winter. Memory and confirmation bias may have influenced previous studies. We therefore systematically searched for and reviewed studies on the topic, but excluded study designs where explicit referrals to seasonality were included in questions, interviews or data collection.

METHODS

Systematic literature search in Cochrane database, DARE, Medline, Embase, PsychINFO and CINAHL, reporting according to the PRISMA framework, and study quality assessment using the Newcastle-Ottawa scale. Two authors independently assessed each study for inclusion and quality assessment. Due to large heterogeneity, we used a descriptive review of the studies.

RESULTS

Among the 41 included studies, there was great heterogeneity in regards to included symptoms and disorder definitions, operationalisation and measurement. We also observed important heterogeneity in how definitions of 'seasons' as well as study design, reporting and quality. This heterogeneity precluded meta-analysis and publication bias analysis. Thirteen of the studies suggested more depression in winter. The remaining studies suggested no seasonal pattern, seasonality outside winter, or inconclusive results.

CONCLUSIONS

The results of this review suggest that the research field of seasonal variations in mood disorders is fragmented, and important questions remain unanswered. There is some support for seasonal variation in clinical depression, but our results contest a general population shift towards lower mood and more sub-threshold symptoms at regular intervals throughout the year. We suggest future research on this issue should be aware of potential bias by design and take into account other biological and behavioural seasonal changes that may nullify or exacerbate any impact on mood.

Ambient temperature and solar insolation are associated with decreased prevalence of SSRI-treated psychiatric disorders

Serotonergic function is known to fluctuate in association with light and temperature. Serotonin-related behaviors and disorders similarly vary with climatic exposure, but the associations are complex. This complexity may reflect the importance of dose and timing of exposure, as well as acclimation. This cross-sectional study tests how average climate exposures (ambient temperature and solar insolation) vary with the prevalence of a group of SSRI-treated disorders. For comparison, we similarly studied a group of disorders not treated by SSRIs (i.e substance use disorders). Psychiatric prevalence data were obtained from the Collaborative Psychiatric Epidemiology Surveys (CPES). Average yearly solar insolation was obtained from NASA's NLDAS-2 Forcing Dataset Information. Average yearly temperature was obtained from NOAA's US Climate Normals. Logistic regression models were generated to assess the relationship between these two climatic factors and the prevalence of SSRI-treated and substance use disorders. Age, gender, race, income, and education were included in the models to control for possible confounding. Temperature and insolation were significantly associated with the SSRI-responsive group. For an average 1 GJ/m²/year increase, OR was 0.90 (95% CI 0.85-0.96, p = 0.001), and for an average 10 °F increase, OR was 0.93 (95% CI 0.88-0.97, p = 0.001). This relationship was not seen with substance use disorders (insolation OR: 0.97, p = 0.682; temperature OR: 0.96, p = 0.481). These results warrant further investigation, but they support the hypothesis that chronic exposure to increased temperature and light positively impact serotonin function, and are associated with reduced prevalence of some psychiatric disorders. They also support further investigation of light and hyperthermia treatments.

Correlation Analysis to Identify the Effective Data in Machine Learning: Prediction of Depressive Disorder and Emotion States

Correlation analysis is an extensively used technique that identifies interesting relationships in data. These relationships help us realize the relevance of attributes with respect to the target class to be predicted. This study has exploited correlation analysis and machine learning-based approaches to identify relevant attributes in the dataset which have a significant impact on classifying a patient’s mental health status. For mental health situations, correlation analysis has been performed in Weka, which involves a dataset of depressive disorder symptoms and situations based on weather conditions, as well as emotion classification based on physiological sensor readings. Pearson’s product moment correlation and other different classification algorithms have been utilized for this analysis. The results show interesting correlations in weather attributes for bipolar patients, as well as in features extracted from physiological data for emotional states.

Weather and Health Symptoms

Weather affects the daily lives of individuals. However, its health effects have not been fully elucidated. It may lead to physical symptoms and/or influence mental health. Thus, we evaluated the association between weather parameters and various ailments. We used daily reports on health symptoms from 4548 individuals followed for one month in October of 2013, randomly sampled from the entirety of Japan. Weather variables from the monitoring station located closest to the participants were used as weather exposure. Logistic mixed effects model with a random intercept for each individual was applied to evaluate the effect of temperature and humidity on physical symptoms. Stratified analyses were conducted to compare weather effects by sex and age group. The lag day effects were also assessed. Joint pain was associated with higher temperature (1.87%, 95% CI = 1.15 to 2.59) and humidity (1.38%, 95% CI = 0.78 to 2.00). Headaches was increased by 0.56% (95% CI = −0.55 to 1.77) per 1 °C increase in the maximum temperature and by 1.35% per 1 °C increase in dew point. Weather was associated with various physical symptoms. Women seem to be more sensitive to weather conditions in association with physical symptoms, especially higher humidity and lower temperature.

Meteorological parameters and air pollen count in association with self-reported peripartum depressive symptoms

BACKGROUND

Meteorological parameters and air pollen count have been associated with affective disorders and suicide. Regarding peripartum depression, the literature is restricted and inconclusive.

METHODS

This cross-sectional study included women (pregnant, n = 3843; postpartum, n = 3757) who participated in the BASIC (Biology, Affect, Stress, Imaging, and Cognition) study 2010-2015 and the UPPSAT (Uppsala-Athens) study (postpartum, n = 1565) in 2006-2007. Cases were defined according to presence of depressive symptoms during pregnancy (gestational week 32) and 6 weeks postpartum, using the Edinburgh Postnatal Depression Scale (EPDS). Exposure of sunshine, temperature, precipitation, snow coverage, and air pollen counts of durations of 1, 7, and 42 days prior to the outcome were studied for associations with depressive symptoms, using negative binomial regression.

RESULTS

Prior to Bonferroni correction, the concentration of mugwort pollen, both one week and six weeks before the EPDS assessment at gestational week 32, was inversely associated with depressive symptoms in pregnancy, both before and after adjustment for season. No associations were found between the exposure to meteorological parameters and pollen and depressive symptoms, at the same day of depressive symptoms' assessment, the previous week, or the six weeks prior to assessment, either during pregnancy or postpartum after Bonferroni correction.

CONCLUSIONS

There was no evidence that neither short-term nor long-term exposure to meteorological parameters or air pollen counts were associated with self-reported peripartum depressive symptoms in Uppsala, Sweden.

Weather conditions influence the number of psychiatric emergency room patients

The specific impact of weather factors on psychiatric disorders has been investigated only in few studies with inconsistent results. We hypothesized that meteorological conditions influence the number of cases presenting in a psychiatric emergency room as a measure of mental health conditions. We analyzed the number of patients consulting the emergency room (ER) of a psychiatric hospital in Berlin, Germany, between January 1, 2008, and December 31, 2014. A total of N = 22,672 cases were treated in the ER over the study period. Meteorological data were obtained from a publicly available data base. Due to collinearity among the meteorological variables, we performed a principal component (PC) analysis. Association of PCs with the daily number of patients was analyzed with autoregressive integrated moving average model. Delayed effects were investigated using Granger causal modeling. Daily number of patients in the ER was significantly higher in spring and summer compared to fall and winter (p < 0.001). Three PCs explained 76.8% percent of the variance with PC1 loading mostly on temperature, PC2 on cloudiness and low pressure, and PC3 on windiness. PC1 and PC2 showed strong association with number of patients in the emergency room (p < 0.010) indicating higher patient numbers on warmer and on cloudy days. Further, PC1, PC2, and PC3 predicted the number of patients presenting in the emergency room for up to 7 days (p < 0.050). A secondary analysis revealed that the effect of temperature on number of patients was mostly due to lower patient numbers on cold days. Although replication of our findings is required, our results suggest that weather influences the number of psychiatric patients consulting the emergency room. In particular, our data indicate lower patient numbers during very cold temperatures.

Seasonality of depressive symptoms in women but not in men: A cross-sectional study in the UK Biobank cohort

BACKGROUND

We examined whether seasonal variations in depressive symptoms occurred independently of demographic and lifestyle factors, and were related to change in day length and/or outdoor temperature.

METHODS

In a cross-sectional analysis of >150,000 participants of the UK Biobank cohort, we used the cosinor method to assess evidence of seasonality of a total depressive symptoms score and of low mood, anhedonia, tenseness and tiredness scores in women and men. Associations of depressive symptoms with day length and mean outdoor temperature were then examined.

RESULTS

Seasonality of total depressive symptom scores, anhedonia and tiredness scores was observed in women but not men, with peaks in winter. In women, increased day length was associated with reduced reporting of low mood and anhedonia, but with increased reporting of tiredness, independent of demographic and lifestyle factors. Associations with day length were not independent of the average outdoor temperature preceding assessment.

LIMITATIONS

This was a cross-sectional investigation - longitudinal studies of within-subject seasonal variation in mood are necessary. Outcome measures relied on self-report and measured only a subset of depressive symptoms.

CONCLUSION

This large, population-based study provides evidence of seasonal variation in depressive symptoms in women. Shorter days were associated with increased feelings of low mood and anhedonia in women. Clinicians should be aware of these population-level sex differences in seasonal mood variations in order to aid recognition and treatment of depression and subclinical depressive symptoms.

Meteorological analysis of symptom data for people with seasonal affective disorder

It is thought that variation in natural light levels affect people with Seasonal Affective Disorder (SAD). Several meteorological factors related to luminance can be forecast but little is known about which factors are most indicative of worsening SAD symptoms. The aim of this meteorological analysis is to determine which factors are linked to SAD symptoms. The symptoms of 291 individuals with SAD in and near Groningen have been evaluated over the period 2003-2009. Meteorological factors linked to periods of low natural light (sunshine, global radiation, horizontal visibility, cloud cover and mist) and others (temperature, humidity and pressure) were obtained from weather observation stations. A Bayesian zero adjusted auto-correlated multilevel Poisson model was carried out to assess which variables influence the SAD symptom score BDI-II. The outcome of the study suggests that the variable sunshine duration, for both the current and previous week, and global radiation for the previous week, are significantly linked to SAD symptoms.

Highs and lows, ups and downs: Meteorology and mood in bipolar disorder

Seasonal variation of manic and depressive symptoms is a controversial topic in bipolar disorder research. Several studies report seasonal patterns of hospital admissions for depression and mania and variation in symptoms that appear to follow a seasonal pattern, whereas others fail to report such patterns. Differences in research methodologies, data analysis strategies, and temporal resolution of data may partly explain the variation in findings between studies. The current study adds a novel perspective to the literature by investigating specific meteorological factors such as atmospheric pressure, hours of sunshine, relative humidity, and daily maximum and minimum temperatures as more proximal predictors of self-reported daily mood change in people diagnosed with bipolar disorder. The results showed that daily maximum temperature was the only meteorological variable to predict clinically-relevant mood change, with increases in temperature associated with greater odds of a transition into manic mood states. The mediating effects of sleep and activity were also investigated and suggest at least partial influence on the prospective relationship between maximum temperature and mood. Limitations include the small sample size and the fact that the number and valence of social interactions and exposure to natural light were not investigated as potentially important mediators of relationships between meteorological factors and mood. The current data make an important contribution to the literature, serving to clarify the specific meteorological factors that influence mood change in bipolar disorder. From a clinical perspective, greater understanding of seasonal patterns of symptoms in bipolar disorder will help mood episode prophylaxis in vulnerable individuals.

Effects of personalised exposure on self-rated electromagnetic hypersensitivity and sensibility - A double-blind randomised controlled trial

BACKGROUND

Previous provocation experiments with persons reporting electromagnetic hypersensitivity (EHS) have been criticised because EHS persons were obliged to travel to study locations (seen as stressful), and that they were unable to select the type of signal they reported reacting to. In our study we used mobile exposure units that allow double-blind exposure conditions with personalised exposure settings (signal type, strength, duration) at home. Our aim was to evaluate whether subjects were able to identify exposure conditions, and to assess if providing feedback on personal test results altered the level of self-reported EHS.

METHODS

We used double-blind randomised controlled exposure testing with questionnaires at baseline, immediately before and after testing, and at two and four months post testing. Participants were eligible if they reported sensing either radiofrequency or extremely low frequency fields within minutes of exposure. Participants were visited at home or another location where they felt comfortable to undergo testing. Before double-blind testing, we verified together with participants in an unblinded exposure session that the exposure settings were selected were ones that the participant responded to. Double-blind testing consisted of a series of 10 exposure and sham exposures in random sequence, feedback on test results was provided directly after testing.

RESULTS

42 persons participated, mean age was 55years (range 29-78), 76% were women. During double-blind testing, no participant was able to correctly identify when they were being exposed better than chance. There were no statistically significant differences in the self-reported level of EHS at follow-up compared to baseline, but during follow-up participants reported reduced certainty in reacting within minutes to exposure and reported significantly fewer symptoms compared to baseline.

CONCLUSION

Our results suggest that a subgroup of persons exist who profit from participation in a personalised testing procedure.

Sunshine on my shoulders: Weather, pollution, and emotional distress

BACKGROUND

Researchers have examined the relationship between mental health and weather/pollution with mixed results. The current study aimed to examine a range of weather and atmospheric phenomena and their association with time-bound mental health data.

METHODS

Nineteen different weather/pollution variables were examined in connection with an archive of self-reported mental health data for university students participating in mental health treatment (n=16,452) using the Outcome Questionnaire 45.2 (OQ-45). Statistical approach involved randomly selecting 500 subjects from the sample 1000 different times and testing each variable of interest using mixed models analyses.

RESULTS

Seasonal changes in sun time were found to best account for relationships between weather variables and variability in mental health distress. Increased mental health distress was found during periods of reduced sun time hours. A separate analysis examining subjects' endorsement of a suicidality item, though not statistically significant, demonstrated a similar pattern. Initial results showed a relationship between pollution and changes in mental health distress; however, this was mediated by sun time.

LIMITATIONS

This study examined a relatively homogenous, predominantly European American, and religious sample of college counseling clients from an area that is subject to inversions and is at a high altitude and a latitude where sun time vacillates significantly more than locations closer to the equator.

CONCLUSIONS

Seasonal increases in sun time were associated with decreased mental health distress. This suggests the need for institutions and public health entities to plan for intervention and prevention resources and strategies during periods of reduced sun time.

Geographical and climatic factors and depression risk in the SUN project

BACKGROUND

Depression incidence has been related with seasonal periodicity and climate. The aim of the study was to estimate the possible association between depression and specific meteorological factors, namely temperature, light and rain.

METHODS

In total, 13,938 participants from the SUN (Seguimiento Universidad de Navarra) cohort study were included in the analysis. Subjects were classified according to daily mean temperature, number of daylight hours and amount of rain, by year, at their geographical area of residence, data supplied by the Spanish Agency of Meteorology. Participants were considered as incident cases of depression whenever they reported a physician diagnosis of depression or the use of antidepressant medication in any of the follow-up questionnaires. Cox regression models were fit to assess the relationship between climatic and geographical factors and the incidence of depression.

RESULTS

Male subjects living in the south and centre areas of Spain showed a higher risk to develop depression compared with those living in the north area (hazard ratio = 1.6, 95% CI = 1.16-2.23 and hazard ratio = 1.41, 95% CI = 1.06-1.87, respectively). Moreover, among males, a direct association between the number of daily light hours and mean temperature and the risk of depression was also found. For men, living in rainy areas was associated with a lower risk of developing depression.

CONCLUSION

Our results suggest that climate-depression relationship is more complex than previously thought, and strongly different between men and women.

Winter depression and diabetes

Depression is a common and often harmful disorder, which is frequently associated with the winter season. Research has shown a link between type 2 diabetes mellitus and depression. Furthermore, diabetics with depression have a higher rate of adverse outcomes. Little has been published regarding the seasonality of depression in diabetics. The case report described in this article concerns a 65-year-old woman with type 2 diabetes and a history of winter depression. Current evidence-based management options are reviewed.

Is there a negative impact of winter on mental distress and sleeping problems in the subarctic: the Tromsø Study

BACKGROUND

Prior studies have suggested that the darkness of winter impacts the level of mental distress and sleeping problems. Our study investigated whether people living in the sub-arctic had more sleeping problems or mental distress during winter.

METHODS

The cross sectional population Tromsø Study was conducted in Tromsø, North Norway, at 69.4 degrees North and above the Arctic Circle. The study included entire birth cohorts and random samples of the population aged 30 to 87 years. Data was collected continuously from 1 October 2007 to the end of December 2008 except July. 8951 persons completed questionnaires including the HSCL-10 and the MCTQ.

RESULTS

There were no significant differences in the reporting of current mental distress depending on season. Significantly more reported current sleeping problems in winter than in the other seasons, and less sleeping problems was found in spring.

CONCLUSIONS

In this sub-arctic population, insomnia was most prevalent in winter, but there were no significant seasonal differences in mental distress. Although some people in the sub-arctic clearly are mentally negatively affected by the darkness of winter, the negative impact of winter on mental distress for the adult population is not conclusive.

Atmospheric pressure and suicide attempts in Helsinki, Finland

The influence of weather on mood and mental health is commonly debated. Furthermore, studies concerning weather and suicidal behavior have given inconsistent results. Our aim was to see if daily weather changes associate with the number of suicide attempts in Finland. All suicide attempts treated in the hospitals in Helsinki, Finland, during two separate periods, 8 years apart, were included. Altogether, 3,945 suicide attempts were compared with daily weather parameters and analyzed with a Poisson regression. We found that daily atmospheric pressure correlated statistically significantly with the number of suicide attempts, and for men the correlation was negative. Taking into account the seasonal normal value during the period 1971-2000, daily temperature, global solar radiation and precipitation did not associate with the number of suicide attempts on a statistically significant level in our study. We concluded that daily atmospheric pressure may have an impact on suicidal behavior, especially on suicide attempts of men by violent methods (P < 0.001), and may explain the clustering of suicide attempts. Men seem to be more vulnerable to attempt suicide under low atmospheric pressure and women under high atmospheric pressure. We show only statistical correlations, which leaves the exact mechanisms of interaction between weather and suicidal behavior open. However, suicidal behavior should be assessed from the point of view of weather in addition to psychiatric and social aspects.

The association between sunshine duration and paroxetine response time in patients with major depressive disorder

INTRODUCTION

A recent study indicates that the serotonin transporter function varies with the duration of monthly sunshine. This finding may suggest that the efficacy of serotonin selective reuptake inhibitors (SSRIs) is associated with the duration of monthly sunshine, but information on this possible association is lacking.

METHODS

Ninety-one Japanese subjects with depression completed a 6-week treatment with paroxetine. Clinical evaluation was performed using the Montgomery and Asberg Depression Rating Scale (MADRS) before treatment and after 1, 2, 4 and 6 weeks of treatment. Data on the duration of monthly sunshine were obtained from the meteorological agency website. We divided the patients into four groups: nonresponders (NRs), later responders (LRs), early responders (ERs) and ultra-early responders (UERs).

RESULTS

The responses to paroxetine treatment of the group that began treatment in fall and winter and of the group that began treatment in spring and summer did not differ significantly. The effect of the duration of monthly sunshine on paroxetine response time did not differ significantly among the four groups, whereas the change in the duration of monthly sunshine had a significant effect on paroxetine response time.

LIMITATIONS

Our sample of patients with MDD was small and only included the Hirosaki area.

CONCLUSION

The change in the duration of monthly sunshine is associated with paroxetine response time.

Sunshine-exposure variation of human striatal dopamine D(2)/D(3) receptor availability in healthy volunteers

BACKGROUND

In addition to the serotonergic system, the central dopaminergic system has been reported to be correlated with seasonality. The aim of this study was to explore the difference in striatal dopamine D(2)/D(3) receptor availability between healthy volunteers who had a high-sunshine exposure and those who had a low exposure.

METHODS

Sixty-eight participants were enrolled, and those in the upper and lower quartiles in terms of sunshine exposure were categorized into high- (n = 17) and low-sunshine-exposure (n = 18) subgroups. Single photon emission computed tomography with [(123)I] iodo-benzamide was used to measure striatal dopamine D(2)/D(3) receptor availability.

RESULTS

Striatal dopamine D(2)/D(3) receptor availability was significantly greater in the subjects with high-sunshine exposure than in those with low-sunshine exposure (F = 7.97, p = 0.01) after controlling for age, sex, and smoking status.

LIMITATIONS

Different subjects were examined at different time points in our study. In addition, the sex and tobacco use distributions differed between groups.

CONCLUSION

The central dopaminergic system may play a role in the neurobiological characteristics of sunshine-exposure variation.