Seasonal influences on admissions for mood disorders and schizophrenia in a teaching psychiatric hospital in Egypt

Effects of seasonality in emergency admissions for mental disorders: two years of clinical experience

OBJECTIVES

This retrospective study, conducted in Turin, Italy, between January 2021 and February 2023, investigates the impact of seasonal heatwaves on emergency department (ED) admissions for mental disorders.

METHODS

Through the analysis of data from 2,854 patients, this research found a significant link between the occurrence of heatwaves, especially from June to August, and an elevated rate of ED admissions for psychiatric conditions.

RESULTS

The data indicate a clear seasonal pattern, with admissions peaking during the hot months and diminishing in the colder months. Particularly, the study delineates an enhanced correlation between heatwaves and admissions for severe psychiatric disorders, such as bipolar disorder, major depression, personality disorders, and schizophrenia, accounting for 1,868 of the cases examined. This correlation was most pronounced among individuals aged 50-59 years.

CONCLUSIONS

The results of this study highlight a critical association between the incidence of seasonal heatwaves and an uptick in ED visits for psychiatric disorders, with a distinct impact on severe cases. It underscores the urgency for healthcare systems to anticipate seasonal fluctuations in psychiatric ED admissions and to allocate resources effectively to support patients during peak periods.

Seasonal peak and the role of local weather in schizophrenia occurrence: A global analysis of epidemiological evidence

BACKGROUND

Many studies have shown that the onset of schizophrenia peaked in certain months within a year and the local weather conditions could affect the morbidity risk of schizophrenia. This study aimed to conduct a systematic analysis of schizophrenia seasonality in different countries of the world and to explore the effects of weather factors globally.

METHODS

We searched three databases (PubMed, Web of Science, and China National Knowledge Infrastructure) for eligible studies published up to September 2022. Schizophrenia seasonality was compared between hemispheres and within China. A meta-analysis was conducted to pool excess risk (ER, absolute percentage increase in risk) of the onset of schizophrenia associated with various weather factors including temperature (an increase or decrease of temperature as a reflection of high or low temperature; heatwave; temperature variation), precipitation, etc. RESULTS: We identified 84 relevant articles from 22 countries, mainly in China. The seasonality analysis found that the onset of schizophrenia mostly peaked in the cold season in the southern hemisphere but in the warm season in the northern hemisphere. Interestingly in China, schizophrenia seasonality presented two peaks, respectively in the late cold and warm seasons. The meta-analysis further revealed an increased risk of schizophrenia after short-term exposure to high temperature [ER%: 0.45 % (95 % confidence interval (CI): 0.14 % to 0.76 %)], low temperature [ER%: 0.52 % (95%CI: 0.29 % to 0.75 %)], heatwave [ER%: 7.26 % (95%CI: 4.45 % to 10.14 %)], temperature variation [ER%: 1.02 % (95%CI: 0.55 % to 1.50 %)], extreme precipitation [ER%: 3.96 % (95%CI: 2.29 % to 5.67 %)]. The effect of other weather factors such as sunlight on schizophrenia was scarcely investigated with inconsistent findings.

CONCLUSION

This study provided evidence of intra- and inter-country variations in schizophrenia seasonality, especially the double-peak seasons in China. Exposure to local weather conditions mainly temperature changes and precipitation could affect the onset risk of schizophrenia.

A Systematic Review on the Impact of Seasonality on Severe Mental Illness Admissions: Does Seasonal Variation Affect Coercion?

Coercion in psychiatry is associated mainly with involuntary admissions. The purpose of this study was to investigate the associations between hospital admissions of patients suffering from affective and schizophrenic disorders and seasonality. A systematic literature search using PubMed, Scopus and Google Scholar was conducted, including studies with affective and schizophrenia disorder admissions, published from October 1992 to August 2020. A total of 31 studies were included in the review. Four broad severe mental illness admission categories were identified regarding seasonality: affective disorders, schizophrenia disorders, involuntary admission affective disorders and involuntary admission schizophrenia disorders. There was clear and strong evidence for spring and summer peaks for severe mental illness admissions; data provided for age, gender and involuntary admissions was limited. Seasonality may have a significant effect on the onset and exacerbation of psychopathology of severe mental illness and should be considered as a risk factor in psychiatric admissions, violence and the risk of mental health coercion. A better understanding of the impact of seasonality on severe mental illness will help professionals to provide the best practices in mental health services in order to reduce and prevent psychiatric hospitalizations (especially involuntary admissions) resulting in further coercive measures.

Seasonality of hospitalization for schizophrenia and mood disorders: A single-center cross-sectional study in China

BACKGROUND

Seasonal patterns exist in many disorders and even serve as potential drivers of some disorders, but in schizophrenia and affective disorders, there is no uniform conclusion on the seasonal pattern.

METHODS

A total of 100,621 inpatients were surveyed in this study over 16 years, and 21,668 inpatients were ultimately included in the count after standard exclusion criteria were applied.

RESULTS

There was an uneven seasonal distribution of mental illness admissions (χ2 = 48.299, df = 18, P < .001). The peak of schizophrenia admissions occurred in the winter and the trough in the spring (52.6 % vs 50 %, P < .05). The peaks for depression and bipolar disorder were in the fall and spring, respectively, while the troughs were in the winter and fall, respectively (24.7 % vs 21.7 %, P < .05; 15.2 % vs 13.2 %, P < .05). Admissions for childhood mood disorders peaked in the fall (P < .05). We also found that the length of stay was also correlated with the season of admission, and that this seasonal fluctuation was not consistent across male and female populations.

LIMITATIONS

To avoid the effect of repeated hospitalizations, we maintained a registry of each patient's first admission only, which also resulted in our inability to explore the seasonal pattern of each disease recurrence at the individual level.

CONCLUSIONS

We found that the seasonal distribution of psychiatric admissions was not uniform. And there was also an uneven seasonal distribution of length of stay for patients admitted in different seasons. This may imply that certain environmental factors that vary with the seasons are potential drivers of mental illness.

The mental health of women and climate change: Direct neuropsychiatric impacts and associated psychological concerns

Climate change brings exposures to heat, air pollution, poorer quality food, and infectious disease that have significant direct effects on women and their mental health. These environmental impacts are multifaceted in their consequences and raise risks of depression, suicide, violent victimization, post-traumatic stress disorder, and various other neuropsychiatric symptoms. Women also suffer increased climate psychological risks from higher rates of stillbirth, preterm birth, and developmental problems in their children. Here we review what is known about the overlap of women's individual mental health and climate change, and highlight areas where more research is needed.

Explainable Gated Recurrent Unit to explore the effect of co-exposure to multiple air pollutants and meteorological conditions on mental health outcomes

Mental health conditions have the potential to be worsened by air pollution or other climate-sensitive factors. Few studies have empirically examined those associations when we faced to co-exposures, as well as interaction effects. There would be an urgent need to use deep learning to handle complex co-exposures that might interact in multiple ways, and the model performance reinforced by SHapely Additive exPlanations (SHAP) enabled our predictions interpretable and hence actionable. Here, to evaluate the mixed effect of short-term co-exposure, we conducted a time-series analysis using approximately 1.47 million hospital outpatient visits of mental disorders (i.e., depressive disorder-DD, Schizophrenia-SP, Anxiety Disorder-AD, Bipolar Disorder-BD, Attention Deficit and Hyperactivity Disorder-ADHD, Autism Spectrum Disorder-ASD), with matched meteorological observations from 2015 through 2019 in Nanjing, China. The global insights of gated recurrent unit model revealed that most of input features with similar effect size caused the illness risk of SP and ASD increase, and most markedly, 73% of relative humidity, 44.6 µg/m³ of NO₂, and 14.1 µg/m³ of SO₂ at 5-year average level associated with 2.27, 1.14, and 1.29 visits increase for DD, SP, and AD, respectively. Both synergic and antagonistic effect among informative paired-features were distinguished from local feature dependence. Interestingly, variation tendencies of excessive visits of bipolar disorder when atmospheric pressure, PM_2.5, and O₃ interacted with one another were inconsistent. Our results provided added qualitative and quantitative support for the conclusion that short-term co-exposure to ambient air pollutants and meteorological conditions posed threats to human mental health.

Recent Techniques in Determining the Effects of Climate Change on Depressive Patients: A Systematic Review

Climate change is amongst the most serious issues nowadays. Climate change has become a concern for the scientific community as it could affect human health. Researchers have found that climate change potentially impacts human mental health, especially among depressive patients. However, the relationship is still unclear and needs further investigation. The purpose of this systematic review is to systematically evaluate the evidence of the association between climate change effects on depressive patients, investigate the effects of environmental exposure related to climate change on mental health outcomes for depressive patients, analyze the current technique used to determine the relationship, and provide the guidance for future research. Articles were identified by searching specified keywords in six electronic databases (Google Scholar, PubMed, Scopus, Springer, ScienceDirect, and IEEE Digital Library) from 2012 until 2021. Initially, 1823 articles were assessed based on inclusion criteria. After being analyzed, only 15 studies fit the eligibility criteria. The result from included studies showed that there appears to be strong evidence of the association of environmental exposure related to climate change in depressive patients. Temperature and air pollution are consistently associated with increased hospital admission of depressive patients; age and gender became the most frequently considered vulnerability factors. However, the current evidence is limited, and the output finding between each study is still varied and does not achieve a reasonable and mature conclusion regarding the relationship between the variables. Therefore, more evidence is needed in this domain study. Some variables might have complex patterns, and hard to identify the relationship. Thus, technique used to analyze the relationship should be strengthened to identify the relevant relationship.

The pattern of inpatient psychiatry admissions at a general hospital psychiatry unit in South India: A retrospective study

BACKGROUND

Mental illnesses are becoming a major health issue across the world. The availability of inpatient facilities for mentally ill patients is very much limited in developing countries such as India.

AIM

This study was aimed to explore the pattern of psychiatric admissions at a general hospital psychiatry unit (GHPU) in South India.

METHODOLOGY

The study was conducted at a multispecialty tertiary care hospital in South India. A retrospective, chart-based study design was adopted to achieve the objectives. All inpatient case records available from the department of psychiatry, the medical records department, and the electronic hospital information system of the institute were reviewed between April 2006 and March 2016.

RESULTS

A total of 3082 patients were admitted as psychiatry inpatients during the 10-year study period, representing an average of 308.2 admissions per calendar year. The majority of inpatients were male (n = 1824; 59.2%). Concerning diagnostic categories, mood disorders were accounted for 33.6% of admissions, followed by psychotic disorders (26.4%) and substance use disorders (19.3%), respectively. The median length of hospital stay was 14 days (range 0-163 days). A statistically significant seasonality pattern was noticed for mood disorders (December to February) and anxiety and neurotic disorders (August to October).

CONCLUSION

It is obvious that treatment-seeking attitude among individuals with mental illnesses is increasing and the awareness regarding treatment aspects is also increasing among the general public. Hence, there is a need to improve the existing resources to facilitate intensive management for better treatment outcomes and this, in turn, will enhance the quality of life of mentally ill individuals.

Assessing evidence for seasonality of hospital admissions for schizophrenia in Queensland, Australia: a time series observational study

Most evidence on seasonal admission patterns for schizophrenia derives from the Northern Hemisphere with results from the Southern Hemisphere less documented. This study examines seasonal patterns in hospital admissions due to schizophrenia in Queensland, Australia, a large area that has a range of different climatic features. Daily hospital admissions data for people with the primary diagnosis of schizophrenia were collected from Queensland Health Department for the period from January 1996 to December 2015. A generalised linear regression model with Quasi-Poisson distribution was used to assess seasonal admission patterns across different climatic regions. The evidence for seasonality was also explored in subgroups that had different socio-demographic characteristics or history of prior hospitalisation for psychiatric disorders. Overall, a significant winter pattern (RR 1.05, 95%CI 1.01-1.13) was found with a peak in August (RR 1.08, 95%CI 1.03-1.17) in temperate Southeast Queensland. However, the hot humid North and Far North Queensland showed a peak in October (RR 1.10, 95%CI 1.02-1.22). Males (RR 1.11, 95%CI 1.07-1.14), people aged 40-59 years old (RR 1.10, 95%CI 1.05-1.15) and those who had never married (RR 1.09, 95%CI 1.06-1.12), were Australian by birth (RR 1.07, 95%CI 1.04-1.10) or were unemployed (RR 1.13, 95%CI 1.09-1.18) had significantly higher risk for hospital admissions, particularly during the winter months. The seasonal admission pattern for schizophrenia did not change significantly according to admission status and history of outpatient or community psychiatric treatment. The study found some evidence for seasonality of hospital admissions for schizophrenia that differed from northern tropical to southern temperate regions of Queensland.

Investigating the association between temperature and hospital admissions for major psychiatric diseases: A study in Greece

Evidence has emerged regarding the role of seasonality and several meteorological parameters on bipolar disorder, schizophrenia and depression. We investigated the relationship between ambient and apparent temperature and hospital admissions of major psychiatric diseases in a psychiatric clinic of a General Hospital situated in Northern Greece during 2013-19. Temperature data was provided by the National Observatory of Athens and diagnosis for psychotic, schizophrenic, manic and bipolar and unipolar depression were retrieved from medical records. A total of 783 admissions were recorded. Poisson regression models adjusted for time trends were applied to analyze the impact of temperature on monthly admissions. A summer peak was observed for the bipolar disorder, irrespectively of substance/alcohol use status. Seasonality emerged also for psychotic and schizophrenic patients with a through in winter. An increase of 1 °C in either ambient or apparent temperature was associated with an increase 1-2% in the monthly admissions in most outcomes under investigation. Alcohol and drug abuse did not modify this effect. Although our results indicate effects of temperature on psychiatric admissions, they are not consistent across subgroups populations and need to be replicated by other methodologically superior studies.

Association between extreme temperatures and emergency room visits related to mental disorders: A multi-region time-series study in New York, USA

BACKGROUND

There is growing evidence suggesting that extreme temperatures have an impact on mental disorders. We aimed to explore the effect of extreme temperatures on emergency room (ER) visits for mental health disorders using 2.8 million records from New York State, USA (2009-2016), and to examine potential effect modifications by individuals' age, sex, and race/ethnicity through a stratified analysis to determine if certain populations are more susceptible.

METHOD

To assess the short-term impact of daily average temperature on ER visits related to mental disorders, we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, as well as long-term and seasonal time trends. We also conducted a meta-analysis to pool the region-specific risk estimates and construct the overall cumulative exposure-response curves for all regions.

RESULTS

We found positive associations between short-term exposure to extreme heat (27.07 ^∘C) and increased ER visits for total mental disorders, as well as substance abuse, mood and anxiety disorders, schizophrenia, and dementia. We did not find any statistically significant difference among any subgroups of the population being more susceptible to extreme heat than any other.

CONCLUSIONS

Our findings suggest that there is a positive association between short-term exposure to extreme heat and increased ER visits for total mental disorders. This extreme effect was also found across all sub-categories of mental disease, although further research is needed to confirm our finding for specific mental disorders, such as dementia, which accounted for less than 1% of the total mental disorders in this sample.

Immediate and delayed effects of climatic factors on hospital admissions for schizophrenia in Queensland Australia: A time series analysis

BACKGROUND

Evidence of immediate and delayed effects of climatic drivers on hospital admissions for schizophrenia is limited and inconsistent. We aimed to assess the association between climatic factors and daily hospital admissions for schizophrenia in Queensland, Australia.

METHODS

Daily hospital admissions for schizophrenia from January 1, 1996 to December 31, 2015 in all private and public hospitals of Queensland were obtained from Queensland Health. The association between climatic factors and hospital admissions for schizophrenia were analysed using Generalised Linear Models with Poisson distribution (GLM) and Distributed Lag non-linear Models (DLNM) across different climatic zones.

RESULTS

In South East Queensland, only daily mean temperature showed an immediate negative effect on schizophrenia admissions (RR 0.93, 95%CI 0.90-0.98, p value < 0.001). For other regions, the adverse effect of temperature on hospital admissions was not significant, however, relative humidity (North: RR 1.01, 95%CI 1.00-1.02, p = 0.05) and air pressure (North: RR 1.03, 95%CI 1.00-1.05, p = 0.04; South West: RR 1.01, 95%CI 1.00-1.02, p = 0.05) had an immediate and positive effect on hospital admissions. Moreover, climatic factors had some delayed effects on schizophrenia admissions in different regions of Queensland, i.e. temperature over 0-4 lag days (South East: RR 0.97, 95%CI 0.94-0.98, p = 0.05; South West: RR 0.96, 95%CI 0.94-0.98, p = 0.01), relative humidity over 0-7 lag days (North: RR 0.95, 95%CI 0.92-0.98, p = 0.01; Central: RR 1.02, 95%CI 1.00-1.03, p = 0.05) and rainfall over 0-21 lag days (North: RR 1.03, 95%CI 1.01-1.04, p = 0.01). Meta-analysis showed significant pooled delayed effects of temperature (0-15 days lag: RR 0.95, 95% CI 0.93-0.98, p value < 0.001), relative humidity (0-7 days: RR 0.96, 95%CI 0.92-0.99, p < 0.001); rainfall (0-21 lag days: RR 1.03, 95%CI 1.01-1.04, p < 0.001) and air pressure (0-7 days lag: RR 1.02, 95%CI 1.00-1.04, p < 0.001) on schizophrenia admissions in Queensland.

DISCUSSION

As this is the largest study from Australia and also internationally to extensively examine both short term and delayed association between climatic factors and daily admissions for schizophrenia, the results of the study indicate that climate plays an important role in the sudden exacerbation of acute episodes of schizophrenia. Thus, preventive measures could be taken to reduce the severity of symptoms as well as hospital admissions due to schizophrenia during vulnerable periods.

Hospitalization trends and chronobiology for mental disorders in Spain from 2005 to 2015

Rhythm research has had a long tradition in psychiatry, especially in affective disorders. The study of trends in incidence plays a central role in epidemiology and public health. The aims of this research were to describe the socio-demographic and clinical characteristics of persons admitted for psychiatric hospitalization and their trends and periodicity in cases (global and by groups) in Spain over the 11 year study span. We conducted a cross-sectional study of the hospital discharge database of Castilla y León from 2005 to 2015, selecting hospitalizations for psychiatric reasons. Trends in the rates of hospitalization were studied by joinpoint regression analysis. Time series analysis for periodicities was done by spectral analysis, fast Fourier transform, and cosinor analysis. Some 49501 hospitalizations due to psychiatric disorders, out of 2717192 hospital admissions, took place during the study span. Hospitalizations for psychosis were frequent (15949, 32.2%), while such for eating disorders were infrequent, but showed the highest average stay (28 days) and DRG relative weight (2.41). The general trend was a statistically significant 2% annual increase in psychiatric hospitalizations over the 11 year span; substance abuse was the only exception to this trend. The whole population and the subgroups of psychosis and bipolar disorders showed significant circannual (one-year) variation in admissions. The rhythm percentage of the global group was 11.4%, while the rhythm percentages of the psychosis, bipolar, and eating disorders were 17.1%, 17.5%, and 9.6%, respectively (p < .05).

Seasonality and schizophrenia: a comprehensive overview of the seasonal pattern of hospital admissions and potential drivers

Schizophrenia is a severe neuropsychiatric disorder with heterogeneous aetiology mostly affecting younger people and causing immense disability. Seasonal patterns may be observed in schizophrenia hospital admissions with possible association with changing climatic parameters and socio-demographic characteristics. This study critically reviewed studies that have assessed seasonal variations of hospital admissions for schizophrenia and/or explored an association with climate parameters and/or other potential factors. Following PRISMA guidelines, a systematic literature search was conducted using electronic databases (e.g. MEDLINE, Science Direct, PsycINFO, Pub Med) from inception to February 29, 2020. Thirty five papers were identified, of which only six (17.1%) examined evidence for a seasonal pattern or monthly excess of hospital admissions and the remaining twenty nine (82.9%) assessed climatic and socio-demographic attributes relating to the seasonal pattern or increased hospitalisation for schizophrenia. While most studies reported a summer peak in hospital admission rates, other studies reported a winter peak. Most of the evidence indicated that higher temperatures (> 28 °C) were positively correlated with schizophrenia admission rates. The individual effects of other climatic parameters (e.g. relative humidity, rainfall, atmospheric pressure, sunlight) were less frequently assessed. Males, people of 21-60 years old, and those married were more vulnerable to climatic variability specifically to higher temperatures. Further studies using large sample sizes, analysis of a wide range of interacting environmental variables and sophisticated statistical approaches are needed to better understand the underlying mechanisms involved. This will also provide more reliable statistical evidence that will help in the prevention and better management of cases.

Seasonality in schizophrenia-An analysis of a nationwide registry with 110,735 hospital admissions

Background.

Seasonal patterns in hospitalizations have been observed in various psychiatric disorders, however, it is unclear whether they also exist in schizophrenia. Previous studies found mixed results and those reporting the presence of seasonality differ regarding the characteristics of these patterns. Further, they are inconclusive whether sex is an influencing factor. The aim of this study was therefore to examine if seasonal patterns in hospitalizations can be found in schizophrenia, with special regard to a possible influence of sex, by using a large national dataset.

Methods.

Data on all hospital admissions within Austria due to schizophrenia (F20.0–F20.6) for the time period of 2003–2016 were included. Age standardized monthly variation of hospitalization for women and men was analyzed and the level of significance adjusted for multiple testing.

Results.

The database comprised of 110,735 admissions (59.6% men). Significant seasonal variations were found in the total sample with hospitalization peaks in January and June and a trough in December (p < 0.0001). No significant difference in these patterns was found between women and men with schizophrenia (p < 0.0001).

Conclusion.

Our study shows that schizophrenia-related hospitalizations follow a seasonal pattern in both men and women. The distribution of peaks might be influenced by photoperiod changes which trigger worsening of symptoms and lead to exacerbations in schizophrenia. Further research is necessary to identify underlying factors influencing seasonal patterns and to assess whether a subgroup of patients with schizophrenia is especially vulnerable to the impact of seasonal variations.

Seasonal and temperature effect on serum lithium concentrations

BACKGROUND

Lithium remains the gold standard treatment for bipolar disorder. However, it has a very narrow therapeutic index (0.6-0.8 mmol/L). It has been suggested that high environmental temperature can lead to dehydration, elevated plasma lithium concentration and then lithium toxicity.

OBJECTIVES

We aimed to investigate the effect of seasonal and short-term changes in temperature on serum lithium concentrations in Sydney, Australia.

METHODS

We retrospectively analysed data from all patients who had serum lithium concentrations taken from the Prince of Wales and Sutherland Hospitals between 2008 and 2018. Temperature data came from the Bureau of Meteorology. We examined correlations between lithium concentrations and the preceding 5 days maximum temperatures, month and season. We also performed a longitudinal analysis of the effect of temperature and seasons within selected patients who had repeated levels.

RESULTS

A total of 11,912 serum lithium concentrations from 2493 patients were analysed. There was no significant association between higher lithium concentration and preceding higher temperatures (r = -0.008, p = 0.399). There was also no important seasonal or monthly variation, across all patients or in the smaller cohort with longitudinal data (n = 123, r = 0.008, 95% confidence interval: [-0.04, 0.06]).

CONCLUSION

There were no clinically important differences in serum lithium concentration related to seasons, months or temperatures, which suggests that patients on lithium are able to adequately maintain hydration during hot weather in Sydney.

Exposure-lag-response association between sunlight and schizophrenia in Ningbo, China

Previous studies found that mental disorders such as bipolar disorder, seasonal affective disorder and schizophrenia, often show seasonal variability, which usually be attributed to the variations in the number of natural sunlight. However, few studies have been conducted on the acute effects of exposure to sunlight on the onset of these disease. The aim of this study was to evaluate the exposure-response relationship between sunshine duration and the hospital admissions for schizophrenia. We obtained data on hospital admissions for schizophrenia from the largest psychiatric hospital in Ningbo, China, during 2012-2016. A Distributed lag non-linear model was used to estimate the exposure-lag-response relationship between sunlight and schizophrenia. We calculated the effects of short and long sunshine duration, defined using the cutoffs at the 1st and 99th sunshine duration percentiles. We detected significant and non-linear associations between sunlight and schizophrenia, and the overall estimated relative risk (RR) for a lag of 0-21 days was 1.45 (95% CI: 1.07, 1.97) and 1.41(95% CI: 0.72, 2.75) for short and long sunshine duration, respectively. The burden of schizophrenia was greater during periods with short sunshine duration than during periods with long sunshine duration, with the AFs of 19.94% (95% CI: 8.65%, 28.24%) and 2.12% (95% CI: -2.70%, 5.57%), respectively. The female and people more than 45 years old were most susceptible to these effects. We repeated our analysis by using global solar radiation as a continuous exposure variable of sunlight intensity in the model, and the result shows that the female and middle-aged and eldly patients were also susceptible to the effects of low levels of global solar radiation. Our findings suggest that there may be a relationship between lack of exposure to sunlight and increased risk of hospital admissions for schizophrenia. Policymakers and doctors should promote further understanding of the health benefits of sunlight and take effective measures to prevent schizophrenia.

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.

Assessing Effect Modification of Excess Winter Death by Causes of Death and Individual Characteristics in Zhejiang Province, China: A Multi-Community Case-Only Analysis

Mortality in many parts of the world has a seasonal pattern, with a marked excess of deaths during winter. To date, however, there is very little published evidence on the nature of this wintertime excess in low- and middle-income countries. In this study, we aimed to quantify the extent of the death peak in winter and to assess effect modification on excess winter death (EWD) by individual characteristics and cause of deaths in China. We used a Cosinor model to examine seasonal patterns for specific causes of deaths and a case-only analysis of deaths in winter compared with other seasons to assess effect modification by individual characteristics. A total of 398,529 deaths were investigated between January 2010 and December 2013 in Zhejiang Province, China. Deaths peaked in winter, and overall mortality was around 30% higher in winter than in summer. Although diseases of the respiratory and circulatory systems were highly seasonal, surprisingly we observed that deaths from mental and behavioral disorders exhibited greater fluctuation. Males, the elderly and illiterate individuals suffered high EWD. EWDs were also particularly common in emergency rooms, at home, on the way to hospitals, and in nursing homes/family wards. This study highlighted the high EWD in some previously unreported groups, indicating new information to facilitate the targeting of necessary preventive measures to those at greatest risk in order to mitigate wintertime death burdens.

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.

Association between Ambient Temperatures and Mental Disorder Hospitalizations in a Subtropical City: A Time-Series Study of Hong Kong Special Administrative Region

Background: Mental disorders have been found to be positively associated with temperature in cool to cold climatic regions but the association in warmer regions is unclear. This study presented the short-term association between temperatures and mental disorder hospitalizations in a subtropical city with a mean annual temperature over 21 °C. Methods: Using Poisson-generalized additive models and distributed-lagged nonlinear models, daily mental disorder hospitalizations between 2002 and 2011 in Hong Kong were regressed on daily mean temperature, relative humidity, and air pollutants, adjusted for seasonal trend, long-term trend, day-of-week, and holiday. Analyses were stratified by disease class, gender and age-group. Results: 44,600 admissions were included in the analysis. Temperature was positively associated with overall mental-disorder hospitalizations (cumulative relative risk at 28 °C vs. 19.4 °C (interquartile range, lag 0-2 days) = 1.09 (95% confidence interval 1.03, 1.15)), with the strongest effect among the elderly (≥75 years old). Transient mental disorders due to conditions classified elsewhere and episodic mood disorders also showed strong positive associations with temperature. Conclusion: This study found a positive temperature-mental-disorder admissions association in a warm subtropical region and the association was most prominent among older people. With the dual effect of global warming and an aging population, targeted strategies should be designed to lower the disease burden.

Effect of increasing temperature on daily hospital admissions for schizophrenia in Hefei, China: a time-series analysis

OBJECTIVE

To investigate the relationship between ambient temperature and hospital admissions for schizophrenia in Hefei, China.

STUDY DESIGN

An ecological design was used to explore the effect of ambient temperature on hospital admissions for schizophrenia.

METHODS

Daily data on hospital admissions for schizophrenia and meteorological data for the warm season (May-October) in 2005-2014 were obtained from Anhui Mental Health Centre and Hefei Bureau of Meteorology, respectively. Poisson generalised linear regression model combined with a distributed lag non-linear model was used to analyse the effects of temperature on admissions for schizophrenia. Stratified analyses according to individual characteristics, such as age and sex, were also conducted.

RESULTS

A significant relationship was found between ambient temperature and admissions for schizophrenia. High temperature appeared to have a delayed effect on admissions for schizophrenia, and a temperature of 28°C (75th percentile) at lag 0-4 days was associated with a 7% (95% confidence interval: 4-11%) increase in admissions for schizophrenia. Stratified analyses showed that male patients, patients aged 21-60 years and married patients were more vulnerable to high temperature, and the temperature effects for those groups occurred at a lag of 1 day.

CONCLUSION

High temperature poses significant risks for schizophrenia in subtropical regions. Future preventive measures for reducing the occurrence of schizophrenia should be considered for susceptible populations.

Bipolar disorders: is there an influence of seasonality or photoperiod?

Objective:

To increase understanding of the influence of photoperiod variation in patients with bipolar disorders.

Methods:

We followed a sample of Italian bipolar patients over a period of 24 months, focusing on inpatients. All patients admitted to the Psychiatric Inpatient Unit of San Luigi Gonzaga Hospital in Orbassano (Turin, Italy) between September 1, 2013 and August 31, 2015 were recruited. Sociodemographic and clinical data were collected.

Results:

Seven hundred and thirty patients were included. The admission rate for bipolar patients was significantly higher during May, June and July, when there was maximum sunlight exposure, although no seasonal pattern was found. Patients with (hypo)manic episodes were admitted more frequently during the spring and during longer photoperiods than those with major depressive episodes.

Conclusions:

Photoperiod is a key element in bipolar disorder, not only as an environmental factor but also as an important clinical parameter that should be considered during treatment.

Discovery of temporal and disease association patterns in condition-specific hospital utilization rates

Identifying temporal variation in hospitalization rates may provide insights about disease patterns and thereby inform research, policy, and clinical care. However, the majority of medical conditions have not been studied for their potential seasonal variation. The objective of this study was to apply a data-driven approach to characterize temporal variation in condition-specific hospitalizations. Using a dataset of 34 million inpatient discharges gathered from hospitals in New York State from 2008-2011, we grouped all discharges into 263 clinical conditions based on the principal discharge diagnosis using Clinical Classification Software in order to mitigate the limitation that administrative claims data reflect clinical conditions to varying specificity. After applying Seasonal-Trend Decomposition by LOESS, we estimated the periodicity of the seasonal component using spectral analysis and applied harmonic regression to calculate the amplitude and phase of the condition's seasonal utilization pattern. We also introduced four new indices of temporal variation: mean oscillation width, seasonal coefficient, trend coefficient, and linearity of the trend. Finally, K-means clustering was used to group conditions across these four indices to identify common temporal variation patterns. Of all 263 clinical conditions considered, 164 demonstrated statistically significant seasonality. Notably, we identified conditions for which seasonal variation has not been previously described such as ovarian cancer, tuberculosis, and schizophrenia. Clustering analysis yielded three distinct groups of conditions based on multiple measures of seasonal variation. Our study was limited to New York State and results may not directly apply to other regions with distinct climates and health burden. A substantial proportion of medical conditions, larger than previously described, exhibit seasonal variation in hospital utilization. Moreover, the application of clustering tools yields groups of clinically heterogeneous conditions with similar seasonal phenotypes. Further investigation is necessary to uncover common etiologies underlying these shared seasonal phenotypes.

Preventing involuntary admissions: special needs for distinct patient groups

BACKGROUND

Coercive measures in psychiatry are a controversial topic and raise ethical, legal and clinical issues. Involuntary admission of patients is a long-lasting problem and indicates a problematic pathway to care situations within the community, largely because personal freedom is fundamentally covered by the UN declaration of human rights and the German constitution.

METHODS

In this study, a survey on a large and comprehensive population of psychiatric in-patients in the eastern part of North Rhine-Westphalia, Germany, was carried out for the years 2004-2009, including 230.678 treatment cases. The data were collected from the dataset transferred to health insurance automatically, which, since 2004 is available in an electronic form. In addition, a wide variety of information on treatment, sociodemographic and illness-related factors were collected and analysed. Data were collected retrospectively and analyses were calculated using statistical software (IBM SPSS Statistics 19.0^®). Quantitative data are presented as mean and standard deviation. Due to the unequal group sizes, group differences were calculated by means of Chi-square tests or independent sample t tests. A Bonferroni correction was applied to control for multiple comparisons.

RESULTS

We found an over-representation of involuntary admissions in young men (<21 years) suffering from schizophrenia and in female patients aged over 60 with a diagnosis of dementia. Most of our results are concordant with the previous literature. Also admission in hours out of regular out-patient services elevated the risk.

CONCLUSION

The main conclusion from these findings is a need for a fortification of ambulatory treatment offers, e.g. sociopsychiatric services or ward round at home for early diagnosis and intervention. Further prospective studyies are needed.

Involuntary admissions in Italy: the impact of seasonality

OBJECTIVE

The aim of this study is to assess the prevalence of involuntary admissions with regard to seasonality and clinical associated features, in a sample of patients admitted to a psychiatric unit in a period of 24 months.

METHODS

All subjects consecutively admitted to the Psychiatric Inpatient Unit of the San Luigi Gonzaga Hospital, Orbassano (University of Turin, Italy) from September 2013 to August 2015 were recruited. Socio-demographic and clinical characteristics were collected.

RESULTS

Seven hundred and thirty admissions in psychiatric ward were recognized. The prevalence of involuntary admission was 15.4%. Patients with involuntary hospitalizations showed a higher education level, a higher prevalence of admission in spring/summer with a significant peak in June, a longer duration of hospitalization and a lower suicide ideation. Among involuntary admissions, physical restraint and suicide attempts were more prevalent during spring compared to the other seasons.

CONCLUSIONS

Seasonality has an important role in the psychopathology of psychiatric disorders, particularly in bipolar and related disorder, and may represent an influencing factor in hospital admissions and hospitalizations. Seasonal pattern must be considered while managing diagnosis and treatment of mental disorders, with regard to prevention and psychoeducation of patients.

Seasonality of hospital admissions for mental disorders in Hanoi, Vietnam

BACKGROUND

Some studies have shown a relationship between seasonality in weather patterns and depressive and behavioural disorders, especially in temperate climate regions. However, there is a lack of studies describing the seasonal patterns of hospital admissions for a variety of mental disorders in tropical and subtropical nations. The aim of this study has been to examine the relationship between seasons and daily hospital admissions for mental disorders in Hanoi, Vietnam.

DESIGNS

A 5-year database (2008-2012) compiled by Hanoi Mental Hospital covering mental disorder admissions diagnosed by the International Classification of Diseases 10 was analysed. A negative binominal regression model was applied to estimate the associations between seasonality and daily hospital admissions for mental disorders, for all causes and for specific diagnoses.

RESULTS

The summer season indicated the highest relative risk (RR=1.24, confidence interval (CI)=1.1-1.39) of hospital admission for mental disorders, with a peak in these cases in June (RR=1.46, CI=1.19-1.7). Compared to other demographic groups, males and the elderly (aged over 60 years) were more sensitive to seasonal risk changes. In the summer season, the RR of hospital visits among men increased by 26% (RR=1.26, CI=1.12-1.41) and among the elderly by 23% (RR=1.23, CI=1.03-1.48). Furthermore, when temperatures including minimum, mean, and maximum increased 1°C, the number of cases for mental disorders increased by 1.7%, 2%, and 2.1%, respectively.

CONCLUSION

The study results showed a correlation between hospital admission for mental disorders and season.

Psychiatric hospitalizations for affective disorders in Warsaw, Poland: Effect of season and intensity of sunlight

The purpose of this study was to assess any associations between the number of hospitalizations for affective disorders, seasons of the year and the intensity of sunlight in Poland, a country with a very changeable climate and significant seasonal fluctuations. We analyzed 2837 admissions with affective disorders hospitalized in the Institute of Psychiatry and Neurology in Warsaw, between 2002 and 2010 (mania, n=380, mixed episode, n=131, bipolar depression, n=736, recurrent depression, n=681, single depressive episode, n=909). For each diagnostic group admission time series were created and categorized into subgroups according to sex and age, and these were analyzed by means of the Autoregressive Integrated Moving Average (ARIMA) method. Regression models and correlations were used to assess the influence of the intensity of sunlight on the number of hospitalizations. Most mania admissions were noted in spring/summer months and in midwinter, mixed episode-late spring and winter, and depression (bipolar, recurrent and single depressive episode)-spring and autumn months. The association between frequency of admissions and monthly hours of sunshine was observed in some age and sex subgroups of patients with bipolar disorder and single depressive episode. The results support the seasonality of admissions of patients with affective disorders.

Seasonality shows evidence for polygenic architecture and genetic correlation with schizophrenia and bipolar disorder

OBJECTIVE

To test common genetic variants for association with seasonality (seasonal changes in mood and behavior) and to investigate whether there are shared genetic risk factors between psychiatric disorders and seasonality.

METHOD

Genome-wide association studies (GWASs) were conducted in Australian (between 1988 and 1990 and between 2010 and 2013) and Amish (between May 2010 and December 2011) samples in whom the Seasonal Pattern Assessment Questionnaire (SPAQ) had been administered, and the results were meta-analyzed in a total sample of 4,156 individuals. Genetic risk scores based on results from prior large GWAS studies of bipolar disorder, major depressive disorder (MDD), and schizophrenia were calculated to test for overlap in risk between psychiatric disorders and seasonality.

RESULTS

The most significant association was with rs11825064 (P = 1.7 × 10⁻⁶, β = 0.64, standard error = 0.13), an intergenic single nucleotide polymorphism (SNP) found on chromosome 11. The evidence for overlap in risk factors was strongest for schizophrenia and seasonality, with the schizophrenia genetic profile scores explaining 3% of the variance in log-transformed global seasonality scores. Bipolar disorder genetic profile scores were also associated with seasonality, although at much weaker levels (minimum P value = 3.4 × 10⁻³), and no evidence for overlap in risk was detected between MDD and seasonality.

CONCLUSIONS

Common SNPs of large effect most likely do not exist for seasonality in the populations examined. As expected, there were overlapping genetic risk factors for bipolar disorder (but not MDD) with seasonality. Unexpectedly, the risk for schizophrenia and seasonality had the largest overlap, an unprecedented finding that requires replication in other populations and has potential clinical implications considering overlapping cognitive deficits in seasonal affective disorders and schizophrenia.

Acute impacts of extreme temperature exposure on emergency room admissions related to mental and behavior disorders in Toronto, Canada

BACKGROUND

The purpose of this study was to assess the effects of extreme ambient temperature on hospital emergency room visits (ER) related to mental and behavioral illnesses in Toronto, Canada.

METHODS

A time series study was conducted using health and climatic data from 2002 to 2010 in Toronto, Canada. Relative risks (RRs) for increases in emergency room (ER) visits were estimated for specific mental and behavioral diseases (MBD) after exposure to hot and cold temperatures while using the 50th percentile of the daily mean temperature as reference. Poisson regression models using a distributed lag non-linear model (DLNM) were used. We adjusted for the effects of seasonality, humidity, day-of-the-week and outdoor air pollutants.

RESULTS

We found a strong association between MBD ER visits and mean daily temperature at 28°C. The association was strongest within a period of 0-4 days for exposure to hot temperatures. A 29% (RR=1.29, 95% CI 1.09-1.53) increase in MBD ER vists was observed over a cumulative period of 7 days after exposure to high ambient temperature (99th percentile vs. 50th percentile). Similar associations were reported for schizophrenia, mood, and neurotic disorers. No significant associations with cold temperatures were reported.

LIMITATIONS

The ecological nature and the fact that only one city was investigated.

CONCLUSIONS

Our findings suggest that extreme temperature poses a risk to the health and wellbeing for individuals with mental and behavior illnesses. Patient management and education may need to be improved as extreme temperatures may become more prevalent with climate change.

Seasonal changes in gene expression represent cell-type composition in whole blood

Seasonal patterns in behavior and biological parameters are widespread. Here, we examined seasonal changes in whole blood gene expression profiles of 233 healthy subjects. Using weighted gene co-expression network analysis, we identified three co-expression modules showing circannual patterns. Enrichment analysis suggested that this signal stems primarily from red blood cells and blood platelets. Indeed, a large clinical database with 51 142 observations of blood cell counts over 3 years confirmed a corresponding seasonal pattern of counts of red blood cells, reticulocytes and platelets. We found no direct evidence that these changes are linked to genes known to be key players in regulating immune function or circadian rhythm. It is likely, however, that these seasonal changes in cell counts and gene expression profiles in whole blood represent biological and clinical relevant phenomena. Moreover, our findings highlight possible confounding factors relevant to the study of gene expression profiles in subjects collected at geographical locations with disparaging seasonality patterns.

Admission rate of patients with most common psychiatric disorders in relation to seasons and climatic factors during 2010/2011

Introduction:

Climate and its impact on human health and mental illness have been in the focus of the research since years in the field.

Aim:

The aim of the research is to study the admissions rate to the psychiatric clinic in correlation to seasons and climate.

Material and method:

The research was conducted in a Psychiatric clinic of the Clinical Center in Sarajevo. Randomly selected subjects (aged 5-89 years, 1316 males and 1039 females) N=2355, were interviewed by the Structural Clinical Interview (SCID) which generated DSM-IV. In this retrospective-prospective, clinicalepidemiological study subjects were divided into groups according to type of disorders. Correlation between the impact of seasons and the rate of admissions to a Psychiatric clinic was analyzed. Certain data were taken from Federal Hydrometeorological Institute in Sarajevo of the climatic situation for period of the study.

Results and conclusions:

Of the total number of subjects who were admitted to the clinic in the period of 2010/2011 the most common diagnoses were F10-F19, F20-F29, F30-F39, F40-F48, and the suicide attempts as the separate entity. It was found correlation between certain seasons and the effects of the certain weather parameters at an increased admission rate of subjects with the certain diseases.