Investigating the effect of climatic parameters on mental disorder admissions

The Impact of Seasonality on Mental Health Disorders: A Narrative Review and Extension of the Immunoseasonal Theory

The impact of weather on mental illness is widely debated, but the mechanism of this relationship remains unclear. The immunoseasonal theory suggests that in winter, a T-helper 1 (Th1) response predominates, impairing Prefrontal Cortex (PFC) control, which exacerbates symptoms of depression, while after it, in summer, a Th2 response predominates in immunologically prone individuals, activating cortical and mesolimbic centers, which can exacerbate symptoms of psychosis. In this paper, we aim to describe the validity of this theory through a narrative review of data related to weather and immunology in psychiatry. This review extends existing literature by integrating immunological findings with psychiatric seasonality research, offering a mechanistic perspective that links Th1/Th2 shifts to specific symptom exacerbations. Winter Th1 severity may worsen depression and anxiety, while summer Th2 dominance appears to be associated with exacerbations of schizophrenia, mania, impulsivity, and suicide risk. It is possible that the mechanism of Th1 response potentiation and deterioration of PFC function is common to most psychiatric entities and is nonspecific. This suggests that seasonal immune dysregulation may play a broader role in psychiatric disorders than previously recognized, challenging the idea that seasonality impacts only selected conditions. Characteristic dysfunctions within an individual determine further differences in clinical manifestations. The mechanism of Th2 potentiation may not be limited to mania and psychosis but may also be associated with increased impulsivity and suicide risk. If the immunoseasonal theory is confirmed, selected immunological markers could be used not only in the diagnosis of psychiatric exacerbations but also in predicting symptom fluctuations and tailoring treatment strategies. This could enable more personalized interventions, such as seasonally adjusted medication dosing or targeted anti-inflammatory therapies. While this mechanism seems plausible, further research, especially analyzing markers of inflammatory and anti-inflammatory responses, is needed to better understand and confirm it.

A secondary data analysis investigating the link between weather elements and incident presentation for mental disorders at a Ugandan tertiary psychiatric hospital

The link between weather elements and mental disorders is often described in high-income countries, with hardly any data from low-and middle-income countries where the resources to cope with the negative mental health impacts of climate change are extremely constrained. In this paper, we examined the association between weather elements and the incident presentation with a mental disorder at Butabika National Referral Mental Hospital. We used secondary data from two datasets: i) a mental health data set collated from all patients presenting at Butabika National Referral Mental Hospital in 2019; and ii) a climatic dataset for the geographic location of Butabika National Referral Mental Hospital for the same year (2019). The mental health data set included socio-demographic variables and mental disorder diagnoses, while the climatic data set included data on, atmospheric pressure (hPa), rainfall (mm), sunshine (hours/month), humidity (%), temperature (°C) and wind speed (m/s). We performed descriptive statistical analyses to summarize the frequency of mental disorder diagnoses and the monthly averages of weather variables. We then undertook correlation and multiple logistic regression analyses to investigate the associations between specific weather elements and the incident presentation of different mental disorders. In the mental health data, we had 2,827 participants, males were 56.1%(n=1,584), and the median age was 29 years (IQR 23-38). Psychotic disorders were the most common diagnosis at 43.8% (n=1,239). Overall, various weather elements correlated at different strengths with incident presentation of various mental disorders, particularly humidity and rainfall. On controlling for age and sex in the multiple regression models, the strongest associations were between heat elements and incident presentation for psychotic disorders [AOR1.12, 95%CI (1.04; 1.27) p<0.001]. No associations were demonstrated between weather elements and incident presentation for neurocognitive and neurodevelopmental disorders. These preliminary findings point to a possible relationship between incident presentation of mental disorders to a tertiary psychiatric hospital in Uganda and various weather elements. There is need for longitudinal studies to confirm these associations and to explore underlying social and biological mechanisms.

How does the macroenvironment influence brain and behaviour-a review of current status and future perspectives

The environment influences brain and mental health, both detrimentally and beneficially. Existing research has emphasised the individual psychosocial 'microenvironment'. Less attention has been paid to 'macroenvironmental' challenges, including climate change, pollution, urbanicity, and socioeconomic disparity. Notably, the implications of climate and pollution on brain and mental health have only recently gained prominence. With the advent of large-scale big-data cohorts and an increasingly dense mapping of macroenvironmental parameters, we are now in a position to characterise the relation between macroenvironment, brain, and behaviour across different geographic and cultural locations globally. This review synthesises findings from recent epidemiological and neuroimaging studies, aiming to provide a comprehensive overview of the existing evidence between the macroenvironment and the structure and functions of the brain, with a particular emphasis on its implications for mental illness. We discuss putative underlying mechanisms and address the most common exposures of the macroenvironment. Finally, we identify critical areas for future research to enhance our understanding of the aetiology of mental illness and to inform effective interventions for healthier environments and mental health promotion.

Seasonal variations in psychiatry outpatient service utilization in a tertiary health care center in subtropical arid regions of northwestern India

Background

Research on climatic parameters contributing to psychiatric disorder seasonality is limited, particularly in subtropical, arid climates like Rajasthan, necessitating investigation into seasonal variations in psychiatric disorder incidence in the region. This study investigates seasonal variations in psychiatric disorder prevalence over 2 years at a Rajasthan tertiary healthcare center, aiming to uncover links with climatic factors.

Aims

To investigate seasonal variations in the utilization of outpatient psychiatry services and elucidate potential determinants contributing to these temporal variations.

Settings and Design

This is a hospital-based study. A retrospective chart review of all new patients who utilized psychiatry outpatient services from July 2021 to July 2023 was conducted.

Methods and Material

Data were gathered from psychiatric outpatient records of adults (July 2021 to July 2023), diagnosed using ICD-10. Seasons were categorized: winter (November-January), spring (February-April), summer (May-July), and rainy (August-October). Meteorological data, temperature, and day length were obtained. Statistical analyses, including Pearson correlation and Chi-square fitness, assessed seasonal associations with psychiatric disorders.

Results

A total of 29,164 patient records were observed. Depression correlated with temperature and photoperiod. Mania peaked in August, linked to day length. Schizophrenia showed seasonal variation without environmental correlation. Anxiety peaked in March with no statistical significance. Obsessive compulsive disorder cases spiked in June, moderately correlated with temperature and photoperiod. Alcohol-related disorders peaked in December, while opioid dependence remained steady. Cannabis-induced psychosis peaked in summer, strongly correlated with temperature and day length. Headaches surged in August, positively correlated with temperature and day length.

Conclusions

This study reveals complex relationships between seasonality, environmental factors, and psychiatric disorders, emphasizing their importance in mental health research and practice.

Immediate and delayed effects of environmental temperature on schizophrenia admissions in Liuzhou, China, 2013-2020: a time series analysis

This study aimed to investigate the associations between environmental temperature and schizophrenia admissions in Liuzhou, China. A Poisson generalized linear model combined with a distributed lag nonlinear model was used to analyze the effects of daily mean temperature on schizophrenia admissions from 2013 to 2020 in Liuzhou. Additionally, subgroup analyses were conducted to investigate possible modifications stratified by gender, marital status, and age. In this study, 10,420 schizophrenia admissions were included. The relative risks of schizophrenia admissions increased as the temperature rose, and the lag effects of high temperature on schizophrenia admissions were observed when the daily mean temperature reached 21.65°C. The largest single effect was observed at lag0, while the largest cumulative effect was observed at lag6. The single effects of high temperatures on schizophrenia admissions were statistically significant in both males and females, but the cumulative effects were statistically significant only in males, with the greatest effect at lag0-7. The single effect of high temperatures on admissions for unmarried schizophrenics was greatest at lag5, while the maximum cumulative effect for unmarried schizophrenia was observed at lag0-7. The single effects of high temperatures on schizophrenia admissions were observed in those aged 0-20, 21-40, and 41-60. The cumulative effects for schizophrenics aged 21-40 were observed from lag0-3 to lag0-7, with the maximum effect at lag0-7. In conclusion, the risk of schizophrenia admissions increased as the environmental temperature increased. The schizophrenics who were unmarried appeared to be more vulnerable to the single and cumulative effects of high temperature.

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

BACKGROUND

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

How does the macroenvironment influence brain and behaviour - a review of current status and future perspectives

The environment influences mental health, both detrimentally and beneficially. Current research has emphasized the individual psychosocial 'microenvironment'. Less attention has been paid to 'macro-environmental' challenges including climate change, pollution, urbanicity and socioeconomic disparity. With the advent of large-scale big-data cohorts and an increasingly dense mapping of macroenvironmental parameters, we are now in a position to characterise the relation between macroenvironment, brain, and behaviour across different geographic and cultural locations globally. This review synthesises findings from recent epidemiological and neuroimaging studies, aiming to provide a comprehensive overview of the existing evidence between the macroenvironment and the structure and functions of the brain, with a particular emphasis on its implications for mental illness. We discuss putative underlying mechanisms and address the most common exposures of the macroenvironment. Finally, we identify critical areas for future research to enhance our understanding of the aetiology of mental illness and to inform effective interventions for healthier environments and mental health promotion.

Climate and human health: a review of publication trends in the International Journal of Biometeorology

The climate-health nexus is well documented in the field of biometeorology. Since its inception, Biometeorology has in many ways become the umbrella under which much of this collaborative research has been conducted. Whilst a range of review papers have considered the development of biometeorological research and its coverage in this journal, and a few have reviewed the literature on specific diseases, none have focused on the sub-field of climate and health as a whole. Since its first issue in 1957, the International Journal of Biometeorology has published a total of 2183 papers that broadly consider human health and its relationship with climate. In this review, we identify a total of 180 (8.3%, n = 2183) of these papers that specifically focus on the intersection between meteorological variables and specific, named diagnosable diseases, and explore the publication trends thereof. The number of publications on climate and health in the journal increases considerably since 2011. The largest number of publications on the topic was in 2017 (18) followed by 2021 (17). Of the 180 studies conducted, respiratory diseases accounted for 37.2% of the publications, cardiovascular disease 17%, and cerebrovascular disease 11.1%. The literature on climate and health in the journal is dominated by studies from the global North, with a particular focus on Asia and Europe. Only 2.2% and 8.3% of these studies explore empirical evidence from the African continent and South America respectively. These findings highlight the importance of continued research on climate and human health, especially in low- and lower-middle-income countries, the populations of which are more vulnerable to climate-sensitive illnesses.

Exploring the association between precipitation and hospital admission for mental disorders in Switzerland between 2009 and 2019

While several studies proved the relationship between increasing temperatures and poor mental health, limited evidence exists on the effect of other weather factors, such as precipitation. This study assessed the impact of precipitation on hospital admissions for mental disorders in Switzerland between 2009-2019. We defined different precipitation events based on the duration (daily precipitation ≥1mm for 2, 3, or 4 days; PP.2/PP.3/PP.4) and intensity (≥90th percentile for 2 consecutive days; PEP90.2). First, we conducted aggregated time-stratified case-crossover analysis in eight main Swiss cities with distributed lag models to assess the association up to 3 days after the exposure. Then, we pooled the estimates in each city using a multivariate random effects meta-analysis for all hospital admissions and by subgroups (sex, age, diagnosis). Evidence of an association between precipitation and hospital admission for mental disorders was not found in Switzerland (PP.2: 1.003[0.978-1.029]; PP.3: 1.005[0.985-1.026]; PP.4: 0.994[0.960-1.030]; PEP90.2: 1.000[0.953-1.050]). Although the results were highly uncertain, we found an indication of increasing risks of hospital admission with increasing intensity of precipitation in warmer seasons (PP.2: 1.001[0.971-1.032] vs PEP90.2: 1.014[0.955-1.078]), while the risks of hospital admission slightly increased by the duration in colder season (PP.2: 1.009[0.981-1.039]; PP.3: 1.008[0.980-1.036]; PP.4: 1.017[0.956-1.081]). Overall, risks tend to be higher in people aged < 65 years. Duration of the events may influence more than intensity in females, while opposite patterns were observed in males. Risks tended to be larger but still uncertain for schizophrenia, mood disorders, and adult personality disorders. An indication of a negative association was found in neurotic disorders and null risks in the remaining groups. Although our findings did not show a clear association between precipitation and mental disorders, further research is required to clarify the role of precipitation and the potential implications of climate change and extreme precipitation events on mental health.

Cross-Sectional Associations between Living and Built Environments and Depression Symptoms among Chinese Older Adults

In this study, we explored the cross-sectional associations between living and built environments and depression among older Chinese adults. Data from 5822 participants were obtained. Depression symptoms were evaluated through the use of the Patient Health Questionnaire (PHQ-9), with a score higher than 4 categorized as having depression symptoms. The living environment was assessed by asking about dust in the environment and barrier-free facilities. We considered the presence of amenities within a 10 min walking distance and the proportion of green space within an 800 m distance from participants’ dwellings to reflect the built environment. Data were analyzed by multilevel logistic regression. Participants living in a non-dusty environment with proximity to green space had a lower risk of depression (non-dusty environment: OR = 0.784, 95% CI = 0.642, 0.956; green space: OR = 0.834, 95% CI = 0.697, 0.998). However, having no access to barrier-free facilities and hospital proximity increased the depression risk (barrier-free facilities: OR = 1.253, 95% CI = 1.078, 1.457; hospital: OR = 1.318, 95% CI = 1.104, 1.574). Dusty environments, access to barrier-free facilities and proximity to hospitals and green spaces were associated with depression symptoms among older Chinese adults.

Effect of meteorological factors and lunar phases on occurrence of psychogenic nonepileptic seizures

BACKGROUND

Psychogenicnonepilepticseizures (PNES) lack the abnormal electrographical discharges in electroencephalogram seen in epileptic seizures. The notion of the effects of meteorological factors and lunar phases onoccurrence of seizures in patients with PNES has been the subject of very few research studies and the available evidence in the literature is equivocal. In this study, we aimed to study the influence oflunarphases and meteorological factors on the frequency of PNES and its semiological categories.

METHODS

We retrospectively reviewed the medical records of patients discharged with a diagnosis of PNES from our epilepsy monitoring unit in a 3-year period. The 119 patients who met the inclusion criteria were categorized into hypermotor, hypomotor, or intact sensorium based on semiology of their seizures. The occurrence of PNES, in total and in each semiological category, was correlated with the daily average temperature, atmospheric pressure, and the 4 lunar phases.

RESULTS

There were 31.8% and 11.1% more-than-expected captured seizures when the average daily atmospheric pressure was lower or higher, respectively, of what is generally considered a comfortable atmospheric pressure. No consistent relation was found between the full moon phases and occurrence of PNES.

CONCLUSION

A significant association between atmospheric pressure and the occurrence of nonepileptic seizures was found, whereas no consistent increase in PNES was observed during the full moon phases. There is still an open debate about the effect of the lunar phases on human behavior and neurological disorders such as PNES.

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.

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.

The effect of air-pollution and weather exposure on mortality and hospital admission and implications for further research: A systematic scoping review

BACKGROUND

Air-pollution and weather exposure beyond certain thresholds have serious effects on public health. Yet, there is lack of information on wider aspects including the role of some effect modifiers and the interaction between air-pollution and weather. This article aims at a comprehensive review and narrative summary of literature on the association of air-pollution and weather with mortality and hospital admissions; and to highlight literature gaps that require further research.

METHODS

We conducted a scoping literature review. The search on two databases (PubMed and Web-of-Science) from 2012 to 2020 using three conceptual categories of "environmental factors", "health outcomes", and "Geographical region" revealed a total of 951 records. The narrative synthesis included all original studies with time-series, cohort, or case cross-over design; with ambient air-pollution and/or weather exposure; and mortality and/or hospital admission outcomes.

RESULTS

The final review included 112 articles from which 70 involved mortality, 30 hospital admission, and 12 studies included both outcomes. Air-pollution was shown to act consistently as risk factor for all-causes, cardiovascular, respiratory, cerebrovascular and cancer mortality and hospital admissions. Hot and cold temperature was a risk factor for wide range of cardiovascular, respiratory, and psychiatric illness; yet, in few studies, the increase in temperature reduced the risk of hospital admissions for pulmonary embolism, angina pectoris, chest, and ischemic heart diseases. The role of effect modification in the included studies was investigated in terms of gender, age, and season but not in terms of ethnicity.

CONCLUSION

Air-pollution and weather exposure beyond certain thresholds affect human health negatively. Effect modification of important socio-demographics such as ethnicity and the interaction between air-pollution and weather is often missed in the literature. Our findings highlight the need of further research in the area of health behaviour and mortality in relation to air-pollution and weather, to guide effective environmental health precautionary measures planning.

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.

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.