Temporal trends of the association between temperature variation and hospitalizations for schizophrenia in Hefei, China from 2005 to 2019: a time-varying distribution lag nonlinear model

Climate change and disorders of the nervous system

Anthropogenic climate change is affecting people's health, including those with neurological and psychiatric diseases. Currently, making inferences about the effect of climate change on neurological and psychiatric diseases is challenging because of an overall sparsity of data, differing study methods, paucity of detail regarding disease subtypes, little consideration of the effect of individual and population genetics, and widely differing geographical locations with the potential for regional influences. However, evidence suggests that the incidence, prevalence, and severity of many nervous system conditions (eg, stroke, neurological infections, and some mental health disorders) can be affected by climate change. The data show broad and complex adverse effects, especially of temperature extremes to which people are unaccustomed and wide diurnal temperature fluctuations. Protective measures might be possible through local forecasting. Few studies project the future effects of climate change on brain health, hindering policy developments. Robust studies on the threats from changing climate for people who have, or are at risk of developing, disorders of the nervous system are urgently needed.

The relationship between hot temperatures and hospital admissions for psychosis in adults diagnosed with schizophrenia: A case-crossover study in Quebec, Canada

INTRODUCTION

Some studies have found hot temperatures to be associated with exacerbations of schizophrenia, namely psychoses. As climate changes faster in Northern countries, our understanding of the association between temperature and hospital admissions (HA) for psychosis needs to be deepened.

OBJECTIVES

1) Among adults diagnosed with schizophrenia, measure the relationship between mean temperatures and HAs for psychosis during summer. 2) Determine the influence of individual and ecological characteristics on this relationship.

METHODS

A cohort of adults diagnosed with schizophrenia (n = 30,649) was assembled using Quebec's Integrated Chronic Disease Surveillance System (QICDSS). The follow-up spanned summers from 2001 to 2019, using hospital data from the QICDSS and meteorological data from the National Aeronautics and Space Administration's (NASA) Daymet database. In four geographic regions of the province of Quebec, a conditional logistic regression was used for the case-crossover analysis of the relationship between mean temperatures (at lags up to 6 days) and HAs for psychosis using a distributed lag non-linear model (DLNM). The analyses were adjusted for relative humidity, stratified according to individual (age, sex, and comorbidities) and ecological (material and social deprivation index and exposure to green space) factors, and then pooled through a meta-regression.

RESULTS

The statistical analyses revealed a statistically significant increase in HAs three days (lag 3) after elevated mean temperatures corresponding to the 90th percentile relative to a minimum morbidity temperature (MMT) (OR 1.040; 95% CI 1.008-1.074), while the cumulative effect over six days was not statistically significant (OR 1.052; 95% IC 0.993-1.114). Stratified analyses revealed non statistically significant gradients of increasing HAs relative to increasing material deprivation and decreasing green space levels.

CONCLUSIONS

The statistical analyses conducted in this project showed the pattern of admissions for psychosis after hot days. This finding could be useful to better plan health services in a rapidly changing climate.

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.

Sunshine duration and risks of schizophrenia hospitalizations in main urban area: Do built environments modify the association?

BACKGROUND

Although studies have explored the relationship between sunshine duration and schizophrenia, the evidence was ambiguous. Different built environments may alter the effect of sunlight on schizophrenia, thus the purpose of this study was to investigate the effects of built environments on the sunshine duration-schizophrenia association.

MATERIALS AND METHODS

Daily schizophrenia hospitalizations data during 2017-2020 in Hefei's main urban area, China, and corresponding meteorological factors as well as ambient pollutants were collected. The impact of sunshine duration on schizophrenia admissions in urban areas was investigated using a generalized additive model combined with a distributed lagged nonlinear model. Additionally, the various modifying effects of different Building Density, Building Height, Normalized Vegetation Index, and Nighttime Light were also explored between sunshine duration and schizophrenia.

RESULTS

We observed that inadequate sunshine duration (<5.3 h) was associated with an increase in schizophrenia hospital admissions, with a maximum relative risk of 1.382 (95 % confidence interval (CI): 1.069-1.786) at 2.9 h. In turn, adequate sunshine duration reduced the risk of schizophrenia hospitalizations. Subgroup analyses indicated females and old patients were particularly vulnerable. In the case of insufficient sunshine duration, significant positive effects were noticed on schizophrenia risk at High-Building Density and High-Nighttime Light. Higher NDVI as well as Building Height were found to be associated with lower risks of schizophrenia.

CONCLUSIONS

Given that sunshine duration in various built environments might lead to distinct effects on schizophrenia hospitalizations. Our findings assist in identifying vulnerable populations that reside in particular areas, thus suggesting policymakers provide advice to mitigate the onset of schizophrenia by allocating healthcare resources rationally and avoiding adverse exposures to vulnerable populations timely.

A Systematic Literature Review of the Impact of Climate Change on the Global Demand for Psychiatric Services

Climate Change (CC) imposes important global health risks, including on mental health (MH). They are related mostly to psychological suffering caused by climate-related events and to the heat-vulnerability caused by psychiatric disorders. This growing burden may press MH services worldwide, increasing demand on public and private systems in low-, middle-, and high-income countries. According to PRISMA, two independent reviewers searched four databases for papers published before May 2022 that associated climate-related events with healthcare demand for psychiatric conditions. Of the 7432 papers retrieved, we included 105. Only 29 were carried out in low- and middle-income countries. Twelve related the admission numbers to (i) extreme events, while 93 to (ii) meteorological factors-mostly heat. Emergency visits and hospitalizations were significantly higher during hot periods for MH disorders, especially until lag 5-7. Extreme events also caused more consultations. Suicide (completed or attempted), substance misuse, schizophrenia, mood, organic and neurotic disorders, and mortality were strongly affected by CC. This high healthcare demand is evidence of the burden patients may undergo. In addition, public and private services may face a shortage of financial and human resources. Finally, the increased use of healthcare facilities, in turn, intensifies greenhouse gas emissions, representing a self-enforcing cycle for CC. Further research is needed to better clarify how extreme events affect MH services and, in addition, if services in low- and middle-income countries are more intensely demanded by CC, as compared to richer countries.

Short-term effects of extreme meteorological factors on daily outpatient visits for anxiety in Suzhou, Anhui Province, China: a time series study

Anxiety disorders are a major public health concern in China. Previous studies have provided evidence for associations between ambient temperature and anxiety outpatient visits, but no studies have examined short-term effects of other meteorological factors such as sunshine duration, wind speed, and precipitation on increased anxiety outpatient visits. We aimed to assess the association between climatic factors and outpatient visits for anxiety in Suzhou, a city with a temperate climate in Anhui Province, China. Daily anxiety outpatient visits, meteorological factors, and air pollutants from 2017 to 2019 were collected. A quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) was used to quantify the effects of extreme meteorological factors (sunshine duration, wind speed, and precipitation) on anxiety outpatient visits. All effects were presented as relative risk (RR), with the 90th and 10th percentiles of meteorological factors compared to the median. Subgroup analyses by age and gender were performed to identify susceptible subgroups. A total of 11,323 anxiety outpatient visits were reported. Extremely low sunshine duration and low and high wind speed increased the risk of anxiety outpatient visits. The strongest cumulative effects occurred at lag 0-14 days, and the corresponding RRs of extremely low sunshine duration and low and high wind speed were 1.417 (95% CI: 1.056-1.901), 1.529 (95% CI: 1.028-2.275), and 1.396 (95% CI: 1.007-1.935), respectively. Subgroup analyses showed that males and people aged ≥45 years appeared to be more susceptible to the cumulative effects of extremely low sunshine duration. In addition, the adverse effects of extreme wind speed were more pronounced in the cold season. This study provides evidence that extreme climatic factors have a lagged effect on anxiety outpatient visits. In the context of climate change, these findings may help develop weather-based early warning systems to minimize the effects of extreme meteorological factors on anxiety.

Association Between Air Pollutants and Pediatric Respiratory Outpatient Visits in Zhoushan, China

Objective

This study aimed to explore the time-series relationship between air pollutants and the number of children's respiratory outpatient visits in coastal cities.

Methods

We used time series analysis to investigate the association between air pollution levels and pediatric respiratory outpatient visits in Zhoushan city, China. The population was selected from children aged 0–18 who had been in pediatric respiratory clinics for eight consecutive years from 2014 to 2020. After describing the population and weather characteristics, a lag model was used to explore the relationship between outpatient visits and air pollution.

Results

We recorded annual outpatient visits for different respiratory diseases in children. The best synergy lag model found a 10 μg/m³ increase in PM_2.5 for every 4–10% increase in the number of pediatric respiratory outpatient visits (P < 0.05). The cumulative effect of an increase in the number of daily pediatric respiratory clinics with a lag of 1–7 days was the best model.

Conclusions

PM_2.5 is significantly related to the number of respiratory outpatient visits of children, which can aid in formulating policies for health resource allocation and health risk assessment strategies.