Background
Depression is a common psychiatric disorder worldwide, characterized by sustained grief and a lack of interest or pleasure in activities that were previously beneficial or pleasurable [
1]. As of 2019, approximately 280 million people worldwide are suffering from depression [
2]. Depression has become the leading cause of disability worldwide and is a major contributor to the global burden of disease [
3]. Therefore, it is of great importance to identify depression and the associated risk factors.
As is known to all, the risks for depression are both genetically and environmentally determined [
4]. The risk of depression is partly mediated by genetic factors, accounting for less than 40% [
5]. This suggests that environmental factors play an important role in the onset and development of depression. Some epidemiological evidence has shown that meteorological factors are associated with mental illness [
6]. Scholars have studied the effects of meteorological factors such as sunshine, rainfall, temperature and pressure on the occurrence and admission of depression [
7‐
9]. In particular, with the advancement of climate change, extreme weather events have further increased, and the impact of extreme weather events on mental diseases (such as depression, schizophrenia, bipolar disorder, etc.) has begun to be paid more attention [
10]. Floods and rainstorms are gradually taken into account whether they are associated with depression [
11,
12]. However, studies had found that the relationship between precipitation and depression were inconsistent. Some studies reported that precipitation can increase the risk of depression [
7] or that it was a protective factor for depression [
9]. While others discovered that there were no statistical significance effects between precipitation and depression [
13‐
17]. Furthermore, no studies have investigated the impact of extreme precipitation on depression.
Considering the current state of research on depression, our research has three purposes: First, to explore the relationship between extreme precipitation and outpatient visits for depression. The second is to conduct subgroup analysis according to gender, age and visit types (first visit, multiple visits) to identify susceptible groups. The third is to assess the attributable burden of outpatient visits for depression due to extreme precipitation.
Discussion
In recent years, depression has been increasingly recognized as a major health problem, and climate change may exacerbate the burden of depression [
26]. In this study, we examined the impact of extreme precipitation on outpatient visits for depression. And the results showed that extreme precipitation may increase the risk of depression outpatient visits, with significant effects lasting from lag4 to lag7. We further assessed the burden of depression caused by extreme precipitation and found that the AF and AN were 5.00%(95% CI: 1.02–8.82%)and 1318.25, respectively. Besides, female, cases aged ≥65 years and patients with multiple visits appeared to be more susceptible to extreme precipitation.
There is a clear lack in studies on depression and precipitation, and the results varied across different studies. As early as 1996, studies by Molin et al. showed that rainfall was not associated with the onset of winter depression [
13]. Subsequently, studies in the Netherlands, Canada, North America and Sweden also showed that there was no relationship between rainfall and the occurrence of depression [
14‐
17]. In our study, we suggested that extreme precipitation was associated with increasing outpatient visits for depression, which was similar with the results of Hare et al. [
7] and Abbasi et al. [
27]. But Hare used the linear regression models to estimate the effect of climate on depression, and annual cumulative rainfall index only reflected the long-term impact of rainfall on the occurrence of depression rather than daily effect [
7]. In Abbasi’s study, the author took the rainfall regime and the behavior of rainy seasons into more account rather than precipitation itself [
27]. In 2014, a cohort study of Spanish college graduates using cox regression models to assess the relationship between climatic factors and depression, and found that men who lived in rainy areas had a lower risk of developing depression [
9]. These results were inconsistent with the conclusion of our study, which may be due to the fact that our study focused on the impact of extreme precipitation. In addition, different study areas, study designs and statistical methods may also lead to different conclusions [
28,
29]. In view of the inadequacy and inconsistency of previous studies, further research is necessary to explore the association between extreme precipitation and the outpatient visits for depression.
Previous studies have explored the biological mechanism between environmental exposure (such as air pollution, noise) and depression [
30,
31], and provided epidemiological evidence [
32,
33], but the biological mechanism of extreme precipitation increasing the risk of depression outpatients is still unclear. Our findings suggested that extreme precipitation was associated with increased risk of the outpatient visits for depression. The possible explanation is as follows. Firstly, previous studies had found that environment stresses, such as cold or heat stress, which were caused by extreme weather events, were considered as risk factors for mental illness [
34‐
36]. Secondly, extreme precipitation is accompanied by changes in sunlight and temperature. These changes may cause some mental diseases, which may be associated with the fluctuation of the serotonergic function [
37]. A study has shown that the serotonergic varied inversely with daily temperature [
38]. Furthermore, living in a warmer and sunnier climate may encourage people to go out and exercise more, which had been shown to be a protective factor for depression [
39]. Last but not least, studies have reported the relationship between heat waves and mental disorders (such as depression and post-traumatic stress disorder), and indicated that it may increase the incidence of depression [
26,
40,
41]. It is well known that heat wave is one of the reasons for precipitation, which explains our conclusion to some extent. Although some studies have shown the impact of extreme weather events on mental diseases [
10,
42], further studies are needed to reveal the mechanism of extreme precipitation on depression.
In this subgroup analysis, we observed that females were more susceptible to the effect of extreme precipitation on depression than males, with higher rate of AF and AN. The possible reason was that, different from males, females, who possibly have strong stress responsiveness, often bear multiple care responsibilities for their children, spouses and parents, and have experienced more stressful life events [
43]. These stressors may become risk factors for depression and eventually lead to depression [
44]. And females who experienced pregnancy, breast-feeding, menstrual cycle and the menopausal transition were more likely to be affected by the outside environment and had relatively higher rates of depression [
45]. Besides, people with multiple outpatient visits were more vulnerable to extreme precipitation than those with first outpatient visits. Some scholars had given the possible reason that most patients with depression have seasonal characteristics, and weather factors are one of the predisposing factors of recurrent depression [
46]. Moreover, it indicated that extreme precipitation may have an increased effect for depression in the patients aged ≥19 years. Among them, people over 65 years were more vulnerable to extreme precipitation. This may be because with the increase of age, the physiological and psychological functions of the elderly are gradually getting weaken, especially the sensory organs and nervous systems involved in psychological activities may undergo degenerative changes. The physical resistance of the elderly is low, which is accompanied by a decrease in their ability to adapt to changes in the external environment [
20]. Moreover, the elderly suffer from more chronic diseases, and the distress of these diseases may cause depression in the elderly. Therefore, the elderly were more sensitive to rainfall, which was consistent with previous research [
47].
This study has several advantages. Firstly, to our knowledge, this maybe the first study to explore the association between extreme precipitation and depression by using a time series design. We comprehensively and deeply analyzed the RR, AF and AN with patients of depression caused by extreme precipitation, which provided important reference value for the prevention of depression in the region. Secondly, previous studies had reported that air pollutants may increase the risk of depression outpatient visits. Therefore, we added air pollutants into the model for sensitivity analysis to verify the robustness of the model, and finally showed that our results were robust. Thirdly, we used the DLNM to analyze the lag effect of extreme precipitation on depression, and through subgroup analysis, we found that the sensitive population of depression, suggesting that we should attach importance to susceptible population and protect them.
Nevertheless, some limitations should be taken into consideration in our study. Firstly, since we only selected a single city as the study area, this study may not be extended to other areas, especially those with different climates. Secondly, our meteorological data are derived from meteorological stations and therefore cannot accurately estimate the actual exposure of individuals. Thirdly, in this study, we only examined the short-term effects of extreme precipitation on depression, and future studies should explore this relationship in a longer time scale. Finally, in view of the differences in spatial distribution and obvious seasonality, the distribution of rainfall is abnormal and uneven. Therefore, the cut-off value of rainfall is not easy to obtain. In the future, more accurate and complex models may need to be established to simulate the exposure-response relationship.
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