Seasonal variations in psychiatry outpatient service utilization in a tertiary health care center in subtropical arid regions of northwestern India
Department of Psychiatry, Jawahar Lal Nehru Medical College, Ajmer, Rajasthan, India
Department of Psychiatry, Mahatma Gandhi Medical College, Jaipur, Rajasthan, India
Address for correspondence: Dr. Parth S. Meena, P-2, Department of Psychiatry, JLN Medical College, Ajmer, Rajasthan, India. E-mail: parthaiims@gmail.comAbstract
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.
INTRODUCTION
Photoperiod (the length of daylight in 24 hours), a significant factor influenced by latitude, along with other environmental factors like temperature and ultraviolet (UV) radiation, played a crucial role in shaping the evolutionary history of circadian regulatory genes. This perturbation of the circadian clock system is associated with risk variants for neuropsychiatric conditions, including schizophrenia, bipolar affective disorder (BAD), depression, and seasonal affective disorder.[1] Seasonal variations have been consistently observed in various aspects of human behavior, including sleep patterns,[2] appetite,[3] body weight, and suicide rates.[4] As a result, significant interest has emerged in the scientific community regarding research on behavioral changes linked to seasonal transitions.[5]
It has been observed that the prevalence of psychiatric disorders, such as seasonal affective disorder (SAD), major depression, schizophrenia, and suicide attempts, increases with higher latitudes.[56789] Additionally, there is an association between the seasonality of depressive symptoms and high-latitude regions, as compared to countries situated closer to the equator. Humans display a remarkable sensitivity to light, even at low intensities, particularly during twilight transitions.[10]
Season-related social factors and stressors, such as work schedule, school schedules, and holidays, can impact symptoms; however, current scientific literature suggests that biological processes play a substantial role in the observed seasonality. The adjustment of circadian rhythms in neuroendocrine function[11] during different seasons has been found to have a significant impact on endocrine functions (including gonadal hormones), hippocampal functions, cognition, and behavior, all of which also exhibit seasonal variation.[12] Nevertheless, the specific mechanisms through which biological adaptations influence seasonal patterns in mood and behavior as well as the reasons why some individuals experience more significant seasonality than others with adverse effects on their daily life and functioning remain unknown.[10]
Climatic parameters, such as daily ambient temperature, relative humidity, atmospheric pressure, rainfall, and hours of sunshine, have been found to contribute to seasonal variations in admission rate of psychiatric disorders.[13] However, research conducted in regions outside the temperate zones of the northern and southern hemispheres is scarce.
Most of these studies have been conducted in countries with temperate climates, which may not accurately represent the climatic conditions of India. A few studies from southern India have investigated the seasonal pattern of hospital admission rates and hospital service utilization among psychiatric patients.[1415] However, there has been a dearth of such studies in the context of subtropical, arid climates with significant temperature variations, as found in Northwest India.[16] This study seeks to uncover seasonal variations in the incidence of various psychiatric disorders, including substance abuse disorders, in the northwestern region of the country. The aim of the current study was to estimate seasonal variations in the occurrence of various psychiatric disorders, identify seasonal peaks associated with different psychiatric disorders, and ascertain the causes of these seasonal peaks.
SUBJECTS AND METHODS
The study was conducted at the Department of Psychiatry of a state-run medical college in Rajasthan after obtaining approval from the Institutional Ethics Committee vide letter no. 2875/acad/mca/2023. This tertiary care health center caters to the healthcare needs of four districts of Rajasthan, with a total population of approximately 1 crore (97.22 lakh as per census 2011). The estimated male-to-female ratio for the population was 1.148:1.[16] Mental health care facilities are scarce in the region; consequently, this center becomes the primary destination for individuals seeking treatment. Patients are first evaluated by residents and then referred to a consultant psychiatrist to confirm the diagnosis. All diagnoses are made according to the International Classification of Diseases-10 (ICD-10). Demographic and clinical information of the patients is meticulously recorded and maintained. A retrospective chart review of all new patients who utilized psychiatry outpatient services from July 2021 to June 2023 was conducted.
Data from all patients above 18 years of age were extracted. Patient data were first categorized according to the months of the year and then according to the diagnoses. Although the data were grouped together on a monthly basis, we categorized the seasons as winter (November to January), spring (February to April), summer (May to July), and rainy/monsoon (August to October). Meteorological measurements, namely, day length (photoperiod) and temperature, were obtained from www.weatherspark.com and the meteorological department, with Ajmer as the epicenter. In this study, we included data from patients who were diagnosed and treated for the following psychiatric disorders: depression, mania, schizophrenia, acute and transient psychotic disorder (ATPD), obsessive compulsive disorder (OCD), anxiety disorders, headaches, and substance-related disorders. Patients above age of 18 years who visited the outpatient department (OPD) for the first time were included in the study. Cases with only one primary diagnosis (according to ICD-10) were included to avoid confounding factors and for simplicity. Patients suffering with significant neurological conditions like dementia and severe head injury were excluded from the study.
Only new cases were included in the study. Our department maintains separate entries for new cases and follow-up cases. If the same patient visited multiple times during the study period, he would be recruited only once as a new case, and on subsequent visits, he would be registered as a follow-up case. Hence, the error of a spuriously high rate was eliminated.
Statistical analysis: We used Statistical Package for the Social Sciences (SPSS) version 25, IBM Inc., USA, to analyze the data. Pearson correlation was used to find associations between continuous variables, which included seasonal factors like temperature (measured in degree Celsius) and day length (measured in hours) and incidence of specific disorders. Chi-square fitness of good test was used to find significance of difference in monthly variation in OPD visits by patients. A P value of ≤0.05 was considered significant for determining the correlation’s significance.
RESULTS
A total of 81,262 patients utilized the OPD over the 2-year study period. Among these, 35,009 were new patients. A total of 13,449 patients were excluded from the study, with 10,822 being excluded due to having multiple diagnoses and 2627 excluded due to comorbid neurological illnesses. In this retrospective chart review, a total of 21,560 patient records were included. Of these, 63.7% (n = 13,713) were male, with the remaining being female. The demographic profile of patients is given in Table 1. The monthly variation in the occurrence of psychiatric disorders is illustrated in Figure 1, while the average monthly photoperiod and temperature are shown in Figures 2 and 3, respectively.
| Diagnosis | Total Patients (n, %) | Males (n, %) | Females (n, %) | Mean age in years | ||||
|---|---|---|---|---|---|---|---|---|
| BAD | 4048 (18.8%) | 2574 (63.59%) | 1474 (36.41%) | 44.61 (±7.23) | ||||
| ATPD | 752 (3.5%) | 423 (56.25%) | 329 (43.75%) | 30 (±6.52) | ||||
| ANXIETY | 2060 (9.6%) | 1255 (60.97%) | 805 (39.03%) | 40.6 (±7.07) | ||||
| OCD | 424 (1.9%) | 294 (69.38%) | 130 (30.62%) | 36.3 (±6.04) | ||||
| SCHIZ | 1836 (8.5%) | 1104 (60.17%) | 732 (39.83%) | 38 (±5.73) | ||||
| DEP | 7276 (33.7%) | 3197 (43.93%) | 4079 (56.07%) | 40.77 (±8.32) | ||||
| ADS | 2832 (13.1%) | 2514 (88.80%) | 318 (11.20%) | 40.08 (±8.91) | ||||
| ODS | 2080 (9.6%) | 2035 (97.81%) | 45 (2.19%) | 37.46 (±9.63) | ||||
| CANNABIS | 252 (1.1%) | 217 (86.20%) | 35 (13.80%) | 44.4 (±7.19) |
The highest number of patients had depression, totaling 7276 (33.7%). The maximum number of patients with depression visited the outpatient department in July (n = 804, 11%), while the lowest number was in January (n = 432, 5.9%). The data indicate that the highest number of patients with depression visited the OPD during the summer months of May, June, and July (n = 2,116, 29.1%). In contrast, during the winter months (November, December, and January), the number of patients (n = 1,656, 22.7%) was at its lowest. The incidence of depression was found to be positively correlated with both temperature (r = 0.43, P = 0.76) and day length (photoperiod) (r = 0.54, P = 0.038).
According to the data, the number of patients presenting with mania (bipolar affective disorder, current episode mania) was 4048 (18.8%). The maximum number of such patients presented in August (460, 11.3%), followed by July (420, 10.4%) and March (400, 9.8%), while the minimum was in November (200, 4.9%). The incidence of mania was strongly and positively correlated with day length (r = 0.61, P = 0.018) but not significantly correlated with temperature (r = 0.4, P = 0.09).
The total number of patients with schizophrenia visiting the hospital was 1836 (8.5%), with the maximum in July (n = 300, 16.33%) and the minimum in January (n = 76, 4.13%). The highest number of patients with schizophrenia occurred during the summer season (n = 568, 30.93%), while in winter (November, December, and January) (n = 372, 20.26%) and autumn (n = 364, 19.8%), the opposite condition was observed. In contrast, no overall seasonal variation was found with photoperiod (r = 0.29, P = 0.19) and temperature (r = 0.12, P = 0.35).
The number of patients receiving the diagnosis of ATPD was 752 (3.5%), with the maximum number of patients visiting in December (n = 104, 13.8%) and the minimum number of patients visiting in January (n = 40, 5.3%). No correlation was observed between the incidence of ATPD and temperature and photoperiod (r = -0.24, P = 0.22 and r = -0.14, P = 0.34).
Approximately 2060 (9.6%) patients were diagnosed with anxiety disorder, with the maximum number of patients visiting the hospital in March (n = 236, 11.6%) and the minimum visiting in November (n = 96, 4.72%). Although the general trend indicates an increase in anxiety disorders in winters, the difference was not statistically significant (r = 0.3, P = 0.12).
Among the primary diagnostic entities, the least number of cases were of OCD, with a total of 424 (1.9%) patients, and the maximum number of patients visited in June (n = 60, 14.15%) and the minimum number of patients visited in November (n = 20, 4.7%). The incidence of OCD was moderately correlated with temperature and photoperiod, but it was not found to be statistically significant.
In substance abuse disorder, a total of 5164 (24%) consultations were taken. The most abused substance was alcohol, with a total of 2832 (13.1%) patients. The maximum visitations were for alcohol dependence (ADS) in December (n = 368, 7.12%) and the minimum in July (n = 88, 1.70%). Although the number of patients with alcohol-related disorders was higher in the winter season (n = 756, 14.63%) than in summers (636, 12.31%), no significant seasonal variation was observed.
The second most common diagnosis among substance use disorders was opioid dependence (ODS), with a total of 2080 (9.6%) patients. The maximum number of such patients visited in April (n = 268, 12.88%), and the minimum in January (n = 116, 5.5%). No significant seasonal association was found between the incidence of opium-related disorders and temperature or day length (r = 0.37, P = 0.23 and r = 0.46, P = 0.13).
The incidence of cannabis-induced psychosis and other cannabis-related disorders was 252 (1.1%); maximum cases were reported in the months of April and July (60, 23.8%) each month. The total number of patients in summers was higher (n = 140, 55.55%), although the month of June showed a sharp dip (n = 20, 7.9%) in incidence rate. The incidence rate was strongly correlated with day length (r = 0.72, P = 0.01) and temperature (r = 0.66, P = 0.02).
A statistically significant variation was observed in the monthly utilization of OPD services, as determined by the Chi-square goodness-of-fit test.
DISCUSSION
This study represents one of the very few, if not the first, attempts to describe the seasonal patterns of major psychiatric illnesses, including depression, manic episodes, anxiety, OCD, headaches, and substance-related disorders in a region having an arid and dry climate with scorching summers and cold winters. Despite being a retrospective chart review, it is quite reliable due to the substantial dataset, meticulous record-keeping, and the fact that the diagnoses were made in accordance with the ICD-10.
In case of depression, the study reported the maximum OPD attendance in July and the lowest in January. Notably, the data showed a clear seasonal pattern, with the highest number of depressive cases occurring during the summer months of May, June, and July when both the average temperature and daylight hours reached their maximum. Conversely, during the winter months of November, December, and January, patient numbers dropped to their lowest levels. It is worth highlighting that depression demonstrated a positive correlation with both temperature and photoperiod. The results contradicted prior research documenting elevated rates of depression during winter months. A systematic literature review encompassing 2121 studies revealed a higher prevalence of depression during winter periods characterized by reduced daylight.[17] Many such investigations[791018] were conducted in Nordic regions or areas situated at higher latitudes, characterized by harsh winter conditions typified by extreme cold temperatures and shortened daylight hours. Rosen et al.[5] observed significantly higher rates of winter seasonal affective disorder (SAD) and subsyndromal SAD at more northern latitudes, with no discernible correlation between latitude and summer SAD. Conversely, a large-scale population study in the United States failed to identify any association between duration of sun exposure and depression prevalence.[19] Avasthi et al.’s[20] study in North India revealed a pronounced peak in depressive episodes of SAD during the summer months, particularly in May, June, and April, followed by occurrences in winter and monsoon seasons. Nonseasonal depression exhibited prevalence peaks in December and January.
We postulate that the increased incidence of depression during summer in northwest India may be attributed to elevated ambient temperatures, heatwaves, and high humidity. A systematic review and meta-analysis by Liu et al.[21] documented a positive correlation between heightened ambient temperatures and/or heatwaves and adverse mental health outcomes, including depression.
When examining cases of mania in the OPD, a distinct seasonal pattern emerged. The study observed a significant peak in mania cases during the months of June, July, and August. This peak coincided with the onset of the monsoon season, characterized by hot and humid weather, as well as the period of maximum average monthly temperature and daylight hours. Intriguingly, mania displayed a strong and positive correlation with day length.
These findings suggest that seasonal variations in temperature and daylight hours may play a significant role in the occurrence and exacerbation of mood disorders like depression and mania. Further research is needed to delve deeper into the mechanisms underlying these patterns and to explore potential implications for treatment and management strategies.
In the context of bipolar mania, a Dutch revealed an intriguing peak of depressive episodes during the summer months.[22] Symonds and Williams noted a distinct surge in manic episodes occurring primarily in August.[23] Furthermore, a comprehensive analysis, comprising 197 papers conducted by Wang B and Chen D, unveiled seasonal patterns in manic episodes for many individuals with bipolar disorder, with peaks occurring during the spring or summer.[24] In a systematic review of 51 studies, Geoffroy et al.[25] concluded that manic episodes peaked in spring and summer, followed by autumn; depressive episodes peaked in early winter and were less frequent in summer. Avasthi et al.[20] identified the highest incidence of manic episodes during the monsoon season, followed by winter. Peak incidence of mood disorders was observed from May to July in a study by Singh GP et al.[26] Another Indian study by Srivastava and Sharma[27] suggested that summer depression holds significant clinical relevance. Moreover, investigations by Rosenthal et al.[28] and Wehr et al.[29] suggest a correlation between the incidence of summer depression and factors such as decreasing latitude and increasing temperature.
The findings suggest that mood disorders may be influenced by a complex interplay of factors beyond just photoperiod or light deficiency. The heat period could also serve as a triggering factor, and socioeconomic conditions associated with monsoon seasons may play a significant role in precipitating mood disorders. Economic consequences of weather events, such as heavy rains or droughts, are crucial considerations as they can lead to financial strain and stress. Additionally, the combination of hot weather, humidity, and reduced sunlight exposure can contribute to mood problems. This complex relationship between environmental factors and socioeconomic conditions highlights the need for further study to fully understand the influences on mood disorders.[30]
In case of schizophrenia, the highest patient count occurred in July, while the lowest was in January. More patients utilized OPD services in spring and summers as compared to the winter and autumn, reflecting different conditions. Interestingly, there was no significant seasonal variation observed in relation to photoperiod or temperature. The assessment of seasonality in schizophrenia is limited compared to affective disorders. In the northern hemisphere, a nationwide analysis of hospital admissions revealed peaks in hospitalizations for schizophrenia in January and June, with a trough in December.[31] In China, a study found a relationship between reduced exposure to sunlight and an increased risk of hospital admissions for schizophrenia, particularly among females and middle-aged to elderly individuals.[32] Another study in China conducted by Shiloh et al.[18] reported a significantly higher admission rate of patients with schizophrenia during the summer.
Additionally, studies by Davies et al.[33] and Owens et al.[34] indicated that schizophrenia is more likely to occur during winter in the southern hemisphere. It is suggested that extreme temperatures and inadequate exposure to sunlight may contribute to dysfunction in serotonin and dopamine systems and disrupt circadian rhythms, leading to acute psychotic episodes in schizophrenia.[832] In a critical review, Jahan S et al.[35] observed a peak of schizophrenia admission in both summer and winter but found strong positive relation between high temperature and temperature variation and hospital admission, which is similar to the present study. Nationwide registry in Austria between 2003 and 2016 found most schizophrenic patients in January and June and minimum in December.[31] In contrary, a Chinese study done by Yao Y et al.[36] in February 2023 observed a schizophrenic peak in winter and trough in spring, while an Iranian study showed positive relation between foggy, rainy days with decreased sunlight and schizophrenia.[37] Our study could not relate strongly the increased incidence of schizophrenia with any specific season.
The diagnosis of acute and transient psychotic disorders (ATPDs) saw the highest number of patients in December, with the lowest number recorded in January. However, no correlation was found between the incidence of ATPD and temperature or photoperiod.
The highest number of patients with anxiety disorders visited the OPD in March. In contrast, the lowest attendance was recorded in November, with just 12 patients. While the general trend suggests an increase in anxiety disorders during the winter months, this difference did not reach statistical significance. Interestingly, a study by Zhang et al. in 2021,[38] analyzing data from US and Sweden health registers, found that anxiety disorders were least prevalent in the summer. Similarly, a Dutch study indicated that panic disorder and generalized anxiety disorder were more common in the winter.[22] Conversely, a study by Lepine et al.[39] in 1991 reported an increased prevalence of anxiety disorders in the summer. According to an Indian study by Singh GP et al.,[26] the maximum number of patients with neurotic stress-related and somatoform disorders came in July to September.
Among the disorders included in the study, prevalence of OCD was the least common. Increased OPD visits were recorded in the month of June, and it exhibited a moderate correlation with temperature and photoperiod, but it did not reach statistical significance. The survey conducted in the Netherlands found the highest occurrence of OCD in the autumn and the lowest in the summer.[22] However, no significant seasonal differences were observed in substance abuse and schizophrenia cases.
In cases of substance abuse disorder, the most commonly abused substance was alcohol, marking a reversal in the trend. The highest number of visits for alcohol dependence occurred in winters, but overall seasonality was not associated with an increase in alcohol use disorders.
Zhang et al.[38] reported a similar trend, with the highest number of patients seeking treatment for substance abuse in winter and the lowest in summer. Additionally, a study by D.G. Uitenbroek[40] from Scotland identified a peak in alcohol intake in December, which aligns with the findings of this present study. These results are consistent with the findings reported by Ventura-Cots et al.,[41] who observed an inverse correlation between mean average temperature and sunshine hours with per capita alcohol consumption in a global cohort.
The second most common disorder among substance abuse-related disorders was opioid dependence. The number of patients receiving treatment for opioid dependence remained relatively constant throughout all seasons. On the other hand, the incidence of cannabis-induced psychosis and other cannabis-related disorders was higher during the summer, showing a strong correlation with day length and temperature. Researchers like Palamar JJ et al.[42] from New York University have noted that the consistent decrease in marijuana use during the winter months could be due to various factors, such as a lower supply of cannabis during this time, colder weather encouraging people to stay indoors, or individuals quitting marijuana as part of a New Year’s resolution.
Limitations: The study has several limitations. Its retrospective design relies on pre-existing data, potentially introducing bias and limiting the ability to control for confounding variables or establish causality. As a single-center study, the findings may not be generalizable to other regions or healthcare settings. The exclusion of patients with multiple diagnoses or comorbid neurological illnesses could introduce selection bias, narrowing the scope of the results. Other unmeasured variables, such as socioeconomic status, cultural practices, and healthcare access, may also confound the observed patterns. Finally, the use of average monthly temperature and photoperiod simplifies the complex environmental influences, potentially overlooking other relevant factors like humidity, precipitation, and daily weather variations.
Implications and future directions
This study has significant implications. First, it could assist health departments and hospital administrations in optimizing resource allocation and workforce planning by aligning them with seasonal patterns in psychiatric illnesses. Additionally, we can enhance patient care by providing psychoeducation to patients and their family members about potential seasonal variations in psychiatric symptoms and the climatic conditions that might precipitate a particular psychiatric illness.
As climatic and psychosocial conditions vary across different countries and regions, conducting cross-cultural research in the future can illuminate the complex interactions between environmental factors and psychiatric conditions, thereby improving our understanding and treatment of these disorders. In India, which is largely an agrarian society, socioeconomic factors such as agricultural activities and the success of crops, which are closely tied to climatic variations and associated stressors, may also play a role in precipitating mental health problems. Therefore, such socioeconomic factors should be taken into consideration when planning future research.
CONCLUSION
The study sheds light on the intriguing relationship between psychiatric disorders and seasonal patterns, particularly within the unique arid climate with scorching summers and cold winters in northwestern India. The study reports a clear seasonal pattern in depression, with peak cases during the summer months when temperatures and daylight hours are at their highest. Mania, on the other hand, exhibits a peak during the monsoon season, correlating with longer daylight and hot and humid weather. Schizophrenia showed consistent patterns throughout the year, with noticeable peaks in month of July and December. These observations suggest that temperature and daylight duration may influence the occurrence and exacerbation of mood disorders and psychoses. Conditions like ATPD, OCD, and anxiety have lower patient numbers but show a relatively stable pattern across the months. Alcohol dependence syndrome (ADS), other drug use (ODS), and cannabis-related issues appear to have lower and more variable numbers. This variability could indicate less predictability in these conditions or reflect underreporting or underutilization of services. These findings warrant further exploration and may have implications for timely and effective interventions and management strategies.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.