Local daily temperatures, thermal seasons, and suicide rates in Finland from 1974 to 2010
© The Japanese Society for Hygiene 2014
Received: 15 October 2013
Accepted: 31 March 2014
Published: 3 May 2014
Suicide peaks in late spring and October are still seen in Finland among many countries. Weather factors have been suggested as explanations for these peaks, although with inconsistent results. Since the exact timing of these peaks varies each year, the length of daylight and changes in it seem inadequate as an explanation. We hypothesized that ambient temperature and the timing of thermal seasons might associate with suicide rate.
Suicide rates from three areas across Finland (N = 10,802) were analyzed with Poisson regression in six different models against variables calculated from the local ambient daily temperature, diurnal temperature range, and the duration from the onset of thermal seasons. Separate models for men and women were constructed.
The temperature change over 5 days associated with the suicide rate of men in Helsinki region, or in other words, the lower the suicide rate was, the higher the temperature decrease had been. For women, the results were more inconsistent.
Our study is in line with some earlier studies which imply that impairment of thermoregulation might exist among suicide victims.
In our earlier nationwide study from Finland, suicide rate correlated with monthly mean temperature along with global radiation , and in another Finnish study, the ambient temperature variation was shown to explain even 60 % of the annual suicide variance in extra-long time series from 1751 to 2008 in Finland . Furthermore, the diurnal temperature variation associated with spring peak of suicides in Helsinki metropolitan area . However, contradictive data on the associations between suicide and ambient temperature exist as well [4, 5], and recent studies found inverse associations between annual ambient temperature and suicide rate [6, 7], and a study concerning monthly mean temperature and suicide rate, no association whatsoever . Moreover, the analysis of long series of monthly data on suicide and weather in Switzerland concluded that the association between temperature and suicide is not due to warm temperatures but due to the lack of low temperatures, or in other words, it is not heat but the lack of cold that contributes to this association . However, the comparison of the results between different studies may be problematic since ambient temperature has been analyzed by using different lengths, mostly from 1 month to 1 year. Furthermore, differences between local climates may influence acclimatization, i.e., the physiological as well as psychological adjustment of individuals into local climate changes, and thereby may explain the conflicting results to some extent .
Seasonal peaks in suicide rates exist in Finland among many other countries [11–18]. A smaller peak in suicide rate is seen in October, especially for women [19–21], and the highest mean in the daily suicide rate emerges between May 15 and July 25 in Finland . However, from year to year, the timings of these two peaks seem to vary. The early summer peak fluctuates between April and August, and the autumn peak between August and December.
Therefore, since the change of astronomical seasons, that is the length of day relative to night, follows a regular timetable year after year, we hypothesized that thermal seasons with a varying timetable each year influence the timings of the peaks in suicide rate. We aimed to study whether the daily variability in ambient temperature and thermal seasons associated with suicide rates in three areas and their local climates in Finland during a 37-year-long period.
Materials and methods
Suicides from 1974 to 2010 by sex and study area
Rate per 100,000
95 % CI for the rate
Minimum, mean, and maximum lengths of thermal seasons from 1974 to 2010 by study area
Number of days
Winter T < 0 °C
Spring T = 0° − 10 °C
Summer T > 10 °C
Autumn T = 10° − 0 °C
For the statistical models, altogether 21 explanatory variables were formulated. They were named and numbered as follows: (1) the daily mean temperature T(day 0) at the day of completed suicides, (2) change in the daily mean temperature from the previous day, ∆T 1 = T(day0) − T(day-1), (3) change in the daily mean temperature compared to the daily mean temperature 2 days before, ∆T 2 = T(day0) − T(day-2), (4) change in the daily mean temperature compared to the daily mean temperature 3 days before, ∆T 3 = T(day0) − T(day-3), (5) change in the daily mean temperature compared to the daily mean temperature 4 days before, ∆T 4 = T(day0) − T(day-4), (6) change in the daily mean temperature compared to the daily mean temperature 5 days before, ∆T 5 = T(day0) − T(day-5), (7) the diurnal temperature change at the day of completed suicides ∆T d = T max(day 0) − T min(day 0), (8) thermal seasons as categorical variables, (9) the number of days from the onset of thermal spring, (10) the number of days from the onset of thermal summer, (11) the number of days from the onset of thermal autumn, (12) the number of days from the onset of thermal winter, (13) astronomical seasons as categorical variables, (14) the number of days from the onset of astronomical spring, (15) the number of days from the onset of astronomical summer, (16) the number of days from the onset of astronomical autumn, (17) the number of days from the onset of astronomical winter, (18) the number of days during which astronomical and thermal seasons do not overlap, (19) weekday, (20) the number of days from the onset of each calendar year, and (21) the calendar year from 1974 to 2010 inclusive.
We did not have any socio-economic background variables for the suicide victims. We had the gender and the age of the suicide victims, but the age was not included in the models in order to retain the statistical power. All of the models were constructed in separate for men and women.
Explanatory variables by statistical model
∆T 1 = T(day 0) − T(day-1)
∆T 2 = T(day 0) − T(day-2)
∆T 3 = T(day 0) − T(day-3)
∆T 4 = T(day 0) − T(day-4)
∆T 5 = T(day 0) − T(day-5)
∆T d = T max (day 0) − T min (day 0)
Thermal seasons (spring, summer, autumn, winter)
Number of days (from the onset of thermal spring)
Number of days (from the onset of thermal summer)
Number of days (from the onset of thermal autumn)
Number of days (from the onset of thermal winter)
Astronomical seasons (spring, summer, autumn, winter)
Number of days (from the onset of astronomical spring)
Number of days (from the onset of astronomical summer)
Number of days (from the onset of astronomical autumn)
Number of days (from the onset of astronomical winter)
Mismatch days of astronomical and thermal seasons
Number of days (from the onset of calendar year)
Minimum, mean, and maximum daily mean temperatures from 1974 to 2010 by the astronomic periods (used in the statistical models #5 and #6) and study area
Astronomical spring and summer 21 Mar–21 Sep (model #5)
Astronomical fall and winter 22 Sep–20 Mar (model #6)
The statistical program R, version 2.15.0 , with the packages Epi  and natural spline , was used for the statistical analyses. Natural spline method was applied for all of the variables, except numbers 7, 8, 13, 18, and 19, which were analyzed as categorical variables.
For the interpretation of the chi-square tests, p values of <0.05 were considered as significant. In addition, rate ratio was calculated in order to further visualize the results. Rate ratio (RR) compares rate (risk) among one group with the risk among another group (reference group).
Table 3 shows which explanatory variables were included in the six statistical models that are referred to in the following results.
Suicide rate in relation to the number of days from the onset of calendar year, calendar year, and weekday
The calendar year from 1974 to 2010 associated with the suicide rates in all of the three study areas (data not shown) in all of the six models, except with the rate of women in Oulu, suggesting a simultaneous general trend in the suicide rates in these three areas. In addition, the suicide rate of men in Helsinki associated with the number of days from the onset of each calendar year in the models 1 and 2, yielding the increased rate ratio in spring and early summer (p = 0.02). An association with the day of the week was found for suicide rate of women in Helsinki in the models 1, 2, 5, and 6. Thursdays had the lowest suicide rate by rate ratio of 0.79 (CI 0.68–0.93), (p = 0.003), compared to Sundays, which were chosen as reference.
Suicide rate in relation to temperature variables
Daily mean temperature associated with the suicide rate of men in Helsinki in the models 4 (p = 0.01), (Suppl.Fig. S1), and 6 (p = 0.002), (Suppl.Fig. S2), with the suicide rate of men in Oulu in the model 2 (p = 0.01), (Suppl.Fig. S3), and with the suicide rate of women in Helsinki in the model 6 (p = 0.04), (Suppl.Fig. S4).
The change in daily mean temperature compared to the previous day associated with the suicide rate of men in Jyväskylä in the model 5 (p = 0.02), (Suppl.Fig. S5).
Diurnal temperature change between maximum and minimum daily temperatures associated with the suicide rate of women in Jyväskylä in the model 4 by the rate ratio of 1.024 per each degree of Celsius (CI 1.0–1.05), (p = 0.02).
Thermal seasons as categorical variables associated with the suicide rate of women in Jyväskylä in the model 2 (p = 0.02) in descending order as follows: spring (RR = 2.23, CI 1.6–8.8), winter (reference), autumn (RR = 0.98, CI 0.3–3.5), and summer (RR = 0.71, CI 0.7–3.1).
Suicide rate in relation to astronomical seasons
Variables concerning astronomical seasons associated with suicide rates of men and women only in Jyväskylä, in the model 1. Astronomical seasons used as categorical variables in the model 1 associated with the suicide rate of women in Jyväskylä in following order: summer (RR = 5.58, CI 1.5–20.6), spring (RR = 1.37, CI 0.5–3.8), winter (reference), and autumn (RR = 0.63, CI 0.2–2.6). The numbers of days from the onsets of astronomical spring (p = 0.002) and autumn (p = 0.003) associated with suicide rate of women in Jyväskylä. Suicide rate of men in Jyväskylä associated with the number of days from the onset of astronomical summer (p = 0.04).
The mismatch time period, that is, the days that overlap between thermal and astronomical seasons, did not associate with suicide rate in any of the study areas.
There was diversity in our results, and no single explanatory variable associated uniformly with suicide rates of men and women in the three study areas. Our results seem to suggest that cold temperatures or cooling down may associate with lower suicide rates in Helsinki, and men in Oulu. For women in Oulu, the results are difficult to interpret. In Jyväskylä, the associations seem to be different, if not opposite in direction.
Limitations and strengths
In evaluating our results, some limitations should be taken into account. First, the main aim of our eco-epidemiologic study was to estimate the association of ambient temperatures with deaths from suicide. Therefore, the p values do not present a formal hypothesis testing, but they are of only a descriptive value and should be considered with caution for interpretation of the results.
Second, although suicide rate in Finland has been among the highest in the world during the study period, with a peak of 38 per 100,000 in 1990, it has decreased down to 15.4 per 100,000 in 2012. Considering the rather small population of 5.4 million in Finland, the absolute numbers of suicides, especially in women in Jyväskylä and Oulu regions, can, from the statistical point of view, be seen as a limitation (Table 1).
Third, socio-economic factors or data of psychiatric morbidity of the suicide victims were not available. However, these three study areas represent urban settings, with lively universities, implicitly suggesting similarities in the socio-economic structure and psychiatric treatment possibilities.
Fourth, no mediation of weather or interaction of ambient temperature with other weather variables such as humidity or wind speed which all affect to the way we sense temperature could be taken into account. Therefore, our study describes only a narrow segment of weather and its possible association with suicide rate.
The strengths of this study are the daily data of suicides relative to the size of the population for a 37-year-long period, with the local daily weather data, from a country with a relatively high suicide rates. In addition, the suicide statistics may be considered liable and consistent during the study period, due to long and systematical tradition in statistics in general in Finland. In addition, the death from suicide does not carry any legal or religious punishments in Finland.
Suicide rate of men
In the southern coast, in Helsinki region, the rate ratio for men’s suicide rate was lower, the lower the daily mean temperature was, both in the year-round analysis (Suppl. Fig. S1) and in the autumn–winter half-year analysis (Suppl. Fig. S2). Furthermore, the smaller the suicide rate of men in Helsinki was, the more robust the decrease in ambient temperature during the preceding 5 days had been (Fig. 3). In contrast to the findings in Helsinki, in the continental part of Finland, in Jyväskylä region, the rate ratio for men’s suicide rate slightly decreased the more the daily mean temperature had increased from the previous day (Suppl. Fig. S5). For men, in Oulu region, the rate ratio increases as the daily mean temperature gets higher (Suppl. Fig. S3), and in turn, the rate ratio decreases up till approximately 30 days from the onset of thermal winter when ambient temperature goes below 0° of Celsius by definition during thermal winter (Fig. 5). The results from Helsinki and Oulu seem to be consistent with the finding of Ajdacic-Gross et al. , suggesting that it is the lack of cold that may increase the risk of suicide.
Suicide rate of women
For women in Helsinki region, the rate ratio seems to slightly increase, the higher is the daily mean temperature during the autumn–winter period (Suppl. Fig. S4). For women’s suicide rate in Jyväskylä region, three associations were found. First, the rate ratio descends in the following order with the thermal seasons: spring, winter, autumn, and summer. Second, the rate ratio increases up till a duration of approximately 30 days during thermal spring (Fig. 2). Third, the rate ratio increases by 1.024 per degree of Celsius of diurnal change between the daily maximum and minimum temperatures. These results seem to suggest that it maybe the change in temperature that increases the suicide risk. This study does not reveal the possible reasons for this, but it can be speculated that vulnerable individuals cannot thermally adapt as quickly as others due to possibly disrupted thermoregulation. In this respect, thermal spring may be more challenging than other thermal seasons, because ambient daily temperatures typically roller coaster between cold at night and warm during the day. A difference between the daily minimum and maximum temperatures may well be of up to 20° in Celsius (thus, to visualize, generating a rate ratio of up to 20.48) during spring, despite of the fact that the daily mean temperature stays between 0° and 10° of Celsius by definition. During thermal summer, autumn, and winter, the diurnal variation in ambient temperature is typically smaller than in spring in Finland.
For women, in Oulu region, the pattern with a slight decrease in rate ratio with a slight decrease in temperature, and a slight increase or rate ratio with a moderate increase in temperature, and further, the “tail” with decrease in rate ratio, while a clear increase in temperature is different from the results of women in Helsinki and Jyväskylä (Suppl. Fig. S6).
Temperature and risk factors for suicides
In favor of a true association between suicides and ambient temperature are studies showing that psychiatric disorders with elevated suicide risk associate with various thermo regulative abnormalities. It has been shown that the sensation of thermal comfort is influenced by mood and that distressed individuals do not tolerate high temperatures . Furthermore, dysregulation of body temperature has been demonstrated during depressive episodes and in depressive disorder [26, 27] and suspected in schizophrenia . In addition, ambient temperature has associated with hospital admissions due to depressive episodes of bipolar disorder  and with those due to schizophrenia .
Although the possible biological explanations for these aforementioned associations are beyond our methods, some suggestions are presented herein. Over-active brown adipose tissue has been found among depressed suicide victims , and changes in brain metabolism have been found in people with activated brown adipose tissue . Activated brown adipose tissue appears to produce a hypermetabolic change in the right inferior parietal lobule and a hypometabolic change in the left insula . In depressed adolescents with bipolar disorder, the neural activity in the left insula during emotional processing increases after successful treatment , whereas in patients with chronic treatment-resistant depression, the left insula volume is smaller than in healthy controls . Furthermore, peripheral cold receptors in the skin can induce, via the thermoregulatory afferent pathway [35, 36], not only heat from brown adipose tissue but also behavioral changes . Exposure to cold, via influence on neurons in the lateral parabrachial nucleus, activates interneurons in the preoptic area to inhibit warm-sensitive inhibitory output neurons and thereby drives thermogenesis . In line with this, thermoregulatory cooling, and the subsequent alleviation of depression, was induced by stimulating peripheral warm-sensitive thermoafferent spinoparabrachial pathway among patients with major depression .
We hypothesize herein that it is the increasing thermal stress on warm days after cold nights during spring that may over-activate brown adipose tissue and impair heat tolerance. This impairment is suggested to change neural activity in the brain areas receiving projections from brown adipose tissue  and thereby to deepen depression and increase the risk of suicide. Furthermore, reactions along the thermoregulatory afferent pathway seem to depend on phosphatidylinositol 4,5-bisphosphate , which is reduced by treatment with lithium [42, 43], which might help in slowing down the over-activated brown adipose tissue. It is of note that neuroleptics may impair thermoregulation [28, 44]. What comes to the possible differences in thermoregulation between genders, there are several possibilities that may provide an explanation. For instance, the receptor activator of NF-kB ligand (also known as RANKL) and its tumor necrosis factor (TNF) family receptor RANK, which play an essential role in body temperature regulation and are involved in fever mechanisms, seem to interact with ovarian hormones and take part in the physiological temperature regulation in females . If this holds for women and contributes to suicide vulnerability, it is not known.
Concerning genes and gene–environment interactions, there are currently no studies on the possible triggering role of physiologically stressful environmental stimuli, such as weather, in relation to suicidal behavior [46, 47]. However, adrenergic signaling in brown adipose tissue seems to be involved in the regulation of the clock gene expression . Moreover, rapid improvement of depressive mood by total sleep deprivation therapy has been suggested to emerge through the resetting of clock gene functions, leading to correction of the misalignment between the circadian rhythms and sleep .
Besides differences in biological vulnerability, a climatic perspective may offer one explanation to the variation in results across the three study areas. Finland is situated between 60 and 70 latitudes, but the climate is not as cold as might be expected, and four seasons with warm and light summers and cold and dark winters can be clearly distinguished. However, due to the fact that Finland is over 1100 km in length in south–north direction, the climatic conditions across Finland vary markedly. In addition, due to the frequently passing high and low pressures, high variability in the daily weather is more typical than in lower latitudes in general. As a consequence, the local climates of these study areas Helsinki, Jyväskylä, and Oulu differ from each other. Helsinki and Oulu are both located by the Baltic Sea, Oulu 600 km north of Helsinki, and Jyväskylä is in the halfway of Helsinki, and Oulu by south–north axis, but situated inland, and weather phenomena typical for coastal areas lack from Jyväskylä. Therefore, in our study areas, similar ambient temperature conditions can prevail in different kind of synoptic weather situations with different air humidity, wind speed, and atmospheric pressure, which can be experienced differently from the human point of view. Furthermore, in these areas, the timings of thermal seasons in relation to astronomical seasons and the length of day light differ clearly from each other (Tables 2, 4). Different adaptation mechanisms both psychologically and physiologically are needed in order to acclimatize properly.
In conclusion, thermal seasons and ambient daily temperature associated with suicide rates suggesting lower suicide rate with lower temperatures, especially among men. Based on our results, the association of ambient temperature with seasonally recurring peaks in suicide rate cannot be ruled out. Further studies are needed to reveal the meaning of our results on individual level. The biological mechanisms, if any, underlying these associations remain to be elucidated in order to find and focus adequate preventive measures to those in need.
The Finnish National Graduate School for Clinical Investigation allocated scholarships (to LH) for this project, but had no further role in the study design.
Conflict of interest
The authors declare that they have no conflict of interest.
- Ruuhela R, Hiltunen L, Venalainen A, Pirinen P, Partonen T. Climate impact on suicide rates in Finland from 1971 to 2003. Int J Biometeorol. 2009;53:167–75.PubMedView ArticleGoogle Scholar
- Helama S, Holopainen J, Partonen T. Temperature-associated suicide mortality: contrasting roles of climatic warming and the suicide prevention program in Finland. Environ Health Prev Med. 2013;18:349–55.PubMedView ArticleGoogle Scholar
- Holopainen J, Helama S, Partonen T. Does diurnal temperature range influence seasonal suicide mortality? Assessment of daily data of the Helsinki metropolitan area from 1973 to 2010. Int J Biometeorol. 2013 Jun 18, (Epub ahead of print). doi:10.1007/s00484-013-0689-0.
- Deisenhammer EA. Weather and suicide: the present state of knowledge on the association of meteorological factors with suicidal behaviour. Acta Psychiatr Scand. 2003;108:402–9.PubMedView ArticleGoogle Scholar
- Page LA, Hajat S, Kovats RS. Relationship between daily suicide counts and temperature in England and Wales. Br J Psychiatry. 2007;191:106–12.PubMedView ArticleGoogle Scholar
- Ishii N, Terao T, Araki Y, Kohno K, Mizokami Y, Arasaki M, et al. Risk factors for suicide in Japan: a model of predicting suicide in 2008 by risk factors of 2007. J Affect Disord. 2013;147:352–4.PubMedView ArticleGoogle Scholar
- Inoue K, Nishimura Y, Fujita Y, Ono Y, Fukunaga T. The relationship between suicide and five climate issues in a large-scale and long-term study in Japan. West Indian Med J. 2012;61:532–7.PubMedView ArticleGoogle Scholar
- Dixon PG, McDonald AN, Scheitlin KN, Stapleton JE, Allen JS, Carter WM, et al. Effects of temperature variation on suicide in five U.S. counties, 1991–2001. Int J Biometeorol. 2007;51:395–403.PubMedView ArticleGoogle Scholar
- Ajdacic-Gross V, Lauber C, Sansossio R, Bopp M, Eich D, Gostynski M, et al. Seasonal associations between weather conditions and suicide–evidence against a classic hypothesis. Am J Epidemiol. 2007;165:561–9.PubMedView ArticleGoogle Scholar
- Yin J, Zheng Y, Wu R, Tan J, Ye D, Wang W. An analysis of influential factors on outdoor thermal comfort in summer. Int J Biometeorol. 2012;56:941–8.PubMedView ArticleGoogle Scholar
- Nayha S. Short and medium-term variations in mortality in Finland. A study on cyclic variations, annual and weekly periods and certain irregular changes in mortality in Finland during period 1868–1972. Scand J Soc Med Suppl. 1981;21:1–101.PubMedGoogle Scholar
- Hakko H, Rasanen P, Tiihonen J. Seasonal variation in suicide occurrence in Finland. Acta Psychiatr Scand. 1998;98:92–7.PubMedView ArticleGoogle Scholar
- Rock D, Greenberg DM, Hallmayer JF. Increasing seasonality of suicide in Australia 1970–1999. Psychiatry Res. 2003;120:43–51.PubMedView ArticleGoogle Scholar
- Partonen T, Haukka J, Nevanlinna H, Lonnqvist J. Analysis of the seasonal pattern in suicide. J Affect Disord. 2004;81:133–9.PubMedView ArticleGoogle Scholar
- Rocchi MB, Miotto P, Preti A. Seasonal variation in suicides and in deaths by unintentional illicit acute drug intoxications. Addict Biol. 2004;9:255–63.PubMedView ArticleGoogle Scholar
- Bridges FS, Yip PS, Yang KC. Seasonal changes in suicide in the United States, 1971 to 2000. Percept Mot Skills. 2005;100:920–4.PubMedView ArticleGoogle Scholar
- Zonda T, Bozsonyi K, Veres E. Seasonal fluctuation of suicide in Hungary between 1970–2000. Arch Suicide Res. 2005;9:77–85.PubMedView ArticleGoogle Scholar
- Christodoulou C, Douzenis A, Papadopoulos FC, Papadopoulou A, Bouras G, Gournellis R, et al. Suicide and seasonality. Acta Psychiatr Scand. 2012;125:127–46. (Epub 2011 Aug 13.2011).doi:10.1111/j.1600-0447.2011.01750.x.
- Meares R, Mendelsohn FA, Milgrom-Friedman J. A sex difference in the seasonal variation of suicide rate: a single cycle for men, two cycles for women. Br J Psychiatry. 1981;138:321–5.PubMedView ArticleGoogle Scholar
- Nayha S. Autumn incidence of suicides re-examined: data from Finland by sex, age and occupation. Br J Psychiatry. 1982;141:512–7.PubMedView ArticleGoogle Scholar
- Micciolo R, Zimmermann-Tansella C, Williams P, Tansella M. Seasonal variation in suicide: is there a sex difference? Psychol Med. 1989;19:199–203.PubMedView ArticleGoogle Scholar
- Hiltunen L, Suominen K, Lonnqvist J, Partonen T. Relationship between daylength and suicide in Finland. J Circadian Rhythms. 2011;9:10.PubMed CentralPubMedView ArticleGoogle Scholar
- R Core Team 2012, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, http://www.R-project.org/. Accessed 28 Mar 2014.
- Carstensen B, Plummer M, Laara E, Hills M. 2012. Epi: A Package for Statistical Analysis in Epidemiology, R package version 1.1.49, http://CRAN.R-project.org/package=Epi. Accessed 28 Mar 2014.
- Hastie TJ. Natural spline, Chap 7 of Statistical Models in S. In: Chambers JM, Hastie TJ, editors. Generalized additive models. Wadsworth & Brooks/Cole; 1992.Google Scholar
- Germain A, Kupfer DJ. Circadian rhythm disturbances in depression. Hum Psychopharmacol. 2008;23:571–85.PubMed CentralPubMedView ArticleGoogle Scholar
- Albrecht U. Circadian clocks in mood-related behaviors. Ann Med. 2010;42:241–51.PubMedView ArticleGoogle Scholar
- Chong TW, Castle DJ. Layer upon layer: thermoregulation in schizophrenia. Schizophr Res. 2004;69:149–57.PubMedView ArticleGoogle Scholar
- Shapira A, Shiloh R, Potchter O, Hermesh H, Popper M, Weizman A. Admission rates of bipolar depressed patients increase during spring/summer and correlate with maximal environmental temperature. Bipolar Disord. 2004;6:90–3.PubMedView ArticleGoogle Scholar
- Sung TI, Chen MJ, Lin CY, Lung SC, Su HJ. Relationship between mean daily ambient temperature range and hospital admissions for schizophrenia: results from a national cohort of psychiatric inpatients. Sci Total Environ. 2011;410–411:41–6.PubMedView ArticleGoogle Scholar
- Huttunen P, Kortelainen ML. Long-term alcohol consumption and brown adipose tissue in man. Eur J Appl Physiol Occup Physiol. 1990;60:418–24.PubMedView ArticleGoogle Scholar
- Huang YC, Hsu CC, Huang P, Yin TK, Chiu NT, Wang PW, et al. The changes in brain metabolism in people with activated brown adipose tissue: a PET study. Neuroimage. 2011;54:142–7.PubMedView ArticleGoogle Scholar
- Diler RS, Ladouceur CD, Segreti A, Almeida JR, Birmaher B, Axelson DA, et al. Neural correlates of treatment response in depressed bipolar adolescents during emotion processing. Brain Imaging Behav. 2013;7:227–35.PubMedView ArticleGoogle Scholar
- Serra-Blasco M, Portella MJ, Gomez-Anson B, de Diego-Adelino J, Vives-Gilabert Y, Puigdemont D, et al. Effects of illness duration and treatment resistance on grey matter abnormalities in major depression. Br J Psychiatry. 2013;202:434–40. (Epub Apr 25.2013). doi:10.1192/bjp.bp.112.116228.
- Bratincsak A, Palkovits M. Evidence that peripheral rather than intracranial thermal signals induce thermoregulation. Neuroscience. 2005;135:525–32.PubMedView ArticleGoogle Scholar
- Nakamura K, Morrison SF. A thermosensory pathway that controls body temperature. Nat Neurosci. 2008;11:62–71.PubMed CentralPubMedView ArticleGoogle Scholar
- Almeida MC, Hew-Butler T, Soriano RN, Rao S, Wang W, Wang J, et al. Pharmacological blockade of the cold receptor TRPM8 attenuates autonomic and behavioral cold defenses and decreases deep body temperature. J Neurosci. 2012;32:2086–99.PubMed CentralPubMedView ArticleGoogle Scholar
- Morrison SF, Nakamura K, Madden CJ. Central control of thermogenesis in mammals. Exp Physiol. 2008;93:773–97.PubMed CentralPubMedView ArticleGoogle Scholar
- Hanusch KU, Janssen CH, Billheimer D, Jenkins I, Spurgeon E, Lowry CA, et al. Whole-body hyperthermia for the treatment of major depression: associations with thermoregulatory cooling. Am J Psychiatry. 2013;170:802–4.PubMedView ArticleGoogle Scholar
- Vaughan CH, Bartness TJ. Anterograde transneuronal viral tract tracing reveals central sensory circuits from brown fat and sensory denervation alters its thermogenic responses. Am J Physiol Regul Integr Comp Physiol. 2012;302:R1049–58.PubMed CentralPubMedView ArticleGoogle Scholar
- Fujita F, Uchida K, Takaishi M, Sokabe T, Tominaga M. Ambient temperature affects the temperature threshold for TRPM8 Activation through Interaction of Phosphatidylinositol 4, 5-Bisphosphate. J Neurosci. 2013;33:6154–9.PubMedView ArticleGoogle Scholar
- Detera-Wadleigh SD. Lithium-related genetics of bipolar disorder. Ann Med. 2001;33:272–85.PubMedView ArticleGoogle Scholar
- Jardín I, Redondo PC, Salido GM, Rosado JA. Phosphatidylinositol 4,5-bisphosphate enhances store-operated calcium entry through hTRPC6 channel in human platelets. Biochimica et Biophysica Acta (BBA)—Molecular. Cell Res. 2008;1783:84–97.Google Scholar
- Cuddy ML. The effects of drugs on thermoregulation. AACN Clin Issues. 2004;15:238–53.PubMedGoogle Scholar
- Hanada R, Leibbrandt A, Hanada T, Kitaoka S, Furuyashiki T, Fujihara H, et al. Central control of fever and female body temperature by RANKL/RANK. Nature. 2009;462:505–9.PubMedView ArticleGoogle Scholar
- Antypa N, Serretti A, Rujescu D. Serotonergic genes and suicide: a systematic review. Eur Neuropsychopharmacol. 2013;23:1125–42.PubMedView ArticleGoogle Scholar
- Mandelli L, Serretti A. Gene environment interaction studies in depression and suicidal behavior: An update. Neurosci Biobehav Rev. 2013; 37:2375-97. (Epub 2013 Jul 22). doi:10.1016/j.neubiorev.2013.07.011.
- Li S, Yu Q, Wang GX, Lin JD. The biological clock is regulated by adrenergic signaling in brown fat but is dispensable for cold-induced thermogenesis. PLoS ONE. 2013;8:e70109.PubMed CentralPubMedView ArticleGoogle Scholar
- Bunney BG, Bunney WE. Mechanisms of rapid antidepressant effects of sleep deprivation therapy: clock genes and circadian rhythms. Biol Psychiatry. 2013;73:1164–71.PubMedView ArticleGoogle Scholar