Abstract
Background
The aim of this study was to determine whether the specific season of the year during which the first trimester of pregnancy takes place is significantly associated with the course (intensification and frequency of occurrence) of an episode of recurrent depressive disorder in adult life.
Material/Methods
We enrolled 184 patients treated for recurrent depressive disorders.
Results
An analysis of the results obtained indicates that the greatest number of people suffering from a major depressive episode were born in the spring and summer (from April to September), meaning that the first trimester of pregnancy occurred between October and March. However, our results were not statistically significant, perhaps due to the small size of the examined group.
Conclusions
The results obtained indicate that birth month may be significantly associated with the course of recurrent depressive disorders. In patients from Central Europe, the first trimester of pregnancy falling in autumn and winter seems to be significant. These results need to be interpreted with caution due to the small size of the examined group.
MeSH Keywords: Depression, Seasonal Affective Disorder, Seasons
Background
Many reports have found an association of birth season with the occurrence, intensification, and clinical course of mental disorders [1–3]. The etiology of schizophrenia [4,5] and bipolar affective disorder [6] has been studied most thoroughly so far, and the importance of the virus hypothesis for their development was emphasized [7]. However, there are few publications that focus on the association between the season of birth the intensification of depressive disorders in children and adults. Disanto et al. [8] carried out wide-ranging studies on a British population (N=57.971), examining the risk of developing schizophrenia, bipolar affective disorders, and depression. For depression, the association between the month of birth and the occurrence of the disease was the weakest, while people born in late spring had the highest lifetime risk of developing depression. Similar results were observed by Torrey et al. [9] in their studies on an American population conducted in the mid-1990s, and by Joiner et al. [10], who examined the risk of depression in Australia. In studies in a British population, Solib et al. [11] analyzed the link between the month of birth and the risk of a suicide attempt. People who committed suicide were significantly more likely to have been born between April and June, and this association was strongest in women. Mino et al. [12] reported that patients in Japan treated due to mood disorders (N=13.969) were more likely to have been born in winter and early spring. Björkstén and Bjerregaard [13] found that among the inhabitants of Greenland born in the years 1961–1980 and raised in Western culture, the risk of committing suicide was the highest in those born between March and June, but this association was not found among people born from 1903 to 1950 and raised in a non-Western, traditional manner.
Various studies have focused on the importance of birth month in the regulation of circadian rhythm cycles [14], the process of character and personality traits shaping [15,16], and even the occurrence of obesity in adult life [17]. Moreover, the link between the season of birth, fertility, and numerous somatic diseases has been described [18]. After analyzing the results of a multicenter trial (almost 2 million examined individuals), Boland et al. [18] indicated the existence of such a correlation in the case of 55 diseases. This phenomenon may also be observed in the population of people who are not treated at present or were not treated in the past for mental or somatic disorders [19,20].
The aim of this study was to determine whether the specific season of the year in which the first trimester of pregnancy took place is significantly associated with the course (intensification and frequency of occurrence) of an episode of recurrent depressive disorders in adult life.
Material and Methods
Material
We enrolled 184 people (ages 17–67 years, mean age (M)=45.49, SD=11.91) treated for recurrent depressive disorders. The criteria for inclusion in the study were based on the diagnostic criteria for an episode of depression and recurrent depressive disorders in accordance with the ICD-10 guidelines (F32.0–7.32.2, F33.0–F33.8) [21].
The patients took part in the study during hospitalization. Participation in the study did not affect the applied treatment modalities (pharmacotherapy and psychotherapy). The people with a history confirming the occurrence in the past of mental disorders other than depressive episodes, somatic diseases that may potentially have an impact on the course of a depressive episode, and the people who did not give voluntary written informed consent to participate in the experiment, were excluded from the study. The patients were treated with standard antidepressant pharmacotherapy using drugs from the group of selective serotonin reuptake inhibitors (SSRIs) [22].
Qualification for participation in the experiment was performed at random without replacement sampling. Only people for whom the interview confirmed uncomplicated pregnancy and labor were qualified for the study. Pregnancy lasting from 38 to 42 weeks was considered normal, and the average pregnancy duration was 40 weeks. The seasons in which subsequent pregnancy trimesters took place were determined based on that.
Methods
The Hamilton Depression Rating Scale [HDRS, HAM-D), developed by M. Hamilton in 1960, was used to evaluate the dynamics of intensification of recurrent depressive disorder symptoms. Cronbach’s alpha calculated for this scale totals 0.70 on average; the sensitivity coefficient is 0.78, and the test relevance coefficient is 0.75 [23]. A scoring system developed by Demyttenaere and De Fruyt [24] was applied when analyzing the intensity of depressive episode symptoms.
Furthermore, the CIDI questionnaire (version 3.0) was used in the experiment. This tool is based on the diagnostic criteria of the ICD-10 and DSM-IV classifications, and is recommended by WHO and WMH for use in epidemiological studies on psychiatry. It enables the estimation of mental disorders dissemination as well as the evaluation of their advancement and the subjective burden of the disease [25].
In each case, an evaluation of the mental state and depressive disorder symptoms intensification was conducted by the same person, who was a specialist in clinical psychology. The CIDI questionnaire was used at the stage of qualifying patients to participate in the study. An examination based on the application of the HDRS scale was performed twice: once on the day of qualification of a specific person to the experiment, and once after clinical condition improvement (after 8 weeks of treatment, on average).
All the patients qualified for the study were unrelated native Poles from central Poland. Participation in the experiment was voluntary. The respondents made a decision to participate in the study after they had been informed of the purpose and were assured that their participation was voluntary, and the personal details and results of the tests conducted would not be distributed, but used only and exclusively in general comparisons. Each patient gave written consent to participate in the experiment in accordance with the report approved by the Bioethics Committee of the Medical University of Łódź (approval no. RNN/534/10/KB of 07/09/2010).
Statistical analysis of results
Selected methods of descriptive statistics and methods of statistical reasoning were used in the statistical analysis of the collected material. During a statistical verification of the hypotheses, a two-tailed critical area was assumed.
Appropriate structural indicators (i.e., prevalence of a given trait expressed as percentage) were applied in the description of qualitative features in the examined group of affected patients and the control group. Arithmetic mean (M) was calculated to describe the value of average quantitative features. The scope of values (with the minimum and maximum value determined) and standard deviation (SD) were used as measures of dispersion.
The character of distribution of all variables was examined using the Shapiro-Wilk test. The hypothesis on the normality of distribution was rejected. The following non-parametric tests were used for non-parametric variables for statistical comparisons between the examined groups: Pearson’s chi-squared test and the Mann-Whitney U test. The level of statistical significance was set at p<0.05 [26]. All statistical calculations were conducted using STATISTICA PL, version 12.
Results
The social and demographic characteristics of the studied group and the information regarding the course of the underlying disease are presented in Table 1.
Table 1.
Age (years) | |
M (SD) | M=45.49 (SD=11.91) |
| |
Women/men | |
n (%) | 112/72 (60.87/39.13) |
| |
HDRS-I | |
M (SD) | M=21.65 (SD=7.12) |
| |
HDRS-II | |
M (SD) | M=5.89 (SD=4.17) |
| |
Number of depressive episodes | |
M (SD) | M=4.05 (SD=2.86) |
| |
Duration of disease (years) | |
M (SD) | M=5.06 (SD=2.53) |
HDRS I – Hamilton Depression Rating Scale on the day of qualification for the experiment; HDRS II – Hamilton Depression Rating Scale after response to the pharmacological treatment applied.
Table 2 presents the characteristics of birth frequency of the examined individuals in specific seasons of the year. The most numerous group were the patients born in spring and summer. No statistically significant differences between birth season and birth half-year and the frequency of occurrence of an episode of depression were found.
Table 2.
Birth quarter | n (%) | HDRS I M (SD) | HDRS II M (SD) |
---|---|---|---|
1st quarter January–March |
46 (25%) | 22.72 (6.91) | 6.22 (4.85) |
2nd quarter April–June |
48 (26%) | 22.01 (6.84) | 6.07 (4.36) |
3rd quarter July–September |
53 (28%) | 20.79 (6.19) | 5.45 (3.81) |
4th quarter October-December |
37 (21%) | 21.08 (5.59) | 5.89 (3.52) |
1st half-year | 93 (50.5%) | 22.39 (6.87) | 6.16 (4.61) |
2nd half-year | 91 (49.5%) | 20.89 (5.89) | 5.61 (3.66) |
Mann-Whitney U test | p=0.192 | p=0.421 |
HDRS I – Hamilton Depression Rating Scale on the day of qualification for the experiment; HDRS II – Hamilton Depression Rating Scale after response to the pharmacological treatment applied.
During the subsequent stage of the analysis, we analyzed the relationship between the birth season of a patient and the intensification of depression symptoms measured using the HDRS scale. The results of this analysis are shown in Table 3, indicating that differences in the intensity of depressive disorders between people born in different seasons were not statistically significant. However, the analysis of the results obtained indicates that the greatest number of people suffering from a major episode of depression were born between April and September. Accepting the assumption regarding the duration of pregnancy made at the beginning of the analysis, it is possible to calculate that the first trimester of pregnancy in the people suffering from a major depressive episode occurred between October and March.
Table 3.
HDRS I N=184 |
1st quarter January–March |
2nd quarter April–June |
3rd quarter July–September |
4th quarter October–December |
Pearson’s chi-squared test |
---|---|---|---|---|---|
8–12 mild intensification of depressive disorder symptoms |
4 | 5 | 6 | 3 | p=0.292 |
13–17 moderate intensification of depressive disorder symptoms |
7 | 6 | 10 | 8 | |
18–29 heavy intensification of depressive disorder symptoms |
28 (24.35%) | 30 (26.09%) | 33 (28.71%) | 24 (20.87) | |
>30 extreme intensification of depressive disorder symptoms |
7 | 6 | 3 | 2 | |
HDRS II N=179 |
1st quarter January–March |
2nd quarter April–June |
3rd quarter July–September |
4th quarter October–December |
Pearson’s chi-squared test |
>7 no symptoms of depressive disorders |
29 | 33 | 38 | 25 | p=0.655 |
8–12 mild intensification of depressive disorder symptoms |
10 | 9 | 9 | 9 | |
13–17 moderate intensification of depressive disorder symptoms |
5 | 3 | 4 | 2 | |
18–29 heavy intensification of depressive disorder symptoms |
2 | 1 | 0 | 0 |
HDRS I – Hamilton Depression Rating Scale on the day of qualification for the experiment; HDRS II – Hamilton Depression Rating Scale after response to the pharmacological treatment applied.
Discussion
The literature on the correlation between birth season and frequency of occurrence and course of recurrent depressive disorders is sparse. Owing to the size of the studied group and the nature of the population (inhabitants of Central Europe), the conclusions formulated on this basis in the present article may not be generalizable. However, there are other reports in the literature that confirm the tendencies observed.
Similar observations were described by Park et al. [27], who examined 891 patients from South Korea treated for unipolar non-psychotic major depressive disorders (MDD). The patients were divided into 2 groups: those born in spring/summer (n=457) and those born in autumn/winter (n=434). These 2 groups did not differ significantly in clinical course of disease, but those born in the spring and summer tended to have a worse prognosis. Among those born in the spring or summer, the first episode of the disease occurred significantly earlier in life and they had worse deficits in concentration and self-control.
In the work by Fountoulakis et al. [28], patients treated for depressive disorders did not differ significantly from healthy subjects in terms of the frequency of birth in subsequent seasons. However, people born in the spring had higher results on the Hamilton Depression Rating Scale during disease recurrence. Joiner et al. [29] emphasized that people born between September and November in the southern hemisphere, and between March and May in the northern hemisphere, were characterized by greater intensification of depression symptoms and an elevated risk of suicide-related behaviors.
When presenting results of their studies, Henriksson et al. [30] reported that postpartum depression symptoms at 6 weeks after labor were observed more often in women who gave birth between October and December compared to women who gave birth between April and June. The same pattern of symptoms was observed in women who before getting pregnant underwent antidepression therapy due to the presence of depression symptoms; access to daylight and vitamin D insufficiency may be particularly important factors in this case [31]. Bauer et al. [32] found that in bipolar affective disorder, greater availability of sunlight (access to natural sunlight) during the first 3 months of life was associated with delayed onset of the first symptoms of disease. On the other hand, Pjrek et al. [33] indicated specific habits of parents during early stages of a child’s development, depending on the season of the year when the child was born. This relationship is a separate problem we intend to address in our subsequent papers.
Dysregulation of the immune system, as an etiological factor that also affects the course of depression, no longer raises any doubt [34]. Using the expression ‘emotional immunity’, D’Acquisto [35] reported that the immune system and the affective system are both dynamic systems, which undergo constant changes and are a mirror reflection of one another. Among the factors that may be of importance for the occurrence of the phenomenon described by us, it is appropriate to pay attention to an increased risk of viral and bacterial infections during the autumn and winter seasons in our climatic zone. They may be conducive to the emergence of depression symptoms in adulthood, irrespective of the moment when an infectious factor was active. Infections during both the prenatal period [36,37] and early childhood are important as they affect the functional dynamics of mutual relationships between the frontal lobes and the limbic system [38]. Furthermore, infections affecting patients at subsequent stages of life are equally important [39,40].
We are facing a two-sided dependence. A depressive episode is linked with the dysregulation of the immune system, yet primal immunological deterioration of the organism – through sickness behavior and somatic comorbidity – is also conducive to the development of depression [41]., Henríquez-Sánchez et al. [42] paid attention to such factors significant for the development of the disease as: the amount of daylight, average daily temperature, or average daily precipitation. On the other hand, Marques et al. [43] and Vohr et al. [44] reported that a mother’s restricted access to nutrient-rich foods during pregnancy may be also important. Correct nutritional ingredients are of high significance for the proper development of the immune system of the fetus [45].
To sum up, it is important to approach the results presented herein with caution. We definitely should not formulate any “health-related horoscopes” for Central Europe inhabitants based on them. Nevertheless, these data are compatible with the results of studies conducted at other scientific centers and indicate a series of factors that may be of importance in the etiology of depressive disorders, such as climatic conditions, risk of infections, and availability of sunlight. Undoubtedly, this issue requires further investigations. The results presented in this article serve as a confirmation for the assumptions of the neurodevelopmental theory of depression, which indicates that the prenatal period has an impact on the prevalence of depression in adult life [46].
Conclusions
Birth month may be significant for the course of recurrent depressive disorders.
In the case of patients from Central Europe, the first trimester of pregnancy occurring in autumn and winter months seems to be of importance. The results recorded need to be approached with caution due to the small size of the examined group.
Footnotes
Conflict of interest
None.
Source of support: This study was supported with scientific research grants from the Medical University of Łódź, No. 503/5-062-02/503-51-004, 502-03/5-062-02/502-54-217 and grant No. 502-03/5-062-02/502-54-208
References
- 1.Troisi A, Pasini A, Spalletta G. Season of birth, gender and negative symptoms in schizophrenia. Eur Psychiatry. 2001;16(6):342–48. doi: 10.1016/s0924-9338(01)00589-2. [DOI] [PubMed] [Google Scholar]
- 2.Jordaan E, Niehaus DJ, Koen L, et al. Season of birth, age and negative symptoms in a Xhosa schizophrenia sample from the Southern Hemisphere. Aust N Z J Psychiatry. 2006;40(8):698–703. doi: 10.1080/j.1440-1614.2006.01870.x. [DOI] [PubMed] [Google Scholar]
- 3.Tonetti L, Fabbri M, Martoni M, Natale V. Season of birth and mood seasonality in late childhood and adolescence. Psychiatry Res. 2012;195(1–2):66–68. doi: 10.1016/j.psychres.2011.07.033. [DOI] [PubMed] [Google Scholar]
- 4.Giezendanner S, Walther S, Razavi N, et al. Alterations of white matter integrity related to the season of birth in schizophrenia: A DTI study. PLoS One. 2013;8(9):e75508. doi: 10.1371/journal.pone.0075508. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Konrath L, Beckius D, Tran US. Season of birth and population schizotypy: Results from a large sample of the adult general population. Psychiatry Res. 2016;242:245–50. doi: 10.1016/j.psychres.2016.05.059. [DOI] [PubMed] [Google Scholar]
- 6.Kroon JS, Wohlfarth TD, Dieleman J, et al. Incidence rates and risk factors of bipolar disorder in the general population: A population-based cohort study. Bipolar Disord. 2013;15(3):306–13. doi: 10.1111/bdi.12058. [DOI] [PubMed] [Google Scholar]
- 7.Crow TJ. A re-evaluation of the viral hypothesis: is psychosis the result of retroviral integration at a site close to the cerebral dominance gene? Br J Psychiatry. 1984;145:243–53. doi: 10.1192/bjp.145.3.243. [DOI] [PubMed] [Google Scholar]
- 8.Disanto G, Morahan JM, Lacey MV, et al. Seasonal distribution of psychiatric births in England. PLoS One. 2012;7(4):e34866. doi: 10.1371/journal.pone.0034866. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Torrey EF, Rawlings RR, Ennis JM, et al. Birth seasonality in bipolar disorder, schizophrenia, schizoaffective disorder and stillbirths. Schizophr Res. 1996;21:141–49. doi: 10.1016/0920-9964(96)00022-9. [DOI] [PubMed] [Google Scholar]
- 10.Joiner TE, Pfaff JJ, Acres JG, Johnson F. Birth month and suicidal and depressive symptoms in Australians born in the Southern vs. the Northern hemisphere. Psychiatry Res. 2002;112(1):89–92. doi: 10.1016/s0165-1781(02)00183-x. [DOI] [PubMed] [Google Scholar]
- 11.Salib E, Cortina-Borja M. Effect of month of birth on the risk of suicide. Br J Psychiatry. 2006;188:416–22. doi: 10.1192/bjp.bp.105.009118. [DOI] [PubMed] [Google Scholar]
- 12.Mino Y, Oshima I, Okagami K. Seasonality of birth in patients with mood disorders in Japan. J Affect Disord. 2000;59(1):41–46. doi: 10.1016/s0165-0327(99)00130-5. [DOI] [PubMed] [Google Scholar]
- 13.Björkstén KS, Bjerregaard P. Season of birth is different in Inuit suicide victims born into Traditional than into Modern Lifestyle: A register study from Greenland. BMC Psychiatry. 2015;15:147. doi: 10.1186/s12888-015-0506-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Caci H, Robert P, Dossios C, Boyer P. Morningness-Eveningness for Children Scale: Psychometric properties and month of birth effect. Encephale. 2005;31(1 Pt 1):56–64. doi: 10.1016/s0013-7006(05)82372-3. [DOI] [PubMed] [Google Scholar]
- 15.Kirkpatrick B, Messias E, LaPorte D. Schizoid-like features and season of birth in a nonpatient sample. Schizophr Res. 2008;103(1–3):151–55. doi: 10.1016/j.schres.2007.12.479. [DOI] [PubMed] [Google Scholar]
- 16.Rihmer Z, Erdos P, Ormos M, et al. Association between affective temperaments and season of birth in a general student population. J Affect Disord. 2011;132(1–2):64–70. doi: 10.1016/j.jad.2011.01.015. [DOI] [PubMed] [Google Scholar]
- 17.Soreca I, Cheng Y, Frank E, et al. Season of birth is associated with adult body mass index in patients with bipolar disorder. Chronobiol Int. 2013;30(4):577–82. doi: 10.3109/07420528.2012.754452. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Boland MR, Shahn Z, Madigan D, et al. Birth month affects lifetime disease risk: A phenome-wide method. J Am Med Inform Assoc. 2015;22(5):1042–53. doi: 10.1093/jamia/ocv046. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Natale V, Adan A, Chotai J. Season of birth modulates mood seasonality in humans. Psychiatry Res. 2007;153(2):199–201. doi: 10.1016/j.psychres.2006.12.022. [DOI] [PubMed] [Google Scholar]
- 20.Gonda X, Fountoulakis KN, Csukly G, et al. Star-crossed? The association of the 5-HTTLPR s allele with season of birth in a healthy female population, and possible consequences for temperament, depression and suicide. J Affect Disord. 2012;143(1–3):75–83. doi: 10.1016/j.jad.2012.05.031. [DOI] [PubMed] [Google Scholar]
- 21.International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) Genewa: World Health Organization; 2015. [Google Scholar]
- 22.Bazire S. The professionals’ pocket handbook an aide memoire. Lloyd-Reinhold Publications Ltd.; 2016. Psychotropic Drug Directory 2016. [Google Scholar]
- 23.Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56–62. doi: 10.1136/jnnp.23.1.56. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Demyttenaere K, De Fruyt J. Getting what you ask for: On the selectivity of depression rating scales. Psychothery Psychosom. 2003;72:61–70. doi: 10.1159/000068690. [DOI] [PubMed] [Google Scholar]
- 25.Kessler RC, Ustün TB. The World Mental Health (WMH) survey initiative version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI) Int J Methods Psychiatr Res. 2004;13(2):93–121. doi: 10.1002/mpr.168. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Kirkwood B, Sterne J. Essential medical statistics. 2nd edition. Wiley-Bleckwell; 2003. [Google Scholar]
- 27.Park SC, Sakong JK, Koo BH, et al. Potential relationship between season of birth and clinical characteristics in major depressive disorder in Koreans: Results from the CRESCEND Study. Yonsei Med J. 2016;57(3):784–89. doi: 10.3349/ymj.2016.57.3.784. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Fountoulakis KN, Iacovides A, Karamouzis M, et al. Season of birth, clinical manifestations and Dexamethasone Suppression Test in unipolar major depression. Ann Gen Psychiatry. 2007;6:20. doi: 10.1186/1744-859X-6-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Joiner TE, Pfaff JJ, Acres JG, Johnson F. Birth month and suicidal and depressive symptoms in Australians born in the Southern vs. the Northern hemisphere. Psychiatry Res. 2002;112(1):89–92. doi: 10.1016/s0165-1781(02)00183-x. [DOI] [PubMed] [Google Scholar]
- 30.Henriksson HE, Sylvén SM, Kallak TK, et al. Seasonal patterns in self-reported peripartum depressive symptoms. Eur Psychiatry. 2017;43:99–108. doi: 10.1016/j.eurpsy.2017.03.001. [DOI] [PubMed] [Google Scholar]
- 31.Robinson M, Whitehouse AJ, Newnham JP, et al. Low maternal serum vitamin D during pregnancy and the risk for postpartum depression symptoms. Arch Womens Ment Health. 2014;17(3):213–19. doi: 10.1007/s00737-014-0422-y. [DOI] [PubMed] [Google Scholar]
- 32.Bauer M, Glenn T, Alda M, et al. Influence of light exposure during early life on the age of onset of bipolar disorder. J Psychiatr Res. 2015;64:1–8. doi: 10.1016/j.jpsychires.2015.03.013. [DOI] [PubMed] [Google Scholar]
- 33.Pjrek E, Winkler D, Praschak-Rieder N, et al. Season of birth in siblings of patients with seasonal affective disorder. A test of the parental conception habits hypothesis. Eur Arch Psychiatry Clin Neurosci. 2007;257(7):378–82. doi: 10.1007/s00406-007-0720-8. [DOI] [PubMed] [Google Scholar]
- 34.Euteneuer F, Dannehl K, Del Rey A, et al. Peripheral Immune alterations in major depression: The role of subtypes and pathogenetic characteristics. Front Psychiatry. 2017;8:250. doi: 10.3389/fpsyt.2017.00250. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.D’Acquisto F. Affective immunology: Where emotions and the immune response converge. Dialogues Clin Neurosci. 2017;19(1):9–19. doi: 10.31887/DCNS.2017.19.1/fdacquisto. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Gilman SE, Cherkerzian S, Buka SL, et al. Prenatal immune programming of the sex-dependent risk for major depression. Transl Psychiatry. 2016;6(5):e822. doi: 10.1038/tp.2016.91. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Murphy SK, Fineberg AM, Maxwell SD, et al. Maternal infection and stress during pregnancy and depressive symptoms in adolescent offspring. Psychiatry Res. 2017;257:102–10. doi: 10.1016/j.psychres.2017.07.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Catena-Dell’Osso M, Bellantuono C, Consoli G, et al. Inflammatory and neurodegenerative pathways in depression: A new avenue for antidepressant development? Curr Med Chem. 2011;18(2):245–55. doi: 10.2174/092986711794088353. [DOI] [PubMed] [Google Scholar]
- 39.Gale SD, Berrett AN, Erickson LD, et al. Association between virus exposure and depression in US adults. Psychiatry Res. 2017;261:73–79. doi: 10.1016/j.psychres.2017.12.037. [DOI] [PubMed] [Google Scholar]
- 40.Kopschina Feltes P, Doorduin J, Klein HC, et al. Anti-inflammatory treatment for major depressive disorder: implications for patients with an elevated immune profile and non-responders to standard antidepressant therapy. J Psychopharmacol. 2017;31(9):1149–65. doi: 10.1177/0269881117711708. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Talarowska M, Szemraj J, Berk M, et al. Oxidant/antioxidant imbalance is an inherent feature of depression. BMC Psychiatry. 2015;15:71. doi: 10.1186/s12888-015-0454-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Henríquez-Sánchez P, Doreste-Alonso J, Martínez-González MA, et al. Geographical and climatic factors and depression risk in the SUN project. Eur J Public Health. 2014;24(4):626–31. doi: 10.1093/eurpub/cku008. [DOI] [PubMed] [Google Scholar]
- 43.Marques AH, Bjørke-Monsen AL, Teixeira AL, Silverman MN. Maternal stress, nutrition and physical activity: Impact on immune function, CNS development and psychopathology. Brain Res. 2015;1617:28–46. doi: 10.1016/j.brainres.2014.10.051. [DOI] [PubMed] [Google Scholar]
- 44.Vohr BR, Poggi Davis E, Wanke CA, Krebs NF. Neurodevelopment: The impact of nutrition and inflammation during preconception and pregnancy in low-resource settings. Pediatrics. 2017;139(Suppl 1):S38–49. doi: 10.1542/peds.2016-2828F. [DOI] [PubMed] [Google Scholar]
- 45.John CC, Black MM, Nelson CA., 3rd Neurodevelopment: The impact of nutrition and inflammation during early to middle childhood in low-resource settings. Pediatrics. 2017;139(Suppl 1):S59–71. doi: 10.1542/peds.2016-2828H. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Gałecki P, Talarowska M. Neurodevelopmental theory of depression. Prog Neuropsychopharmacol Biol Psychiatry. 2018;80:267–72. doi: 10.1016/j.pnpbp.2017.05.023. [DOI] [PubMed] [Google Scholar]