Biological Trace Element Research

, Volume 178, Issue 2, pp 180–188 | Cite as

Association of Mood Disorders with Serum Zinc Concentrations in Adolescent Female Students

  • Kobra Tahmasebi
  • Reza Amani
  • Zahra Nazari
  • Kambiz Ahmadi
  • Sara Moazzen
  • Seyed-Ali Mostafavi


Among various factors influencing mood disorders, the impact of micronutrient deficiencies has attracted a great attention. Zinc deficiency is considered to play a crucial role in the onset and progression of mood disorders in different stages of life. The main objective of this study was to assess the correlation between serum zinc levels and mood disorders in high school female students. This cross-sectional study was conducted on a random sample of 100 representative high school female students. The participants completed 24-h food recall questionnaires to assess the daily zinc intakes. Serum zinc status was assessed using flame atomic absorption spectrometry, and zinc deficiency was defined accordingly. Mood disorders were estimated by calculating the sum of two test scores including Beck’s depression inventory (BDI) and hospital anxiety depression scale (HADS) tests. General linear model (GLM) and Pearson’s regression test were applied to show the correlation of serum zinc levels and mood disorder scores and the correlation between zinc serum levels and BDI scores, respectively. Dietary zinc intake was higher in subjects with normal zinc concentrations than that of zinc-deficient group (p = 0.001). Serum zinc levels were inversely correlated with BDI and HADS scores (p < 0.05). Each 10 μg/dL increment in serum zinc levels led to 0.3 and 0.01 decrease in depression and anxiety scores, respectively (p < 0.05). Serum zinc levels were inversely correlated with mood disorders including depression and anxiety in adolescent female students. Increasing serum levels of zinc in female students could improve their mood disorders.


Female Mood disorders Serum zinc levels Students Zinc 


The burden of mental health disorders is considerably greater than what previously assumed [1]. It is estimated that mood disorders are responsible for almost half of the total burden of diseases among young adults all over the world [2].

Depression is a common mood disorder which is associated with impaired function, significant disability, morbidity, and mortality [3]. As a psychiatric disorder, depression is the cause of 50–70% of suicides [4]. According to the report of the World Health Organization by 2020, depression will be the second most important cause of human disability [2]. The lifetime risk for depression is 10 to 25% and 5 to 12% in women and men, respectively [5].

Among other mood disorders, anxiety is described as an emotional state that includes feeling apprehension, tension, and nervousness which is accompanied by physiological arousal [6]. Anxiety disorders are the most prevalent psychiatric illnesses in the general community, present in 15–20% of all patients [7].

There is increasing body of evidence revealing the role of nutrition in depression and anxiety [8, 9]. Among nutritional factors, trace element deficiencies have been the subject of considerable interest. Biologically, zinc has three roles as follows: regulatory, catalytic, and construction. As an important trace element, zinc is essential for proper function of over 300 metalloenzymes in the body [10]. Moreover, zinc plays an important role in the DNA replication, transcription, and protein synthesis, influencing cell division and differentiation [11]. In addition, the human genes encode about 3000 zinc proteins. Furthermore, zinc acts as a signaling ion in the human brain [10]. Considering the highest levels of zinc in areas of the brain known to be important in manifestation of depression and anxiety, including cerebral cortical regions, hippocampus, and lateral septum compared to the other parts of the central nervous system (CNS), low levels of zinc have been linked to mood disorders. The association of zinc with prevalence of neurologic and mood disorders has been considered for different age groups [12, 13, 14, 15]. Maes M. and colleagues reported a significant decrease in serum zinc concentration in patients with depression [13]. Sawada, T. and colleagues evaluated the effect of 7-mg zinc supplementation for 10 weeks on mood states in young women and observed a significant reduction in anger and depression [12]. Despite the growing evidence indicating the role of zinc in mood disorders, scarce studies have investigated the relationship between zinc status and prevalence of anxiety and depression. The higher risk of zinc deficiency has been observed among adolescents that might be due to their unhealthy food habits and poor bioavailability of zinc from plant-based diets [16]. This study was, therefore, designed to evaluate the association between serum zinc concentration and mood states including depression and anxiety in female adolescent students.


Study protocol was approved by the Medical Ethics Committee at Jundishapur University of Medical Sciences and was registered under the number U-90276. The main researcher (KT) obtained written informed consent from all parents and the subjects assented to participate in our study. Furthermore, the subjects were allowed to refuse to participate and were free to leave the study by any reason. In addition, the subjects’ anonymity was reserved in all levels of the study from data gathering to manuscript publication.

Material and Methods

Data Source

The data were collected from a random sample of high school girls (15–20 years) living in Izeh city, Khuzestan province, southwest of Iran. There was one vocational female high school in the city that was selected for this study (the other one was a high school boy). About 25% of the student population was randomly selected yielding 105 students. The first author (KT) performed the randomization from the list of all the students by means of a random number table. Five students were unable to follow the course due to unwillingness of their parents; totally, 100 students remained to finish the study. They were interviewed by the first author (KT), and their medical record sheets were evaluated by the high school health instructor. The study protocol was described to them, and all the parents gave the written consent and the subjects assented to participate. Inclusion criteria were being healthy student and willing to participate. Exclusion criteria consisted of being on medications for any chronic diseases such as mental/congenital or metabolic diseases; and any abnormalities in hematology, liver, renal, and thyroid function confirmed by screening laboratory reports. Those taking vitamin/mineral supplements were also excluded.

Participants’ History and Demographic Data

Baseline data were collected as part of a general history including age, weight, height, breakfast and snack consumption, economic status [17], daily physical activity, and sleep pattern (Table 1).
Table 1

Basic characteristics of the female students based on their serum zinc status


Zinc deficient (n = 17)

Normal zinc status (n = 83)

p value

Age (year)

17.92 ± 1.21

17.53 ± 1.03


Height (cm)

158 ± 5.44

159 ± 4.91


Weight (kg)

55.9 ± 12.14

53.4 ± 10.61


BMI (kg/m2)

22.38 ± 4.43

20.99 ± 4.11


Zinc status

Dietary intake (mg/day)

7.61 ± 1.19

9.88 ± 2.03


Serum levels (μg/dL)

62.23 ± 4.34

114.38 ± 27.40


Fiber (g/day)

14.9 ± 7.3

17.4 ± 6.5


Iron (mg/day)

10.6 ± 2.6

10.9 ± 3.4


Copper (mg/day)

1.4 ± 0.35

1.5 ± 0.4


Ca (mg/day)

483 ± 206

506 ± 218


Physical activity level (min/day)



- Less than 10


11 (13.3)


- 10 to 20




- More than 20




Sleeping patterns (hours/day)



- Less than 4



- 4 to 6



- 6 to 8




- More than 8




Monthly income of family



- Low (<300 USD)




- Usual (300–700 USD)




- High (>700 USD)




Having breakfast



- Always




- Seldom




- Never




Having snacks



- Always




- Seldom




- Never




Meat consumption

Red meats:



- Daily




- 3–4 times/week




- Once a week




- Seldom




White meats:



- Daily



- 3–4 times/week




- Once a week




- Seldom




Percentage is shown in parentheses. Serum zinc status was defined as deficient: zinc serum < 70 μg/dL and normal: zinc serum ≥ 70 μg/dL [20]

aVariables are shown as mean (SD)

Socioeconomic Status

Socioeconomic status (SES) was assessed by parental education levels and family income status. The SES questions were adapted from a modified Ethiopia demographic and health survey 2005 report [18].

Dietary and Anthropometric Measurement

The participants completed 24-h food recall questionnaires to assess the daily zinc intakes. Height and weight were measured by a trained dietitian in the same and standard situations. Student’s weight was measured on a digital scale (Seca; Hamburg, Germany) and recorded to the nearest 100 g. The scale was calibrated before measurements using the calibration weights. The students wore light clothing, with no shoes and heavy outer wears (e.g., sweaters) before the measurements. Height was measured using a non-stretched Seca wall height scale (Seca 206, Seca GMBH & Co.; Hamburg, Germany) to the nearest 0.1 cm.

The subjects were asked to remove any hair ornaments, jewelry, buns, or braids from the top of the head. Also, the examiner checked that the subjects stand straight without shoes, and the “back of the head, shoulder blades, buttocks, and heels made contact with the backboard at time of measurement” [19].

Sample Collection

A venous blood sample (5 mL) was collected from each participant in a sitting position after 8- to 10-h overnight fast (between 8:00 am and 10:00 am) done by an experienced laboratory technician. Supernatant serums were separated using 3000-rpm centrifuge for 10 min and were then stored at −80 C for further analyses. No hemolysis sample was observed in the specimens.

Serum zinc levels were measured using atomic absorption spectrometer (Chemtech, model CTA 3000; England) by setting wavelength 213.9 nm and slit width 0.7 nm. Serum zinc concentrations lower than 70 μg/dL were regarded as deficiency [20].

Mood Disorder Tests

A 21-item Beck’s depression inventory (BDI) questionnaire was applied to assess depression symptoms and severity in the students. Scores below 15, 15–19, 20–29, and 30–63 were regarded as normal, mild, moderate, and severe depression, respectively [21]. This instrument is a self-scoring tool for reporting severity of the symptoms of depression. Reliability and validity of the Persian version of 21-item BDI was acceptable with satisfactory test-retest reliability (r = 0.74) and a high internal consistency with Cronbach’s alpha = 0.87 [22].

The hospital anxiety and depression scale (HADS) was applied to measure both anxiety and depression in out-patient populations. Each sub-scale comprised seven items which were rated on a four-point scale and scored from 0 to 3 with total scores, therefore, ranging from 0 to 21 for each sub-scale. Scores between 0 and 7 represent “no case,” 8 to 10 indicate “possible case,” and 11 to 21 suggest a “probable case of anxiety/depression” [23]. This instrument had been validated in Persian society, before. Its internal consistency was acceptable with Cronbach’s alpha coefficient of 0.78 for the HADS anxiety sub-scale and 0.86 for the HADS depression sub-scale. Also, discriminate validity of this instrument for both anxiety and depression sub-scales has been confirmed by diagnosing between sub-groups of patients differing in clinical status as defined by their disease stage [24]. Mood disorder score was calculated as the sum of the two disorders mentioned above. The abovementioned tests were performed in a comfortable condition while the subjects were seating on a comfortable chair in a private room without any tensions.

Statistical Analysis

Data were exported to SPSS® (version 18) and were analyzed using selected descriptive and analytical statistical measures. Pearson’s regression test was used to show the correlation between serum zinc levels and depression/anxiety. General linear model (GLM) was used to determine the correlation between serum zinc levels and mood disorder scores.


A total sample of 100 participants was recruited to the study. Table 1 indicates the baseline characteristics of the participants. Accordingly, the mean scores for depression and anxiety tests were 18.2 ± 10.42 and 9.7 ± 4.3, respectively. Of all, 46% were non-depressed, 11% were affected with mild depression, 27% with moderate depression, and 16% with severe depression; 21% were affected with mild anxiety, 30% with moderate anxiety, and 15% with severe anxiety, and 34% were not affected with anxiety.

Results on meat consumption in Table 1 indicate that there were no significant differences between the groups regarding the consumption of two types of meats as the main dietary zinc sources in local nutritional pattern.

Both dietary zinc intake and serum levels were significantly higher in subjects with normal zinc concentrations than those of zinc-deficient group (p = 0.001). Dietary zinc intake and serum zinc concentration were significantly correlated (r = 0.515, p < 0.01; Fig. 1). There was a significant inverse correlation between zinc serum concentrations and BDI scores (r = −0.23, p < 0.001; Fig. 2). Depression and anxiety tests were also correlated (r = 0.64, p < 0.001; Fig. 3). Mood disorders were calculated by the sum of depression and anxiety scores. Serum zinc concentrations were inversely correlated with depression, anxiety, and mood disorder score (Fig. 4) after adjusting for age, height, weight, family economic status, physical activity, and having breakfast and snack habit; but this correlation was weak. Using GLM model, the impact of each 10-μg/dL increase of zinc serum levels on depression, anxiety, and mood disorder scores is shown in Table 2. For each 10-μg/dL elevation of zinc serum concentrations, the scores of depression, anxiety, and mood disorder tests were decreased by 0.1, 0.03, and 0.135, respectively (p < 0.05 for all). We performed partial correlations of diet zinc with mood functions, depression, and anxiety after controlling for dietary iron, calcium, copper, and fiber as main inhibitors of zinc absorption, and we observed no powerful correlation coefficients (r = 0.25, p = 0.01; r = −0.039, p = 0.7; r = 0.037, p = 0.7; respectively).
Fig. 1

Correlation between dietary zinc intake and serum zinc (r = 0.515, p < 0.01)

Fig. 2

Correlation between Beck’s scores and zinc serum concentrations (r = −0.23, p < 0.001)

Fig. 3

Correlation between depression scores and anxiety score (r = 0.64, p < 0.001)

Fig. 4

Correlation between serum zinc concentrations and mood disorder score (r = −0.04, p = 0.6)

Table 2

Correlation between serum zinc concentrations and mood disorder scores of the female students


Mean (SD)


Standard error

%95 confidence interval

p value

Anxiety (HADS)

Decrease in scores

9.7 (4.3)






Depression (Beck’s)

Decrease in scores

18.2 (10.4)






Mood disordersb

Decrease in scores







Analysis was done using general linear model (GLM) after adjusting for age, height, weight, BMI, sleeping patterns, physical activity, having breakfast and snack habit, and family economic status

aIndependent variable: zinc serum levels; dependent variables: depression, anxiety, and mood disorders. Decrements in mood variables are calculated for each 10-μg/dL increase in serum zinc levels. Depression and anxiety tests were correlated (r = 0.64, p < 0.001)

bMood disorders are the sum of scores of the depression and anxiety tests


To our best knowledge, this is the first study in which the relation of serum zinc levels with depression and anxiety in young girls is investigated. A significant inverse correlation between serum zinc concentrations and depression and anxiety scores was observed. Each 10-μg/dL increase in serum zinc levels led to 0.1 and 0.03 mark decreases in depression and anxiety scores, respectively (Table 2).

Among the proposed mechanisms for the role of zinc in attenuating mood disorders, modulating n-methyl diaspartate (NMDA) function, inhibiting chronic over production of cortisol, and neuroproducing role of zinc in the brain are considered crucial [25, 26, 27].

The finding of our study was in agreement with other studies conducted by Islam et al., Yary et al., and Jacka et al. on subjects with depression [28, 29, 30]. In a cross-sectional study conducted by Amani et al., significant lower levels of serum zinc were observed in depressed female students in comparison with healthy matched subjects. Moreover, in their study, inverse correlation was seen between both dietary zinc intake and serum zinc levels with depression scores [31]. In another study on pregnant women, it was shown that lower zinc intake, higher stress, and social disadvantage were associated with the occurrence of depressive symptoms, which were, in turn, attenuated by higher zinc intake [32]. Moreover, Siwek et al. found that treatment-resistant depressed patients exhibit much lower-serum zinc concentrations than their non-treatment-resistant depressed counterparts [33]. The latter finding might provide more evidence in favor of zinc deficiency on mood disorders in developing countries, where mild to moderate zinc deficiency is common [34]. Ranjbar E. and colleagues conducted a 12-week double-blind clinical trial to investigate the effects of 25-mg zinc augmentation to selective serotonin reuptake inhibitors (SSRIs), in the treatment of depression. The results of this study indicate that zinc supplementation together with SSRI antidepressant medication significantly improved major depressive disorders [35]. Ranjbar E. et al. proposed that zinc supplementation may reduce the inflammatory cytokines and elevate the brain-derived neurotrophic factor (BDNF) and, accordingly, plays a role in reducing the severity of major depression [36].

On the other hand, limited studies have shown no relation between zinc status and mood disorders [13, 37]. Considering the limitations indicated in the previous studies [28, 29, 37, 38], and in order to modulate the impact of confounding factors such as socioeconomic status (SES), a complete information of the SES were obtained from our participants and then were adjusted in data analysis.

Furthermore, some concerns exist about hidden zinc deficiency [39] which may have minimal effect on our results since false negatives make our results more conservative. Also, here, zinc deficiency pathology in adolescent girls is worthy of attention; Yokoi found simple food frequency and menorrhagia predicted low-zinc status measure [40]. Zinc absorption and hence serum zinc concentration can be predicted from dietary zinc intake. Bioavailability of dietary zinc increases in zinc-deficient subjects. In fact, they absorb dietary zinc more efficiently from low-zinc diets at least for more than a few weeks [41]. Paying attention to the zinc kinetics and its bioavailability and adaptation is critical for interpretation of the results of zinc deficiency studies. Zinc bioavailability depends on the amount of zinc stored in the body, dietary zinc content, and inhibitors of zinc absorption. Zinc from animal sources absorbs more efficiently; phytate in the plant sources, such as whole grain and legumes, binds tightly to zinc in the gastrointestinal tract and decreases zinc bioavailability. Since phytate is the main inhibitor of zinc absorption, dietary phytate:zinc molar ratio is used to estimate the efficiency of zinc absorption [42]. Furthermore, interaction with other cations in the intestinal lumen may also affect the bioavailability of zinc. As mentioned before, the main objective of this study was to assess the correlation between serum zinc levels and mood disorders in high school female students. Hence, we did not intend to assess the bioavailability of dietary zinc. However, to show that zinc bioavailability has not affected our results, we compared the mean intake of common inhibitors of zinc absorption (including fiber, iron, calcium, and copper; Table 1) and observed no significant difference between zinc-deficient and normal-serum zinc groups.

As a strong point of our study, it should be mentioned that each test was applied separately on a particular day. Moreover, the tests were performed in comfortable conditions. Besides, the surrounding environment was totally prepared while administering the mood tests. As the limitation of this study, we can name the importance of zinc absorption inhibitors such as phytates that should be taken into account in local dietary pattern.

Considering the suggested mechanisms for the potent role of zinc in the brain and maintaining its function, this study could be regarded as a preliminary evidence for the key role of zinc status in mood disorders in young girls at pilot scale [25]. Based on this study, we would suggest that further studies are needed to focus on the bioavailability of dietary zinc in the region. At this point, controlled randomized trials are required in order to precisely investigate the effects of zinc status on mood disorders in different ages and physiological conditions. Longitudinal studies that include performance in school would be useful as well.



We wish to thank all the participants and their parents and also the colleagues at the high school who kindly co-operated with us.

Compliance with Ethical Standards


This study was a part of Ms. Kobra Tahmasebi’s MSc thesis, and the laboratory costs were covered by a grant of Vice-chancellor for Research at the Jundishapur University of Medical Sciences.

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

“All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from parents of all subjects and assent was obtained from all individual participants included in the study.”


  1. 1.
    Crawford MA, Bazinet RP, Sinclair AJ (2009) Fat intake and CNS functioning: ageing and disease. Ann Nutr Metab 55(1–3):202–228CrossRefPubMedGoogle Scholar
  2. 2.
    WHO (2002) Estimates of DALYs by sex, cause and level of development for 2002
  3. 3.
    WHO (2006) Department of non-communicable disease surveillance.
  4. 4.
    Lecomte DaPF (1998) Suicide among youth and young adults, 15 through 24 years of age: a report of 392 cases from Paris, 1989–1996. J For Sci 1998Google Scholar
  5. 5.
    Fava M (2007) Augmenting antidepressants with folate: a clinical perspective. The Journal of clinical psychiatry 68(Suppl 10):4–7PubMedGoogle Scholar
  6. 6.
    Spielberger CD (2010) State-trait anxiety inventory. In: Corsini encyclopedia of psychologyGoogle Scholar
  7. 7.
    Malani PN (2012) Harrison’s principles of internal medicine. The Journal of the American Medical Association 308(17):1813–1814CrossRefGoogle Scholar
  8. 8.
    Ahmadi SM, Keshavarzi S, Mostafavi SA, Bagheri Lankarani K (2015) Depression and obesity/overweight association in elderly women: a community-based case-control study. Acta medica Iranica 53(11):686–689PubMedGoogle Scholar
  9. 9.
    Ahmadi SM, Mohammadi MR, Mostafavi SA, Keshavarzi S, Kooshesh SM, Joulaei H, Sarikhani Y, Peimani P, Heydari ST, Lankarani KB (2013) Dependence of the geriatric depression on nutritional status and anthropometric indices in elderly population. Iranian journal of psychiatry 8(2):92–96PubMedPubMedCentralGoogle Scholar
  10. 10.
    Maret W (2013) Zinc biochemistry: from a single zinc enzyme to a key element of life. Adv Nutr 4(1):82–91. doi:10.3945/an.112.003038 CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Li YVaCJF (2013) Zinc-secreting neurons, gluzincergic and zincergic neurons. Encyclopedia of metalloproteins. SpringerGoogle Scholar
  12. 12.
    Sawada T, Yokoi K (2010) Effect of zinc supplementation on mood states in young women: a pilot study. Eur J Clin Nutr 64(3):331–333. doi:10.1038/ejcn.2009.158 CrossRefPubMedGoogle Scholar
  13. 13.
    Maes M, D’Haese PC, Scharpe S, D’Hondt P, Cosyns P, De Broe ME (1994) Hypozincemia in depression. J Affect Disord 31(2):135–140CrossRefPubMedGoogle Scholar
  14. 14.
    Marcellini F, Giuli C, Papa R, Gagliardi C, Dedoussis G, Herbein G, Fulop T, Monti D, Rink L, Jajte J, Mocchegiani E (2006) Zinc status, psychological and nutritional assessment in old people recruited in five European countries: Zincage study. Biogerontology 7(5–6):339–345. doi:10.1007/s10522-006-9048-4 CrossRefPubMedGoogle Scholar
  15. 15.
    Seyed-Ali Mostafavi SH (2015) Foods and dietary supplements in prevention and treatment of neurodegenerative disease in older adults. In: Watson RR (ed) Foods and dietary supplements in the prevention and treatment of disease in older adults. Elsevier Inc., New York, pp 63–67CrossRefGoogle Scholar
  16. 16.
    De la Cruz-Gongora V, Gaona B, Villalpando S, Shamah-Levy T, Robledo R (2012) Anemia and iron, zinc, copper and magnesium deficiency in Mexican adolescents: National Health and Nutrition Survey 2006. Salud publica de Mexico 54(2):135–145CrossRefPubMedGoogle Scholar
  17. 17.
    Leite LD, de Medeiros Rocha ED, das Gracas Almeida M, Rezende AA, da Silva CA, Franca MC, Marchini JS, Brandao-Neto J (2009) Sensitivity of zinc kinetics and nutritional assessment of children submitted to venous zinc tolerance test. J Am Coll Nutr 28 (4):405–412Google Scholar
  18. 18.
    Agency CS (2005) Ethiopia Demographic and Health Survey 2005—Unicef. MEASURE DHS ORC. Accessed September 2016
  19. 19.
    (NHANES) NHaNES (2007) Anthropometry procedures manual. CDCGoogle Scholar
  20. 20.
    Burtis CA, E.R. Ashwood, and D.E. Bruns, (2012) Tietz textbook of clinical chemistry and molecular diagnostics. Elsevier Health SciencesGoogle Scholar
  21. 21.
    Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J (1961) An inventory for measuring depression. Arch Gen Psychiatry 4:561–571CrossRefPubMedGoogle Scholar
  22. 22.
    Ghassemzadeh H, Mojtabai R, Karamghadiri N, Ebrahimkhani N (2005) Psychometric properties of a Persian-language version of the Beck depression inventory—second edition: BDI-II-PERSIAN. Depression and anxiety 21(4):185–192. doi:10.1002/da.20070 CrossRefPubMedGoogle Scholar
  23. 23.
    Zigmond AS, Snaith RP (1983) The hospital anxiety and depression scale. Acta Psychiatr Scand 67(6):361–370CrossRefPubMedGoogle Scholar
  24. 24.
    Montazeri A, Vahdaninia M, Ebrahimi M, Jarvandi S (2003) The hospital anxiety and depression scale (HADS): translation and validation study of the Iranian version. Health and quality of life outcomes 1:14. doi:10.1186/1477-7525-1-14 CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Takeda A (2000) Movement of zinc and its functional significance in the brain. Brain Res Brain Res Rev 34(3):137–148CrossRefPubMedGoogle Scholar
  26. 26.
    Fraker PJ, King LE (2004) Reprogramming of the immune system during zinc deficiency. Annu Rev Nutr 24:277–298. doi:10.1146/annurev.nutr.24.012003.132454 CrossRefPubMedGoogle Scholar
  27. 27.
    Prasad AS, Bao B, Beck FW, Kucuk O, Sarkar FH (2004) Antioxidant effect of zinc in humans. Free Radic Biol Med 37(8):1182–1190. doi:10.1016/j.freeradbiomed.2004.07.007 CrossRefPubMedGoogle Scholar
  28. 28.
    Islam MR, Ahmed MU, Mitu SA, Islam MS, Rahman GK, Qusar MM, Hasnat A (2013) Comparative analysis of serum zinc, copper, manganese, iron, calcium, and magnesium level and complexity of interelement relations in generalized anxiety disorder patients. Biol Trace Elem Res 154(1):21–27. doi:10.1007/s12011-013-9723-7 CrossRefPubMedGoogle Scholar
  29. 29.
    Yary T, Aazami S (2012) Dietary intake of zinc was inversely associated with depression. Biol Trace Elem Res 145(3):286–290. doi:10.1007/s12011-011-9202-y CrossRefPubMedGoogle Scholar
  30. 30.
    Jacka FN, Maes M, Pasco JA, Williams LJ, Berk M (2012) Nutrient intakes and the common mental disorders in women. J Affect Disord 141(1):79–85. doi:10.1016/j.jad.2012.02.018 CrossRefPubMedGoogle Scholar
  31. 31.
    Amani R, Saeidi S, Nazari Z, Nematpour S (2010) Correlation between dietary zinc intakes and its serum levels with depression scales in young female students. Biol Trace Elem Res 137(2):150–158. doi:10.1007/s12011-009-8572-x CrossRefPubMedGoogle Scholar
  32. 32.
    Roy A, Evers SE, Avison WR, Campbell MK (2010) Higher zinc intake buffers the impact of stress on depressive symptoms in pregnancy. Nutr Res 30(10):695–704. doi:10.1016/j.nutres.2010.09.011 CrossRefPubMedGoogle Scholar
  33. 33.
    Siwek M, Dudek D, Schlegel-Zawadzka M, Morawska A, Piekoszewski W, Opoka W, Zieba A, Pilc A, Popik P, Nowak G (2010) Serum zinc level in depressed patients during zinc supplementation of imipramine treatment. J Affect Disord 126(3):447–452. doi:10.1016/j.jad.2010.04.024 CrossRefPubMedGoogle Scholar
  34. 34.
    Narang RL, Gupta KR, Narang AP, Singh R (1991) Levels of copper and zinc in depression. Indian J Physiol Pharmacol 35(4):272–274PubMedGoogle Scholar
  35. 35.
    Ranjbar E, Kasaei MS, Mohammad-Shirazi M, Nasrollahzadeh J, Rashidkhani B, Shams J, Mostafavi SA, Mohammadi MR (2013) Effects of zinc supplementation in patients with major depression: a randomized clinical trial. Iranian journal of psychiatry 8(2):73–79PubMedPubMedCentralGoogle Scholar
  36. 36.
    Ranjbar E, Shams J, Sabetkasaei M, M-Shirazi M, Rashidkhani B, Mostafavi A, Bornak E, Nasrollahzadeh J (2014) Effects of zinc supplementation on efficacy of antidepressant therapy, inflammatory cytokines, and brain-derived neurotrophic factor in patients with major depression. Nutr Neurosci 17(2):65–71. doi:10.1179/1476830513Y.0000000066 CrossRefPubMedGoogle Scholar
  37. 37.
    Nguyen PH, Grajeda R, Melgar P, Marcinkevage J, DiGirolamo AM, Flores R, Martorell R (2009) Micronutrient supplementation may reduce symptoms of depression in Guatemalan women. Archivos latinoamericanos de nutricion 59(3):278–286PubMedGoogle Scholar
  38. 38.
    Irmisch G, Schlaefke D, Richter J (2010) Zinc and fatty acids in depression. Neurochem Res 35(9):1376–1383. doi:10.1007/s11064-010-0194-3 CrossRefPubMedGoogle Scholar
  39. 39.
    Sandstead HH, Prasad AS, Penland JG, Beck FW, Kaplan J, Egger NG, Alcock NW, Carroll RM, Ramanujam VM, Dayal HH, Rocco CD, Plotkin RA, Zavaleta AN (2008) Zinc deficiency in Mexican American children: influence of zinc and other micronutrients on T cells, cytokines, and antiinflammatory plasma proteins. Am J Clin Nutr 88(4):1067–1073PubMedGoogle Scholar
  40. 40.
    Yokoi K, Sandstead HH, Egger NG, Alcock NW, Sadagopa Ramanujam VM, Dayal HH, Penland JG (2007) Association between zinc pool sizes and iron stores in premenopausal women without anaemia. Br J Nutr 98(6):1214–1223. doi:10.1017/S0007114507803394 CrossRefPubMedGoogle Scholar
  41. 41.
    Hunt JR, Beiseigel JM, Johnson LK (2008) Adaptation in human zinc absorption as influenced by dietary zinc and bioavailability. Am J Clin Nutr 87(5):1336–1345PubMedGoogle Scholar
  42. 42.
    Moran VH, Stammers AL, Medina MW, Patel S, Dykes F, Souverein OW, Dullemeijer C, Perez-Rodrigo C, Serra-Majem L, Nissensohn M, Lowe NM (2012) The relationship between zinc intake and serum/plasma zinc concentration in children: a systematic review and dose-response meta-analysis. Nutrients 4(8):841–858. doi:10.3390/nu4080841 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Kobra Tahmasebi
    • 1
  • Reza Amani
    • 1
    • 2
  • Zahra Nazari
    • 3
  • Kambiz Ahmadi
    • 4
  • Sara Moazzen
    • 1
  • Seyed-Ali Mostafavi
    • 5
  1. 1.Department of Nutrition, School of Paramedicine, Health Research Institute, Diabetes Research CenterJundishapur University of Medical SciencesAhvazIran
  2. 2.Food Security Center, School of Nutrition and Food ScienceIsfahan University of Medical SciencesIsfahanIran
  3. 3.Department of Toxicology, School of PharmacyJundishapur UniversityAhvazIran
  4. 4.Department of Statistics and Epidemiology, School of Public HealthJundishapur University of Medical SciencesAhvazIran
  5. 5.Psychiatry Research Center, Roozbeh HospitalTehran University of Medical SciencesTehranIran

Personalised recommendations